Search

This paper presents a comprehensive non-contact computer vision-based system for monitoring cable vibrations in cable-supported bridges, addressing challenges related to low image resolution and feature extraction difficulties at long distances. The proposed system utilizes deep learning techniques to enhance cable vibration recognition accuracy and offers a practical solution for cable monitoring without the need for target assistance. The core of the system is a novel two-stage model, which combines a super-resolution (SR) video reconstruction algorithm with state-of-the-art Resnet-34 and Swin-B models for precise target foreground segmentation. This approach significantly improves the recognition of target details and enhances the accuracy of cable vibration data in monitoring videos. Furthermore, a phase-based motion estimation (PME) algorithm is employed for precise cable vibration measurement. Field tests conducted on two cable-supported bridges validate the effectiveness of the system. The results demonstrate superior accuracy and noise immunity compared to traditional methods, achieving sub-pixel level precision with a maximum error rate below 2%. This system represents a significant advancement in non-contact structural health monitoring for long-distance cable vibration monitoring in cable-supported bridges. [ABSTRACT FROM AUTHOR]

The dispersion of structural waves, where wave speed varies with frequency, introduces significant challenges in accurately localizing occupants in a building based on vibrations caused by their movements. This study presents a novel multi-sensor vibro-localization technique that accounts for dispersion effects, enhancing the accuracy and robustness of occupant localization. The proposed method utilizes a model-based approach to parameterize key propagation phenomena, including wave dispersion and attenuation, which are fitted to observed waveforms. The localization is achieved by maximizing the joint likelihood of the occupant's location based on sensor measurements. The effectiveness of the proposed technique is validated using two experimental datasets: one from a controlled environment involving an aluminum plate and the other from a building-scale experiment conducted at Goodwin Hall, Virginia Tech. Results for the proposed algorithm demonstrates a significant improvement in localization accuracy compared to benchmark algorithms. Specifically, in the aluminum plate experiments, the proposed technique reduced the average localization precision from 7.77 cm to 1.97 cm, representing a ∼74% improvement. Similarly, in the Goodwin Hall experiments, the average localization error decreased from 0.67 m to 0.3 m, with a ∼55% enhancement in accuracy. These findings indicate that the proposed approach outperforms existing methods in accurately determining occupant locations, even in the presence of dispersive wave propagation. [ABSTRACT FROM AUTHOR]

In this study, we introduce progress in intelligent control for reducing structural vibrations. The field of intelligent control for dampening structural vibrations is evolving rapidly, driven by advancements in materials science, AI, and actuator technology. These innovations have led to more efficient, reliable, and adaptable vibration-control systems with applications ranging from civil engineering to aerospace. The use of smart materials has opened new avenues for vibration control of piezoelectric materials. When mechanical stress is applied to these materials, an electric charge response is formed, allowing for precise control over the vibrations. Improved computational models and simulations play crucial roles in the design and testing of vibration-control systems. Finite element analysis helps in accurately predicting the behavior of structures under various loads, thereby aiding in the design of effective vibration-control systems. In our work, we use intelligent control theory to dampen structural vibrations in engineering structures.

Abstract In designing control systems, it is known that fractional-order proportional integral derivative (FOPID) controllers often provide greater flexibility than conventional proportional integral derivative (PID) controllers. This higher level of flexibility has proven to be extremely valuable for various applications such as vibration suppression in structural engineering. In this paper, we study the optimization of FOPID controllers using twelve well-established algorithms to minimize structural responses under seismic excitations. The algorithms include crystal structure algorithm (CryStAl), stochastic paint optimizer, particle swarm optimization, krill herd, harmony search, ant colony optimization, genetic algorithm, grey wolf optimizer, Harris hawks optimization, sparrow search algorithm, hippopotamus optimization algorithm, and duck swarm algorithm. In addition to highlighting the benefits of fractional calculus in structural control, this study provides a detailed analysis of FOPID controllers as well as a brief description of the algorithms used to optimize them. To evaluate the efficiency of the proposed techniques, two building models with different numbers of stories are examined. FOPID controllers are designed based on oustaloup’s approximation and the El Centro earthquake data. Using five well-known metrics, the performances of the developed methods are evaluated against five earthquake scenarios, including the recent earthquake in Turkey. A non-parametric (Friedman) test is also employed to compare the algorithms based on their corresponding vibration reduction. The findings of this analysis show that CryStAl consistently performs better than the other algorithms for both building models, thus resulting in superior vibration suppression.

