scholarly journals An Improved Empirical Wavelet Transform and Refined Composite Multiscale Dispersion Entropy-Based Fault Diagnosis Method for Rolling Bearing

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 168732-168742 ◽  
Author(s):  
Jinde Zheng ◽  
Siqi Huang ◽  
Haiyang Pan ◽  
Kuosheng Jiang
Keyword(s):  
Wavelet Transform ◽  
Fault Diagnosis ◽  
Rolling Bearing ◽  
Empirical Wavelet Transform ◽  
Diagnosis Method

Fault diagnosis method based on integration of RSSD and wavelet transform to rolling bearing

Measurement ◽  
2019 ◽  
Vol 131 ◽  
pp. 400-411 ◽  
Author(s):  
Baojia Chen ◽  
Baoming Shen ◽  
Fafa Chen ◽  
Hongliang Tian ◽  
Wenrong Xiao ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Fault Diagnosis ◽  
Rolling Bearing ◽  
Diagnosis Method

scholarly journals Fault Diagnosis of Rolling Bearing Based on Tunable Q-Factor Wavelet Transform and Convolutional Neural Network

2020 ◽  
Vol 16 (02) ◽  
pp. 47
Author(s):  
Liqun Hou ◽  
Zijing Li
Keyword(s):  
Neural Network ◽  
Wavelet Transform ◽  
Fault Diagnosis ◽  
Convolutional Neural Network ◽  
Vibration Signal ◽  
Rolling Bearing ◽  
Operating Conditions ◽  
Fault Classification ◽  
Rolling Ball ◽  
Diagnosis Method

Rolling bearing plays an important role in rotary machines and industrial processes. Effective fault diagnosis technology for rolling bearing directly affects the life and operator safety of the devices. In this paper, a fault diagnosis method based on tunable-Q wavelet transform (TQWT) and convolutional neural network (CNN) is proposed to reduce the influence of noise on bearing vibration signal and the dependence on the experience of traditional diagnosis methods. TQWT is used to decompose and denoise the vibration signal, while the CNN is adopted to extract fault features and carry out fault classification. Seven motor operating conditions—normal, drive end rolling ball failure (DE-B), drive end inner raceway failure (DE-IR), drive end outer raceway failure (DE-OR), fan end rolling ball failure (FE-B), fan end inner raceway fault (FE-IR) and fan end outer raceway fault (FE-OR)—are used to evaluate the proposed approach. The experimental results indicate that the fault diagnosis accuracy of the proposed method reaches 99.8%.

An improved empirical wavelet transform method for rolling bearing fault diagnosis

2020 ◽  
Vol 63 (11) ◽  
pp. 2231-2240
Author(s):  
HaiRun Huang ◽  
Ke Li ◽  
WenSheng Su ◽  
JianYi Bai ◽  
ZhiGang Xue ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Fault Diagnosis ◽  
Rolling Bearing ◽  
Transform Method ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis ◽  
Empirical Wavelet Transform
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