A Novel Fault Diagnosis Method for Rolling Bearing Based on TVFEMD Energy Entropy and PFA-LSSVM Optimization Model-Reference-Cited by-同舟云学术

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A Novel Fault Diagnosis Method for Rolling Bearing Based on TVFEMD Energy Entropy and PFA-LSSVM Optimization Model

Published:2023-11-25 Issue: Volume: Page:252-256
ISSN:
Container-title:2023 3rd International Signal Processing, Communications and Engineering Management Conference (ISPCEM)
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Author:

Hu Zhiping¹,Xu Yanhe²,Lu Junze³,Jiang Wei³

Affiliation:

1. Hubei Bailianhe Pumped Storage Co., Ltd,Huanggang,China,438600

2. Huazhong University of Science and Technology,Hubei Provincial Key Laboratory of Digital Watershed Science and Technology,Wuhan,China,430074

3. Huaiyin Institute of Technology,Jiangsu Key Laboratory of Advanced Manufacturing Technology,Huai'an,China,223003

Funder

Natural Science Foundation of Jiangsu Province

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10499280/10498137/10499353.pdf?arnumber=10499353

Reference9 articles.

1. Convolutional neural network based bearing fault diagnosis of rotating machine using thermal images

2. Hidden Markov Model based Stochastic Resonance and its Application to Bearing Fault Diagnosis

3. ISVD-Based In-Band Noise Reduction Approach Combined With Envelope Order Analysis for Rolling Bearing Vibration Monitoring Under Varying Speed Conditions

4. Fault diagnosis in spur gears based on genetic algorithm and random forest

5. A wavelet convolutional capsule network with modified super resolution generative adversarial network for fault diagnosis and classification

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