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Unsupervised domain adaptation alleviates the dependencies of conventional fault diagnosis methods on sufficient labeled data and strict data distributions. Nonetheless, the current domain adaptation methods only concentrate on the data distributions and ignore the feature gradient distributions, leading to some samples being misclassified due to large gradient discrepancies, thus affecting diagnosis performance. In this paper, a gradient aligned domain adversarial network (GADAN) is proposed. First, the discrepancies of the marginal and conditional distribution between the source and target domain are reduced by minimizing the joint maximum mean discrepancy. Then, a pseudo-labeling approach based on a clustering self-supervised strategy is utilized to attain high-quality pseudo-labels of target domains, and most importantly in the dimension of the data gradient, the feature gradient distributions are aligned by adversarial learning to further reduce the domain shift, even if the distributions of the two domains are close enough. Finally, experiments and engineering applications demonstrate the effectiveness and superiority of GADAN for transfer diagnosis between various working conditions or different machines. • Reducing distribution discrepancies by minimizing joint maximum mean discrepancy. • Obtaining pseudo-labels using a self-supervised pseudo-labeling strategy. • Aligning feature gradient distribution discrepancies using adversarial learning. • The effectiveness was verified using real cases between different machines. [ABSTRACT FROM AUTHOR]

Infrared thermal technology plays a vital role in the health condition monitoring of gearbox. In the traditional infrared thermal technology-based methods, Gaussian pyramid is applied as the feature extraction approach, which has disadvantages of noise influence and information missing. Focus on such disadvantages, an improved multi-scale decomposition method combined with convolutional neural network is proposed to extract the fault features of the multi-scale infrared images in this paper. It can enlarge the data length at large scales, and thus reduce the fluctuations of feature values and reserve the fault information. The effectiveness of the proposed method is validated using the experiment infrared data of one industrial gearbox. Results demonstrate that our proposed method has the best performance comparing with five methods. • A reliable multi-scale decomposition method for CNN is proposed. • MSCNN extracts fault information over multiple scales with better feature extraction ability. • The proposed method yields best diagnostic ability by comparing with other five methods. [ABSTRACT FROM AUTHOR]

Infrared thermal technology plays a vital role in the health condition monitoring of gearbox. In the traditional infrared thermal technology-based methods, Gaussian pyramid is applied as the feature extraction approach, which has disadvantages of noise influence and information missing. Focus on such disadvantages, an improved multi-scale decomposition method combined with convolutional neural network is proposed to extract the fault features of the multi-scale infrared images in this paper. It can enlarge the data length at large scales, and thus reduce the fluctuations of feature values and reserve the fault information. The effectiveness of the proposed method is validated using the experiment infrared data of one industrial gearbox. Results demonstrate that our proposed method has the best performance comparing with five methods. • A reliable multi-scale decomposition method for CNN is proposed. • MSCNN extracts fault information over multiple scales with better feature extraction ability. • The proposed method yields best diagnostic ability by comparing with other five methods. [ABSTRACT FROM AUTHOR]

This article presents a standardized analysis of failures in wind turbines concerning the main technologies classified in the literature, as well as identifies critical components and trends for the most modern wind farm facilities, which seek greater efficiency, robustness and reliability to mitigate failures and reduce wind turbine downtime. Through the application of Pareto's rule, a set of components has been identified; although these provide little in terms of fault contribution, they do account for almost all downtime when they occur. Wind turbines fail around twice every year with an average downtime of 150 h per failure. The gearbox is one of the most critical components in terms of downtime that represents generation losses, where the faults in the frequency converter are directly influenced by the thermal cycle of the semiconductor switches in normal operation and accentuated by transient load fluctuations during the generation process. In order to identify the optimum point for preventive interventions that do not impact the overall maintenance cost, at the end a maintenance cost of a 2 MW wind turbine is discussed. [ABSTRACT FROM AUTHOR]

Single flank testing is used to measure the quality of a gearset. The paring of two specific flank geometries leads to a unique transmission error curve. The challenge in quality assurance is to find a way to differentiate flank geometries by evaluating the transmission error curves. Therefore, characteristic values are needed to efficiently analyze the huge amount of data. In this paper, characteristic values in time and frequency domain are used to compare the results of an arbitrary amount of transmission error curves. With the data, an additional method is developed to estimate the geometry from the given transmission error. [ABSTRACT FROM AUTHOR]

