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The implementation of Structural Health Monitoring (SHM) offers the prospect for sustainable and safe service-life extension of existing bridges, a large portion of which is approaching the end of their nominal life. Many SHM frameworks for civil infrastructure address timely damage detection and identification. However, the scarcity of case studies on real damaged bridges hinders the generalized application of SHM in practice. In this contribution, monitoring data from a four-day campaign on the Ponte-Moesa bridge, a three-span concrete box-girder bridge, is presented as a benchmark for data-driven damage diagnosis schemes. The monitoring data, covering accelerations from ambient and forced vibrations, contains the reference state after concluding the service life along with several gradually increasing dam-age states, including drilling holes and cutting reinforcement rebars and prestressed cables. The potential of damage-sensitive features to identify damage is presented and the uncertainties, resulting from the environmental and operational conditions and sensor malfunctioning, pertaining to robust damage detection are discussed. Drawing from real bridge monitoring data, a range of prospects and open challenges of vibration-based SHM for bridges are reviewed., Peer Reviewed, Objectius de Desenvolupament Sostenible::11 - Ciutats i Comunitats Sostenibles, Objectius de Desenvolupament Sostenible::9 - Indústria, Innovació i Infraestructura, Postprint (published version)

В данной статье приведены результаты разработки методики проведения вибрационного контроля с использованием корпоративной программы «Dream for Windows»., This article presents the results of the development of a method for conducting vibration control using the corporate program « Dream for Windows».

The major goal of the pre-study is to identify and prepare the required information, knowledge, tools, modules, and technologies for a project within Smart Manufacturing in the spirit of the collaboration between Sweden and India.WP3 focus is: Identification of the technologies needed to be considered in Smart-Pro project as an Innovation action. This means that the input technologies that will be identified in the Pre-study project should be in about TRL 3-, and the demonstrated results of Smart-Pro should be in about TRL 6-7. Smart Pro project will be based on effective collaboration between universities/research institutes and industry.In WP3, we will develop a list of the tools, methods, modules and technologies (in the areas below) which are available at the members of the Pre-study consortium (and in industry in general), and necessary for developing Smart-Pro system.According to the project description, WP3 has two Tasks:• T3.1: Production-maintenance technologies needed for Smart-Pro.• T3.2: Communication and integration technologies needed for Smart-Pro.The tasks have been distributed between E-maintenance AB (Emaint), which the leader of the WP and the two tasks, Linnaeus University (LNU), Uppsala University (UU) and Stockholm University (SU)., Vinnova funded project- Pre-Study: Info & technology needed for Cloud based smart sustainable integrated production-maintenance system 98

The major goal of the pre-study is to identify and prepare the required information, knowledge, tools, modules, and technologies for a project within Smart Manufacturing in the spirit of the collaboration between Sweden and India.WP3 focus is: Identification of the technologies needed to be considered in Smart-Pro project as an Innovation action. This means that the input technologies that will be identified in the Pre-study project should be in about TRL 3-, and the demonstrated results of Smart-Pro should be in about TRL 6-7. Smart Pro project will be based on effective collaboration between universities/research institutes and industry.In WP3, we will develop a list of the tools, methods, modules and technologies (in the areas below) which are available at the members of the Pre-study consortium (and in industry in general), and necessary for developing Smart-Pro system.According to the project description, WP3 has two Tasks:• T3.1: Production-maintenance technologies needed for Smart-Pro.• T3.2: Communication and integration technologies needed for Smart-Pro.The tasks have been distributed between E-maintenance AB (Emaint), which the leader of the WP and the two tasks, Linnaeus University (LNU), Uppsala University (UU) and Stockholm University (SU)., Vinnova funded project- Pre-Study: Info & technology needed for Cloud based smart sustainable integrated production-maintenance system 98

The major goal of the pre-study is to identify and prepare the required information, knowledge, tools, modules, and technologies for a project within Smart Manufacturing in the spirit of the collaboration between Sweden and India.WP3 focus is: Identification of the technologies needed to be considered in Smart-Pro project as an Innovation action. This means that the input technologies that will be identified in the Pre-study project should be in about TRL 3-, and the demonstrated results of Smart-Pro should be in about TRL 6-7. Smart Pro project will be based on effective collaboration between universities/research institutes and industry.In WP3, we will develop a list of the tools, methods, modules and technologies (in the areas below) which are available at the members of the Pre-study consortium (and in industry in general), and necessary for developing Smart-Pro system.According to the project description, WP3 has two Tasks:• T3.1: Production-maintenance technologies needed for Smart-Pro.• T3.2: Communication and integration technologies needed for Smart-Pro.The tasks have been distributed between E-maintenance AB (Emaint), which the leader of the WP and the two tasks, Linnaeus University (LNU), Uppsala University (UU) and Stockholm University (SU)., Vinnova funded project- Pre-Study: Info & technology needed for Cloud based smart sustainable integrated production-maintenance system 98

Vibration monitoring is well proven procedure for estimation of a condition of a machine system. Excessive vibrations indicate the unexpected problems in operation. Moreover, vibration analysis often can help to discover the cause of the problem. In this paper procedure for system monitoring, data logging, collected data analysis and necessary actions for vibration level dampening at the hydro power plant is described. In order to lower the level of vibration of an operating machine it is necessary to measure vibration intensity and frequency first. Then, through the Fast Fourier Transformation (FFT), collected data is transformed from the time to the frequency domain. Frequency domain signal indicates the possible causes of elevated vibration amplitudes. Every cause of perturbation forces and high vibration levels has its own distinctive frequency domain graph. Frequency of dominant amplitudes (most commonly seven highest amplitudes are taken into consideration) determines the cause of the problem. Rotational machines most often have a problem with dynamic imbalance and/or shaft misalignment. These problems are discovered by excessive vibrations at the rotational frequency and double rotational frequency respectively. On the other hand static structures most commonly change their modal characteristics (natural frequency) due to loss of structural integrity. When the cause of the excessive vibrations is determined it is possible to design the optimal solution. In this case, it was provided through the tailor made modular lightweight steel construction, mounted in order to raise the stiffness of the oscillatory system

The major goal of the pre-study is to identify and prepare the required information, knowledge, tools, modules, and technologies for a project within Smart Manufacturing in the spirit of the collaboration between Sweden and India.WP3 focus is: Identification of the technologies needed to be considered in Smart-Pro project as an Innovation action. This means that the input technologies that will be identified in the Pre-study project should be in about TRL 3-, and the demonstrated results of Smart-Pro should be in about TRL 6-7. Smart Pro project will be based on effective collaboration between universities/research institutes and industry.In WP3, we will develop a list of the tools, methods, modules and technologies (in the areas below) which are available at the members of the Pre-study consortium (and in industry in general), and necessary for developing Smart-Pro system.According to the project description, WP3 has two Tasks:• T3.1: Production-maintenance technologies needed for Smart-Pro.• T3.2: Communication and integration technologies needed for Smart-Pro.The tasks have been distributed between E-maintenance AB (Emaint), which the leader of the WP and the two tasks, Linnaeus University (LNU), Uppsala University (UU) and Stockholm University (SU)., Vinnova funded project- Pre-Study: Info & technology needed for Cloud based smart sustainable integrated production-maintenance system 98

The major goal of the pre-study is to identify and prepare the required information, knowledge, tools, modules, and technologies for a project within Smart Manufacturing in the spirit of the collaboration between Sweden and India.WP3 focus is: Identification of the technologies needed to be considered in Smart-Pro project as an Innovation action. This means that the input technologies that will be identified in the Pre-study project should be in about TRL 3-, and the demonstrated results of Smart-Pro should be in about TRL 6-7. Smart Pro project will be based on effective collaboration between universities/research institutes and industry.In WP3, we will develop a list of the tools, methods, modules and technologies (in the areas below) which are available at the members of the Pre-study consortium (and in industry in general), and necessary for developing Smart-Pro system.According to the project description, WP3 has two Tasks:• T3.1: Production-maintenance technologies needed for Smart-Pro.• T3.2: Communication and integration technologies needed for Smart-Pro.The tasks have been distributed between E-maintenance AB (Emaint), which the leader of the WP and the two tasks, Linnaeus University (LNU), Uppsala University (UU) and Stockholm University (SU)., Vinnova funded project- Pre-Study: Info & technology needed for Cloud based smart sustainable integrated production-maintenance system 98