This paper presents a novel adaptation of the conventional approximate Bayesian computation sequential Monte Carlo (ABC-SMC) sampling algorithm for parameter estimation in the presence of uncertainties, coined combinatorial ABC-SMC. Inference of this type is used in situations where there does not exist a closed form of the associated likelihood function, which is replaced by a simulating model capable of producing artificial data. In the literature, conventional ABC-SMC is utilised to perform inference on continuous parameters. The novel scheme presented here has been developed to perform inference on parameters that are high-dimensional binary, rather than continuous. By altering the form of the proposal distribution from which to sample candidates in subsequent iterations (referred to as waves), high-dimensional binary variables may be targeted and inferred by the scheme. The efficacy of the proposed scheme is demonstrated through application to vibration data obtained in a structural dynamics experiment on a fibre-optic sensor simulated as a finite plate with uncertain boundary conditions at its edges. Results indicate that the method provides sound inference on the plate boundary conditions, which is validated through subsequent application of the method to multiple vibration datasets. Comparisons between appropriate forms of the metric function used in the scheme are also developed to highlight the effect of this element in the schemes convergence. [ABSTRACT FROM AUTHOR]

This study presents a robot-assisted solution for the automated identification of bridge frequencies and high-spatial-resolution mode shapes using a minimal number of sensors. The proposed approach employs programmable wheeled robots, whose movement can be remotely controlled, as the mobile platform carrying accelerometers. The output-only frequency domain decomposition (FDD) algorithm is adopted for use with the proposed stop-and-go mobile sensing scheme, resulting in the identification of frequencies and high-resolution mode shapes. The solution was verified via two numerical case studies and was validated on a full-scale test of a footbridge. The results reveal that the frequencies and high-resolution shapes of the excited structural modes are identified successfully using only two accelerometers, confirming the satisfactory practicality and efficiency of the proposed solution. [ABSTRACT FROM AUTHOR]

In designing control systems, it is known that fractional-order proportional integral derivative (FOPID) controllers often provide greater flexibility than conventional proportional integral derivative (PID) controllers. This higher level of flexibility has proven to be extremely valuable for various applications such as vibration suppression in structural engineering. In this paper, we study the optimization of FOPID controllers using twelve well-established algorithms to minimize structural responses under seismic excitations. The algorithms include crystal structure algorithm (CryStAl), stochastic paint optimizer, particle swarm optimization, krill herd, harmony search, ant colony optimization, genetic algorithm, grey wolf optimizer, Harris hawks optimization, sparrow search algorithm, hippopotamus optimization algorithm, and duck swarm algorithm. In addition to highlighting the benefits of fractional calculus in structural control, this study provides a detailed analysis of FOPID controllers as well as a brief description of the algorithms used to optimize them. To evaluate the efficiency of the proposed techniques, two building models with different numbers of stories are examined. FOPID controllers are designed based on oustaloup's approximation and the El Centro earthquake data. Using five well-known metrics, the performances of the developed methods are evaluated against five earthquake scenarios, including the recent earthquake in Turkey. A non-parametric (Friedman) test is also employed to compare the algorithms based on their corresponding vibration reduction. The findings of this analysis show that CryStAl consistently performs better than the other algorithms for both building models, thus resulting in superior vibration suppression. [ABSTRACT FROM AUTHOR]

With the growing demand for infrastructure and transportation facilities, the need for advanced structural health monitoring (SHM) systems is critical. This study introduces two innovative, cost-effective, standalone, and open-source data acquisition devices designed to enhance SHM through the latest sensing technologies. The first device, termed CEDAS_acc, integrates the ADXL355 MEMS accelerometer with a RaspberryPi mini-computer, ideal for measuring strong ground motions and assessing structural modal properties during forced vibration tests and structural monitoring of mid-rise buildings. The second device, CEDAS_geo, incorporates the SM24 geophone sensor with a Raspberry Pi, designed for weak ground motion measurements, making it suitable for seismograph networks, seismological research, and early warning systems. Both devices function as acceleration/velocity Data Acquisition Systems (DAS) and standalone data loggers, featuring hardware components such as a single-board mini-computer, sensors, Analog-to-Digital Converters (ADCs), and micro-SD cards housed in protective casings. The CEDAS_acc includes a triaxial MEMS accelerometer with three ADCs, while the CEDAS_geo uses horizontal and vertical geophone elements with an ADC board. To validate these devices, rigorous tests were conducted. Offset Test, conducted by placing the sensor on a leveled flat surface in six orientations, demonstrating the accelerometer's ability to provide accurate measurements using gravity as a reference; Frequency Response Test, performed at the Gebze Technical University Earthquake and Structure Laboratory (GTU-ESL), comparing the devices' responses to the GURALP-5TDE reference sensor, with CEDAS_acc evaluated on a shaking table and CEDAS_geo's performance assessed using ambient vibration records; and Noise Test, executed in a low-noise rural area to determine the intrinsic noise of CEDAS_geo, showing its capability to capture vibrations lower than ambient noise levels. Further field tests were conducted on a 10-story reinforced concrete building in Gaziantep, Turkey, instrumented with 8 CEDAS_acc and 1 CEDAS_geo devices. The building's response to a magnitude 3.2 earthquake and ambient vibrations was analyzed, comparing results to the GURALP-5TDE reference sensors and demonstrating the devices' accuracy in capturing peak accelerations and modal frequencies with minimal deviations. The study also introduced the Record Analyzer (RECANA) web application for managing data analysis on CEDAS devices, supporting various data formats, and providing tools for filtering, calibrating, and exporting data. This comprehensive study presents valuable, practical solutions for SHM, enhancing accessibility, reliability, and efficiency in structural and seismic monitoring applications and offering robust alternatives to traditional, costlier systems. [ABSTRACT FROM AUTHOR]

