Rotating Electrical and Mechanical Fault Diagnosis Based on Motor Current and Vibration Signals

The Induction motors are mainly used in industrial applications. The unnecessary stopping of the machine will decrease the productivity and it leads to loss. In this paper we are detecting the bearing fault (40%) and the rotor fault (20%) of the three phase induction motor fault and classify them by using the soft computing techniques. Application of artificial intelligence tool is inevitable in modern process industry to diagnosis the health of the motor. We are using the LABVIEW for modeling and MATLAB for analyzing. The signal is extracted from the acquired stator current signals and is used in conjunction with machine learning techniques based on Neural Network, ANFIS to identify the motor faults. In addition, this diagnostic method not only classifies the fault but also find the severity of the fault.