The major goal of the pre-study is to identify and prepare the required information, knowledge, tools, modules, and technologies for a project within Smart Manufacturing in the spirit of the collaboration between Sweden and India.WP3 focus is: Identification of the technologies needed to be considered in Smart-Pro project as an Innovation action. This means that the input technologies that will be identified in the Pre-study project should be in about TRL 3-, and the demonstrated results of Smart-Pro should be in about TRL 6-7. Smart Pro project will be based on effective collaboration between universities/research institutes and industry.In WP3, we will develop a list of the tools, methods, modules and technologies (in the areas below) which are available at the members of the Pre-study consortium (and in industry in general), and necessary for developing Smart-Pro system.According to the project description, WP3 has two Tasks:• T3.1: Production-maintenance technologies needed for Smart-Pro.• T3.2: Communication and integration technologies needed for Smart-Pro.The tasks have been distributed between E-maintenance AB (Emaint), which the leader of the WP and the two tasks, Linnaeus University (LNU), Uppsala University (UU) and Stockholm University (SU)., Vinnova funded project- Pre-Study: Info & technology needed for Cloud based smart sustainable integrated production-maintenance system 98

Paper presents research of short-term monitoring of vibration response of turbine table top foundation structure in Power Plant Nikola Tesla - A: unit A4 in Obrenovac – Republic of Serbia. Research included short-term monitoring of vibration of the structure in ambient and in-operation condition, numerical modelling of the structure according to available information of masses and stiffness of structural elements, as well as extraction of mode shapes and operational deflection shapes. Measurement of vibrations, during in and out of operating conditions, carried at the same set of points on the upper slab of foundation supporting structure using sensitive accelerometers in frequency range of 0 - 300 Hz, while acquisition carried out using 24-bits acquisition system. Extraction of modes, frequencies and shapes, carried out using state of the art software package ARTeMIS. The same extraction procedure applied for extraction of deflection shapes according to acquired acceleration data during in-operation conditions. Numerical modelling performed using SAP2000 software package for structural static and dynamic analysis, with application of beam elements and additional masses with eccentricity from top level of the foundation structure. Additional masses, according to available data of weights of turbines, turbogenerator and other installed equipment, are taken into account. Finally, during analysis and comparison of experimental and numerical results, find out quite good matches of mode shapes and operational deflection shapes, which clearly have been discussed in conclusion.

The subject of the research is rationing and monitoring of the vibration of knife refiners. GOST 26493-85, specifying the permissible values of the vibration amplitude of the mills, is outdated. This standard does not take into account new designs of knife refiners and the requirements of national and international standards. It is proposed to establish two criteria for assessing the vibration state of the refiners. The first criterion normalizes the amplitude of vibration in octave strips of frequencies, while the second criterion specifies the vibration trend on the general level. It is proposed to use the vibration velocity as the measured parameter. The necessity of separating the refiners into two groups was revealed: with a disc or cone diameter up to 1000 mm and with a diameter over 1000 mm. The boundaries of zones and vibration trends are determined: good; satisfactorily; need improvement and unacceptable. After that, a decision is made to limit the functioning of these machines (prevention and stop). The introduction of standards and vibration monitoring will accelerate the transition to repairs of machines on the technical condition. Methods of rationing and monitoring can be used in other industries, for example, in the mining and metallurgical industries. © Published under licence by IOP Publishing Ltd.

The subject of the research is rationing and monitoring of the vibration of knife refiners. GOST 26493-85, specifying the permissible values of the vibration amplitude of the mills, is outdated. This standard does not take into account new designs of knife refiners and the requirements of national and international standards. It is proposed to establish two criteria for assessing the vibration state of the refiners. The first criterion normalizes the amplitude of vibration in octave strips of frequencies, while the second criterion specifies the vibration trend on the general level. It is proposed to use the vibration velocity as the measured parameter. The necessity of separating the refiners into two groups was revealed: with a disc or cone diameter up to 1000 mm and with a diameter over 1000 mm. The boundaries of zones and vibration trends are determined: good; satisfactorily; need improvement and unacceptable. After that, a decision is made to limit the functioning of these machines (prevention and stop). The introduction of standards and vibration monitoring will accelerate the transition to repairs of machines on the technical condition. Methods of rationing and monitoring can be used in other industries, for example, in the mining and metallurgical industries. © Published under licence by IOP Publishing Ltd.

Paper presents research of short-term monitoring of vibration response of turbine table top foundation structure in Power Plant Nikola Tesla - A: unit A4 in Obrenovac – Republic of Serbia. Research included short-term monitoring of vibration of the structure in ambient and in-operation condition, numerical modelling of the structure according to available information of masses and stiffness of structural elements, as well as extraction of mode shapes and operational deflection shapes. Measurement of vibrations, during in and out of operating conditions, carried at the same set of points on the upper slab of foundation supporting structure using sensitive accelerometers in frequency range of 0 - 300 Hz, while acquisition carried out using 24-bits acquisition system. Extraction of modes, frequencies and shapes, carried out using state of the art software package ARTeMIS. The same extraction procedure applied for extraction of deflection shapes according to acquired acceleration data during in-operation conditions. Numerical modelling performed using SAP2000 software package for structural static and dynamic analysis, with application of beam elements and additional masses with eccentricity from top level of the foundation structure. Additional masses, according to available data of weights of turbines, turbogenerator and other installed equipment, are taken into account. Finally, during analysis and comparison of experimental and numerical results, find out quite good matches of mode shapes and operational deflection shapes, which clearly have been discussed in conclusion.

This paper provides a review on condition monitoring analysis methods for electrical machines. An overview of condition monitoring is provided where online as well as offline monitoring is discussed. A section on vibration monitoring is included, since vibration monitoring is one of the most important online monitoring techniques. As part of vibration monitoring, background vibration, the effect of machine speed and load and variation of a signal at constant operating conditions are discussed. The paper further discussed time and process domain averaging, temperature effects, spurious low frequency ‘ski-slope’ effect and evaluation standards related to vibration monitoring. Various analysis methods exist for the condition monitoring of machines. These analysis methods are divided and discussed in this paper as deterministic and non-deterministic (or statistical analysis approach) methods. The paper ends with sections on condition monitoring measurements and noise filtering during condition monitoring

This paper provides a review on condition monitoring analysis methods for electrical machines. An overview of condition monitoring is provided where online as well as offline monitoring is discussed. A section on vibration monitoring is included, since vibration monitoring is one of the most important online monitoring techniques. As part of vibration monitoring, background vibration, the effect of machine speed and load and variation of a signal at constant operating conditions are discussed. The paper further discussed time and process domain averaging, temperature effects, spurious low frequency ‘ski-slope’ effect and evaluation standards related to vibration monitoring. Various analysis methods exist for the condition monitoring of machines. These analysis methods are divided and discussed in this paper as deterministic and non-deterministic (or statistical analysis approach) methods. The paper ends with sections on condition monitoring measurements and noise filtering during condition monitoring

Machining systems (i.e., machine tools, cutting processes and their interaction) cannot produce accurate parts if performance degradation due to wear in their subsystems (e.g., feed-drive systems and spindle units) is not identified, monitored and controlled. Appropriate maintenance actions delay the possible deterioration and minimize/avoids the machining system stoppage time that leads to lower productivity and higher production cost. Moreover, measuring and monitoring machine tool condition has become increasingly important due to the introduction of agile production, increased accuracy requirements for products and customers' requirements for quality assurance.Condition Based Maintenance (CBM) practices, such as vibration monitoring of machine tool spindle units, are therefore becoming a very attractive, but still challenging, method for companies operating high-value machines and components. CBM is being used to plan for maintenance action based on the condition of the machines and to prevent failures by solving the problems in advance as well as controlling the accuracy of the machining operations. By increasing the knowledge in this area, companies can save money through fewer acute breakdowns, reduction in inventory cost, reduction in repair times, and an increase in the robustness of the manufacturing processes leading to more predictable manufacturing. Hence, the CBM of machine tools ensures the basic conditions to deliver the right ability or capability of the right machine at the right time. One of the most common problems of rotating equipment such as spindles is the bearing condition (due to wear of the bearings). Failure of the bearings can cause major damage in a spindle. Vibration analysis is able to diagnose bearing failures by measuring the overall vibration of a spindle or, more precisely, by frequency analysis.Several factors should be taken into consideration to perform vibration monitoring on a machine tool’s spindle. Some of these factors are, QC 20170711

