Imbalanced fault diagnosis of rolling bearing using improved MsR-GAN and feature enhancement-driven CapsNet

Mechanical Systems and Signal Processing ◽

10.1016/j.ymssp.2021.108664 ◽

2022 ◽

Vol 168 ◽

pp. 108664

Author(s):

Jie Liu ◽

Changhe Zhang ◽

Xingxing Jiang

Keyword(s):

Fault Diagnosis ◽

Rolling Bearing ◽

Feature Enhancement

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Rolling bearing fault diagnosis using impulse feature enhancement and nonconvex regularization

Mechanical Systems and Signal Processing ◽

10.1016/j.ymssp.2020.106790 ◽

2020 ◽

Vol 142 ◽

pp. 106790 ◽

Author(s):

Huibin Lin ◽

Fangtan Wu ◽

Guolin He

Keyword(s):

Fault Diagnosis ◽

Rolling Bearing ◽

Bearing Fault ◽

Feature Enhancement ◽

Bearing Fault Diagnosis ◽

Nonconvex Regularization

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Early fault diagnosis of rolling bearing based on noise-assisted signal feature enhancement and stochastic resonance for intelligent manufacturing

The International Journal of Advanced Manufacturing Technology ◽

10.1007/s00170-019-04333-6 ◽

2019 ◽

Vol 107 (3-4) ◽

pp. 1017-1023 ◽

Author(s):

Heng Wang ◽

Jinhai Chen ◽

Yiwen Zhou ◽

Guangxian Ni

Keyword(s):

Fault Diagnosis ◽

Stochastic Resonance ◽

Rolling Bearing ◽

Intelligent Manufacturing ◽

Feature Enhancement

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An improved SVM model with double quantum genetic optimization and its application in fault diagnosis of rolling bearing

International Journal of Neural Systems Engineering ◽

10.21742/ijnse.2017.1.1.02 ◽

2017 ◽

Vol 1 (1) ◽

pp. 7-14

Author(s):

Ge Janghua ◽

◽

Xu Di ◽

Wang Yaping ◽

Xu Jiazhong ◽

...

Keyword(s):

Fault Diagnosis ◽

Rolling Bearing ◽

Double Quantum ◽

Genetic Optimization ◽

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Rolling Bearing Fault Diagnosis via ConceFT-Based Time-Frequency Reconfiguration Order Spectrum Analysis

IEEE Access ◽

10.1109/access.2018.2877711 ◽

2018 ◽

Vol 6 ◽

pp. 67131-67143 ◽

Author(s):

Dongdong Liu ◽

Weidong Cheng ◽

Weigang Wen

Keyword(s):

Fault Diagnosis ◽

Spectrum Analysis ◽

Rolling Bearing ◽

Time Frequency ◽

Bearing Fault ◽

Bearing Fault Diagnosis ◽

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Fault diagnosis method of rolling bearing based on multiple classifier ensemble of the weighted and balanced distribution adaptation under limited sample imbalance

ISA Transactions ◽

10.1016/j.isatra.2020.12.034 ◽

2020 ◽

Author(s):

Renxiang Chen ◽

Jukun Zhu ◽

Xiaolin Hu ◽

Haonian Wu ◽

Xiangyang Xu ◽

...

Keyword(s):

Fault Diagnosis ◽

Rolling Bearing ◽

Classifier Ensemble ◽

Limited Sample ◽

Multiple Classifier ◽

Balanced Distribution ◽

Diagnosis Method

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Modified multiscale weighted permutation entropy and optimized support vector machine method for rolling bearing fault diagnosis with complex signals

ISA Transactions ◽

10.1016/j.isatra.2020.12.054 ◽

2021 ◽

Author(s):

Zhenya Wang ◽

Ligang Yao ◽

Gang Chen ◽

Jiaxin Ding

Keyword(s):

Support Vector Machine ◽

Fault Diagnosis ◽

Rolling Bearing ◽

Permutation Entropy ◽

Support Vector ◽

Complex Signals ◽

Machine Method ◽

Support Vector Machine Method ◽

Bearing Fault ◽

Bearing Fault Diagnosis

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Rolling Bearing Fault Diagnosis using Transient-extracting Transform and Linear Discriminant Analysis

Measurement ◽

10.1016/j.measurement.2021.109298 ◽

2021 ◽

pp. 109298

Author(s):

Yuguo Zhou ◽

Shaoting Yan ◽

Yanbo Ren ◽

Shiliang Liu

Keyword(s):

Fault Diagnosis ◽

Discriminant Analysis ◽

Linear Discriminant Analysis ◽

Rolling Bearing ◽

Linear Discriminant ◽

Bearing Fault ◽

Bearing Fault Diagnosis

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Rolling bearing fault diagnosis method based on VMD and LSSVM

Journal of Physics Conference Series ◽

10.1088/1742-6596/1792/1/012035 ◽

2021 ◽

Vol 1792 (1) ◽

pp. 012035

Author(s):

Xingtong Zhu ◽

Zhiling Huang ◽

Jinfeng Chen ◽

Junhao Lu

Keyword(s):

Fault Diagnosis ◽

Rolling Bearing ◽

Bearing Fault ◽

Bearing Fault Diagnosis ◽

Diagnosis Method

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Fault Diagnosis of Rolling Bearing based on Permutation Entropy Optimized Maximum Correlation Kurtosis Deconvolution

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/1043/2/022029 ◽

2021 ◽

Vol 1043 (2) ◽

pp. 022029

Author(s):

Ping Liu ◽

Zhonghai Lin ◽

Min Zhang ◽

Yingkui Gu

Keyword(s):

Fault Diagnosis ◽

Rolling Bearing ◽

Permutation Entropy ◽

Maximum Correlation

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Rolling Bearing Fault Diagnosis Method Based on Improved Deep Belief Network

Journal of Physics Conference Series ◽

10.1088/1742-6596/1820/1/012105 ◽

2021 ◽

Vol 1820 (1) ◽

pp. 012105

Author(s):

Bingbing Hu ◽

Jiahui Tang ◽

Jimei Wu ◽

Jie Liu

Keyword(s):

Fault Diagnosis ◽

Rolling Bearing ◽

Deep Belief Network ◽

Belief Network ◽

Bearing Fault ◽

Bearing Fault Diagnosis ◽

Diagnosis Method

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