Hierarchical fuzzy entropy and improved support vector machine based binary tree approach for rolling bearing fault diagnosis

2016 ◽  
Vol 98 ◽  
pp. 114-132 ◽  
Author(s):  
Yongbo Li ◽  
Minqiang Xu ◽  
Haiyang Zhao ◽  
Wenhu Huang
Keyword(s):  
Support Vector Machine ◽  
Fault Diagnosis ◽  
Binary Tree ◽  
Rolling Bearing ◽  
Fuzzy Entropy ◽  
Support Vector ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis ◽  
Improved Support Vector Machine ◽  
Tree Approach

A novel deep stacking least squares support vector machine for rolling bearing fault diagnosis

2019 ◽  
Vol 110 ◽  
pp. 36-47 ◽  
Author(s):  
Xin Li ◽  
Yu Yang ◽  
Haiyang Pan ◽  
Jian Cheng ◽  
Junsheng Cheng
Keyword(s):  
Support Vector Machine ◽  
Fault Diagnosis ◽  
Least Squares ◽  
Rolling Bearing ◽  
Support Vector ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis

scholarly journals A rolling bearing fault diagnosis method based on VMD – multiscale fractal dimension/energy and optimized support vector machine

2016 ◽  
Vol 18 (6) ◽  
pp. 3581-3595
Author(s):  
Binbin Xu ◽  
Fei Chen ◽  
Xiaojuan Chen ◽  
Zhaojun Yang ◽  
Qunya Xie ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Fractal Dimension ◽  
Fault Diagnosis ◽  
Rolling Bearing ◽  
Support Vector ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis ◽  
Diagnosis Method

scholarly journals Rolling Bearing Fault Diagnosis Based on Convolutional Neural Network and Support Vector Machine

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 137395-137406 ◽  
Author(s):  
Laohu Yuan ◽  
Dongshan Lian ◽  
Xue Kang ◽  
Yuanqiang Chen ◽  
Kejia Zhai
Keyword(s):  
Neural Network ◽  
Support Vector Machine ◽  
Fault Diagnosis ◽  
Convolutional Neural Network ◽  
Rolling Bearing ◽  
Support Vector ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis
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