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

  • Zhiqiang HuoEmail author
  • Yu Zhang
  • Lei Shu
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 221)


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.


Fault diagnosis Rotating machinery Entropy 



This work is partially supported by International and Hong Kong, Macao & Taiwan collaborative innovation platform and major international cooperation projects of colleges in Guangdong Province (No. 2015KGJHZ026), The Natural Science Foundation of Guangdong Province (No. 2016A030307029), and Maoming Engineering Research Center on Industrial Internet of Things (No. 517018).


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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018

Authors and Affiliations

  1. 1.School of EngineeringUniversity of LincolnLincolnUK
  2. 2.Guangdong Provincial Key Laboratory on Petrochemical Equipment Fault DiagnosisGuangdong University of Petrochemical TechnologyMaomingChina

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