Comprehensive Overview on Computational Intelligence Techniques for Machinery Condition Monitoring and Fault Diagnosis-Reference-Cited by-同舟云学术

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Comprehensive Overview on Computational Intelligence Techniques for Machinery Condition Monitoring and Fault Diagnosis

Published:2017-05-15 Issue:4 Volume:30 Page:782-795
ISSN:1000-9345
Container-title:Chinese Journal of Mechanical Engineering
language:en
Short-container-title:Chin. J. Mech. Eng.

Author:

Zhang Wan,Jia Min-Ping,Zhu Lin,Yan Xiao-An

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering

Link

http://link.springer.com/article/10.1007/s10033-017-0150-0/fulltext.html

Reference154 articles.

1. A K S Jardine, D M Lin, D Banjevic. A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical Systems and Signal Processing, 2006, 20(7): 1483–1510.

2. Z W Gao, C Cecati, S X Ding. A Survey of Fault Diagnosis and Fault-Tolerant Techniques Part I: Fault Diagnosis with Model- Based and Signal-Based Approaches. IEEE Transactions on Industrial Electronics, 2015, 62(6): 3757–3767.

3. R B Randall. Vibration-based condition monitoring: industrial, aerospace and automotive applications. Chichester: John Wiley & Sons, Ltd., 2011.

4. J Z Sikorska, M Hodkiewicz, L Ma. Prognostic modelling options for remaining useful life estimation by industry. Mechanical Systems and Signal Processing, 2011, 25(5): 1803–1836.

5. A W Heng, S Zhang, A C C Tan, et al. Rotating machinery prognostics: State of the art, challenges and opportunities. Mechanical Systems and Signal Processing, 2009, 23(3): 724–739.

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