Review of Diagnosis Technique for Equipment Faults and its Development Trend
Author:
Publisher
EDP Sciences
Subject
General Medicine
Link
http://www.matec-conferences.org/10.1051/matecconf/20152203007/pdf
Reference21 articles.
1. Wang Xin. 2014.The Fault Diagnosis Technology of Mechanical Equipment and Application.Beijing: China Coal Industry Publishing House.
2. Wu Sitao & Chow Tommy W.S.. 2004. Induction machine fault detection using SOM-based RBF neural networks.IEEE Transactions on Industrial Electronics.
3. Isermann Rolf. 2005. Model-based fault-detection and diagnosis-status and applications.Annual Reviews in Control.
4. Skvarenina Timothy L.. 2002.The Power Electronics Handbook. CRC Press LLC.
5. Wang Quanxian. 2013.The Fault Diagnosis Technology of Mechanical Equipment. Wuhan: Huazhong University of Science and Technology Press.
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. Challenges and Opportunities of Deep Learning Models for Machinery Fault Detection and Diagnosis: A Review;IEEE Access;2019
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