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Journal of Central South University 2016年第7期23卷 1682-1689页

作者：赵德尊李建勇程卫东王天杨温伟刚 School of Mechanical Electronic and Control Engineering Beijing Jiaotong University

The accurate estimation of the rolling element bearing instantaneous rotational frequency(IRF) is the key capability of the order tracking method based on time-frequency analysis. The rolling element bearing IRF can be accurately estimated according to the instantaneous fault characteristic frequency(IFCF). However, in an environment with a low signal-to-noise ratio(SNR), e.g., an incipient fault or function at a low speed, the signal contains strong background noise that seriously affects the effectiveness of the aforementioned method. An algorithm of signal preprocessing based on empirical mode decomposition(EMD) and wavelet shrinkage was proposed in this work. Compared with EMD denoising by the cross-correlation coefficient and kurtosis(CCK) criterion, the method of EMD soft-thresholding(ST) denoising can ensure the integrity of the signal, improve the SNR, and highlight fault features. The effectiveness of the algorithm for rolling element bearing IRF estimation by EMD ST denoising and the IFCF was validated by both simulated and experimental bearing vibration signals at a low SNR.

关键词： rolling element bearing low signal-to-noise ratio empirical mode decomposition soft-thresholding denoising instantaneous fault characteristic frequency instantaneous rotational frequency

rolling element bearing Diagnostics by Combination of Envelope Analysis and Wavelet Transform

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Journal of University of Science and Technology Beijing 2001年第1期8卷 69-74页

作者： Ying Tang, Qiao Sun Mechanical Engineering School, University of Science and Technology Beijing, Beijing 100083, China Department of Mechanical Engineering, University of Calgary Calgary Alberta T2N 1N4, Canada Univ Sci & Technol Beijing Sch Mech Engn Beijing 100083 Peoples R China Univ Calgary Dept Mech Engn Calgary AB T2N 1N4 Canada

rolling element-bearing diagnostics has been studied over the last thirty years, and envelope analysis is widely recognized as being the best approach for detection and diagnosis of rolling element bearing incipient failure. But one of the on-going difficulties with envelope technique is to determine the best frequency band to envelop. Here, wavelet transform technique is introduced into envelope analysis to solve the problem by capturing bearing defects-sensory scales (i.e. frequency bands). A modulated Gaussian function is chosen to be the analytical wavelet because it coincides well with bearing defect-induced vibration signal patterns. Vibration signals measured from railway bearing tests were studied by the proposed method. Cases of bearings with single and multiple defects on inner and outer race under different testing conditions are presented. Experimental results showed that the proposed method allowed a more accurate local description and separation of transient signal part, which were caused by impacts between defects and the mating surfaces in the bearing. The combination method provides an effective signal detection technique for rolling element-bearing diagnostics.

关键词： continuous wavelet transform envelope analysis rolling element bearing diagnostics

Feature Extraction and Recognition for rolling element bearing Fault Utilizing Short-Time Fourier Transform and Non-negative Matrix Factorization

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Chinese Journal of Mechanical Engineering 2015年第1期28卷 96-105页

作者： GAO Huizhong LIANG Lin CHEN Xiaoguang XU Guanghua School of Mechanical Engineering Xi'an Jiaotong University The 705 Research Institute China Shipbuilding Industry Corporation Key Laboratory for Modern Design and Rotor-bearing System of Education Ministry Xi'an Jiaotong University State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University

Due to the non-stationary characteristics of vibration signals acquired from rolling element bearing fault, thc time-frequency analysis is often applied to describe the local information of these unstable signals smartly. However, it is difficult to classitythe high dimensional feature matrix directly because of too large dimensions for many classifiers. This paper combines the concepts of time-frequency distribution（TFD） with non-negative matrix factorization（NMF）, and proposes a novel TFD matrix factorization method to enhance representation and identification of bearing fault. Throughout this method, the TFD of a vibration signal is firstly accomplished to describe the localized faults with short-time Fourier transform（STFT）. Then, the supervised NMF mapping is adopted to extract the fault features from TFD. Meanwhile, the fault samples can be clustered and recognized automatically by using the clustering property of NMF. The proposed method takes advantages of the NMF in the parts-based representation and the adaptive clustering. The localized fault features of interest can be extracted as well. To evaluate the performance of the proposed method, the 9 kinds of the bearing fault on a test bench is performed. The proposed method can effectively identify the fault severity and different fault types. Moreover, in comparison with the artificial neural network（ANN）, NMF yields 99.3% mean accuracy which is much superior to ANN. This research presents a simple and practical resolution for the fault diagnosis problem of rolling element bearing in high dimensional feature space.

