Fault Detection in Induction Motors: Recent Advances and Future Prospects

The induction motor is the most prevalent type of electrical equipment utilized in residential, commercial, and industrial settings. Because of electric motor failures in industry, unplanned downtime, lost output, increased costs of operation, and lost revenues are common. It is required to guarantee the reliable functioning of these motors, which calls for the use of strong fault detection approaches. This study provides a thorough overview of fault detection strategies for induction motors through a comprehensive assessment of the literature. The goal is to compile and integrate knowledge from previous studies to ensure that practitioners, engineers, and academics have a comprehensive understanding of the current state of fault detection in induction motors. In the paper, the first section covers the introductory ideas behind induction motor fault detection, such as the kinds of problems that are repeatedly found and how they affect motor performance. Also, a thorough examination of the present fault detection methods is provided. A critical analysis is conducted to evaluate the advantages and disadvantages of common monitoring signals. The association of cutting-edge technology in fault detection for induction motors, such as machine learning and signal processing techniques, is covered in the literature study. Recent developments in the subject are summed up, and an evaluation of how well these new techniques work to enhance fault detection accuracy and flexibility is given. A discussion of new developments, possible avenues for future research, and areas where defect detection methods for induction motors could be enhanced are covered in the review's conclusion.