Due to the increasing share of new renewable energies like wind and solar in the generation of electricity the need for power regulation and energy storage is becoming of paramount importance. One of the systems to store huge amounts of energy is pumped storage using reversible hydropower units. The machines used in these power plants are pump-turbines, which can operate as a pump and as a turbine. The surplus of electrical energy during low consumption hours can be converted into potential hydraulic energy by pumping water to a higher level. The stored energy can be converted into electricity again by operating the runner as a turbine. Due to new regulation requirements machines have to extend the operating range in order to match energy generation with consumption for the grid stability. In this paper the consequences of extending the operating range in existing pump-turbines have been studied. For that purpose, the data obtained after two years of condition monitoring were analyzed. Vibrations and pressure fluctuations of two pump-turbines of 85 MW each have been studied during pump and turbine operation. For turbine operation the effects of extending the operating range from the standard range of 45–85 MW to and increased range of 20–85 MW were analyzed. The change in vibration levels and signatures at very low load are presented with the identification of the phenomena that occur under these conditions. The influence of head in the vibration behavior is also presented. The appearance of fluid instabilities generated at part load that may produce power swing is also presented. Finally, the effect of head on the vibration levels for pump operation is shown and analyzed., Postprint (published version)

Industriellt underhåll har upplevt en utveckling från det ursprungliga akuta avhjälpande underhållet till dagens möjligheter till underhåll baserat på data, så kallat tillståndsbaserat underhåll (CBM). För CBM genomförs endast underhåll vid behov och detta bestäms av aktuell data från den studerade utrustningen. Onödigt underhåll minimeras och antalet plötsliga haverier minskar. Utvecklingen mot Internet of Things (IoT) ger upphov till en stor mängd data som potentiellt kan användas vid CBM-underhåll. En utmaning uppstår dock i att identifiera sådan data och hur denna data kan användas. Denna studie har syftat till att undersöka hur sådan data kan identifieras och hur den kan tänkas användas vid CBM-underhåll. Studien har utförts tillsammans med Quant i Karlskrona där Quant genomför alla underhållsrelaterade aktiviteter åt ABB High Voltage Cables, ett industriföretag som tillverkar högspänningskablar. Arbetet har utgått från tre frågeställningar som har syftat till att: Identifiera datavariabler som kan tänkas ha relevans för CBM-underhåll. Tolka de identifierade datavariablerna för att bedöma hur de kan användas i CBM. Bedöma lämpligheten av en potentiell CBM-implementation baserat på identifierad data jämfört med existerande underhållsmetod. Arbetet har avgränsats genom att fokusera på ett enskilt företag och en enskild fabrik. Utöver detta har en avgränsning gjorts där fokus lagts på några få enskilda maskiner och komponenter. Sekretess har även behövt beaktas vid hantering av känslig information. Studien har huvudsakligen utförts kvalitativt, genom att på djupet fokusera på ett fåtal maskiner och komponenter. Arbetet har genomförts i nära samarbete med några av Quants anställda. Processdata har samlats in direkt från maskinerna och analyserats genom att identifiera och studera avvikelser i data. Intervjuer av olika slag, kompletterade med dokument, har varit en viktig metod för att inhämta information från anställda på Quant, både kring hur data kan tolkas men ä, Industrial maintenance has experienced an evolution from the initial corrective maintenance to the possibility of using data based maintenance techniques, so called condition-based maintenance (CBM). Maintenance is only performed when needed under CBM and this is decided based on the data retrieved from the studied equipment. Unnecessary maintenance is minimized and the number of sudden breakdowns decreases. The trend towards Internet of Things (IoT) gives rise to a large amount of data that can potentially be used in CBM maintenance. 'A challenge arises in identifying and using such data. This study has aimed to investigate how such data can be identified and how it might be used in CBM maintenance. This study has been carried out together with Quant in Karlskrona, Sweden, where Quant performs all maintenance related activities for ABB High Voltage Cables, an industrial manufacturing company. The study has been based on three questions that have aimed to: Identify data variables that might be relevant for CBM maintenance. Interpret the identified data variables to assess how they can be used in CBM. Assess the suitability of a potential CBM implementation based on the identified data compared to the existing maintenance method. The study has been delimited by focusing on a single company and a single factory. In addition, a delimitation has been made to focus on a few individual machines and components. A nondisclosure agreement also had to be considered when dealing with sensitive information. This study has mainly been conducted qualitatively, by focusing in-depth on a few machines and components. The work has been done in close collaboration with Quant’s employees. Process data has been collected from the machines and analyzed by identifying and studying data anomalies. Interviews, complemented with documents, has been an important method in obtaining information from Quant employees, both regarding how data can be interpreted but also on how the various process

Industriellt underhåll har upplevt en utveckling från det ursprungliga akuta avhjälpande underhållet till dagens möjligheter till underhåll baserat på data, så kallat tillståndsbaserat underhåll (CBM). För CBM genomförs endast underhåll vid behov och detta bestäms av aktuell data från den studerade utrustningen. Onödigt underhåll minimeras och antalet plötsliga haverier minskar. Utvecklingen mot Internet of Things (IoT) ger upphov till en stor mängd data som potentiellt kan användas vid CBM-underhåll. En utmaning uppstår dock i att identifiera sådan data och hur denna data kan användas. Denna studie har syftat till att undersöka hur sådan data kan identifieras och hur den kan tänkas användas vid CBM-underhåll. Studien har utförts tillsammans med Quant i Karlskrona där Quant genomför alla underhållsrelaterade aktiviteter åt ABB High Voltage Cables, ett industriföretag som tillverkar högspänningskablar. Arbetet har utgått från tre frågeställningar som har syftat till att: Identifiera datavariabler som kan tänkas ha relevans för CBM-underhåll. Tolka de identifierade datavariablerna för att bedöma hur de kan användas i CBM. Bedöma lämpligheten av en potentiell CBM-implementation baserat på identifierad data jämfört med existerande underhållsmetod. Arbetet har avgränsats genom att fokusera på ett enskilt företag och en enskild fabrik. Utöver detta har en avgränsning gjorts där fokus lagts på några få enskilda maskiner och komponenter. Sekretess har även behövt beaktas vid hantering av känslig information. Studien har huvudsakligen utförts kvalitativt, genom att på djupet fokusera på ett fåtal maskiner och komponenter. Arbetet har genomförts i nära samarbete med några av Quants anställda. Processdata har samlats in direkt från maskinerna och analyserats genom att identifiera och studera avvikelser i data. Intervjuer av olika slag, kompletterade med dokument, har varit en viktig metod för att inhämta information från anställda på Quant, både kring hur data kan tolkas men ä, Industrial maintenance has experienced an evolution from the initial corrective maintenance to the possibility of using data based maintenance techniques, so called condition-based maintenance (CBM). Maintenance is only performed when needed under CBM and this is decided based on the data retrieved from the studied equipment. Unnecessary maintenance is minimized and the number of sudden breakdowns decreases. The trend towards Internet of Things (IoT) gives rise to a large amount of data that can potentially be used in CBM maintenance. 'A challenge arises in identifying and using such data. This study has aimed to investigate how such data can be identified and how it might be used in CBM maintenance. This study has been carried out together with Quant in Karlskrona, Sweden, where Quant performs all maintenance related activities for ABB High Voltage Cables, an industrial manufacturing company. The study has been based on three questions that have aimed to: Identify data variables that might be relevant for CBM maintenance. Interpret the identified data variables to assess how they can be used in CBM. Assess the suitability of a potential CBM implementation based on the identified data compared to the existing maintenance method. The study has been delimited by focusing on a single company and a single factory. In addition, a delimitation has been made to focus on a few individual machines and components. A nondisclosure agreement also had to be considered when dealing with sensitive information. This study has mainly been conducted qualitatively, by focusing in-depth on a few machines and components. The work has been done in close collaboration with Quant’s employees. Process data has been collected from the machines and analyzed by identifying and studying data anomalies. Interviews, complemented with documents, has been an important method in obtaining information from Quant employees, both regarding how data can be interpreted but also on how the various process

