Multi D-norm Driven Algorithm Unfolding Network: A Rolling Bearing Fault Feature Extraction Method-Reference-Cited by-同舟云学术

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Multi D-norm Driven Algorithm Unfolding Network: A Rolling Bearing Fault Feature Extraction Method

Published:2023-09-23 Issue: Volume: Page:1273-1278
ISSN:
Container-title:2023 6th International Conference on Information Communication and Signal Processing (ICICSP)
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Author:

Zhang Han¹,Lin Jianbo¹,Du Zhaohui²,Li Yunfei¹

Affiliation:

1. School of Construction Machinery, Chang'an University,Xi'an,China

2. School of Marine Science and Technology, Northwestern Polytechnical University,Xi'an,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10389815/10388491/10390760.pdf?arnumber=10390760

Reference27 articles.

1. Rolling element bearing diagnostics—A tutorial

2. Segmentation MED method based on kurtosis-frequency curve and its application in bearing diagnosis

3. Advanced bearing diagnostics: A comparative study of two powerful approaches

4. A review on the application of blind deconvolution in machinery fault diagnosis

5. Minimum entropy deconvolution

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An Adaptive Multi-D-Norm-Driven Sparse Unfolding Deconvolutional Network for Bearing Fault Diagnosis;Sensors;2024-04-19

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