Fault diagnosis of electro-mechanical actuator based on WPD-STFT time-frequency entropy and PNN

Jiayao Jing1, Hongmei Liu2, Chen Lu3

1, 2, 3School of Reliability and Systems Engineering, Beihang University, Beijing, 100191, China

3Science & Technology on Reliability & Environmental Engineering Laboratory,
Beijing, 100191, China

2Corresponding author

E-mail: 1sy1614121@buaa.edu.cn, 2liuhongmei@buaa.edu.cn, 3luchen@buaa.edu.cn

Received 29 September 2017; accepted 7 October 2017

DOI https://doi.org/10.21595/vp.2017.19247

 

Abstract. Electro-mechanical actuators (EMAs) are increasingly being used as critical actuation devices of the aircraft. It will cause serious accidents once the fault of EMAs occurs, thus the fault diagnosis of EMAs is essential to maintain the normal operation of aircraft. In this paper, a method based on WPD-STFT time-frequency entropy and PNN is proposed to achieve fault diagnosis of EMAs by processing the vibration signals collected by the accelerometer installed in the EMAs. Firstly, the vibration signals are decomposed by wavelet packet to obtain the signal components of different frequency bands, the signal components are subjected to STFT and spectrograms are obtained. Then, time-frequency entropy is calculated and combined with principal component analysis (PCA) for dimension reduction as the feature vector. Finally, the probabilistic neural network (PNN) classifier is introduced to classify the fault modes. The experimental result shows that this method can accomplish the accurate fault diagnosis of EMAs. Moreover, the performance of the proposed WPD-STFT time-frequency entropy method has an advantage over that of WPD-PCA method or STFT combined with mass-moment entropy method for feature extraction.

Keywords: electro-mechanical actuators, fault diagnosis, WPD-STFT, time-frequency entropy, PNN.

References

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[2]        Liu J., Zhang L., Li H. Application of GM(1, 1) model and improved EMD in fault diagnosis of airborne direct-driven electro-mechanical actuators. Journal of Grey System, Vol. 25, Issue 1, 2013, p. 24‑31.

[3]        Xiao Lei, Li Yinghui, Zhao Kun, et al. Fault diagnosis of aircraft power actuation system based on wavelet transform. Journal of Air Force Engineering University, Natural Science Edition, Vol. 10, Issue 5, 2009, p. 55‑58.

[4]        Sun J., Lu C., Ding Y. Fault diagnosis for hydraulic pump based on intrinsic time-scale decomposition and softmax regression. Vibroengineering Procedia, Vol. 10, 2016, p. 229‑234.

Cite this article

Jing Jiayao, Liu Hongmei, Lu Chen Fault diagnosis of electro‑mechanical actuator based on WPD‑STFT time‑frequency entropy and PNN. Vibroengineering PROCEDIA, Vol. 14, 2017, p. 130‑135.

 

JVE International Ltd. Vibroengineering PROCEDIA. Oct 2017, Vol. 14. ISSN 2345-0533