Modeling of AMT gearshift and clutch controls has attracted considerable attention in the past decade for optimizing the algorithms and simulation of control strategy and shift calibration, for reducing development time and costs involved in physical validation. Modeling of AMT system for simulation of gearbox and clutch performance is done using MATLAB/Simulink software. Time to market and investment for development can be greatly reduced through the use of a simulation-based design. A complete vehicle system simulation can allow multiple iterations without need for physical validation of the design concepts, prior to manufacturing test samples. This simulation methodology enables optimisation of interface components and sub-systems. Furthermore, design concepts can be tested using software model without the need of prototype parts, test vehicle, test track and test rig or test track. [ABSTRACT FROM AUTHOR]

The article deals with a technical design of the reduction gearbox with motion transmission using the inlet crankshaft and bellows. It describes the original technical design and presents the proposed elimination of the drawbacks of the original design which has also been practically executed by producing a prototype device which was observed to exhibit absolute functionality. [ABSTRACT FROM AUTHOR]

Copyright of Mechanics & Advanced Technologies is the property of National Technical University of Ukraine KPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Gearbox is an indispensable element allied with mechanical industries to fluctuate speed and load in accordance with the requirements. More improvements in its mechanical structure and procedure can increase the efficiency of the industries. For those reasons, the gearbox was designed and manufactured very carefully with the zero tolerance of defects. Gearbox failure can lead to an increase in financial loss and decrease in production strength. Vibration signal analysis is used to monitor the gearbox condition. But, non-stationary properties of vibration signal make this procedure very challenging. Therefore, this paper presents a unique gearbox fault investigation technique based on advanced computational intelligence. Firstly, Time Synchronous Averaging algorithm was used to study the nonstationary properties of the raw vibration signal. Then, nine types of time domain arithmetical features were calculated from the pre-processed TSA vibration signal. After that, the J48 algorithm was used for significant features selection of gearbox fault and Naïve Bayes algorithm for features classification of gearbox fault. A computer-aided fault simulator was used for experimental study. MATLAB and WEKA platforms were used for signal processing, features selection, and features classification of the gearbox faults. The performance of the proposed method shows meaningful results for gearbox fault diagnosis. [ABSTRACT FROM AUTHOR]

The gearbox is a key component in wind turbines, and the fault diagnosis of gearboxes in wind turbines is a significant process of reliability management. Therefore, a SAE-BP transfer neural network is proposed in this paper for fault diagnosis of gearboxes in wind turbines. The proposed method is conducted by two processes. Firstly, a source task data is served as the training process to pretrain the SAE-BP neural network. The final learned network structure is the transferable weights or parameters that contain the feature information. Then, the learned weights are transferred into a target task with different working and fault conditions as the initial weight of a neural network model. To extract more fault-sensitive features, fast Fourier transform (FFT) is introduced to transform the raw data into a frequency domain. Several comparison experiments are conducted to validate the proposed method, and the results show that the proposed method achieves higher classification accuracy. [ABSTRACT FROM AUTHOR]

This paper details an Integrated Prognostics Module for real-time condition monitoring of the dry clutch system and gearbox used on Automated Manual Transmission (AMT). The real-time sensor data of the clutch actuator and gear actuator piston positions are analysed for monitoring the condition of the clutch system and gearbox synchroniser. Original parameters of the new clutch and gearbox hardware are stored in the Electrically Erasable Programmable Read-only Memory (EEPROM) of the AMT controller and the real-time data is used by the integrated prognostics module for assessing the degradation/wear. Clutch slip during torque transmission and the synchronization time are continuously monitored for providing timely alert for re-calibration of the AMT system. Thus, Condition monitoring of an AMT system provides enhanced prognostic functionality which ensures consistent clutch performance, gear shift quality and timely warning for recalibration, repair and/or replacement of the critical wear and tear parts. Also, systematic analysis of the monitored data provides an accurate diagnosis of a developing fault. [ABSTRACT FROM AUTHOR]

