An optimized VMD method and its applications in bearing fault diagnosis

Li, Hua; Liu, Tao; Wu, Xing; Chen, Qing

doi:10.1016/j.measurement.2020.108185

An optimized VMD method and its applications in bearing fault diagnosis

Journal Article · Mon Nov 30 23:00:00 EST 2020 · Measurement

DOI:https://doi.org/10.1016/j.measurement.2020.108185· OSTI ID:2280221

Li, Hua; Liu, Tao; Wu, Xing; Chen, Qing

Not Available

View Accepted Manuscript (Publisher)

Sponsoring Organization:: USDOE

OSTI ID:: 2280221

Journal Information:: Measurement, Journal Name: Measurement Journal Issue: C Vol. 166; ISSN 0263-2241

Publisher:: ElsevierCopyright Statement

Country of Publication:: United Kingdom

Language:: English

References (25)

Application of EEMD and improved frequency band entropy in bearing fault feature extraction Li, Hua; Liu, Tao; Wu, Xing ISA Transactions, Vol. 88 https://doi.org/10.1016/j.isatra.2018.12.002	journal	May 2019
An insight concept to select appropriate IMFs for envelope analysis of bearing fault diagnosis Tsao, Wen-Chang; Li, Yi-Fan; Le, Duc Du Measurement, Vol. 45, Issue 6 https://doi.org/10.1016/j.measurement.2012.02.030	journal	July 2012
A novel bearing fault diagnosis model integrated permutation entropy, ensemble empirical mode decomposition and optimized SVM Zhang, Xiaoyuan; Liang, Yitao; Zhou, Jianzhong Measurement, Vol. 69 https://doi.org/10.1016/j.measurement.2015.03.017	journal	June 2015
Wheel-bearing fault diagnosis of trains using empirical wavelet transform Cao, Hongrui; Fan, Fei; Zhou, Kai Measurement, Vol. 82 https://doi.org/10.1016/j.measurement.2016.01.023	journal	March 2016
Demodulation analysis based on adaptive local iterative filtering for bearing fault diagnosis An, Xueli; Zeng, Hongtao; Li, Chaoshun Measurement, Vol. 94 https://doi.org/10.1016/j.measurement.2016.08.039	journal	December 2016
Fault detection of a wheelset bearing in a high-speed train using the shock-response convolutional sparse-coding technique Ding, Jianming Measurement, Vol. 117 https://doi.org/10.1016/j.measurement.2017.12.010	journal	March 2018
Filter bank property of variational mode decomposition and its applications Wang, Yanxue; Markert, Richard Signal Processing, Vol. 120 https://doi.org/10.1016/j.sigpro.2015.09.041	journal	March 2016
Variational mode decomposition denoising combined the detrended fluctuation analysis Liu, Yuanyuan; Yang, Gongliu; Li, Ming Signal Processing, Vol. 125 https://doi.org/10.1016/j.sigpro.2016.02.011	journal	August 2016
Multilevel thresholding selection based on variational mode decomposition for image segmentation Li, Jiafu; Tang, Wenyan; Wang, Jun Signal Processing, Vol. 147 https://doi.org/10.1016/j.sigpro.2018.01.022	journal	June 2018
Independence-oriented VMD to identify fault feature for wheel set bearing fault diagnosis of high speed locomotive Li, Zipeng; Chen, Jinglong; Zi, Yanyang Mechanical Systems and Signal Processing, Vol. 85 https://doi.org/10.1016/j.ymssp.2016.08.042	journal	February 2017
Research on variational mode decomposition in rolling bearings fault diagnosis of the multistage centrifugal pump Zhang, Ming; Jiang, Zhinong; Feng, Kun Mechanical Systems and Signal Processing, Vol. 93 https://doi.org/10.1016/j.ymssp.2017.02.013	journal	September 2017
Research on bearing fault feature extraction based on singular value decomposition and optimized frequency band entropy Li, Hua; Liu, Tao; Wu, Xing Mechanical Systems and Signal Processing, Vol. 118 https://doi.org/10.1016/j.ymssp.2018.08.056	journal	March 2019
Precise feature extraction from wind turbine condition monitoring signals by using optimised variational mode decomposition Shi, Pu; Yang, Wenxian IET Renewable Power Generation, Vol. 11, Issue 3 https://doi.org/10.1049/iet-rpg.2016.0716	journal	January 2017
