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Fault diagnosis of spur gearbox based on random forest and wavelet packet decomposition
Diego CABRERA,Fernando SANCHO,René-Vinicio SÁNCHEZ,Grover ZURITA,Mariela CERRADA,Chuan LI,Rafael E. VÁSQUEZ
《机械工程前沿（英文）》 2015年 第10卷 第3期 页码 277-286 doi: 10.1007/s11465-015-0348-8
This paper addresses the development of a random forest classifier for the multi-class fault diagnosis in spur gearboxes. The vibration signal’s condition parameters are first extracted by applying the wavelet packet decomposition with multiple mother wavelets, and the coefficients’ energy content for terminal nodes is used as the input feature for the classification problem. Then, a study through the parameters’ space to find the best values for the number of trees and the number of random features is performed. In this way, the best set of mother wavelets for the application is identified and the best features are selected through the internal ranking of the random forest classifier. The results show that the proposed method reached 98.68% in classification accuracy, and high efficiency and robustness in the models.
关键词： fault diagnosis spur gearbox wavelet packet decomposition random forest
Gear fault diagnosis using gear meshing stiffness identified by gearbox housing vibration signals
《机械工程前沿（英文）》 2022年 第17卷 第4期 doi: 10.1007/s11465-022-0713-3
关键词： gearbox fault diagnosis meshing stiffness identification transfer path signal processing
Pengxing YI,Peng HUANG,Tielin SHI
《机械工程前沿（英文）》 2016年 第11卷 第4期 页码 388-402 doi: 10.1007/s11465-016-0404-z
Wind turbine gearbox (WTG), which functions as an accelerator, ensures the performance and service life of wind turbine systems. This paper examines the distinctive modal properties of WTGs through finite element (FE) and experimental modal analyses. The study is performed in two parts. First, a whole system model is developed to investigate the first 10 modal frequencies and mode shapes of WTG using flexible multi-body modeling techniques. Given the complex structure and operating conditions of WTG, this study applies spring elements to the model and quantifies how the bearings and gear pair interactions affect the dynamic characteristics of WTGs. Second, the FE modal results are validated through experimental modal analyses of a 1.5 WM WTG using the frequency response function method of single point excitation and multi-point response. The natural frequencies from the FE and experimental modal analyses show favorable agreement and reveal that the characteristic frequency of the studied gearbox avoids its eigen-frequency very well.
关键词： wind turbine gearbox modal analysis finite element analysis modal frequency bearing equivalence
Experimental investigation of fatigue behavior of spur gear in altered tooth-sum gearing
H. K. SACHIDANANDA, Joseph GONSALVIS, H. R. PRAKASH
《机械工程前沿（英文）》 2012年 第7卷 第3期 页码 268-278 doi: 10.1007/s11465-012-0331-6
This paper deals with the contact stress, power loss, and pitting of spur gear tooth in altered tooth-sum gearing for a tooth-sum of 100 teeth when altered by±4% tooth-sum. Analytical and experimental methods were performed to investigate and compare the altered tooth-sum gearing against the standard tooth-sum gearing. The experiments were performed using a power recirculating type test rig. The tooth loads for the experimental investigations were determined considering the surface durability of gears. A clear picture of the surface damage was obtained using a scanning electron microphotograph. The negative alteration in the tooth-sum performed better than the positive alteration in a tooth-sum operating between specified center distances.
关键词： spur gear power recirculating test rig altered tooth-sum gearing scanning electron microscopy (SEM)
Digital twin-assisted gearbox dynamic model updating toward fault diagnosis
《机械工程前沿（英文）》 2023年 第18卷 第2期 doi: 10.1007/s11465-023-0748-0
关键词： digital twin gearbox model construction model updating physical–virtual interaction
Mesh relationship modeling and dynamic characteristic analysis of external spur gears with gear wear
《机械工程前沿（英文）》 2022年 第17卷 第1期 页码 9-9 doi: 10.1007/s11465-021-0665-z
关键词： gear wear mesh relationship mesh stiffness transmission error vibration characteristics
Intelligent fault diagnostic system based on RBR for the gearbox of rolling mills
Lixin GAO, Lijuan WU, Yan WANG, Houpei WEI, Hui YE
《机械工程前沿（英文）》 2010年 第5卷 第4期 页码 483-490 doi: 10.1007/s11465-010-0118-6
关键词： rule-based reasoning fault diagnosis intelligent system gear box
Guilian YI, Yunkang SUI, Jiazheng DU
《机械工程前沿（英文）》 2011年 第6卷 第2期 页码 229-234 doi: 10.1007/s11465-011-0128-z
To reduce vibration and noise, a damping layer and constraint layer are usually pasted on the inner surface of a gearbox thin shell, and their thicknesses are the main parameters in the vibration and noise reduction design. The normal acceleration of the point on the gearbox surface is the main index that can reflect the vibration and noise of that point, and the normal accelerations of different points can reflect the degree of the vibration and noise of the whole structure. The K-S function is adopted to process many points’ normal accelerations as the comprehensive index of the vibration characteristics of the whole structure, and the vibration acceleration level is adopted to measure the degree of the vibration and noise. Secondary development of the Abaqus preprocess and postprocess on the basis of the Python scripting programming automatically modifies the model parameters, submits the job, and restarts the analysis totally, which avoids the tedious work of returning to the Abaqus/CAE for modifying and resubmitting and improves the speed of the preprocess and postprocess and the computational efficiency.