Participants in the Asia Pacific Conference of the Prognostics and Health Management Society 2017 (PHMAP 2017) Data Challenge were given measured vibration signals from motor-driven gearboxes used in pulverizers. Using this information, participants were requested to predict failure dates and the faulty components. The measured signals were affected by significant noise and disturbance, as the pulverizers in the provided data worked under actual operating conditions. This paper thus presents a fault prediction method for a motor-driven gearbox in a pulverizer system that can perform under external noise and disturbance conditions. First, two fault features, an RMS value in the higher frequency zones (HRMS) and an amplitude of a period for high-speed shaft in the quefrency domain (QAHSS), were extracted based on frequency analysis using the higher and lower sampling rate data. The two features were then applied to each pulverizer based on results of frequency responses to impact loadings. Then, a regression analysis was used to predict the failure date using the two extracted features. A weighted regression analysis was used to compensate for the imbalance of the features in the given period. In addition, the faulty components in the motor-driven gearboxes were predicted based on the modulated frequency components. The score predicted by the proposed approach was ranked first in the PHMAP 2017 Data Challenge. [ABSTRACT FROM AUTHOR]

The finite element analysis and experimental measurement are used to study the vibration characteristics of gearbox impact faults. Parametric models of gearbox gear train are built through three-dimensional modeling software, and the finite element software transient dynamics module is used to analyze the vibration acceleration response of the gearbox under different conditions of impact load. Compare the actual acceleration response which is collected from fault simulation experiment with the finite element simulation results to verify the accuracy of the parametric models. Meantime, the vibration response of the gear box impact failure is analyzed, and the sensor layout optimization scheme is proposed, which reduces the blindness of vibration measuring point arrangement and reduces the necessary channels for the monitoring and diagnosis. As a result, the cost of monitoring could be reduced. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Vibration Engineering is the property of Nanjing University of Aeronautics & Astronautics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article reviews the peculiarities of application of a methodology of multifactorial the electric motor selection for force compensating manipulator account for the fulfillment of the following conditions: coordination of freight and the engine transferring, minimization of maximum motor torque, freight transferring of maximum weight with the required maximum constant speed and maximum defined acceleration, providing standing mode of motor alive. According to the results of the performed review we selected a power part of electromechanical system of the manipulator and a practical test of high-speed and medium-speed synchronous electric motors driving from permanent magnets at application of gearboxes made by Sew Euro Drive and Russian-manufactured is carried out. The review showed that for the implementation of vertical movement system of freight it is reasonable to apply a DSM series electric motor of general industrial use that will allow reducing the cost of the perspective force compensating manipulator. [ABSTRACT FROM AUTHOR]

We review the peculiarities of application of a methodology for the multifactorial choice of the electric motor for force compensating manipulator taking into account the fulfillment of the following conditions: coordination of freight and the engine transferring, minimization of maximum motor torque, freight transferring of maximum weight with the required maximum constant speed and maximum defined acceleration, providing standing mode of motor alive. According to the results of the performed review we selected a power part of electromechanical system of the manipulator and a practical test of high-speed and medium-speed synchronous electric motors driving from permanent magnets at application of gearboxes made by Sew Euro Drive and Russian-manufactured is carried out. The review showed that for the implementation of the vertical movement system of freight it is reasonable to apply the electric motor of general industrial use of DSM series that will allow reducing the cost of the perspective force compensating manipulator. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Vibration Engineering is the property of Nanjing University of Aeronautics & Astronautics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article describes modeling and simulation of the vehicle physical model. The vehicle model is simplified and it is made up of body and 4 tires. The model contains elementary information of the vehicle geometry - dimensions and center of gravity position. These information about the vehicle are sufficient for mathematical description of vehicle. The model is made of basic elements like engine, gearbox, differential and tires, which are represented by blocks. The model includes also other blocks, which are used to show measured outputs and control blocks, that make the vehicle mechatronic systems controllable according the driver model inputs. There are also studied the forces on tires and the engine speed of the vehicle model. [ABSTRACT FROM AUTHOR]

Different gear failure modes are strongly correlated with lubricant status, for example low oil level or starved lubrication leads to significant gear damages. In order to develop an early detection and accurate diagnosis of gearbox lubricant serving conditions based on online vibration measurements, this study will investigate the effect of lubricant starvation on the gearbox vibration responses. A two-stage helical industrial gearbox was tested under different lubricant shortage conditions. Any shortages in the oil service volume reduce the consumption power of the driving motor due to the decreasing of dipping oil churning losses and the submerge depth of gears. However, breakdown in the oil film and increasing in the sliding friction between the contact tooth surfaces are more expected, which affect the vibration characteristics of the gear system. The test was carried out with normal oil quantity and two lubricant shortages under different operating conditions. The results show that the gearbox vibration signature changes significantly with lubricant starvation, which includes more consistent increase in the amplitudes of vibration responses at meshing frequency harmonics and their associated sideband components. These changes correspond that vibration signal can be considered to normalise condition indicator of gearbox lubricant starvations. [ABSTRACT FROM AUTHOR]

