Fault Detection by Means of Hilbert–Huang Transform of the Stator Current in a PMSM With Demagnetization

Abstract

This paper presents a novel method to diagnose demagnetization in permanent-magnet synchronous motor (PMSM). Simulations have been performed by 2-D finite-element analysis in order to determine the current spectrum and the magnetic flux distribution due to this failure. The diagnostic just based on motor current signature analysis can be confused by eccentricity failure because the harmonic content is the same. Moreover, it can only be applied under stationary conditions. In order to overcome these drawbacks, a novel method is used based upon the Hilbert-Huang transform. It represents time-dependent series in a 2-D time-frequency domain by extracting instantaneous frequency components through an empirical-mode decomposition process. This tool is applied by running the motor under nonstationary conditions of velocity. The experimental results show the reliability and feasibility of the methodology in order to diagnose the demagnetization of a PMSM.Index Terms-Demagnetization, empirical-mode decomposition (EMD), fault diagnosis, finite-element analysis (FEA), HilbertHuang transform (HHT), permanent-magnet synchronous motor (PMSM).

Demagnetization Fault Diagnosis in IPMSM Using Linear Interpolation

“…분석 기법이 있으며 모터 모델을 이용한 모델 기반 기법 등이 있다 [6], [7]. 주파수 분석 기법의 경우 고장으로 인해 특정 주파 수에서 발생하는 성분을 찾아내어 고장을 진단한다.…”

“…주파수 분석 기법의 경우 고장으로 인해 특정 주파 수에서 발생하는 성분을 찾아내어 고장을 진단한다. 이 때 고장 성분은 불균일한 감자의 경우에만 발생하며 동작 주파수의 ±배수의 주파수에서 나타나게 된다 [6]. 는 …”

Demagnetization Detection for IPM-type BLDCMs According to Irreversible Demagnetization Patterns and Pole-Slot Coefficients

“…The irreversible demagnetization of PMs is mainly caused by the armature reaction that occurs when the demand for starting torque is high [10].…”

Detection of Partial Demagnetization Fault in PMSMs Operating Under Nonstationary Conditions

“…Thus, early and accurate detection of the partial demagnetization fault is of great significance for the operation & maintenance of PMSMs and associated machinery and electromechanical systems. So far, the commonly monitored parameters for Partial Demagnetization Fault Detection (PDFD) are stator current [3][4][5], zero sequence voltage component [6], Back-EMF [7], shaft trajectory [8] and vibration [9]. Following the classical motor current signature analysis approach, the characteristic demagnetization fault frequencies, fd, are 1 , where f0 is the electrical fundamental frequency, k is an integer, and is the number of pole pairs [3][4][5][6][7][8][10][11][13][14].…”

“…So far, the commonly monitored parameters for Partial Demagnetization Fault Detection (PDFD) are stator current [3][4][5], zero sequence voltage component [6], Back-EMF [7], shaft trajectory [8] and vibration [9]. Following the classical motor current signature analysis approach, the characteristic demagnetization fault frequencies, fd, are 1 , where f0 is the electrical fundamental frequency, k is an integer, and is the number of pole pairs [3][4][5][6][7][8][10][11][13][14]. Thus, the PDFD under stationary conditions of speed and torque is commonly based on the identification of such characteristic fault frequencies throughout the spectrum analysis, estimated by means of conventional Fourier Analysis (FA) [6][7][8].…”