Industriellt underhåll har upplevt en utveckling från det ursprungliga akuta avhjälpande underhållet till dagens möjligheter till underhåll baserat på data, så kallat tillståndsbaserat underhåll (CBM). För CBM genomförs endast underhåll vid behov och detta bestäms av aktuell data från den studerade utrustningen. Onödigt underhåll minimeras och antalet plötsliga haverier minskar. Utvecklingen mot Internet of Things (IoT) ger upphov till en stor mängd data som potentiellt kan användas vid CBM-underhåll. En utmaning uppstår dock i att identifiera sådan data och hur denna data kan användas. Denna studie har syftat till att undersöka hur sådan data kan identifieras och hur den kan tänkas användas vid CBM-underhåll. Studien har utförts tillsammans med Quant i Karlskrona där Quant genomför alla underhållsrelaterade aktiviteter åt ABB High Voltage Cables, ett industriföretag som tillverkar högspänningskablar. Arbetet har utgått från tre frågeställningar som har syftat till att: Identifiera datavariabler som kan tänkas ha relevans för CBM-underhåll. Tolka de identifierade datavariablerna för att bedöma hur de kan användas i CBM. Bedöma lämpligheten av en potentiell CBM-implementation baserat på identifierad data jämfört med existerande underhållsmetod. Arbetet har avgränsats genom att fokusera på ett enskilt företag och en enskild fabrik. Utöver detta har en avgränsning gjorts där fokus lagts på några få enskilda maskiner och komponenter. Sekretess har även behövt beaktas vid hantering av känslig information. Studien har huvudsakligen utförts kvalitativt, genom att på djupet fokusera på ett fåtal maskiner och komponenter. Arbetet har genomförts i nära samarbete med några av Quants anställda. Processdata har samlats in direkt från maskinerna och analyserats genom att identifiera och studera avvikelser i data. Intervjuer av olika slag, kompletterade med dokument, har varit en viktig metod för att inhämta information från anställda på Quant, både kring hur data kan tolkas men ä, Industrial maintenance has experienced an evolution from the initial corrective maintenance to the possibility of using data based maintenance techniques, so called condition-based maintenance (CBM). Maintenance is only performed when needed under CBM and this is decided based on the data retrieved from the studied equipment. Unnecessary maintenance is minimized and the number of sudden breakdowns decreases. The trend towards Internet of Things (IoT) gives rise to a large amount of data that can potentially be used in CBM maintenance. 'A challenge arises in identifying and using such data. This study has aimed to investigate how such data can be identified and how it might be used in CBM maintenance. This study has been carried out together with Quant in Karlskrona, Sweden, where Quant performs all maintenance related activities for ABB High Voltage Cables, an industrial manufacturing company. The study has been based on three questions that have aimed to: Identify data variables that might be relevant for CBM maintenance. Interpret the identified data variables to assess how they can be used in CBM. Assess the suitability of a potential CBM implementation based on the identified data compared to the existing maintenance method. The study has been delimited by focusing on a single company and a single factory. In addition, a delimitation has been made to focus on a few individual machines and components. A nondisclosure agreement also had to be considered when dealing with sensitive information. This study has mainly been conducted qualitatively, by focusing in-depth on a few machines and components. The work has been done in close collaboration with Quant’s employees. Process data has been collected from the machines and analyzed by identifying and studying data anomalies. Interviews, complemented with documents, has been an important method in obtaining information from Quant employees, both regarding how data can be interpreted but also on how the various process

Industriellt underhåll har upplevt en utveckling från det ursprungliga akuta avhjälpande underhållet till dagens möjligheter till underhåll baserat på data, så kallat tillståndsbaserat underhåll (CBM). För CBM genomförs endast underhåll vid behov och detta bestäms av aktuell data från den studerade utrustningen. Onödigt underhåll minimeras och antalet plötsliga haverier minskar. Utvecklingen mot Internet of Things (IoT) ger upphov till en stor mängd data som potentiellt kan användas vid CBM-underhåll. En utmaning uppstår dock i att identifiera sådan data och hur denna data kan användas. Denna studie har syftat till att undersöka hur sådan data kan identifieras och hur den kan tänkas användas vid CBM-underhåll. Studien har utförts tillsammans med Quant i Karlskrona där Quant genomför alla underhållsrelaterade aktiviteter åt ABB High Voltage Cables, ett industriföretag som tillverkar högspänningskablar. Arbetet har utgått från tre frågeställningar som har syftat till att: Identifiera datavariabler som kan tänkas ha relevans för CBM-underhåll. Tolka de identifierade datavariablerna för att bedöma hur de kan användas i CBM. Bedöma lämpligheten av en potentiell CBM-implementation baserat på identifierad data jämfört med existerande underhållsmetod. Arbetet har avgränsats genom att fokusera på ett enskilt företag och en enskild fabrik. Utöver detta har en avgränsning gjorts där fokus lagts på några få enskilda maskiner och komponenter. Sekretess har även behövt beaktas vid hantering av känslig information. Studien har huvudsakligen utförts kvalitativt, genom att på djupet fokusera på ett fåtal maskiner och komponenter. Arbetet har genomförts i nära samarbete med några av Quants anställda. Processdata har samlats in direkt från maskinerna och analyserats genom att identifiera och studera avvikelser i data. Intervjuer av olika slag, kompletterade med dokument, har varit en viktig metod för att inhämta information från anställda på Quant, både kring hur data kan tolkas men ä, Industrial maintenance has experienced an evolution from the initial corrective maintenance to the possibility of using data based maintenance techniques, so called condition-based maintenance (CBM). Maintenance is only performed when needed under CBM and this is decided based on the data retrieved from the studied equipment. Unnecessary maintenance is minimized and the number of sudden breakdowns decreases. The trend towards Internet of Things (IoT) gives rise to a large amount of data that can potentially be used in CBM maintenance. 'A challenge arises in identifying and using such data. This study has aimed to investigate how such data can be identified and how it might be used in CBM maintenance. This study has been carried out together with Quant in Karlskrona, Sweden, where Quant performs all maintenance related activities for ABB High Voltage Cables, an industrial manufacturing company. The study has been based on three questions that have aimed to: Identify data variables that might be relevant for CBM maintenance. Interpret the identified data variables to assess how they can be used in CBM. Assess the suitability of a potential CBM implementation based on the identified data compared to the existing maintenance method. The study has been delimited by focusing on a single company and a single factory. In addition, a delimitation has been made to focus on a few individual machines and components. A nondisclosure agreement also had to be considered when dealing with sensitive information. This study has mainly been conducted qualitatively, by focusing in-depth on a few machines and components. The work has been done in close collaboration with Quant’s employees. Process data has been collected from the machines and analyzed by identifying and studying data anomalies. Interviews, complemented with documents, has been an important method in obtaining information from Quant employees, both regarding how data can be interpreted but also on how the various process