Deep belief nets consist of several-layered unsupervised restricted Boltzmann machines and one-layered supervised feedback neural network. It digs the inner structure and pattern of the complex input data through effective information abstraction layer by layer, which can well reflect the input mode. However, the hidden layer numbers and the feature dimension are difficult to determine. The feedback process exhibits the vanishing gradient problem, which results in ineffective structural parameters training for lower layers. Moreover, noise affects the recognition results directly. To aim at the problem, a transformation matrix between samples and labels is made for each layer to realize adaptive adjustment of the parameter of hidden layer, and the feature of the hidden layer is de-noised for improving recognition accuracy and calculation efficiency. Simulation experiments on fault diagnosis of a gearbox in complex working conditions have proved the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Augmenting gearing systems efficiency is a key issue in developing innovative aero-engines with low specific fuel consumption. The transmission system directly affects the engine overall efficiency, therefore it is essential maximizing its performance. In high speed applications fluid-dynamic losses become predominant and are directly connected to the lubrication method. Oil jet systems are generally used in order to achieve a proper cooling and lubrication of tooth surface. A novel rotating test rig was exploited for investigating oil jet lubrication by means of high speed visualizations. An oil jet impinging radially on a single spur gear was generated by a spray-bar, assessing which parameters affect the oil jet behavior. [ABSTRACT FROM AUTHOR]

In this paper, we would like to focus on modeling main parts of the wind turbines (blades, gearbox, tower, generator and pitching system) from a mechatronics viewpoint using the Bond-Graph Approach (BGA). Then, these parts are combined together in order to simulate the complete system. Moreover, the real dynamic behavior of the wind turbine is taken into account and with the new model; final load simulation is more realistic offering benefits and reliable system performance. This model can be used to develop control algorithms to reduce fatigue loads and enhance power production. Different simulations are carried-out in order to validate the proposed wind turbine model, using real data provided in the open literature (blade profile and gearbox parameters for a 750 kW wind turbine). [ABSTRACT FROM AUTHOR]

Based on the analysis of gearboxes designs a microprocessor-based car engine control system is developed, which allows semi-automatic or automatic gear shifting, thus facilitating driving, decreasing the fuel consumption, increasing the durability of transmission. The microprocessor-based control system of the car engine, which allows the automatic synchronization of angular speeds of entrance and output power stream, and carrying out gear shifting without switching off the clutch was described. The block diagram of microprocessor-based car engine control system, the construction of electro-pneumatic actuator and photo of the gearbox with the executive mechanism was presented. [ABSTRACT FROM AUTHOR]

Observer based approaches are commonly embedded in sensorless variable speed drives for the purpose of speed control. It estimates system variables to produce errors or residual signals in conjunction with corresponding measurements. The residual signals then are relied to tune control parameters to maintain operational performance even if there are considerable disturbances such as noises and component faults. Obviously, this control strategy outcomes robust control performances. However, it may produce adverse consequences to the system when faults progress to high severity. To prevent the occurrences of such consequences, this research proposes the utilisation of residual signals as detection features to raise alerts for incipient faults on mechanical systems. Based on a gear transmission system with a sensorless variable speed drive (VSD), observers for speed, flux and torque are developed for examining their residuals under two mechanical faults: tooth breakage with different degrees of severities and lubricant shortage at different levels are investigated. It shows that power residual signals can be based on to indicate different faults, showing that the observer based approaches are effective for monitoring VSD based mechanical systems. Moreover, it also shows that these two types fault can be separated based on the dynamic components in the voltage signals. [ABSTRACT FROM AUTHOR]

Acoustics Emissions (AE) technology has emerged as a promising diagnostic approach. AE was originally developed for non-destructive testing of static structures, however, in recent times its application has been extended to health monitoring of rotating machines. This paper introduces a novel method for application of AE in monitoring of helicopter gearboxes. In addition this paper investigates the application of signal separation techniques in detection of bearing faults within the epicyclic module of a large helicopter (CS-29) main gearbox using Acoustic Emissions (AE). The results showed successful of AE in detection bearing fault within the helicopter gearbox. Detection of the small bearing defect gives the AE an indisputable diagnosis advantage and prove ability of application of AE in helicopter gearboxes. [ABSTRACT FROM AUTHOR]

