A short survey on fault diagnosis of rotating machinery using entropy techniques

Huo, Zhiqiang and Zhang, Yu and Shu, Lei (2017) A short survey on fault diagnosis of rotating machinery using entropy techniques. In: 3rd EAI International Conference on Industrial Networks and Intelligent Systems, 4 September 2017, Ho Chi Minh City, Vietnam.

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Item Type:Conference or Workshop contribution (Paper)
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Abstract

Fault diagnosis is significant for identifying latent abnormalities, and implementing fault-tolerant operations for minimizing performance degradation caused by failures in industrial systems, such as rotating machinery. The emergence of entropy theory contributes to precisely measure irregularity and complexity in a time series, which can be used for discriminating prominent fault information in rotating machinery. In this short paper, the utilization of entropy techniques for fault diagnosis of rotating machinery is summarized. Finally, open research trends and
conclusions are discussed and presented respectively.

Keywords:Fault diagnosis, Rotating machinery, Entropy
Subjects:H Engineering > H300 Mechanical Engineering
Divisions:College of Science > School of Engineering
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ID Code:27762
Deposited On:29 Jun 2017 09:18

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