Multi-layer convolutional dictionary learning network for signal denoising and its application to explainable rolling bearing fault diagnosis-Reference-Cited by-同舟云学术

Multi-layer convolutional dictionary learning network for signal denoising and its application to explainable rolling bearing fault diagnosis

Published:2024-04 Issue: Volume:147 Page:55-70
ISSN:0019-0578
Container-title:ISA Transactions
language:en
Short-container-title:ISA Transactions

Author:

Qin Yi,Yang Rui,He Biao,Chen Dingliang^ORCID,Mao Yongfang^ORCID

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference34 articles.

1. Ai T, Liu Z, Wang H, Han H. Robust Vibration Signal Denoising and Diagnosis Using Encoder-Decoder Networks with Cross-layer Residual Connection. 2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing); 2021, 15–17 Oct. 2021. p. 1–5.

2. Analysis of explainers of black box deep neural networks for computer vision: a survey;Buhrmester;Mach Learn Knowl Extraction,2021

3. Case western reserve university (CWRU) bearing data center. 〈https://csegroups.case.edu/bearingdatacenter/pages/download-data-file/〉.

4. Gregor K, LeCun Y. Learning fast approximations of sparse coding. In: Proceedings of the 27th International Conference on International Conference on Machine Learning, Haifa, Israel; 2010. p. 399–406.

5. Intelligent vibration signal denoising method based on non-local fully convolutional neural network for rolling bearings;Han;ISA Trans,2022

Cited by 2 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. Research on rolling bearing fault diagnosis technology based on singular value decomposition;AIP Advances;2024-08-01

2. An Overview of Image Denoising and an Optimization Model Are Presented;Journal of Image and Signal Processing;2024