Every day, millions of people are exposed to noise at work and to all the associated risks. It is a clear fact that the noise is an important problem in the industrial areas and moreover it becomes a significant issue in a wide range of other non-industrial environments as well. The current trend in the construction of gearboxes, regarding the speed increasing, favors the increase of the dynamic loads, which are accompanying the operation of equipments. The dynamic contact phenomena like the friction, collision and shock are generating vibration in a wide frequency spectrum. Vibration transmitted via the housing to the environment creates a complex acoustic field around the gearbox. The acoustic field characteristics depend on the energy sources of the vibration and the acoustic properties of the environment where the gearbox operates. This fact explains why the noise has become a basic indicator for assessing the quality of gearboxes. Thus, the decrease in produced noise has lately become a priority, being one of the important methods against the environmental pollution. The purpose of this paper is to present an innovative method that aims to reduce the gearbox noise by applying a fluoropolymer coating procedure on the gear teeth. [ABSTRACT FROM AUTHOR]

When the gears fault and the bearings fault in a gearbox occur at the same time, the symptoms of the weak fault usually is submerged in the strong fault symptoms. Therefore, it is difficult to detect the weak fault directly through the demodulating analysis of the gearbox vibration signals. For that problem, a method of compound fault diagnosis of gearbox is proposed based on the energy operator demodulating of signal's resonance components. In this method, the gearbox vibration signal is decomposed using resonance-based sparse signal decomposition. The higher-resonance component (the amplitude modulation component) indicates the gear's fault and the lower-resonance component (the impulse component) indicates the bearing's fault to separate them from each other. The separated amplitude modulation component and the impulse component are then analyzed by energy operator demodulating, and each of their instantaneous amplitude can be calculated. According to the spectrum of the instantaneous amplitude, the gear's fault and the bearing's fault can be diagnosed respectively, so the compound fault of a gearbox can be diagnosed. Some simulation and illustrative examples proved the effectiveness of the method. [ABSTRACT FROM AUTHOR]

Gearbox is an essential device employed in industries to vary speed and load conditions according to the requirements. More advancement in its design and operation leads to increase in industrial applications. The failure in any of the components of gearbox can lead to production loss and increase maintenance cost. The component failure has to be detected earlier to avoid unexpected breakdown. Vibration measurements are used to monitor the condition of the machine for predictive maintenance and to predict the gearbox faults successfully. This paper addresses the use of vibration signal for automated fault diagnosis of gearbox. In the experimental studies, good gears and face wear gears are used to collect vibration signals for good and faulty conditions of the gearbox. Each gear is tested with two different speeds and loading conditions. The statistical features are extracted from the acquired vibration signals. The extracted features are given as an input to the support vector machine (SVM) for fault identification. The Performance of the fault identification system using vibration signals are discussed and compared. [ABSTRACT FROM AUTHOR]

The gearbox oil and the wind turbine gearbox condition are correlated. The oil can give the wind turbine operator the necessary information to plan maintenance and avoid costly repairs. Therefore, a test bench that can reproduce the gearbox operating conditions would be necessary to test oil-sensors. This paper presents a first testing approach using a Highly Accelerated Life Test / Highly Accelerated Stress Screening test chamber. It allows assessing the performance of oil properties sensors under extreme ambient temperature and vibration levels, based on measurements from a wind turbine gearbox. Results from a test on an oil properties sensor are presented and discussed. [ABSTRACT FROM AUTHOR]

Gears are very reliable components and normally work 5–6 years without failure. This article is a case study of failure analysis of a gearbox which was failed in three months after its installation. The problem was identified by maintenance engineers through vibration monitoring of gearbox. Hardness measurement of case and core revealed that the core was harder than case and the applied load was sufficiently high for failure of gear. Recommendations were given to improve the fatigue life of gearbox. [ABSTRACT FROM AUTHOR]