关键词： time-frequency distribution non-negative matrix factorization rolling element bearing feature extraction

Fault Diagnosis of rolling element bearing Using Multi-Scale Lempel-Ziv Complexity and Mahalanobis Distance Criterion

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Journal of Shanghai Jiaotong university(Science) 2018年第5期23卷 696-701页

作者： YU Kun TAN Jiwen LIN Tianran School of Mechanical and Automotive Engineering Qingdao University of TechnologyQingdao 266525ShandongChina

A new fault diagnosis technique for rolling element bearing using multi-scale Lempel-Ziv complexity(LZC) and Mahalanobis distance(MD) criterion is proposed in this study. A multi-scale coarse-graining process is used to extract fault features for various bearing fault conditions to overcome the limitation of the single stage coarse-graining process in the LZC algorithm. This is followed by the application of MD criterion to calculate the accuracy rate of LZC at different scales, and the best scale corresponding to the maximum accuracy rate is identified for fault pattern recognition. A comparison analysis with Euclidean distance(ED) criterion is also presented to verify the superiority of the proposed method. The result confirms that the fault diagnosis technique using a multi-scale LZC and MD criterion is more effective in distinguishing various fault conditions of rolling element bearings.

关键词： fault diagnosis rolling element bearing Lempel-Ziv complexity (LZC) Mahalanobis distance (MD)criterion

Investigation on Skidding of rolling element bearing in Loaded Zone

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Journal of Harbin Institute of Technology(New Series) 2013年第1期20卷 34-41页

作者： Yi-Min Shao Wen-Bing Tu Zai-Gang Chen Zhi-Jie Xie Bao-Yu Song State Key Laboratory of Mechanical Transmission Chongqing University School of Mechatronics Engineering Harbin Institute of Technology

Skidding which occurs when rolling element entering into the loaded zone is prone to cause wear and incipient failure to the raceways and rolling elements. This paper presents a dynamic model to investigate the skidding of a rolling element bearing under radial load when the rolling element is entering into the load zone. In this dynamic model, the effects of the contact forces, friction forces on the rolling element-race and rolling element-cage interfaces, gravity, and the centrifugal forces of rolling elements are taken into consideration. The Hertzian contact theory is applied to calculate the non-linear contact forces. The Coulomb friction law is used to calculate the friction forces. The differential equations of rotational motion of the rolling element with regard to its central axis and the central axis of the outer ring are established respectively. The dynamic equations are then solved by using a fourth-order Runge-Kutta algorithm. The skidding characteristics of rolling element at the entry into the loaded zone are exposed, and the effects of the operating parameters on skidding behavior are carefully investigated.

关键词： rolling element bearing skidding loaded zone dynamic model

Condition Monitoring of rolling element bearing Based on Phase-PCA

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Condition Monitoring of Rolling Element Bearing Based on Pha...

An improved resampling algorithm for rolling element bearing fault diagnosis under variable rotational speeds

第25届中国控制与决策会议

作者： Liying Jiang Zhipeng Liu Jianguo Cui Zhonghai Li School of Automation Shenyang Aerospace University

ISBN: (纸本)9781467355339

As the key component of many rotating machineries, running condition of rolling element bearings must be monitored for guaranteeing production efficiency and safety. In this paper, a new method of condition monitoring for rolling element bearing, Phase-PCA, is proposed based on Principal Component Analysis （PCA） and Phase Space Reconstruction （PSR）. Firstly, the phase space of the one dimension vibration signals is gained via using C-C method. Then, PCA is applied in this space. The proposed method is tested with experimental data collected from drive end ball bearing of a 2 hp Reliance Electric motor driven mechanical system. The simulation results show not only SPE statistic but also T 2 statistic can effectively identify different conditions of rolling element bearings and the degree of confidence is further improved.

关键词： Vibration Signals PCA rolling element bearing Condition Monitoring

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Journal of Southeast University(English Edition) 2017年第2期33卷 150-158页

作者：赵德尊李建勇程卫东温伟刚北京交通大学机械与电子控制工程学院北京100044 北京交通大学载运工具先进制造与测控技术教育部重点实验室北京100044

In order to address the issues of traditional resampling algorithms involving computational accuracy and efficiency in rolling element bearing fault diagnosis, an equal division impulse-based（EDI-based） resampling algorithm is proposed. First, the time marks of every rising edge of the rotating speed pulse and the corresponding amplitudes of faulty bearing vibration signal are determined. Then, every adjacent the rotating pulse is divided equally, and the time marks in every adjacent rotating speed pulses and the corresponding amplitudes of vibration signal are obtained by the interpolation algorithm. Finally, all the time marks and the corresponding amplitudes of vibration signal are arranged and the time marks are transformed into the angle domain to obtain the resampling signal. Speed-up and speed-down faulty bearing signals are employed to verify the validity of the proposed method, and experimental results show that the proposed method is effective for diagnosing faulty bearings. Furthermore, the traditional order tracking techniques are applied to the experimental bearing signals, and the results show that the proposed method produces higher accurate outcomes in less computation time.

