Abstract:Due to long-time high load operation, the insulation performance between turns of the stator winding of permanent magnet synchronous motor (PMSM) is prone to decrease, resulting in inter-turn short circuit. At this moment, the vibration intensity of the motor will change. In response to this phenomenon, this study proposed a CEEMDAN-HT nonlinear signal analysis method that combined complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and hilbert transform (HT) and utilized it for extracting fault features from vibration signal. Firstly, the vibration signal was decomposed using CEEMDAN algorithm to obtain a series of intrinsic mode functions (IMF), and the variance contribution rate in principal component analysis was applied to distinguish the IMF component containing fault feature information. Secondly, the IMF with high contribution rate was analyzed using HT, and the main fault features were obtained by presenting time, instantaneous frequency, and amplitude using three-dimensional joint time-frequency diagram. Finally, a short circuit fault simulation of motor was conducted using ANSYS finite element software, and a short circuit fault experimental platform was constructed. By comparing and analyzing the finite element simulation results and experimental results, the effectiveness and accuracy of the method proposed in this study were verified.
夏焰坤,李欣洋,任俊杰,寇坚强. 基于CEEMDAN-HT的永磁同步电机匝间短路振动信号故障特征提取研究[J]. 振动与冲击, 2024, 43(5): 72-81.
XIA Yankun,LI Xinyang,REN Junjie,KOU Jianqiang. Fault feature extraction of inter-turn short circuit vibration signals in PMSM based on CEEMDAN-HT. JOURNAL OF VIBRATION AND SHOCK, 2024, 43(5): 72-81.
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