Recently, magnetic gearboxes (MGBs) are serious contenders to their conventional mechanical counterparts in terms of reduced maintenance requirements, improved reliability, tolerance to mechanical inaccuracies, and inherent overload protection. MGBs are preferably employed in high speed applications and compact harsh environments subjected to severe shock and vibration. A high gear ratio MGB is also a suitable candidate for single stage high-speed transmission applications such as helicopter power transmissions. In this paper, the conventional planetary magnetic gearbox is equipped with a three-phase winding to provide additional magnetic levitation capabilities besides torque transmission, thus creating a bearingless MGB configuration. This was achieved by adding a three-phase winding in the space between the ferromagnetic pieces. The current in this additional winding is controlled to provide decoupled axial forces irrespective of the transmitted mechanical power. This feature is important to reduce the mechanical losses especially for high-speed rotors and can be a viable method for vibration suppression. [ABSTRACT FROM AUTHOR]

In divide-and-combine approach, multi-class support vector machines (SVMs) are divided into several binary SVMs and then the SVMs are combined to obtain multi-class classifiers. In this paper, a new probability voting strategy is presented to combine several binary SVMs. By the method, not only the unclassifiable regions existing in conventional strategy are solved, but also the decision results satisfy the probability distribution. Firstly, two most commonly combining strategy: MaxWins and FSVM are discussed, and their performances are compared through posterior probability distribution. Secondly, an estimate function for the prior probability in a binary classification problem is defined, and an adjustment function satisfying prior probability is normalized in the range of 0∼1. Thirdly, a novel probability voting is improved by considering the conventional voting and the adjustment function. Finally, 5-class SVMs-based fault diagnosis models for gearbox respectively with MaxWins majority voting, FSVM and the presented strategy are tested. All the tests and data indicate that the multi-class SVMs combined by probability voting strategy has more capacity of reliability and robustness, and are suitable for fault diagnosis of gearbox. [ABSTRACT FROM AUTHOR]

Condition monitoring vibration data is widely used to assess the health condition of the gearbox. The objective of this paper is to develop a scheme for early fault detection of a gearbox under varying load condition by considering multi-sensor vibration data. Time synchronous averaging (TSA) method is used to reduce the noise and then remove the periodic signals from the data. Several vector auto-regressive (VAR) models are fitted to the historical data obtained in healthy gearbox condition considering different load levels. After testing the independence and multivariate normality of residual data, a multivariate Hotelling's T-squared control chart is applied to detect the early fault occurrence of a gearbox. [ABSTRACT FROM AUTHOR]

Abstract: In order to develop robust condition monitoring and prognosis technologies and systems for wind turbine gearboxes, a comprehensive review of the state-of-art of condition monitoring and fault diagnosis techniques has been carried out. The challenges and opportunities are identified to guide future research in improving the accuracy and ability of condition monitoring and prognosis systems for wind turbine gearboxes. This review also focuses on the fault diagnosis technologies and application of novel sensors in wind turbine gearbox condition monitoring. [Copyright &y& Elsevier]

Vibration signal-based mechanical fault diagnosis has limitations such as contact measurement and single-channel analysis, whereas acoustic image-based fault diagnosis can overcome these shortcomings. A mechanical fault diagnosis method based on texture features of acoustic images by near-field acoustic holography technique (NAH). Firstly, acoustic images in different running states of machinery are acquired by NAH. Then, in that subtle changes of sound field distribution can be reflected in abundant texture information of acoustic images, texture features in acoustic images are extracted to reveal the running states of machinery, thereby some inner relations between acoustic images and different states are established. Finally, combining support vector machine-based pattern classification fault diagnosis can be realized. Experimental study of gearbox fault diagnosis shows the feasibility and effectiveness of the proposed method, such that faily good diagnosis results can be obtained in the condition of strong interference noise. [ABSTRACT FROM AUTHOR]

Abstract: This work is aiming to study and control of drive train of an electric vehicle based on doubly fed induction machine (DFIM), the power structure of this machine and the control strategy applied allow operating over a wide range of speed variation, for both applications: engine and recovery. Therefore the power of the machine can reach twice its rated power. After modeling different parts of the drive train a numerical simulation in MATLAB/Simulink is carried out. The results show the good performance of the vector control, and the structure of power applied to the DFIM. [Copyright &y& Elsevier]