An Improved VMD With Empirical Mode Decomposition and Its Application in Incipient Fault Detection of Rolling Bearing Jiang, Fan; Zhu, Zhencai; Li, Wei IEEE Access, Vol. 6 https://doi.org/10.1109/ACCESS.2018.2851374	journal	January 2018
Application of Parameter Optimized Variational Mode Decomposition Method in Fault Diagnosis of Gearbox Wang, Zhijian; He, Gaofeng; Du, Wenhua IEEE Access, Vol. 7 https://doi.org/10.1109/ACCESS.2019.2909300	journal	January 2019
Comparative study between VMD and EMD in bearing fault diagnosis Mohanty, Satish; Gupta, Karunesh Kumar; Raju, Kota Solomon 2014 9th International Conference on Industrial and Information Systems (ICIIS) https://doi.org/10.1109/ICIINFS.2014.7036515	conference	December 2014
Real-Time Classification of Healthy and Apnea Subjects Using ECG Signals With Variational Mode Decomposition Smruthy, A.; Suchetha, M. IEEE Sensors Journal, Vol. 17, Issue 10 https://doi.org/10.1109/JSEN.2017.2690805	journal	May 2017
Shockable Rhythm Diagnosis for Automated External Defibrillators Using a Modified Variational Mode Decomposition Technique Nguyen, Minh Tuan; Van Nguyen, Binh; Kim, Kiseon IEEE Transactions on Industrial Informatics, Vol. 13, Issue 6 https://doi.org/10.1109/TII.2017.2740435	journal	December 2017
Variational Mode Decomposition and Decision Tree Based Detection and Classification of Power Quality Disturbances in Grid-Connected Distributed Generation System Achlerkar, Pankaj D.; Samantaray, S. R.; Sabarimalai Manikandan, M. IEEE Transactions on Smart Grid, Vol. 9, Issue 4 https://doi.org/10.1109/TSG.2016.2626469	journal	July 2018
Variational Mode Decomposition Dragomiretskiy, Konstantin; Zosso, Dominique IEEE Transactions on Signal Processing, Vol. 62, Issue 3 https://doi.org/10.1109/TSP.2013.2288675	journal	February 2014
A Novel Fault Diagnosis Model for Bearing of Railway Vehicles Using Vibration Signals Based on Symmetric Alpha-Stable Distribution Feature Extraction Li, Yongjian; Zhang, Weihua; Xiong, Qing Shock and Vibration, Vol. 2016 https://doi.org/10.1155/2016/5714195	journal	January 2016
Rolling Bearing Fault Signal Extraction Based on Stochastic Resonance-Based Denoising and VMD Gu, Xiaojiao; Chen, Changzheng International Journal of Rotating Machinery, Vol. 2017 https://doi.org/10.1155/2017/3595871	journal	January 2017
Denoising of hydropower unit vibration signal based on variational mode decomposition and approximate entropy An, Xueli; Yang, Junjie Transactions of the Institute of Measurement and Control, Vol. 38, Issue 3 https://doi.org/10.1177/0142331215592064	journal	July 2015
The fault detection and diagnosis in rolling element bearings using frequency band entropy Liu, Tao; Chen, Jin; Dong, Guangming Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, Vol. 227, Issue 1 https://doi.org/10.1177/0954406212441886	journal	March 2012
Mechanical Fault Diagnosis of High Voltage Circuit Breakers Based on Variational Mode Decomposition and Multi-Layer Classifier Huang, Nantian; Chen, Huaijin; Cai, Guowei Sensors, Vol. 16, Issue 11 https://doi.org/10.3390/s16111887	journal	November 2016

Similar Records

Application of an improved minimum entropy deconvolution method for railway rolling element bearing fault diagnosis

Journal Article · Sun Jul 01 00:00:00 EDT 2018 · Journal of Sound and Vibration · OSTI ID:1548707

A feature extraction and machine learning framework for bearing fault diagnosis

Journal Article · Sun May 01 00:00:00 EDT 2022 · Renewable Energy · OSTI ID:1865970

Unsupervised domain adaptation via enhanced transfer joint matching for bearing fault diagnosis

Journal Article · Mon Nov 30 23:00:00 EST 2020 · Measurement · OSTI ID:2279631

An optimized VMD method and its applications in bearing fault diagnosis

Citation Formats

References (25)

Similar Records

Related Subjects