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Influence of Blade Pass Frequency Vibrations on MCSA-Based Rotor Fault Detection of Induction Motors

机译:叶片通过频率振动对基于MCSA的感应电动机转子故障检测的影响

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Motor current signature analysis (MCSA) has recently become widespread in industry for on-line detection of rotor cage faults in induction motors for preventing forced outages. Although it can provide low cost remote monitoring of rotor faults, cases of false indications have been reported, where the causes of some false indications are still unknown. It is shown for the first time in this work that high-amplitude blade pass frequency (BPF) vibrations produced in pumps, fans, or compressors can cause false rotor fault indications if the number of motor poles is an integer multiple of the number of blades. The influence of BPF vibration on MCSA-based rotor fault detection is analyzed, and it is shown that the interaction between BPF vibration and rotor faults can produce false positive and negative fault indications. Alternative test methods capable of separating the influence of the BPF vibration and rotor faults are suggested for avoiding false MCSA alarms. The claims made in the paper are verified experimentally on a custom-built 380 V induction motor-centrifugal pump system setup.
机译:电动机电流信号分析(MCSA)最近在工业中广泛用于在线检测感应电动机中的转子笼故障,以防止强制停机。尽管它可以提供低成本的转子故障远程监控,但已经报道了错误指示的情况,其中一些错误指示的原因仍然未知。这项工作首次证明,如果电动机极数是叶片数的整数倍,则泵,风扇或压缩机中产生的高振幅叶片通过频率(BPF)振动会导致错误的转子故障指示。 。分析了BPF振动对基于MCSA的转子故障检测的影响,结果表明BPF振动与转子故障之间的相互作用会产生错误的正负故障指示。为了避免错误的MCSA警报,建议使用能够分离BPF振动和转子故障影响的替代测试方法。本文中提出的权利要求在定制的380 V感应电动机-离心泵系统设置上进行了实验验证。

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