Temporary short circuit detection in induction motor winding using combination of wavelet transform and neural network

摘要

Monitoring system for induction motor is widely developed to detect the incipient fault. Such system isdesirable to detect the fault at the running condition to avoid the motor stop running suddenly. In thispaper, a new method for detection system is proposed that emphasizes the fault occurrences as temporaryshort circuit in induction motor winding. The investigation of fault detection is focused on the transientphenomena during starting and ending points of temporary short circuit. The proposed systemutilizes the wavelet transform for processing the motor current signal. Energy level of high frequency signalfrom wavelet transform is used as the input vriable of neural network which works as detection system.Three types of neural networks are developed and evaluated including feed forward neural network(FFNN), Elman neural network (ELMNN) and radial basis functions neural network (RBFNN). The resultsshow that ELMNN is the most simply and accurate system that can recognize all of unseen data test. Laboratorybased experimental setup is performed to provide real-time measurement data for this research.