Industriellt underhåll har upplevt en utveckling från det ursprungliga akuta avhjälpande underhållet till dagens möjligheter till underhåll baserat på data, så kallat tillståndsbaserat underhåll (CBM). För CBM genomförs endast underhåll vid behov och detta bestäms av aktuell data från den studerade utrustningen. Onödigt underhåll minimeras och antalet plötsliga haverier minskar. Utvecklingen mot Internet of Things (IoT) ger upphov till en stor mängd data som potentiellt kan användas vid CBM-underhåll. En utmaning uppstår dock i att identifiera sådan data och hur denna data kan användas. Denna studie har syftat till att undersöka hur sådan data kan identifieras och hur den kan tänkas användas vid CBM-underhåll. Studien har utförts tillsammans med Quant i Karlskrona där Quant genomför alla underhållsrelaterade aktiviteter åt ABB High Voltage Cables, ett industriföretag som tillverkar högspänningskablar. Arbetet har utgått från tre frågeställningar som har syftat till att: Identifiera datavariabler som kan tänkas ha relevans för CBM-underhåll. Tolka de identifierade datavariablerna för att bedöma hur de kan användas i CBM. Bedöma lämpligheten av en potentiell CBM-implementation baserat på identifierad data jämfört med existerande underhållsmetod. Arbetet har avgränsats genom att fokusera på ett enskilt företag och en enskild fabrik. Utöver detta har en avgränsning gjorts där fokus lagts på några få enskilda maskiner och komponenter. Sekretess har även behövt beaktas vid hantering av känslig information. Studien har huvudsakligen utförts kvalitativt, genom att på djupet fokusera på ett fåtal maskiner och komponenter. Arbetet har genomförts i nära samarbete med några av Quants anställda. Processdata har samlats in direkt från maskinerna och analyserats genom att identifiera och studera avvikelser i data. Intervjuer av olika slag, kompletterade med dokument, har varit en viktig metod för att inhämta information från anställda på Quant, både kring hur data kan tolkas men ä, Industrial maintenance has experienced an evolution from the initial corrective maintenance to the possibility of using data based maintenance techniques, so called condition-based maintenance (CBM). Maintenance is only performed when needed under CBM and this is decided based on the data retrieved from the studied equipment. Unnecessary maintenance is minimized and the number of sudden breakdowns decreases. The trend towards Internet of Things (IoT) gives rise to a large amount of data that can potentially be used in CBM maintenance. 'A challenge arises in identifying and using such data. This study has aimed to investigate how such data can be identified and how it might be used in CBM maintenance. This study has been carried out together with Quant in Karlskrona, Sweden, where Quant performs all maintenance related activities for ABB High Voltage Cables, an industrial manufacturing company. The study has been based on three questions that have aimed to: Identify data variables that might be relevant for CBM maintenance. Interpret the identified data variables to assess how they can be used in CBM. Assess the suitability of a potential CBM implementation based on the identified data compared to the existing maintenance method. The study has been delimited by focusing on a single company and a single factory. In addition, a delimitation has been made to focus on a few individual machines and components. A nondisclosure agreement also had to be considered when dealing with sensitive information. This study has mainly been conducted qualitatively, by focusing in-depth on a few machines and components. The work has been done in close collaboration with Quant’s employees. Process data has been collected from the machines and analyzed by identifying and studying data anomalies. Interviews, complemented with documents, has been an important method in obtaining information from Quant employees, both regarding how data can be interpreted but also on how the various process

Industriellt underhåll har upplevt en utveckling från det ursprungliga akuta avhjälpande underhållet till dagens möjligheter till underhåll baserat på data, så kallat tillståndsbaserat underhåll (CBM). För CBM genomförs endast underhåll vid behov och detta bestäms av aktuell data från den studerade utrustningen. Onödigt underhåll minimeras och antalet plötsliga haverier minskar. Utvecklingen mot Internet of Things (IoT) ger upphov till en stor mängd data som potentiellt kan användas vid CBM-underhåll. En utmaning uppstår dock i att identifiera sådan data och hur denna data kan användas. Denna studie har syftat till att undersöka hur sådan data kan identifieras och hur den kan tänkas användas vid CBM-underhåll. Studien har utförts tillsammans med Quant i Karlskrona där Quant genomför alla underhållsrelaterade aktiviteter åt ABB High Voltage Cables, ett industriföretag som tillverkar högspänningskablar. Arbetet har utgått från tre frågeställningar som har syftat till att: Identifiera datavariabler som kan tänkas ha relevans för CBM-underhåll. Tolka de identifierade datavariablerna för att bedöma hur de kan användas i CBM. Bedöma lämpligheten av en potentiell CBM-implementation baserat på identifierad data jämfört med existerande underhållsmetod. Arbetet har avgränsats genom att fokusera på ett enskilt företag och en enskild fabrik. Utöver detta har en avgränsning gjorts där fokus lagts på några få enskilda maskiner och komponenter. Sekretess har även behövt beaktas vid hantering av känslig information. Studien har huvudsakligen utförts kvalitativt, genom att på djupet fokusera på ett fåtal maskiner och komponenter. Arbetet har genomförts i nära samarbete med några av Quants anställda. Processdata har samlats in direkt från maskinerna och analyserats genom att identifiera och studera avvikelser i data. Intervjuer av olika slag, kompletterade med dokument, har varit en viktig metod för att inhämta information från anställda på Quant, både kring hur data kan tolkas men ä, Industrial maintenance has experienced an evolution from the initial corrective maintenance to the possibility of using data based maintenance techniques, so called condition-based maintenance (CBM). Maintenance is only performed when needed under CBM and this is decided based on the data retrieved from the studied equipment. Unnecessary maintenance is minimized and the number of sudden breakdowns decreases. The trend towards Internet of Things (IoT) gives rise to a large amount of data that can potentially be used in CBM maintenance. 'A challenge arises in identifying and using such data. This study has aimed to investigate how such data can be identified and how it might be used in CBM maintenance. This study has been carried out together with Quant in Karlskrona, Sweden, where Quant performs all maintenance related activities for ABB High Voltage Cables, an industrial manufacturing company. The study has been based on three questions that have aimed to: Identify data variables that might be relevant for CBM maintenance. Interpret the identified data variables to assess how they can be used in CBM. Assess the suitability of a potential CBM implementation based on the identified data compared to the existing maintenance method. The study has been delimited by focusing on a single company and a single factory. In addition, a delimitation has been made to focus on a few individual machines and components. A nondisclosure agreement also had to be considered when dealing with sensitive information. This study has mainly been conducted qualitatively, by focusing in-depth on a few machines and components. The work has been done in close collaboration with Quant’s employees. Process data has been collected from the machines and analyzed by identifying and studying data anomalies. Interviews, complemented with documents, has been an important method in obtaining information from Quant employees, both regarding how data can be interpreted but also on how the various process

At present, pumped storage is the only system to store huge amounts of energy. The surplus of energy in the electrical grid is used for pumping water from a lower to a higher reservoir (pump operation). At peak hours or in case of emergency this water goes down generating electrical energy (turbine operation). In the last years, due to the massive entrance of wind power, the number of start and stop cycles have increased dramatically as well as the operation at very low loads. In this new scenario more cases of damage have been reported and an effective vibration monitoring is necessary. Reversible pump-turbines (RPT) are high performance machines that have to change operation from pump to turbine mode (reversing runner rotation and flow direction) in a short time. Due to their special design characteristics (large power concentration) and operating conditions, they generate large pressure pulsations and forces when in operation. In this paper the vibration monitoring of large RPT units have been analysed. The results obtained after 15 years of monitoring several power plants with this type of machines have been used for the analysis. In the last years, most of the supervised power plants have been monitored on-line remotely. First the monitoring system used is described. The main types of excitation forces expected during the operation of these machines are studied especially the most characteristic and distinctive that are the pressure pulsations due to the rotor/stator interaction. The vibration signatures measured in machines with different designs are analysed in detail and compared with the signatures of conventional turbines. The influence of the operation type (as a pump and or as a turbine) and on the power delivered has been studied and the changes of the signatures presented. After the analysis of the vibration signatures the procedure used for the selection of spectral bands is explained. The analysis of the results obtained with the monitoring is shown., Postprint (author's final draft)

