Diagnostics of stator faults of the single-phase induction motor using thermal images, MoASoS and selected classifiers

Abstract

Abstract Single-phase induction motors are used in the industry commonly. Induction motors are not expensive, so it is a reason to use them. Diagnostics of faults is very important. It prevents financial loss and unplanned downtimes causes by faults. In this paper the authors described fault diagnostic techniques of the single-phase induction motor. Presented techniques were based on the analysis of thermal images of electric motor. The authors measured and analysed 3 states of the single-phase induction motor. In this paper an original method of the feature extraction of thermal images called MoASoS (Method of Area Selection of States) was presented. The proposed method - MoASoS and an image histogram were used to form feature vectors. Classification of the obtained vectors was performed by NN (Nearest Neighbour classifier) and Gaussian Mixture Models (GMM). The described fault diagnostic techniques are useful for reliability of the single-phase induction motors and other rotating electrical machines such as: three-phase induction motors, synchronous motors, DC motors.