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.

感应电动机的健康监测被认为是一种在线检测故障的技术，该故障实际上甚至发生在初始阶段。在本文中，已经设计并仿真了嵌入式系统，以模拟两个主要故障，即转子断条故障和齿轮齿异常故障。对感应电机的故障进行了广泛的综述，对感应电机的诊断技术进行了详细的研究。此外，本文还提出了一种新颖有效的技术，用于检测感应电动机的转子断裂故障和齿轮异常齿故障。电动机故障特征参数的精确发现是感应电动机转子断条故障诊断中的一个新的研究热点。转子条损坏是感应电动机中常见的故障之一，如果没有在正确的时间发现，这也可能导致严重的电机损坏。而且，多年来被普遍认为是机械动力传导中最重要的部件的齿轮在状态监测领域中引起了很多关注，并且当前的研究显然还不能摆脱这一点。实验结果和软件仿真得出的结论是，MPSO为转子条断裂和异常齿轮故障提供了更好的优化。