Resonance of multi-degree-of-freedom system or structure is a basic and important concept in structural vibration theory, but it lacks a complete and rigorous definition. In order to establish an accurate concept of structural resonance, based on the concept of single-degree-of-freedom system resonance and modal orthogonality, this paper discusses the necessary conditions of system resonance by analyzing the displacement response of multi-degree-of-freedom vibration system, that is, while ensuring that the vibration frequency of the system (a certain natural frequency) is equal to the excitation frequency, its displacement response should also present the corresponding modal shape. An example of simply supported beam is used to illustrate its rationality. At the same time, the theoretical method of pure modal resonance of multi-degree-of-freedom system is given by rational allocation of excitation force. The pure modal resonance of multi-degree-of-freedom system or structure can be realized, which can be used to accurately identify the modal parameters of the structure. It is of great theoretical significance and engineering application value to discriminate the concept of multi-degree-of-freedom system or structure resonance. [ABSTRACT FROM AUTHOR]

The statistical energy analysis (SEA) method was popularly employed to handle the high-frequency dynamics problems in many engineering fields such as aerospace and shipping. The damping loss factor and coupling loss factor were the major parameters in the SEA theory, and they can usually be identified with the measured external input power and structural modal energy. The measurement errors of the input power and modal energy were not considered in the traditional parameter identification, where the accuracy of the identified results was relatively low. The interval mathematics method was applied to the parameter identification in this study, and the measurement errors of the input power and modal energy were fully considered. The effects of the measurement errors on the parameter identification were revealed, and the accuracy of the identified results was improved. The work can be helpful for the structure design and safety analysis. [ABSTRACT FROM AUTHOR]

Quantitative analysis of human gait is critical for the early discovery, progressive tracking, and rehabilitation of neurological and musculoskeletal disorders, such as Parkinson's disease, stroke, and cerebral palsy. Gait analysis typically involves estimating gait characteristics, such as spatiotemporal gait parameters and gait health indicators (e.g., step time, length, symmetry, and balance). Traditional methods of gait analysis involve the use of cameras, wearables, and force plates but are limited in operational requirements when applied in daily life, such as direct line-of-sight, carrying devices, and dense deployment. This paper introduces a novel approach for gait analysis by passively sensing floor vibrations generated by human footsteps using vibration sensors mounted on the floor surface. Our approach is low-cost, non-intrusive, and perceived as privacy-friendly, making it suitable for continuous gait health monitoring in daily life. Our algorithm estimates various gait parameters that are used as standard metrics in medical practices, including temporal parameters (step time, stride time, stance time, swing time, double-support time, and single-support time), spatial parameters (step length, width, angle, and stride length), and extracts gait health indicators (cadence/walking speed, left–right symmetry, gait balance, and initial contact types). The main challenge we addressed in this paper is the effect of different floor types on the resultant vibrations. We develop floor-adaptive algorithms to extract features that are generalizable to various practical settings, including homes, hospitals, and eldercare facilities. We evaluate our approach through real-world walking experiments with 20 adults with 12,231 labeled gait cycles across concrete and wooden floors. Our results show 90.5% (RMSE 0.08s), 71.3% (RMSE 0.38m), and 92.3% (RMSPE 7.7%) accuracy in estimating temporal, spatial parameters, and gait health indicators, respectively. [ABSTRACT FROM AUTHOR]

Particle tuned mass damper has received considerable attention on mitigating structural seismic responses recently. However, soil-structure interaction effects have not been considered for the optimization design of particle tuned mass damper in the previous studies yet, which may play significant roles in particle tuned mass damper's effectiveness. This paper investigates the seismic control performance of particle tuned mass damper for tall buildings considering SSI effects. A 40-story benchmark structure is adopted as the primary structure, and different soil conditions including soft, medium, dense soil, and the fixed-base case are considered. Based on the Cuckoo Search algorithm, an optimum design approach for the particle tuned mass damper implemented in SSI system under earthquake excitations is proposed, and the optimum parameters of particle tuned mass damper are obtained from the optimum design process. The optimum results indicate that the optimized particle tuned mass damper can effectively decrease the displacement response without the increase of peak acceleration, and the reduction rates could exceed 30% in some cases. Compared with other soil type cases, under soft soil condition, the optimum parameters of particle tuned mass damper are especially different, and the mitigation effects of the optimized particle tuned mass damper on maximum displacement weaken. Hence, it is necessary to consider the SSI effects for particle tuned mass damper's seismic design. Furthermore, the interaction effects between the primary structure and particle tuned mass damper in SSI system are also evaluated through energy analysis. The results show that considering SSI effects, the optimized particle tuned mass damper device dissipates the overwhelming majority of the input energy, and it greatly decreases the structural energy, displaying excellent energy dissipation performance on seismic vibration control of structure. [ABSTRACT FROM AUTHOR]