In order to analyze the dynamic effects of elastic support on dynamic characteristics of marine planetary reducer, the dynamic model of transmission system is set up in consideration of the time-varying mesh stiffness and gear error, and the dynamic excitations of the system are calculated. The dynamic response model of the gearbox is set up by using finite element method and solved by using mode superposition method. Then the time history and spectrum of node acceleration of the gearbox are obtained, and the effect of support stiffness on vibration transfer and displacement of the gearbox are researched. The study provides useful theoretical guideline to the design of the marine gearbox. [ABSTRACT FROM AUTHOR]

Panel acoustic power contribution analysis is put forward according to panel acoustic contribution analysis methodology investigation. According to gearbox noise radiation, finite element method and boundary element method are used to construct gearbox calculation model. According to the partition regions of gearbox, panel acoustic power contribution can be obtained by every panel calculation. Then, main contribution regions of the power and peak frequency are found according to calculation results. Improvement design and analysis are carried Out based on acoustic power analysis for gearbox. It can be concluded that this method is helpful for gearbox noise control investigation and realization. [ABSTRACT FROM AUTHOR]

Abstract: The non-stationary gearbox vibration signal is frequently covered up by random noises, thus exerting certain difficulties on the extraction of features of fault signals. This paper, under the conditions of LabVIEW, uses the graphical programming language and the wavelet analysis technology to analyze the vibration signal of CA6140 lathe gearbox and to get the characteristic frequency of gearbox faults as well as that of frequency doubling faults of rotating frequency of I axis and II axis, thus providing theoretical basis for further diagnosis. [Copyright &y& Elsevier]

The main driver behind developing advanced condition monitoring (CM) systems for the wind energy industry is the delivery of improved asset management regarding the operation and maintenance of the gearbox and other wind turbine components and systems. Current gearbox CM systems mainly detect faults by identifying ferrous materials, water, and air within oil by changes in certain properties such as electrical fields. In order to detect oil degradation and identify particles, more advanced devices are required to allow a better maintenance regime to he established. Current technologies available specifically for this purpose include Fourier transform infrared (FTIR) spectroscopy and ferrography. There are also several technologies that have not yet been or have been recently applied to CM problems. After reviewing the current state of the art, it is recommended that a combination of sensors would be used that analyze different characteristics of the oil. The information individually would not be highly accurate but combined it is fully expected that greater accuracy can be obtained. The technologies that are suitable in terms of cost, size, accuracy, and development are online ferrography, selective fluorescence spectroscopy, scattering measurements, FTIR, photoacoustic spectroscopy, and solid state viscometers. [ABSTRACT FROM AUTHOR]

Abstract: This paper describes a parametric design methodology implemented to reduce gearbox design phase. A helicopter gearbox is a complex mechanical system, in which parts are heavily loaded in order to save weight but that have to run for thousands of hours without failure. Such a system is strongly optimized therefore the smallest change in specifications or in geometrical environments can drastically jeopardize the scheduling. In order to speed up the gearbox design process and to strengthen its robustness regarding specifications variability, a parametric design methodology has been developed thanks to a close collaboration between the laboratories and Eurocopter. [Copyright &y& Elsevier]

Considering the shock-resistance threshold of equipment on board as the important base for ship shock-resistance design and assessment, a finite element model of marine gearbox was established to get the characteristic of shock-resistance threshold. The shock-resistance threshold was analyzed using endurable stress method. Results indicate that endurable stress method is a direct and effective computational method for getting shock-resistance threshold of marine equipment. The shock-resistance threshold of marine gearbox is related to the peak value of acceleration and pulse width of input load. [ABSTRACT FROM AUTHOR]

Vibration analysis has been widely used in machine fault feature extraction and diagnosis of rotating machinery. The effects of modulation and nonstationarity in vibration signals collected from a faulty gearbox present challenges for fault feature extraction. Hilbert transform and S-transform have the ability to address these issues through demodulation and time-frequency analysis, respectively. In this paper, we propose to use a feature indicator to represent the S-transform coefficients. The proposed method integrates the advantages of Hilbert transform, S-transform, and the proposed feature indicator (FI). The validity of the proposed method is verified with a simulated signal and real gearbox vibration signals. Comparison studies show that the proposed method is more effective and does not require the operators to have a lot of diagnostic experience. [ABSTRACT FROM AUTHOR]