Wireless Sensor Networks (WSNs), in addition to enabling monitoring solutions for numerous new applications areas, have gained huge popularity as a cost-effective, dynamically scalable, easy to deploy and maintainable alternatives to conventional infrastructure-based monitoring solutions. A WSN consists of spatially distributed autonomous wireless sensor nodes that measure desired physical phenomena and operate in a collaborative manner to relay the acquired information wirelessly to a central location. A wireless sensor node, integrating the required resources to enable infrastructure-less distributed monitoring, is constrained by its size, cost and energy. In order to address these constraints, a typical wireless sensor node is designed based on low-power and low-cost modules that in turn provide limited communication and processing performances. Data and computation intensive wireless monitoring applications, on the other hand, not only demand higher communication bandwidth and computational performance but also require practically feasible operational lifetimes so as to reduce the maintenance cost associated with the replacement of batteries. In relation to the communication and processing requirements of such applications and the constraints associated with a typical wireless sensor node, this thesis explores energy efficient wireless sensor node architecture that enables realization of data and computation intensive applications. Architectures enabling raw data transmission and in-sensor processing with various technological alternatives are explored. The potential architectural alternatives are evaluated both analytically and quantitatively with regards to different design parameters, in particular, the performance and the energy consumption. For quantitative evaluation purposes, the experiments are conducted on vibration and image-based industrial condition monitoring applications that are not only data and computation intensive but also are of practical imp

In recent years, the use of fibre-reinforced composite laminates in aerospace, mechanical, and other structural applications has become very popular due to their low density and attractive mechanical properties. However, the low inter-laminar strength of composite laminates makes them predisposed to internal damage in the form of delamination, which leads to loss of structural integrity. It is necessary to detect and assess the severity of possible delamination damage, particularly in aircraft components as early as possible in order to ensure safe operation and prevent loss of life. Detection of delaminations in composite laminates using traditional NDI techniques such as, ultrasonic testing requires aircraft to be grounded, which significantly increases maintenance cost. Implementation of structural health monitoring techniques, which can be applied online and in situ is desirable both in terms of reducing cost as well as detecting damage as soon as it occurs. Vibration monitoring offers promise in this regard.This thesis investigates the use of system identification using vibration measurements to detect and assess delaminations in composite laminates. System identification involves constructing a dynamic model of the structure through identifying system parameters from the measured dynamic response of the structure. In this study, State Space Finite Element System is employed to construct the model and the system parameters such as stiffness and damping are identified using Eigen Realization Algorithm (ERA) from the response of the structure to impulse or other forms of excitation. Damage is identified and located from unexpected variations in the system parameters, specifically, the element stiffness coefficients. A methodology is developed to assess the severity of damage by comparing the reductions in estimated stiffness values to those predicted by theory for the undamaged laminate. The proposed damage assessment technique is first applied to composite beams

Wireless Sensor Networks (WSNs), in addition to enabling monitoring solutions for numerous new applications areas, have gained huge popularity as a cost-effective, dynamically scalable, easy to deploy and maintainable alternatives to conventional infrastructure-based monitoring solutions. A WSN consists of spatially distributed autonomous wireless sensor nodes that measure desired physical phenomena and operate in a collaborative manner to relay the acquired information wirelessly to a central location. A wireless sensor node, integrating the required resources to enable infrastructure-less distributed monitoring, is constrained by its size, cost and energy. In order to address these constraints, a typical wireless sensor node is designed based on low-power and low-cost modules that in turn provide limited communication and processing performances. Data and computation intensive wireless monitoring applications, on the other hand, not only demand higher communication bandwidth and computational performance but also require practically feasible operational lifetimes so as to reduce the maintenance cost associated with the replacement of batteries. In relation to the communication and processing requirements of such applications and the constraints associated with a typical wireless sensor node, this thesis explores energy efficient wireless sensor node architecture that enables realization of data and computation intensive applications. Architectures enabling raw data transmission and in-sensor processing with various technological alternatives are explored. The potential architectural alternatives are evaluated both analytically and quantitatively with regards to different design parameters, in particular, the performance and the energy consumption. For quantitative evaluation purposes, the experiments are conducted on vibration and image-based industrial condition monitoring applications that are not only data and computation intensive but also are of practical imp

Wireless Sensor Networks (WSNs), in addition to enabling monitoring solutions for numerous new applications areas, have gained huge popularity as a cost-effective, dynamically scalable, easy to deploy and maintainable alternatives to conventional infrastructure-based monitoring solutions. A WSN consists of spatially distributed autonomous wireless sensor nodes that measure desired physical phenomena and operate in a collaborative manner to relay the acquired information wirelessly to a central location. A wireless sensor node, integrating the required resources to enable infrastructure-less distributed monitoring, is constrained by its size, cost and energy. In order to address these constraints, a typical wireless sensor node is designed based on low-power and low-cost modules that in turn provide limited communication and processing performances. Data and computation intensive wireless monitoring applications, on the other hand, not only demand higher communication bandwidth and computational performance but also require practically feasible operational lifetimes so as to reduce the maintenance cost associated with the replacement of batteries. In relation to the communication and processing requirements of such applications and the constraints associated with a typical wireless sensor node, this thesis explores energy efficient wireless sensor node architecture that enables realization of data and computation intensive applications. Architectures enabling raw data transmission and in-sensor processing with various technological alternatives are explored. The potential architectural alternatives are evaluated both analytically and quantitatively with regards to different design parameters, in particular, the performance and the energy consumption. For quantitative evaluation purposes, the experiments are conducted on vibration and image-based industrial condition monitoring applications that are not only data and computation intensive but also are of practical imp

Wireless Sensor Networks (WSNs), in addition to enabling monitoring solutions for numerous new applications areas, have gained huge popularity as a cost-effective, dynamically scalable, easy to deploy and maintainable alternatives to conventional infrastructure-based monitoring solutions. A WSN consists of spatially distributed autonomous wireless sensor nodes that measure desired physical phenomena and operate in a collaborative manner to relay the acquired information wirelessly to a central location. A wireless sensor node, integrating the required resources to enable infrastructure-less distributed monitoring, is constrained by its size, cost and energy. In order to address these constraints, a typical wireless sensor node is designed based on low-power and low-cost modules that in turn provide limited communication and processing performances. Data and computation intensive wireless monitoring applications, on the other hand, not only demand higher communication bandwidth and computational performance but also require practically feasible operational lifetimes so as to reduce the maintenance cost associated with the replacement of batteries. In relation to the communication and processing requirements of such applications and the constraints associated with a typical wireless sensor node, this thesis explores energy efficient wireless sensor node architecture that enables realization of data and computation intensive applications. Architectures enabling raw data transmission and in-sensor processing with various technological alternatives are explored. The potential architectural alternatives are evaluated both analytically and quantitatively with regards to different design parameters, in particular, the performance and the energy consumption. For quantitative evaluation purposes, the experiments are conducted on vibration and image-based industrial condition monitoring applications that are not only data and computation intensive but also are of practical imp

Wireless Sensor Networks (WSNs), in addition to enabling monitoring solutions for numerous new applications areas, have gained huge popularity as a cost-effective, dynamically scalable, easy to deploy and maintainable alternatives to conventional infrastructure-based monitoring solutions. A WSN consists of spatially distributed autonomous wireless sensor nodes that measure desired physical phenomena and operate in a collaborative manner to relay the acquired information wirelessly to a central location. A wireless sensor node, integrating the required resources to enable infrastructure-less distributed monitoring, is constrained by its size, cost and energy. In order to address these constraints, a typical wireless sensor node is designed based on low-power and low-cost modules that in turn provide limited communication and processing performances. Data and computation intensive wireless monitoring applications, on the other hand, not only demand higher communication bandwidth and computational performance but also require practically feasible operational lifetimes so as to reduce the maintenance cost associated with the replacement of batteries. In relation to the communication and processing requirements of such applications and the constraints associated with a typical wireless sensor node, this thesis explores energy efficient wireless sensor node architecture that enables realization of data and computation intensive applications. Architectures enabling raw data transmission and in-sensor processing with various technological alternatives are explored. The potential architectural alternatives are evaluated both analytically and quantitatively with regards to different design parameters, in particular, the performance and the energy consumption. For quantitative evaluation purposes, the experiments are conducted on vibration and image-based industrial condition monitoring applications that are not only data and computation intensive but also are of practical imp

