Health monitoring of induction motors through embedded systems-simulation of broker rotor bar fault and abnormal gear teeth fault

Abstract

The health monitoring of induction motor is considered as a developing technology for online detection of faults that actually even take place at initial stage. In the current paper, an embedded system has been designed and simulated to simulate two major faults namely broken rotor bar fault and abnormal gear teeth fault. An extensive review of induction machine faults, diagnostic techniques of induction motor has been investigated in detail. Also, this paper deals with a novel effective technique for detecting the broken rotor fault and abnormal gear teeth fault of the induction motor. A precise finding of the fault characteristic parameter of motor is a new investigation hotspot in the Broken Rotor Bar fault diagnosis of induction motors. Broken Rotor Bar is one of the generally occurred faults in induction motor, which also might initiate critical motor damage to the motor if not found out in a right time. Also, gears that are popularly considered as most important components in the mechanical power conduction have received lots of concern in the area of condition monitoring over years and the current study is not obviously free from this. The experimental results and software simulation concluded that MPSO offers better optimization for both broken rotor bar and abnormal gear teeth fault.