This paper is concerned with the experimental measurement and modelling of the torsional damping levels of a back-to-back gearbox rig. The aims of the investigation were to experimentally measure and analyse modal damping levels for the first nine torsional natural frequencies; to optimize damping parameters for modelling and to assess any limitations of the models for future work. Standard signal processing methods were used to determine modal damping levels from measured torsional frequency responses, with good confidence in the results. A damping sensitivity analysis for the two frequency domain receptance (FDR) models was used to determine optimum damping parameter values. Damping levels for six of nine natural frequencies were well matched with the experimental data. Discrepancies at other frequencies were attributed mainly to torsional-transverse coupling, present in the rig but not the model. Analysis of results for the ninth natural frequency determined a very low level of damping for the gearbox. It was also concluded that the model parameters may be used with confidence in a time domain receptance model for future investigations related to the test gearbox damping. [ABSTRACT FROM AUTHOR]

• This paper studies factors for design dominance in the wind turbine industry. • It focuses on the battle between the gearbox and the direct drive wind turbine. • The results show that energy cost and reliability are the most important factors. • The study opens up the black box of the factor technological characteristics. • Both drive train types still have the potential to become dominant. This paper studies the battle between two types of wind turbines, the gearbox wind turbine and the direct drive wind turbine. Applicable determinants that affect technological dominance for the wind turbine drive trains case are identified. By applying the Best-Worst Method, the relative importance to the determinants to understand which of the two wind turbine drive train types has the highest chance of achieving success are allocated. The results show that energy cost and reliability are the most important determinants, and that at this moment both drive train types still have the potential to become dominant. A contribution is made to the literature on dominant designs by focusing on the energy sector; a sector that has only scarcely been studied before with respect to design dominance. Furthermore, weights for factors for the technology dominance for the case of technology battles for wind turbine technology were established. [ABSTRACT FROM AUTHOR]

Understanding of planetary gearbox vibration spectrum components is helpful for researchers and engineers to develop fault diagnosis methods, however, few literatures has focus on comprehensive explanation of planetary gearbox vibration signal, there is a lack of knowledge on fully understanding of planetary gearbox vibration signal spectrum. To address this problem, a dynamic model of a planetary gearbox is established, signal of gearbox under different health state are simulated, simulation signal is processed to investigate spectrum components of planetary gear vibration signal; experiments are conducted to collect gearbox vibration signal to validate spectrum components analysis result from dynamic model simulation. [ABSTRACT FROM AUTHOR]

Planetary gear train are widely used in wind turbines on account of their properties of lower weight, higher transmission ratio and efficiency, bigger bearing capacity in comparison with fixed-shaft gear train. In wind turbine, the failure rate of planetary gearboxes is extremely high due to the harsh operation conditions. These gearboxes are often installed far off the ground which makes the maintenance cost very high. Due to these facts, developing the techniques for gearbox condition monitoring and early fault diagnosis really makes a lot of sense. Aimed at fault features of planetary gear train, the On-line monitoring system based on LABVIEW can achieve vibration monitoring, rotation monitoring, temperature monitoring and historical data query under a variety of operating conditions. To capture the operational status and to evaluate the health status of the wind turbine in real time, and to transmit it synchronously to the network, so as to provide theoretical guidance and basis for wind turbine maintenance. [ABSTRACT FROM AUTHOR]

The finite element analysis and experimental measurement are used to study the vibration characteristics of gearbox impact faults. Parametric models of gearbox gear train are built through three-dimensional modeling software, and the finite element software transient dynamics module is used to analyze the vibration acceleration response of the gearbox under different conditions of impact load. Compare the actual acceleration response which is collected from fault simulation experiment with the finite element simulation results to verify the accuracy of the parametric models. Meantime, the vibration response of the gear box impact failure is analyzed, and the sensor layout optimization scheme is proposed, which reduces the blindness of vibration measuring point arrangement and reduces the necessary channels for the monitoring and diagnosis. As a result, the cost of monitoring could be reduced. [ABSTRACT FROM AUTHOR]

This paper addresses the weak fault periodic oscillatory feature extraction from vibration signals using Periodicity-induced Overlapping Group Shrinkage (POGS). Incipient signals are considered as periodic group sparse signals submerged in noise. Based on the minimization of a convex cost function involving a group sparsity promoting penalty function and the principle of majorization-minimization, a fast iterative algorithm is engaged for its solution. The method is applied to analyse gearbox vibration signals which was acquired from a machinery fault simulator. The results demonstrate that the method can satisfactorily reveal periodic impulses. [ABSTRACT FROM AUTHOR]