期刊论文详细信息
IEEE Access
Automatic Diagnosis of Rolling Element Bearing Under Different Conditions Based on RVMD and Envelope Order Capture
Xiaolong Wang1  Xin Yu2  Peng Du2  Yingjie Wu3  Xiaoming Li3  Zhongzhong Hu3  Weilun An3 
[1] Department of Mechanical Engineering, North China Electric Power University, Baoding, China;Jilin CPI New Energy Company Ltd., Changchun, China;School of Automation Engineering, Northeast Electric Power University, Jilin, China;
关键词: Rolling element bearing;    automatic fault diagnosis;    recursive variational mode decomposition;    envelope order capture;   
DOI  :  10.1109/ACCESS.2019.2927039
来源: DOAJ
【 摘 要 】

Fault characteristic frequency is the main basis for rolling element bearing diagnostics but finding a suitable frequency band for demodulation and searching for the fault characteristic frequencies consume a lot of time and manpower in practice. A data-driven method based on recursive variational mode decomposition (RVMD), and an envelope order capture is proposed to realize the automatic fault diagnosis of bearing under different operating conditions. The process starts with a new proposed RVMD of the vibration signal, where the mode with maximum kurtosis of the unbiased autocorrelation of the envelope is selected to get envelope order spectrum. Thereafter, an order capture algorithm is designed to automatically search for the fault characteristic orders in theory, which are used for constructing feature vectors for diagnosis. The proposed method is tested on two test-beds which both contain the same type of bearing (SKF6205) but operate in different conditions, and gets good performance in bearing diagnosis. In addition, the fault diagnosis of test-bed two using training samples that are from test-bed one is investigated. This method reveals well generalization capability in the fault diagnosis of the same type of rolling element bearing under different operating conditions.

【 授权许可】

Unknown   

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