摘要
电机电流信号特征分析方法诊断笼型电机转子断条故障时,诊断效果受制于电机运行状态的影响,甚至会发生误诊断。针对这一问题,提出基于瞬时频率分析的笼型电机转子断条故障诊断方法。首先对起动电流进行FIR低通滤波,以提取包含转子断条故障特征的单分量谐波信号,然后采用相位微分方法计算该信号的瞬时频率,并根据f-s平面上的瞬时频率-滑差曲线判断故障发生与否。在3 k W电机试验平台上对所提出的方法进行验证,试验结果表明了所提方法的有效性。
The motor current signature analysis （MCSA） method for diagnosing broken rotor bars faults in squirrel-cage motor had some drawbacks that the diagnostic effects were subject to running state of the motor, which could even lead to a wrong diagnosis of the fault. A novelty approach based on the instantaneous frequency analysis of the start-up transient was presented. The proposed approach consists of extracting the mono-component signals from the start-up current by FIR low-pass filtering technique and calculating the instantaneous frequency of the obtained signal, via the derivative of the phase of the analytical signal, and according to the characteristic pattern of the IF-s on the f-s plane, it was judged if the broken rotor bar defect occurs. The experiment verification was performed on a 3 kW motor test bench ; the experiment results proved the effectiveness of the proposed method.
出处
《电机与控制应用》
北大核心
2017年第8期74-80,共7页
Electric machines & control application
基金
中国科学院重点部署项目(KGZD-EW-302)
辽宁省科学技术计划项目(2015020140)
关键词
故障诊断
笼型电机
转子断条
瞬时频率
fault diagnosis
squirrel.cage motor
broken rotor bars
instantaneous frequency
