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作 者:周洋 王鸿鹄 ZHOU Yang;WANG Honghu(Shanghai Engineering Research Center of Motor System Energy Saving Co.,Ltd.,Shanghai 200063,China)
机构地区:[1]上海电机系统节能工程技术研究中心有限公司,上海200063
出 处:《电机与控制应用》2021年第12期71-77,共7页Electric machines & control application
基 金:上海市服务业发展引导资金——绿色电机系统协同设计服务云平台建设。
摘 要:随着产业升级、可靠性需求逐渐上升,电动机的故障检测成为当前研究的热点问题。由于电机可检测的信号较少、负载工况复杂、信号处理误差等原因,鼠笼型电机转子断条特征存在较难检测的问题。以电机转子断条(坏条)作为研究对象,经过断条故障有限元仿真建模,通过多种信号处理方法研究对比,提出一种准确率较高、抗干扰性较优的检测方法,达到甄别转子断条(坏条)故障类型及预测故障程度的目标。As the industry upgrades, the reliability demand has gradually increased, the fault detection of motor has become the current research hotspot. Since the available detecting signals of the motor are few, the load condition is complex, and there exists signal processing error, the characteristics of broken rotor bar of squirrel-cage motor is difficult to detect. Regarding the broken rotor bar(bad bar) as the research object, finite element simulation and modeling of broken rotor bar are carried out, a variety of signal processing methods are studied comparatively, and a detection method with high accuracy and anti-interference ability is proposed. It can achieve the goal of distinguishing the broken rotor bar(bad bar) type and predicting the fault degree.
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