The dynamic responses of key locations are important inputs for the life and reliability assessment of spacecraft structures. Due to the limited sensing resources, most critical responses are difficult to measure directly. A structural dynamic response reconstruction method is necessary. The responses of target locations can be reconstructed based on the empirical mode decomposition (EMD) of measured signals and the modal superposition. However, the structural modal information contained in the measured signal of a single sensor is limited, affecting the reconstruction accuracy. In this paper, a response reconstruction method based on multi-sensor data fusion is proposed. It is applied to a main load-bearing structure of a spacecraft and its typical components to verify its strain response reconstruction effect under random vibration loads. The experimental results show that multi-sensor data fusion improves the strain reconstruction accuracy. The maximum reduction in reconstruction error is from 8.7% to 1.3%. The reconstruction accuracy is further improved with the increase in the number of sensors. The optimal weighted fusion strategy for this problem is the weights defined by the Euclidean distance (EUC) or the dynamic time warping distance (DTW). The fusion results show a better performance with the increase in the power of the defined distance. The proposed multi-sensor fusion method improves the reconstruction accuracy via supplementing structural information to each other and eliminating the instability of single measured signals. More accurate dynamic responses via reconstruction reduce the large input uncertainty in life prediction and lay the foundation for building structural digital twins and managing structural health more effectively [ABSTRACT FROM AUTHOR]

In light of the complex behavior of vibrating structures, their reliable modeling plays a crucial role in the analysis and system design for vibration control. In this paper, the reverse-path (RP) method is revisited, further developed, and applied to modeling a nonlinear system, particularly with respect to the identification of the frequency response function for a nominal underlying linear system and the determination of the structural nonlinearities. The present approach aims to overcome the requirement for measuring all nonlinear system states all the time during operation. Especially in large-scale systems, this might be a tedious task and often practically infeasible since it would require having individual sensors assigned for each state involved in the design process. In addition, the proper placement and simultaneous operation of a large number of transducers would represent further difficulty. To overcome those issues, we have proposed state estimation in light of the observability criteria, which significantly reduces the number of required sensor elements. To this end, relying on the optimal sensor placement problem, the state estimation process reduces to the solution of Kalman filtering. On this ground, the problem of nonlinear system identification for large-scale systems can be addressed using the observer-based conditioned RP method (OBCRP) proposed in this paper. In contrast to the classical RP method, the current one can potentially handle local and distributed nonlinearities. Moreover, in addition to the state estimation and in comparison to the orthogonal RP method, a new frequency-dependent weighting is introduced in this paper, which results in superior nonlinear system identification performances. Implementation of the method is demonstrated on a multi-degree-of-freedom discretized lumped mass system, representing a substitute model of a physical counterpart used for the identification of the model parameters. [ABSTRACT FROM AUTHOR]

Tower fatigue and strength are crucial operational concerns of floating offshore wind turbines (FOWTs) due to the escalation of the vibration phenomena observed on these structures as compared to land-based ones. FOWT towers are excited by wave and wind polyperiodic disturbances yielding continual transient states of structural vibration that are challenging for vibration mitigation systems. Thus, the paper investigates a novel implementation of nonlinear optimal-based vibration control solutions for the full-scale, tension leg platform (TLP)-based, NREL 5MW wind turbine tower-nacelle model with a 10-ton tuned vibration absorber (TVA), equipped with a magnetorheological (MR) damper, located at the nacelle. The structure is subjected to excessive wave and wind excitations, considering floating platform motions derived from model experiments in a wave tank. The MR damper operates simultaneously with an electromagnetic force actuator (forming a hybrid TVA) or independently (a semiactive TVA). The study includes both actuators' nonlinearities and dynamics, whereby the former are embedded in the Hamilton-principle-based nonlinear control solutions. The TVA is tuned either to the NREL 5MW tower-nacelle 1st bending mode frequency (TVA-TN) or to the TLP surge frequency (TVA-TLP). The optimal control task was redeveloped concerning the TVA stroke and transient vibration minimisation, including the implementation of the protected structure's acceleration and relative displacement terms, as well as the nonzero velocity term in the quality index. The regarded model is embedded in a MATLAB/Simulink environment. On the basis of the obtained results, the TVA-TN solution is by far superior to the TVA-TLP one. All the regarded TVA-TN solutions provide a tower deflection safety factor of ca. 2, while reference systems without any vibration reduction solutions or with a passive TVA-TLP are at risk of tower structural failure as well as the hybrid TVA-TLP system. The obtained TVA stroke reductions of 25.7%/22.0% coincide with 3.6%/10.3% maximum tower deflection reductions for the semiactive/hybrid TVA-TN case (respectively) with regard to the previously developed approaches. Moreover, these reductions are obtained due to the sole control algorithm enhancement; thus, no additional resources are necessary, while this attainment is accompanied by a reduction in the required MR damper force. The lowest obtained TVA stroke amplitude of 1.66 m is guaranteed by the newly introduced semiactive control. Its hybrid equivalent ensures 8% lower primary structure deflection amplitude and reduced nacelle acceleration levels thanks to the utilisation of the force actuator of the relatively low power (ca. 6 kW); the trade-off is an increased TVA stroke amplitude of 2.19 m, which, however, is the lowest among all the tested hybrid solutions. The analysed reference passive TVA systems, along with a modified ground-hook hybrid solution, can hardly be implemented in the nacelle (especially along the demanding side–side direction). The latter, being the well-proven hybrid solution for steady-state tower deflection minimisation, yielded unsatisfactory results. The achievements of the study may be used for an effective design of a full-scale vibration reduction system for the TLP-based floating wind turbine structure. [ABSTRACT FROM AUTHOR]

