A Short Survey on Fault Diagnosis of Rotating Machinery Using Entropy Techniques

Zhiqiang Huo; Yu Zhang; Lei Shu

Industrial Networks and Intelligent Systems. 3rd International Conference, INISCOM 2017, Ho Chi Minh City, Vietnam, September 4, 2017, Proceedings

Research Article

A Short Survey on Fault Diagnosis of Rotating Machinery Using Entropy Techniques

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@INPROCEEDINGS{10.1007/978-3-319-74176-5_24,
    author={Zhiqiang Huo and Yu Zhang and Lei Shu},
    title={A Short Survey on Fault Diagnosis of Rotating Machinery Using Entropy Techniques},
    proceedings={Industrial Networks and Intelligent Systems. 3rd International Conference, INISCOM 2017, Ho Chi Minh City, Vietnam, September 4, 2017, Proceedings},
    proceedings_a={INISCOM},
    year={2018},
    month={1},
    keywords={Fault diagnosis Rotating machinery Entropy},
    doi={10.1007/978-3-319-74176-5_24}
}

Zhiqiang Huo
Yu Zhang
Lei Shu
Year: 2018
A Short Survey on Fault Diagnosis of Rotating Machinery Using Entropy Techniques
INISCOM
Springer
DOI: 10.1007/978-3-319-74176-5_24

Zhiqiang Huo^,*, Yu Zhang¹^,*, Lei Shu^,*

1: University of Lincoln

*Contact email: zhuo@lincoln.ac.uk, yzhang@lincoln.ac.uk, lshu@lincoln.ac.uk

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

Published: 2018-01-25
Appears in: SpringerLink

: http://dx.doi.org/10.1007/978-3-319-74176-5_24