Fault feature extraction method based on Park-HHT

被引：0
|
作者：
Li B. [1 ,2 ]
Zhang L. [1 ]
Wang W. [1 ]
Wang G. [3 ]
机构：
[1] Air Defense and Anti-Missile College, Air Force Engineering University, Xi'an
[2] Unit 93786 of the PLA, Zhangjiakou
[3] Unit 93114 of the PLA, Beijing
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2020年 / 42卷 / 12期
关键词：
Fault diagnosis; Feature extraction; Hilbert-Huang transform (HHT); Park transform;
D O I：
10.3969/j.issn.1001-506X.2020.12.33
中图分类号：
学科分类号：
摘要：
A new fault feature extraction method is proposed for three-phase symmetric system. Firstly, the three-phase output signal of the system is firstly Park transformed by the method, and then the signal goes through Hilbert-Huang transform (HHT). The low-frequency component is selected from the eigenmode function of HHT and the signal amplitude is extracted as the fault characteristic value. This method has the advantages of both Park transformation and HHT, which can improve the fault resolution while reducing the variable dimension, and has a strong anti-noise capability. Finally, the simulation experiment is carried out in the three-phase inverter circuit, and the extraction effect of different methods is evaluated by using the distance distribution between feature vectors, which verify the effectiveness of the proposed method. © 2020, Editorial Office of Systems Engineering and Electronics. All right reserved.
引用
收藏
页码：2944 / 2952
页数：8
相关论文
共 21 条
  • [1] ZHANG B S, ZHANG L, ZHANG B, Et al., Health status classification model of complex equipment based on fault risk scale, Systems Engineering and Electronics, 42, 2, pp. 489-496, (2020)
  • [2] ZHAO D F, LIU S, GU D, Et al., Improved multi-scale entropy and it's application in rolling bearing fault feature extraction, Measurement, 152, C, pp. 114-118, (2020)
  • [3] ZHOU D H, JI H Q, HE X., Fault diagnosis technology of high-speed train information control system, Journal of Automation, 44, 7, pp. 1153-1164, (2018)
  • [4] WANG G B, HE Z J, CHEN X F, Et al., Basic research on mechanical fault diagnosis "where to go, Journal of Mechanical Engineering, 49, 1, pp. 63-72, (2013)
  • [5] ANDREW K S J, DAMING L, DRAGAN B., A review on machinery diagnostics and prognostics implementing condition-based maintenance, Mechanical Systems and Signal Processing, 20, pp. 1483-1510, (2006)
  • [6] LI H, WU X, LIU T, Et al., Fault feature extraction of rolling bearing based on information entropy optimization variational modal decomposition, Vibration and Impact, 37, 23, pp. 219-225, (2018)
  • [7] CHEN D., Fault diagnosis of PWM rectifier, (2012)
  • [8] SHANMUGAM C, SEKARAN E C., Fault detection in electrical equipment's images by using optimal features with deep learning classifier, Multimedia Tools and Applications, 78, 19, pp. 182-187, (2019)
  • [9] WANG N F, JIANG D X, YANG W G., Dual-tree complex wavelet transform and SVD-based acceleration signals denoising and its application in fault features enhancement for wind turbine, Journal of Vibration Engineering & Technologies, 7, 4, pp. 64-68, (2019)
  • [10] HE S S., Research on fault feature extraction method of mine frequency converter, (2016)
123