Detecting induction motor stator faults by leakage flux method and development of prototype

Induction motors are the most widely used electric motors in the industry due to their robustness, simplicity and cheapness. For this reason, induction motor failures cause costly consequences such as production stoppage, loss of workforce and decrease in efficiency. One of the most common faults seen in induction motors is short circuit faults between stator turn-to-turn. The classical method used in the diagnosis of these faults, which are very difficult to notice at the beginning stage, is the Motor Current Signature Analysis (MCSA) method. However, this method can give misleading results in variable load situations and supply source irregularities. In this study, the fault diagnosis method based on the analysis of the leakage flux leaking from the body of the induction motor is emphasized, and a prototype is designed that can detect the stator fault at the initial stage by analyzing the leakage flux. For this purpose, an induction motor model was designed in the ANSYS@Maxwell-2D program using the Finite Element Method-FEM, various failure rates were applied, the leakage flux information collected by operating at different operating loads was analyzed and algorithms that could be used in fault diagnosis were obtained. In the analysis phase, the frequency spectrums of the signals were obtained by applying Fast Fourier Transform (FFT) to the leakage flux signals in the time domain in the Matlab program. By comparing healthy and faulty motor harmonics in the frequency domain, characteristic fault signatures that can be used are determined. In the last stage of the study, a prototype was designed that can detect the short circuit fault between the stator turn-to-turn in real time by measuring the leakage flux. The DSP-based STM32F429 microcontroller card is used for this process. The software based on the algorithm obtained as a result of the simulation, has been loaded on the microcontroller board, and the feasibility of a prototype that could diagnose stator failure with the leakage flux method was demonstrated.