Fibre-reinforced polymer composite laminates are now commonly used in many structural applications, especially in the aerospace industry, where margins of safety are kept low in order to minimise weight. Timely detection and assessment of delaminations in composite laminates is therefore critical, as they can cause loss of structural integrity affecting the safe operation of the aircraft. Traditional NDI methods are time consuming and expensive since they require aircraft to be grounded for inspections. The current trend therefore is towards implementation of structural health monitoring systems which can monitor the structure in situ without down time. Vibration monitoring is one method which has the potential for such application. Among different methods of vibration monitoring, frequency monitoring is the simplest to implement, requiring only single point measurement, and is accurate and reliable. However, while reductions in natural frequencies clearly indicate the presence of damage, the assessment of the location and severity of the damage from measured shifts in frequencies requires the solution of the inverse problem. There have been few comprehensive studies in the past on the efficacy of delamination assessment from measured frequencies solving the inverse problem, especially for laminated plates.In this thesis, three different methods of solving the inverse problem to estimate delamination parameters from measured frequency shifts are investigated: the graphical method, artificial neural network and surrogate assisted optimisation, all applied initially to composite beams with delaminations at different interfaces. The graphical technique has been extended to the three variable problem of assessing delamination size, axial location and interface location for the first time. The artificial neural network and surrogate assisted optimisation are also applied to the five-variable problem of delaminations in plates (two dimensions and three coordinates for the

In the field of structural health monitoring or machine condition monitoring, most vibration based methods reported in the literature require to measure responses at several locations on the structure. In machine condition monitoring, the number of available vibration sensors is often small and it is not unusual that only one single sensor is used to monitor a machine. The aim of this paper is to propose an extension of fault detection techniques that may be used when a reduced set of sensors or even one single sensor is available. Fault detection techniques considered here are based on output-only methods coming from the Blind Source Separation (BSS) family, namely Principal Component Analysis (PCA) and Second Order Blind Identification (SOBI). The advantages of PCA or SOBI rely on their rapidity of use and their reliability. Based on these methods, subspace identification may be performed by using the concept of block Hankel matrices which make possible the use of only one single measurement signal. Thus, the problem of fault detection in mechanical systems can be solved by using subspaces built from active principal components or modal vectors. It consists in comparing subspace features between the reference (undamaged) state and a current state. The angular coherence between subspaces is a good indicator of a dynamic change in the system due to the occurrence of faults or damages. The robustness of the methods is illustrated on industrial examples.

In the field of structural health monitoring or machine condition monitoring, most vibration based methods reported in the literature require to measure responses at several locations on the structure. In machine condition monitoring, the number of available vibration sensors is often small and it is not unusual that only one single sensor is used to monitor a machine. The aim of this paper is to propose an extension of fault detection techniques that may be used when a reduced set of sensors or even one single sensor is available. Fault detection techniques considered here are based on output-only methods coming from the Blind Source Separation (BSS) family, namely Principal Component Analysis (PCA) and Second Order Blind Identification (SOBI). The advantages of PCA or SOBI rely on their rapidity of use and their reliability. Based on these methods, subspace identification may be performed by using the concept of block Hankel matrices which make possible the use of only one single measurement signal. Thus, the problem of fault detection in mechanical systems can be solved by using subspaces built from active principal components or modal vectors. It consists in comparing subspace features between the reference (undamaged) state and a current state. The angular coherence between subspaces is a good indicator of a dynamic change in the system due to the occurrence of faults or damages. The robustness of the methods is illustrated on industrial examples.

The hardware-software organization of computer multichannel systems of the vibrating control is considered. Application of such systems provides carrying out in a mode of real time of the continuous control over a vibrating condition of technical objects, the decision of problems of the signal system and protection by individual criteria in an automatic mode. Ways of the analysis of long realizations of vibrating signals for detection of diagnostic attributes are offered.

The real-time displacement analysis and correction of vibration forces on the rotor of a rotational active magnetic bearing (AMB) system were performed. The real-time system performs four main tasks: fault detection, fault diagnosis, error correction and fault identification. Historical fault data from a fully suspended 250 kW water cooling AMB pump was used in the design process of the fault detection system. A double radial AMB test rack was used to test the effectiveness of the proposed real-time system. The real-time system corrected, identified and minimized the vibration forces to a stable working condition

The real-time displacement analysis and correction of vibration forces on the rotor of a rotational active magnetic bearing (AMB) system were performed. The real-time system performs four main tasks: fault detection, fault diagnosis, error correction and fault identification. Historical fault data from a fully suspended 250 kW water cooling AMB pump was used in the design process of the fault detection system. A double radial AMB test rack was used to test the effectiveness of the proposed real-time system. The real-time system corrected, identified and minimized the vibration forces to a stable working condition

The real-time displacement analysis and correction of vibration forces on the rotor of a rotational active magnetic bearing (AMB) system were performed. The real-time system performs four main tasks: fault detection, fault diagnosis, error correction and fault identification. Historical fault data from a fully suspended 250 kW water cooling AMB pump was used in the design process of the fault detection system. A double radial AMB test rack was used to test the effectiveness of the proposed real-time system. The real-time system corrected, identified and minimized the vibration forces to a stable working condition

Dynamic Compaction is a well established ground improvement technique in which a heavy pounder is dropped from a significant height to improve the soil’s mechanical properties. The pounder impact creates waves that compact the soil; however these waves may also be a nuisance to and damage neighbouring structures and facilities. Peak particle velocity (PPV) has been identified as the most suitable parameter for assessing vibration associated risks. Previous researchers have proposed a number different equations for predicting PPV. Dynamic Compaction has recently been used for soil improvement in Oman’s Blue City Project. Particle velocities and vibration frequencies in three directions have been monitored at several distances during the different phases of ground treatment. In all phases PPV has been recorded to be in the radial direction. It has been observed that although it appears that vibration frequency is not influenced by the deep compaction phase, does increase with the progression of work and application of later phases of Dynamic Compaction. This increase is more pronounced at farther distances, but becomes negligible when impact point is closer than a critical distance.

Vibro Compaction is a ground improvement technique in which the soil is compacted using waves generated from an equipment called a vibroflot. As the vibration magnitude is less than some other vibratory ground improvement methods this technique is sometimes preferred when the improvement zone is relatively close to existing structures and facilities. Unfortunately, not much can be found in literature on peak particle velocity (PPV) that is generated by this method. This paper reports and interprets vibration monitoring of a Vibro Compaction project that was recently performed on about 13 m of hydraulically placed sand in Palm Jumeira, Dubai. PPV was measured at different distances from the vibroflot. The depth of the vibroflot was also varied to provide a better understanding of the critical depth that creates the largest PPV. A formula is also presented to estimate Vibro Compaction generated PPV during planning stage.

The thesis deals with the non-destructive condition assessment of civil engineering structures made of reinforced and prestressed concrete as well as bridges and concentrates on a comparison of static and dynamic investigation methods. The main questions discuss the sensitivity of changes in static as well as in dynamic properties during the mechanical lifetime of those types of structures under laboratory conditions, the sensitivity of these changes when testing in-situ and the dimension of undesired environmental influences on the dynamic properties. Therefore, a gradually loaded laboratory reinforced concrete beam (cp. chapter 7) and a reinforced as well as a prestressed concrete slab (cp. chapter 8) are investigated for changes in their static and dynamic parameters until reaching their ultimate loads. Furthermore, a successively damaged and stepwise loaded laboratory reinforced concrete slab and a prestressed concrete slab (cp. also chapter 8) are under investigation and also compared in changes in their static as well as in dynamic properties during their lifetimes. By means of static and dynamic tests on a successively damaged and stepwise loaded prestressed concrete bridge (cp. chapter 9) it was possible to investigate the amount of changes in static and dynamic properties for a real in-situ object. A long-term measurement of a composite bridge (cp. chapter 10) demonstrates the environmental influences on the static and dynamic properties of a system which have to be considered when conducting comparative non-destructive condition assessment techniques on real objects. All tests are calculated respectively simulated by the method of the integration of stress (cp. chapter 6) or the finite element method by using the softwares ANSYS and SOFISTIK. Furthermore, measured eigenfrequencies and modeshapes are used to adapt finite element models with the aim to improve the model or to locate and quantify damaged areas. The work is a contribution to the application of