Under unstable wind loads, the wind turbine tower, as a supporting component of the horizontal axis experiences inevitable vibration. To explore the vibration characteristics of the tower, a vehicle test platform is established to measure the vibration acceleration component signals at different heights of a 300W small horizontal axis wind turbine tower. The results show that specific vehicle vibration test equipment can accurately test the vibration characteristics and laws of small wind turbine towers. The main vibration form of the tower is low frequency, with noticeable axial vibration at the top and lateral vibration in the middle of the tower due to aerodynamic load from natural wind. These findings can be used as a valuable reference for the safety and reliability design of the whole machine and the low-frequency vibration status monitoring of wind turbines. [ABSTRACT FROM AUTHOR]

Extensive research has significantly improved the vibration isolation performance of off-road vehicle seat suspensions, effectively addressing issues such as driver fatigue, and low-back pain. However, variations caused by road roughness, vehicle speed, and load can lead to stability switches and sudden events in seat vibration excitation. Ignoring these factors in semi-active and active seat suspensions can cause insufficient robustness and excessive costs. To address this, we propose an intelligent damping switching method that optimizes seat suspension damping mode by considering the stability and suddenness of excitation. Utilizing a long short-term memory (LSTM) network, we accurately identify stability, while the multi-input and multi-output optimization (MIMO) method labels the network input through system identification of the seat dynamics model. Event trigger (ET) handles suddenness effectively. By combining these techniques, our approach achieves effective vibration isolation while maintaining the desired suspension deflection. Comparative analysis validates our novel seat suspension control system design approach. [ABSTRACT FROM AUTHOR]

Precision Swine Farming has the potential to directly benefit swine health and industry profit by automatically monitoring the growth and health of pigs. We introduce the first system to use structural vibration to track animals and the first system for automated characterization of piglet group activities, including nursing, sleeping, and active times. PigSense uses physical knowledge of the structural vibration characteristics caused by pig-activity-induced load changes to recognize different behaviors of the sowand piglets. For our system to survive the harsh environment of the farrowing pen for three months, we designed simple, durable sensors for physical fault tolerance, then installed many of them, pooling their data to achieve algorithmic fault tolerance even when some do stop working. The key focus of this work was to create a robust system that can withstand challenging environments, has limited installation and maintenance requirements, and uses domain knowledge to precisely detect a variety of swine activities in noisy conditionswhile remaining flexible enough to adapt to future activities and applications. We provided an extensive analysis and evaluation of all-round swine activities and scenarios from our one-year field deployment across two pig farms in Thailand and the USA. To help assess the risk of crushing, farrowing sicknesses, and poormaternal behaviors, PigSense achieves an average of 97.8% and 94% for sow posture and motion monitoring, respectively, and an average of 96% and 71% for ingestion and excretion detection. To help farmers monitor piglet feeding, starvation, and illness, PigSense achieves an average of 87.7%, 89.4%, and 81.9% in predicting different levels of nursing, sleeping, and being active, respectively. In addition, we show that our monitoring of signal energy changes allows the prediction of farrowing in advance, as well as status tracking during the farrowing process and on the occasion of farrowing issues. Furthermore, PigSense also predicts the daily pattern and weight gain in the lactation cycle with 89% accuracy, a metric that can be used to monitor the piglets' growth progress over the lactation cycle. [ABSTRACT FROM AUTHOR]

In order to explore more efficient damping structure design, based on the theory of damping vibration and noise reduction technology and artificial cycle structure, the vibration and acoustic radiation characteristics of plate structures with periodic free damping design were studied. Firstly, the finite element simulation model of the acoustic and vibration response of plate structures were established. Secondly, the vibration and acoustic radiation characteristics of the plates with periodic free damping and traditional free damping were compared, and the influence of different parameters on the effect of periodic free damping were analyzed. Finally, relevant experimental research and simulation results verification were carried out. The results show that compared with traditional free damping design, the periodic free damping design can obtain better vibration and noise reduction effect, and help to realize the lightweight design of the damping structure, but the acoustic radiation efficiency will also be changed. The selection of damping materials with high elastic modulus, reasonable design of damping unit shape and appropriate reduction of damping units sectional area can help to improve the performance of periodic free damping design, while the change of the paste angle of the damping unit has little impact on its effect. In addition, the experimental results verify the reliability of the results from simulation study. [ABSTRACT FROM AUTHOR]

An original numerical framework is developed in the present research work in order to estimate the free field sound radiation from baffled structural panels subjected to nonhomogeneous turbulent boundary layer flow-induced excitation. A sequence of semi-analytical methods is used to estimate the nonhomogeneous turbulent boundary layer wall pressure spectrum, which is decomposed using the Cholesky technique to obtain the random wall pressure in the frequency domain. Structural panels are modeled using the finite element technique, and a coupled finite element-boundary element modeling technique is developed to estimate the sound power level radiated into the free field. Results are obtained for laminated composite structural panels with various fiber orientations. [ABSTRACT FROM AUTHOR]

