Journal of Northeastern University(Natural Science) ›› 2022, Vol. 43 ›› Issue (9): 1240-1249.DOI: 10.12068/j.issn.1005-3026.2022.09.004

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Method of Actuator Fault Diagnosis via Multiple Angles Feature Extraction

WANG Na1,2, LI Yang1, PENG Kun1   

  1. 1. School of Control Science and Engineering, Tiangong University, Tianjin 300387, China; 2. Tianjin Key Laboratory of Intelligent Control of Electrical Equipment, Tianjin 300387, China.
  • Published:2022-09-16
  • Contact: WANG Na
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Abstract: For the swaying problem of actuator faults, a fault diagnosis method based on multi-angle feature extraction is proposed. The short-time analysis idea is used to frame the actuator data to obtain a short-stable time series. The energy-entropy-ratio concept is introduced to extract the current features of actuator datum frame. Dynamic time-regular thoughts to extract positional characteristics within the actuator data frame is utilized. A multi-angle feature to enhance the significance of input characteristics is formed. On this basis, the bidirectional long-short term memory network is used to improve the accuracy of the subsequent actuator fault classification process. Finally, by the measured data from a certain type actuator swaying, the validity of the proposed method is verified by the comparing with the traditional short term memory network methods.

Key words: actuator fault diagnosis; feature extraction; short-time analysis; energy-entropy-ratio; dynamic time warping; bi-directional long-short term memory network

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