关键词： rolling element bearing fault diagnosis variable rotational speed equal division impulse-based resampling

Fault Diagnosis for rolling element bearing Using EMD-DFDA

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Fault Diagnosis for Rolling Element Bearing Using EMD-DFDA

Synchronous chirp mode extraction: A promising tool for fault diagnosis of rolling element bearings under varying speed conditions

第26届中国控制与决策会议

作者： Liying Jiang Yanpeng Zhang Guangting Gong Zhipeng Liu Jianguo Cui School of Automation Shenyang Aerospace University

A new fault diagnosis method for rolling element bearing is proposed based on empirical mode decomposition（EMD） and fisher discriminant analysis（FDA）. First, non-stationary vibration signals are processed by applying EMD technique, and stationary IMF components are obtained. Then, fault feature vectors with the moving time-lagged windows are composed using the absolute values of IMF components of healthy and detection bearings in order to consider the dynamic behavior. Finally, a DFDA model is construed and a linear discriminant matrix is obtained by which IMF components are projected into the low discriminant space. The diagnosis performance of the proposed method is tested using a dataset from bearing data center of Case Western Reserve University.

关键词： Vibration Signals EMD rolling element bearing DFDA Fault Diagnosis

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Chinese Journal of Aeronautics 2022年第1期35卷 348-364页

作者： Xingxing JIANG Qiang HUANG Changqing SHEN Qian WANG Kun XU Jie LIU Juanjuan SHI Zhongkui ZHU School of Rail Transportation Soochow UniversitySuzhou 215131China Wenzheng College of Soochow University Suzhou 215104China College of Energy and Power Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China Sclool of Hydropower and Infonnation Engineering Huazhong University of Science and TechnologyWuhan 430074China

As critical components in modern aerospace productions,rolling element bearings(REBs)generally work under varying speed conditions,which brings great challenges to their operating health *** novel time–frequency decomposition(TFD)algorithms are established recently to extract nonlinear features from the non-stationary signals effectively,which are promising for realizing fault diagnosis of REBs under varying speed ***,numerous personal experiences must be incorporated and the anti-noise performance of these methods needs to be further *** these issues,a synchronous chirp mode extraction(SCME)-based REB fault diagnosis method is proposed for the health monitoring of REBs under varying speed conditions in this *** mainly consists of following two parts.(a)The shaft rotational frequency(SRF)is initially estimated from the low-frequency band of the vibration ***,an adaptive refining strategy is incorporated to obtain a suitable bandwidth parameter.(b)A cycle-one-step estimation frame is constructed to extract synchronous modes from the envelope waveform of the vibration ***,a synchronous mode spectrum(SMS)is generated using the information of the extracted synchronous modes,which is a novel REBs fault diagnosis technique with tacholess and *** contrast to the current TFD algorithms,the proposed method needs fewer input parameters and owns a well anti-noise performance because there is no iterative optimization in the procedure of construction of *** a result,the health conditions of REBs are evaluated by detecting the exhibited features in the *** and experiments are conducted to validate the effectiveness of the proposed method in terms of REB fault *** results demonstrate that the proposed method outperforms the current TFD algorithm and the conventional order tracking technique for fault diagnosis of REB under varying speed conditions.

关键词： Envelope analysis Fault diagnosis Order tracking rolling element bearing Varying speed

Improving Kinetic Energy Storage for Vehicles through the Combination of rolling element and Active Magnetic bearing

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Journal of Energy and Power Engineering 2014年第7期8卷 1323-1332页

作者： Manes Recheis Armin Buchroithner Ivan Andrasec Thomas Gallien Bernhard Schweighofer Michael Bader Hannes Wegleiter Institute of Electrical Measurement and Measurement Signal Processing Graz University of Technology Graz 8010 Austria Institute of Machine Components and Methods of Development Graz University of Technology Graz 8010 Austria

The demand for short term energy storage providing high power for electric and hybrid-electric vehicles is increasing drastically. Stationary FESS （flywheel energy storage systems） is established as UPS （uninterruptible power supply） and represent an emerging market. In contrast, mobile FESSs are currently only used in a few application, e.g., in motor sports. To enable a wider use in personal and public transportation the life-span of the flywheel＇s bearings needs to be increased significantly. This paper presents an alternative approach to extend the lifespan of the flywheel＇s bearings significantly by using a CREAMB （combination of rolling element and active magnetic bearings）.

关键词： Flywheel energy storage system mechanical battery resilient bearing mount rolling element bearing active magnetic bearing life-span.