Temperature Estimation and Vibration Monitoring for Induction Motors and the Potential Application in Electrical Submersible Motors

Abstract

Condition monitoring is essential for the reliable operation of induction motors. Temperature estimation serves as a basis for motor protection. Developing accurate and real-time temperature calculation algorithms is critical for thermal and overload protection for induction motors. Vibration monitoring is a widely used approach for induction motors' fault diagnosis. Vibration signals are usually analyzed by time-, frequency-, or time-frequency-domain signal processing methods. Recent advancement of fault diagnosis by machine learning makes intelligent approaches feasible. Although decades of efforts have been put on condition monitoring of regular induction motors, electrical submersible motors operating in a very unique downhole environment in the oil industry have not received much attention. Currently, electrical submersible motors rely on downhole monitoring tools to transmit temperature and vibration data measured by sensors from downhole to the surface; however, such data are transmitted at a slow rate, and there are no fault diagnosis algorithms in place. An advanced condition monitoring and fault diagnosis method for electrical submersible motors is needed in the near future. In this paper, a literature review is conducted on temperature estimation and vibration monitoring techniques for induction motors, the state-of-the-art methods are summarized, and their potential application in electrical submersible motors are recommended.