Static Eccentricity Fault Recognition in Three‐Phase Line Start Permanent Magnet Synchronous Motor Using Finite Element Method

Abstract

This paper is dedicated to investigating static eccentricity in a three-phase LSPMSM. The modeling of LSPMSM with static eccentricity between stator and rotor is developed using finite element method (FEM). The analytical expression for the permeance and flux components of nonuniform air-gap due to static eccentricity fault is discussed. Various indexes for static eccentricity detection using stator current signal of IM and permanent magnet synchronous motor (PMSM) are presented. Since LSPMSM is composed of a rotor which is a combination of these two motors, the ability of these features is evaluated for static eccentricity diagnosis in LSPMSM. The simulated stator current signal of LSPMSM in the presence of static eccentricity is analyzed in frequency domain using power spectral density (PSD). It is demonstrated that static eccentricity fault generates a series of low frequency harmonic components in the form of sidebands around the fundamental frequency. Moreover, the amplitudes of these components increase in proportion to the fault severity. According to the mentioned observations, an accurate frequency pattern is specified for static eccentricity detection in three-phase LSPMSM.

Fault detection of broken rotor bar in LS-PMSM using random forests

“…In addition, all applications of random forests to fault detection have been limited to induction motors and they have not been applied to LS-PMSMs. The type of electrical motor has a significant influence on fault detection of the motor due to the differences in structure [18]. Thus, the fault monitoring from induction motors cannot be generalized to LS-PMSMs due to the differences in these two types of motors.…”

“…The limitation of prior work is that most fault analysis has been applied to induction motors, electrical motors, fans, and gear boxes [7][8][9][10][11][12][13][14][15][16][17]. Yet, fault analysis in LS-PMSMs has been limited to a smaller set of faults, such as rotor faults, static eccentricity faults, and demagnetization [18][19][20][21]. Fault analysis in LS-PMSMs also suffers from a number of shortcomings: (1) the use of mathematical and simulated models to analyze faults, as opposed to using an LS-PMSM machine to collect data for fault detection; (2) the use of steady-state current for fault analysis; and (3) lack of machine learning algorithms for fault detection.…”

On the Mathematical Modeling of Line-Start Permanent Magnet Synchronous Motors under Static Eccentricity

“…Vector is called the static eccentricity vector. The degree of static eccentricity is defined as the ratio between the magnitude of static eccentricity vector to the symmetrical airgap length [14], yields: …”

“…For stator inner radius of , the airgap function can be obtained as: (14) Hence, the rotor radius is much larger than the airgap length, the second term in (13) can be represented by . Therefore, (14) can be written as: …”

“…In regards to the analysis of LSPMS motors under static eccentricity fault condition, few attempts were recently published [14,32,33]. They all simulate the motor using the FEM.…”