关键词： Abaqus secondary development Python language vibration and noise reduction K-S function vibration acceleration level
Tacholess order-tracking approach for wind turbine gearbox fault detection
Yi WANG, Yong XIE, Guanghua XU, Sicong ZHANG, Chenggang HOU
《机械工程前沿（英文）》 2017年 第12卷 第3期 页码 427-439 doi: 10.1007/s11465-017-0452-z
Monitoring of wind turbines under variable-speed operating conditions has become an important issue in recent years. The gearbox of a wind turbine is the most important transmission unit; it generally exhibits complex vibration signatures due to random variations in operating conditions. Spectral analysis is one of the main approaches in vibration signal processing. However, spectral analysis is based on a stationary assumption and thus inapplicable to the fault diagnosis of wind turbines under variable-speed operating conditions. This constraint limits the application of spectral analysis to wind turbine diagnosis in industrial applications. Although order-tracking methods have been proposed for wind turbine fault detection in recent years, current methods are only applicable to cases in which the instantaneous shaft phase is available. For wind turbines with limited structural spaces, collecting phase signals with tachometers or encoders is difficult. In this study, a tacholess order-tracking method for wind turbines is proposed to overcome the limitations of traditional techniques. The proposed method extracts the instantaneous phase from the vibration signal, resamples the signal at equiangular increments, and calculates the order spectrum for wind turbine fault identification. The effectiveness of the proposed method is experimentally validated with the vibration signals of wind turbines.
关键词： wind turbine variable-speed operating conditions Vold-Kalman filtering tacholess order tracking
Yun KONG, Tianyang WANG, Zheng LI, Fulei CHU
《机械工程前沿（英文）》 2017年 第12卷 第3期 页码 406-419 doi: 10.1007/s11465-017-0419-0
Planetary transmission plays a vital role in wind turbine drivetrains, and its fault diagnosis has been an important and challenging issue. Owing to the complicated and coupled vibration source, time-variant vibration transfer path, and heavy background noise masking effect, the vibration signal of planet gear in wind turbine gearboxes exhibits several unique characteristics: Complex frequency components, low signal-to-noise ratio, and weak fault feature. In this sense, the periodic impulsive components induced by a localized defect are hard to extract, and the fault detection of planet gear in wind turbines remains to be a challenging research work. Aiming to extract the fault feature of planet gear effectively, we propose a novel feature extraction method based on spectral kurtosis and time wavelet energy spectrum (SK-TWES) in the paper. Firstly, the spectral kurtosis (SK) and kurtogram of raw vibration signals are computed and exploited to select the optimal filtering parameter for the subsequent band-pass filtering. Then, the band-pass filtering is applied to extrude periodic transient impulses using the optimal frequency band in which the corresponding SK value is maximal. Finally, the time wavelet energy spectrum analysis is performed on the filtered signal, selecting Morlet wavelet as the mother wavelet which possesses a high similarity to the impulsive components. The experimental signals collected from the wind turbine gearbox test rig demonstrate that the proposed method is effective at the feature extraction and fault diagnosis for the planet gear with a localized defect.
关键词： wind turbine planet gear fault feature extraction spectral kurtosis time wavelet energy spectrum
Review of the damage mechanism in wind turbine gearbox bearings under rolling contact fatigue
Yun-Shuai SU, Shu-Rong YU, Shu-Xin LI, Yan-Ni HE
《机械工程前沿（英文）》 2019年 第14卷 第4期 页码 434-441 doi: 10.1007/s11465-018-0474-1
关键词： rolling contact fatigue (RCF) white etching area (WEA) white etching crack (WEC) adiabatic shear band (ASB)
Zhaohui DU, Xuefeng CHEN, Han ZHANG, Yanyang ZI, Ruqiang YAN
《机械工程前沿（英文）》 2017年 第12卷 第3期 页码 333-347 doi: 10.1007/s11465-017-0435-0
The gearbox of a wind turbine (WT) has dominant failure rates and highest downtime loss among all WT subsystems. Thus, gearbox health assessment for maintenance cost reduction is of paramount importance. The concurrence of multiple faults in gearbox components is a common phenomenon due to fault induction mechanism. This problem should be considered before planning to replace the components of the WT gearbox. Therefore, the key fault patterns should be reliably identified from noisy observation data for the development of an effective maintenance strategy. However, most of the existing studies focusing on multiple fault diagnosis always suffer from inappropriate division of fault information in order to satisfy various rigorous decomposition principles or statistical assumptions, such as the smooth envelope principle of ensemble empirical mode decomposition and the mutual independence assumption of independent component analysis. Thus, this paper presents a joint subspace learning-based multiple fault detection (JSL-MFD) technique to construct different subspaces adaptively for different fault patterns. Its main advantage is its capability to learn multiple fault subspaces directly from the observation signal itself. It can also sparsely concentrate the feature information into a few dominant subspace coefficients. Furthermore, it can eliminate noise by simply performing coefficient shrinkage operations. Consequently, multiple fault patterns are reliably identified by utilizing the maximum fault information criterion. The superiority of JSL-MFD in multiple fault separation and detection is comprehensively investigated and verified by the analysis of a data set of a 750 kW WT gearbox. Results show that JSL-MFD is superior to a state-of-the-art technique in detecting hidden fault patterns and enhancing detection accuracy.