The dynamic responses of key regions are critical inputs for the structural life estimation of spacecraft. Response reconstruction methods are needed for structural locations where sensors are not placed due to resource limitations. In this paper, a reconstruction method based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is proposed. CEEMDAN can eliminate the mode-mixing phenomenon of traditional empirical mode decomposition (EMD) during signal decompositions to improve the reconstruction accuracy. The proposed method is applied to the reconstruction of acceleration and strain responses at critical locations of a load-bearing structure under sinusoidal and random vibration loads. Numerical and experimental validation are carried out. The numerical results show that the reconstructions are almost unaffected by the selected white noise levels of CEEMDAN and the locations of measured and targeted points. The experimental results show that compared with traditional EMD, the reconstruction accuracy of CEEMDAN is improved by a maximum of 79.94% with almost no additional computational cost. The proposed reconstruction method shows efficiency and accuracy for a wide range of applications. [ABSTRACT FROM AUTHOR]

In order to ensure the safe operation of the nuclear power plant, seismic analysis must be conducted on the battery cabinets of nuclear power plants used for safety level emergency backup direct current (DC) power supply systems. Taking the battery cabinet of a certain nuclear power plant as the research object, the three-dimensional model and finite element analysis model of the battery cabinet were established. The natural frequency and mode shape results of the battery cabinet were obtained through modal analysis. The stress response of the battery cabinet model under the superimposed self-weight load safety shutdown earthquake (SSE) were calculated. The composite stress values of the three types of beams in the battery cabinet are all less than 1. The bending and membrane stress value of the battery cabinet baffle structure is 19. 6 MPa, and the maximum local stress value of the battery cabinet is 22.44 MPa. The composite stress value of the battery cabinet connecting bolts is close to 0. According to Design and construction rules for mechanical components of PWR nuclear islands (RCC-M standard), the composite stress of the beam, the stress of the baffle structure, the maximum local stress, and the composite stress of connected bolts for the battery cabinet all have a large safety margin compared to their allowable value. The design of the battery cabinet meets the requirements of the specification, and the battery cabinet can be applied to the floor where the mechanical and electrical building of a nuclear power plant is located. [ABSTRACT FROM AUTHOR]

This paper focuses on the transmission of vibration response of the seismic simulation shaking table system at Southeast University, and analyzes the effect of this response on the surrounding building. The location of the building is less than 10 m away from the laboratory where the shaking table is located, and during the maximum load test, a student reported that the vibration caused him a sense of discomfort, as well as the shaking of office objects on desktops on high floors, which caused panic. For these reasons, multiple three-directional vibration sensors were placed around the shaking table system and on the 1st, 8th, and 16th floors of the building. Test the vibration response transfer and the vibration response of the building floor while the exercise table is in operation. The test results show that the vibration-weighted acceleration levels of some floors exceed the code limits under sinusoidal wave conditions, which was the cause of the discomfort. The floors will have an amplifying effect on the lateral vibration. For seismic wave excitation, all measurement points of the building meet the limit values required by the GB 50868-2013 Standard for allowable vibration of building engineering. This study can provide a data reference for future shaking table system commissioning and operation. [ABSTRACT FROM AUTHOR]

Structural health monitoring and early detection of structural damage is extremely important to maintain and preserve the service life of civil engineering structures. Identification of structural damage is usually performed using non‐destructive vibration experiments combined with a mathematical procedure called model updating. The finite element model of the investigated structure is updated by incrementally adjusting its parameters so that the model responses gradually approach those of the real possibly damaged structure under investigation. This paper describes the use of two model updating methods. The first method employs metaheuristic optimization technique aimed multilevel sampling to efficiently search the design parameter space to achieve the best match between the deformed structure and its model. The second method approaches model updating as an inverse problem and uses machine learning‐based model to approximate inverse relationship between structural response and structural parameters. Both methods are applied to damage identification of single‐ and double‐span steel trusses. Finally, initial results of the hybrid method are presented. The effect of the damage rate and location on the identification speed and the accuracy of the solution is investigated and discussed. [ABSTRACT FROM AUTHOR]

Nonlinear structural dynamic analysis is required for mechanical structures experiencing nonlinearity through large force-vibration response ranges. Nonlinearities can be caused by large vibration displacements, material properties, or joints. Experimental modal analysis for nonlinear detection is achieved using conventional force-controlled stepped sine testing. However, this approach often encounters premature jumps in frequency response curves before reaching actual resonance peaks. In recent years, response-controlled stepped sine testing (RCT) has been introduced to quantify resonant peaks precisely. This approach, however, has only been limitedly utilised to detect and analyse nonlinearity in jointed structures and structures experiencing large displacement. In this paper, the reliability of the RCT approach is assessed for detecting nonlinearity from different sources. The experimental setup involves placing two magnets on opposite sides of a plate's free end to induce localised nonlinearity through magnet attraction. A low force magnitude of random excitation is employed to identify the frequency range of the first vibration mode using an electromagnetic shaker. Subsequently, RCT is performed within this range to measure the nonlinear forced response. Frequency response functions are measured at ten different controlled displacement amplitudes at the driving point. The analysis observed a symmetry curve of response in the measured FRFs. The results indicate that nonlinear hardening is detected at structures with localised magnet attraction. In conclusion, the reliability of applying the RCT approach for detecting nonlinearity from magnet attraction is achieved due to the absence of a jump issue in FRFs. [ABSTRACT FROM AUTHOR]

