Induction Motors Fault Diagnosis Using Finite Element Method: A Review

Abstract

Condition monitoring and fault diagnosis of induction motors serve as essential techniques toward the reliable operation of critical industrial processes. The finite element method (FEM) offers a great insight into fundamental principle and physical operation of the machine. It can model complex magnetic circuit topology, discrete windings layouts, and nonlinear magnetic material properties of the machine. It determines the machine parameters (such as the magnetic field distribution, flux density, electromagnetic torques, and stator current) and can model localized magnetic saturation due to faults to a high degree of accuracy. Used as fault detection algorithms, the FEM can address the issues such as the lack of comprehensive fault databases through field measurements, and the difficulty in distinguishing fault severity. It can reduce the number of destructive tests required in the field/labs, simulate any faulty states of the machine. Although FEM has been widely used in induction motors’ design and analysis, its application in fault diagnosis is limited despite the promising potential. In this article, a literature review is conducted on induction motor fault diagnosis techniques using FEM. The state-of-the-art techniques reported in the literature are categorized into three streams: first, FEM-based fault diagnosis approach, second, FEM and signal processing-based approach, and third, FEM, machine learning, and other advanced techniques-based approach. The advantages of fault diagnosis techniques using the FEM are demonstrated and the future research direction is recommended.