关键词： joint subspace learning multiple fault diagnosis sparse decomposition theory coupling feature separation wind turbine gearbox
Effect of friction coefficients on the dynamic response of gear systems
Lingli JIANG, Zhenyong DENG, Fengshou GU, Andrew D. BALL, Xuejun LI
《机械工程前沿（英文）》 2017年 第12卷 第3期 页码 397-405 doi: 10.1007/s11465-017-0415-4
The inevitable deterioration of the lubrication conditions in a gearbox in service can change the tribological properties of the meshing teeth. In turn, such changes can significantly affect the dynamic responses and running status of gear systems. This paper investigates such an effect by utilizing virtual prototype technology to model and simulate the dynamics of a wind turbine gearbox system. The change in the lubrication conditions is modeled by the changes in the friction coefficients, thereby indicating that poor lubrication causes not only increased frictional losses but also significant changes in the dynamic responses. These results are further demonstrated by the mean and root mean square values calculated by the simulated responses under different friction coefficients. In addition, the spectrum exhibits significant changes in the first, second, and third harmonics of the meshing components. The findings and simulation method of this study provide theoretical bases for the development of accurate diagnostic techniques.
关键词： dynamic response friction coefficient wind loads wind turbine gearbox
Weak characteristic information extraction from early fault of wind turbine generator gearbox
Xiaoli XU, Xiuli LIU
《机械工程前沿（英文）》 2017年 第12卷 第3期 页码 357-366 doi: 10.1007/s11465-017-0423-4
Given the weak early degradation characteristic information during early fault evolution in gearbox of wind turbine generator, traditional singular value decomposition (SVD)-based denoising may result in loss of useful information. A weak characteristic information extraction based on µ-SVD and local mean decomposition (LMD) is developed to address this problem. The basic principle of the method is as follows: Determine the denoising order based on cumulative contribution rate, perform signal reconstruction, extract and subject the noisy part of signal to LMD and µ-SVD denoising, and obtain denoised signal through superposition. Experimental results show that this method can significantly weaken signal noise, effectively extract the weak characteristic information of early fault, and facilitate the early fault warning and dynamic predictive maintenance.
关键词： wind turbine generator gearbox µ-singular value decomposition local mean decomposition weak characteristic information extraction early fault warning
标题 作者 时间 类型 操作
Fault diagnosis of spur gearbox based on random forest and wavelet packet decomposition
Diego CABRERA,Fernando SANCHO,René-Vinicio SÁNCHEZ,Grover ZURITA,Mariela CERRADA,Chuan LI,Rafael E. VÁSQUEZ
期刊论文
Gear fault diagnosis using gear meshing stiffness identified by gearbox housing vibration signals
期刊论文
Numerical analysis and experimental investigation of modal properties for the gearbox in wind turbine
Pengxing YI,Peng HUANG,Tielin SHI
期刊论文
Experimental investigation of fatigue behavior of spur gear in altered tooth-sum gearing
H. K. SACHIDANANDA, Joseph GONSALVIS, H. R. PRAKASH
期刊论文
Mesh relationship modeling and dynamic characteristic analysis of external spur gears with gear wear
期刊论文
Intelligent fault diagnostic system based on RBR for the gearbox of rolling mills
Lixin GAO, Lijuan WU, Yan WANG, Houpei WEI, Hui YE
期刊论文
Application of python-based Abaqus preprocess and postprocess technique in analysis of gearbox vibration
Guilian YI, Yunkang SUI, Jiazheng DU
期刊论文
Tacholess order-tracking approach for wind turbine gearbox fault detection
Yi WANG, Yong XIE, Guanghua XU, Sicong ZHANG, Chenggang HOU
期刊论文
Fault feature extraction of planet gear in wind turbine gearbox based on spectral kurtosis and time wavelet
Yun KONG, Tianyang WANG, Zheng LI, Fulei CHU
期刊论文
Review of the damage mechanism in wind turbine gearbox bearings under rolling contact fatigue
Yun-Shuai SU, Shu-Rong YU, Shu-Xin LI, Yan-Ni HE
期刊论文
Multiple fault separation and detection by joint subspace learning for the health assessment of wind turbine gearboxes
Zhaohui DU, Xuefeng CHEN, Han ZHANG, Yanyang ZI, Ruqiang YAN
期刊论文
Effect of friction coefficients on the dynamic response of gear systems
Lingli JIANG, Zhenyong DENG, Fengshou GU, Andrew D. BALL, Xuejun LI
期刊论文
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