Floor vibrations for event localization has gained attention recently for its human-related applications such as footstep tracking. However, noise can corrupt signals, reduce signal-to-noise ratios (SNR), and lead to imprecise estimations of the event's amplitude and force. Techniques to remove noise have been developed such as bandpass filters, which eliminate noise without regard to overlapping event frequency components. These methods can corrupt the signal, removing important information about the event. The authors propose adapting a common speech processing technique, called spectral subtraction using half wave rectification, to remove only the noise's contribution. The Event Reconstructing Adaptive Spectral Evaluation (ERASE) approach is compared to unfiltered and Butterworth-filtered data in impact localization and force estimation through the Force Estimation and Event Localization (FEEL) Algorithm. A total of 810 impacts from ball drops of five different heights and impulse hammers across eighteen locations were utilized for testing. Signals were corrupted by noise from different sources. ERASE demonstrated 93.9% average impact localization accuracy and -2.40% ± 1.85% force magnitude error on a 99% confidence interval, improving the SNR verse the other filtering techniques. [ABSTRACT FROM AUTHOR]

This study proposes a deep neural network-based impact locating method on a cantilever beam. The power spectrum of a measured acceleration signal, when an impact is exerted at an arbitrary location on the beam, contains the inherent frequency response of the beam, including resonances and anti-resonances. Especially, the anti-resonances can be a useful feature for estimating the impact location because they are dominated by both the sensor and impact locations. However, in the power spectrum expressed using a linear scale, these anti-resonances may be less noticeable due to their small values relative to the resonances. The proposed impact locating method adopts the power spectrum expressed using a dB scale to highlight the importance of the anti-resonances as the input of a deep neural network. The deep neural network was trained, validated, and tested using a simulated dataset derived from an ideal cantilever beam model with a length of 800 mm, including a single accelerometer. From the test result, the proposed method achieved a root mean square error of about 1 mm in impact locating for a total of 800 impact locations with an interval of 1 mm, a significantly improved accuracy from that using the linear scaled power spectrum. [ABSTRACT FROM AUTHOR]

In light of the complex behavior of vibrating structures, their reliable modeling plays a crucial role in the analysis and system design for vibration control. In this paper, the reverse-path (RP) method is revisited, further developed, and applied to modeling a nonlinear system, particularly with respect to the identification of the frequency response function for a nominal underlying linear system and the determination of the structural nonlinearities. The present approach aims to overcome the requirement for measuring all nonlinear system states all the time during operation. Especially in large-scale systems, this might be a tedious task and often practically infeasible since it would require having individual sensors assigned for each state involved in the design process. In addition, the proper placement and simultaneous operation of a large number of transducers would represent further difficulty. To overcome those issues, we have proposed state estimation in light of the observability criteria, which significantly reduces the number of required sensor elements. To this end, relying on the optimal sensor placement problem, the state estimation process reduces to the solution of Kalman filtering. On this ground, the problem of nonlinear system identification for large-scale systems can be addressed using the observer-based conditioned RP method (OBCRP) proposed in this paper. In contrast to the classical RP method, the current one can potentially handle local and distributed nonlinearities. Moreover, in addition to the state estimation and in comparison to the orthogonal RP method, a new frequency-dependent weighting is introduced in this paper, which results in superior nonlinear system identification performances. Implementation of the method is demonstrated on a multi-degree-of-freedom discretized lumped mass system, representing a substitute model of a physical counterpart used for the identification of the model parameters.

The modal parameters of structures, and in particular their mode shapes, are generally determined based on the measurement of accelerometers or laser vibrometers. However, these sensors do not allow the performance of full-field measurements. In this study, the free vibration of a beam triggered by a shock is investigated using a high-speed camera with high image definition. With the help of digital image correlation (DIC), the beam displacement fields are deduced from the images. To analyse the DIC measurement quality, different tests and analyses are performed. First, the systematic errors and uncertainties in the DIC calculation for a simple translation are analysed considering different speckles. Then, tests on two configurations of a vibrating beam are filmed and full-field displacement measurements are computed. The modal parameters of the beam are deduced from these measurements using a continuous wavelet transform method. Particular care was taken to adapt the method to the post-processing of the numerous and noisy signals obtained for these experiments. All the steps of the post-processing are detailed in this paper. Finally, the modal parameters obtained with the proposed method are compared with those obtained in a more classical way using accelerometers and from the beam theory. In particular, the comparison of the signal-to-noise ratio of the different measurement methods is discussed. [ABSTRACT FROM AUTHOR]

Aiming at transmission tower structure, a damage detection method based on statistical model combined stochastic subspace identification algorithm is given, where vibration responses of transmission tower are used to obtain statistical features and construct highly sensitive damage index in order to diagnosis damage of local components. Firstly, transient dynamic response signals are collected. Secondly, modal parameters are identified by stochastic subspace identification algorithm, nominal modal parameters are built accordingly and the residual vector is defined, which is related to the structural parameters variation. Finally, the sensitivity of the residual to structural parameters is calculated, and then the X statistic value of the residual sensitivity is constructed as the damage detection index. Through numerical simulation and field test, a full-scale transmission tower Is analyzed, the results show that the proposed method can effectively identify local components damage of transmission tower, such as bolt loosening and structural member failure. [ABSTRACT FROM AUTHOR]

