Gray relation weighted wavelet neural network integrated model and its application in rotating machinery fault diagnosis-Reference-Cited by-同舟云学术

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Gray relation weighted wavelet neural network integrated model and its application in rotating machinery fault diagnosis

Published:2023-10-02 Issue: Volume: Page:
ISSN:0268-3768
Container-title:The International Journal of Advanced Manufacturing Technology
language:en
Short-container-title:Int J Adv Manuf Technol

Author:

Jia Xiaohui,Xiao Xinping,Wen Jianghui

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Software,Control and Systems Engineering

Link

https://link.springer.com/content/pdf/10.1007/s00170-023-12381-2.pdf

Reference50 articles.

1. Khan S, Yairi T (2018) A review on the application of deep learning in system health management. Mech Syst Signal Process 107:241–265

2. Liu R, Yang B, Zio E, Chen X (2018) Artificial intelligence for fault diagnosis of rotating machinery: a review. Mech Syst Signal Process 108:33–47

3. T S, Y S, Z Y (2020) Deep learning-based intelligent fault diagnosis methods toward rotating machinery. IEEE Access 8:9335–9346

4. Liu C, Cichon A, Królczyk G, Li Z (2022) Technology development and commercial applications of industrial fault diagnosis system: a review. Int J Adv Manuf Technol 118:3497–3529

5. Yin Z, Hou J (2016) Recent advances on SVM based fault diagnosis and process monitoring in complicated industrial processes. Neurocomputing 174:643–650

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