The thesis deals with the non-destructive condition assessment of civil engineering structures made of reinforced and prestressed concrete as well as bridges and concentrates on a comparison of static and dynamic investigation methods. The main questions discuss the sensitivity of changes in static as well as in dynamic properties during the mechanical lifetime of those types of structures under laboratory conditions, the sensitivity of these changes when testing in-situ and the dimension of undesired environmental influences on the dynamic properties. Therefore, a gradually loaded laboratory reinforced concrete beam (cp. chapter 7) and a reinforced as well as a prestressed concrete slab (cp. chapter 8) are investigated for changes in their static and dynamic parameters until reaching their ultimate loads. Furthermore, a successively damaged and stepwise loaded laboratory reinforced concrete slab and a prestressed concrete slab (cp. also chapter 8) are under investigation and also compared in changes in their static as well as in dynamic properties during their lifetimes. By means of static and dynamic tests on a successively damaged and stepwise loaded prestressed concrete bridge (cp. chapter 9) it was possible to investigate the amount of changes in static and dynamic properties for a real in-situ object. A long-term measurement of a composite bridge (cp. chapter 10) demonstrates the environmental influences on the static and dynamic properties of a system which have to be considered when conducting comparative non-destructive condition assessment techniques on real objects. All tests are calculated respectively simulated by the method of the integration of stress (cp. chapter 6) or the finite element method by using the softwares ANSYS and SOFISTIK. Furthermore, measured eigenfrequencies and modeshapes are used to adapt finite element models with the aim to improve the model or to locate and quantify damaged areas. The work is a contribution to the application of

It is usual when using CM technology for assessing the state of a component and planning maintenance actions using predetermined levels for warnings and replacements. The replacement of a damaged component is usually done at lower or higher than the predetermined level, which both means losses. This is because the probability of doing replacements just at the predetermined level is negligibly small. The accuracy in the assessment of the condition of a component has big technical and economic impact on the output of the machine, production process and consequently company profitability and competitiveness. The higher the accuracy in assessing the condition of a component yields higher probability of avoiding failures and planning maintenance actions at low costs. In this paper, techniques for assessing the state of a component using both mechanistic and other statistical approaches are considered. This paper also applies Cumulative Sum (CUSUM) Chart for identifying the time of damage initiation and reducing false alarms. Techniques for assessing the probability of failure of a component and its residual life, and predicting the vibration level at the next planned measuring opportunity or planned stoppage are introduced, discussed, computerised and tested. The problem addressed is: How is it possible to increase the accuracy of assessing the condition of a component? The major result achieved is; development of a model for more accurate assessment of the condition of a component/equipment through combining different approaches. The main conclusion that can be drawn is; applying the model, it is possible to enhance the accuracy of assessment of the condition of a component/equipment and consequently maintenance decision since the integrated model provides comprehensive and relevant information in one platform., Dynamic Decisions in Maintenance (EU-IP DYNAMITE)

A class of smart paint sensors is proposed for monitoring the structural vibration of beams. The sensor is manufactured from an epoxy resin which is mixed with carbon black nano-particles to make it electrically conducting and sensitive to mechanical excitations. A comprehensive theoretical and experimental investigation is presented to understand the underlying phenomena governing the operation of this class of paint sensors and evaluate its performance characteristics. A theoretical model is developed to model the electromechanical behavior of the sensor system as a lumped-parameter system using the Debye and the Cole-Cole equations. The sensor equations are integrated also with a finite element model of a base beam to which the sensor is bonded to. The resulting multi-field model is utilized to predict the behavior of both the sensor and the beam when subjected to a wide variety of vibration excitations. The predictions of the multi-field finite element model are validated experimentally and the behavior of the sensor is evaluated both in the time and the frequency domains. The performance of the sensor is compared with the performance of conventional strain gages to emphasize its potential and merits. The presented techniques are currently being extended to sensors that can monitor the vibration and structural power flow of two dimensional structures.

Proper management of technical risks during blasting facilitates efficient project management and helps keeping costs and safety at an acceptable level. it is of crucial importance to incorporate the process of risk management in the design and execution of the project. Risk analyses of the environmental effect of blast-induced vibrations are, in many cases, based on crude concepts which do not take into consideration the fundamental nature of vibratory motion. Realistic modeling of wave propagation in soil and rock requires that correct dynamic parameters are considered and appropriate attenuation models are applied. It is possible to apply relatively simple vibration attenuation concepts for prediction of vibrations in soil and rock and their interaction with structures on or below the ground surface., QC 20120105

Prediction and monitoring of vibrations from rock blasting is of practical importance. Damage to rock tunnels caused by blasting is fundamentally different to that of conventional buildings. Different damage mechanisms are discussed as well as methods to monitor the development of cracks by analysis of frequency content. For the assessment of the damage potential it is essential to understand wave propagation in rock and the dynamic response of cavities to vibration excitation. Vibration frequency and wavelength in relation to the size of the cavity are important parameters. Vibration amplification of a circular tunnel to a plane wave is analyzed and guidelines given for practical design applications. Filtering the vibration signal, which is often required in national standards, car. give misleading results for tunnels in rock., QC 20120109

In this paper, the authors distinguish between three real-time fault detection, correction and identification schemes for vibration forces on the rotor of a rotational active magnetic bearing (AMB) system. Historical fault data obtained from a fully suspended 250 kW water cooling AMB pump was used in the design process of the three schemes. The real-time schemes perform three main tasks: 1) fault detection, 2) fault diagnosis and error correction and 3) fault identification. Displacement and current masking were performed during the fault detection stage and the vibratory amplitudes and frequencies were extracted by means of the Wigner-Ville distribution. Pattern recognition techniques, statistical diagnosis and fuzzy logic were used to calculate fault features during the fault diagnosis and error correction stages. During the fault identification stage, data fitting, fuzzy logic and ISO standards were used to calculate the type, parameters, vibratory level and zone of the vibration force. A comparison between the experimental results obtained from a double radial AMB test rack was performed to demonstrate the effectiveness of the proposed schemes in the real-time detection, correction and identification of vibration forces on the rotor of a rotational AMB system. The three real-time schemes were able to correct and minimize vibration forces to a stable working condition

In this paper, the authors distinguish between three real-time fault detection, correction and identification schemes for vibration forces on the rotor of a rotational active magnetic bearing (AMB) system. Historical fault data obtained from a fully suspended 250 kW water cooling AMB pump was used in the design process of the three schemes. The real-time schemes perform three main tasks: 1) fault detection, 2) fault diagnosis and error correction and 3) fault identification. Displacement and current masking were performed during the fault detection stage and the vibratory amplitudes and frequencies were extracted by means of the Wigner-Ville distribution. Pattern recognition techniques, statistical diagnosis and fuzzy logic were used to calculate fault features during the fault diagnosis and error correction stages. During the fault identification stage, data fitting, fuzzy logic and ISO standards were used to calculate the type, parameters, vibratory level and zone of the vibration force. A comparison between the experimental results obtained from a double radial AMB test rack was performed to demonstrate the effectiveness of the proposed schemes in the real-time detection, correction and identification of vibration forces on the rotor of a rotational AMB system. The three real-time schemes were able to correct and minimize vibration forces to a stable working condition

In this paper, the authors distinguish between three real-time fault detection, correction and identification schemes for vibration forces on the rotor of a rotational active magnetic bearing (AMB) system. Historical fault data obtained from a fully suspended 250 kW water cooling AMB pump was used in the design process of the three schemes. The real-time schemes perform three main tasks: 1) fault detection, 2) fault diagnosis and error correction and 3) fault identification. Displacement and current masking were performed during the fault detection stage and the vibratory amplitudes and frequencies were extracted by means of the Wigner-Ville distribution. Pattern recognition techniques, statistical diagnosis and fuzzy logic were used to calculate fault features during the fault diagnosis and error correction stages. During the fault identification stage, data fitting, fuzzy logic and ISO standards were used to calculate the type, parameters, vibratory level and zone of the vibration force. A comparison between the experimental results obtained from a double radial AMB test rack was performed to demonstrate the effectiveness of the proposed schemes in the real-time detection, correction and identification of vibration forces on the rotor of a rotational AMB system. The three real-time schemes were able to correct and minimize vibration forces to a stable working condition