• Methodology: We introduce a novel analytical approach based on the spectral element method for assessing the vibrational characteristics of discontinuously connected cylindrical shell structures. The method's validity is corroborated by comparing the vibrational frequency responses from finite element computations and experimental tests, demonstrating accurate predictions of structural vibrations. • Frequency analysis: The inherent frequencies of rib-reinforced cylindrical shells calculated using the spectral element method show a high degree of agreement with those obtained from ABAQUS finite element analysis, with a total error margin of less than 2 %. Minor discrepancies in peak magnitudes are noted; however, the general trends, peak positions, and numerical values of the frequency responses are fundamentally aligned. • Comparative evaluation: When juxtaposed with the test results from the discontinuously connected cylindrical shell test rig, the acceleration frequency response curves derived from free-state mechanical impedance tests, finite element simulations, and analytical method analyses exhibit a high level of congruence in both overall trends and numerical values. The maximum relative errors in the natural frequencies across the three test conditions are 4.2 %, 5.8 %, and 2.6 %, respectively, for experimental calculations and finite element simulations. Common shell of revolution, such as cylindrical, conical, and spherical shells, are widely used in marine, aerospace, and other engineering fields due to their excellent support and pressure-resistant properties. Research on their vibration characteristics has progressed from single shells to composite shells, from ribbed shells to those with complex internal substructures, and from uniform to discontinuous connections. The discontinuities in wave propagation at the boundaries of discontinuously connected cylindrical shells result in highly complex equation of vibration control, leading to limited studies in this area. This study first models the uniform cylindrical shell and annular plate as spectral elements, using trigonometric and Bessel functions to describe displacement solutions and obtain vibration responses for arbitrary boundary conditions. Then, based on artificial virtual spring theory and the weighted least squares method, the discontinuous connection between the cylindrical shell and annular plate is modeled as a circumferentially varying stiffness distribution, leading to the derivation of dynamic stiffness matrices for both continuous and discontinuous connections. Finite element simulations are conducted using ABAQUS to analyze the vibration characteristics of the discontinuously connected cylindrical shell under free, clamped, and simply supported boundary conditions. Finally, an experimental setup is used to measure the vibration response under harmonic excitation and perform impedance testing with an impact hammer. The results show that the spectral element method accurately calculates the natural frequencies of the stiffened cylindrical shell, with an overall error of less than 2 %, while the maximum error for the experimental shell is 5.8 %. [ABSTRACT FROM AUTHOR]

This article presents a step-by-step methodology for calculating transformer tank vibrations caused by electromagnetic forces. This approach uses 3D finite element models for both magnetic and structural calculations. Particular attention was paid to the description of momentum transfer between structural and fluid areas of the transformer. The actual geometry of the coils in the phase windings was taken into account. The dominant role of the axial component of the Lorentz force is the main conclusion of the article. The results are given in the form of three-dimensional displacement fields of the transformer tank presented together with the acoustic pressure field in the oil. The theoretical analysis is verified by laser-scanned vibration patterns on the tank wall. [ABSTRACT FROM AUTHOR]

This research is motivated by the need for rapidly deployable technologies such as wireless, non-contact or remote sensing for evaluating bridges under operating conditions to minimize the data collection time, avoid the disruption of traffic and increase the inspector's safety. The objective established for this research is to explore the use of remote sensing (e.g., Light Detection and Ranging (LiDAR)) for characterizing the structural vibration of bridges to support and improve bridge assessment practices. To satisfy this objective, a field study was performed on a 12-span steel stringer bridge in the Philadelphia region. This structure was subjected to extensive LiDAR scanning and conventional vibration data collection through the use of accelerometers for validation purposes. The analysis of the data collected in the field revealed LiDAR's capability for detecting the structure's vibration. The field data displayed an error for LiDAR vs. accelerometers of between 1.9 and 10 percent. Additionally, numerical modeling was performed on MATLAB to allow for a better understanding of the interaction between the scanner and the structure. The numerical model presents a vibrating plate to represent a simply supported single-span bridge and a terrestrial LiDAR sensor located under the plate which scans while it is vibrating constantly without attenuation. Finally, a set of recommendations were established for the use of LiDAR scanning to evaluate the structure's frequency of vibration. [ABSTRACT FROM AUTHOR]

In order to improve the damping capacity of building isolation system, this paper studies the damping isolation control system of the building structure based on negative stiffness. In this paper, the dynamic equation of the damping isolation control system is derived and its parameters are optimized by H2 norm theory and Monte Carlo pattern search method. Taking the 5-story building structure as an example, this paper analyzes and evaluates the damping performance of the damping isolation control system of the building structure under the actual earthquake. The results show that negative stiffness can improve the damping capacity of traditional isolation system. Additionally, the negative stiffness ratio under the condition of stability, the smaller the negative stiffness ratio, the stronger the vibration reduction ability of the negative stiffness. The damping isolation control system of building structure based on negative stiffness shows good damping effect under the actual earthquake. [ABSTRACT FROM AUTHOR]