利用导数自由卡尔曼滤波检测感应电动机转子断条

S. Kumar, J. Prakash, S. Siva Kumar
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引用次数: 9

摘要

本文在仿真研究的基础上,设计并实现了联合无气味卡尔曼滤波器(JUKF)和双无气味卡尔曼滤波器(DUKF),用于感应电动机转子棒故障的检测与监测。转子断条本质上导致了感应电动机转子电阻的增加。所采用的方法基本上是基于模型的故障检测,将故障检测问题视为参数变化的检测和估计问题。进行了广泛的蒙特卡罗模拟研究,以评估两种滤波器在各种工作条件下的相对性能。仿真研究结果表明,DUKF对大范围调谐参数范围内转子电阻的变化更为敏感,在转子电阻的检测和估计方面优于JUKF。然而,DUKF对负载扰动也表现出很高的灵敏度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection of Broken Rotor Bars in Induction Motor Using Derivative Free Kalman Filters
This paper deals with design and implementation of Joint Unscented Kalman filter (JUKF) and Dual Unscented Kalman filter (DUKF) for the detection and monitoring of rotor bar faults in induction motor under simulation studies. A broken rotor bar essentially leads to an increase in rotor resistance of the induction motor. The methodology used is basically model based fault detection in which the problem is treated as one of detection and estimation of parameter variation. An extensive monte carlo simulation study has been carried out to assess the relative performance of the two filters under various operating conditions. The results of the simulation studies show that DUKF is more sensitive to rotor resistance variation over wide range of tuning parameters and gives better performance than JUKF in detecting and estimating the rotor resistance . However DUKF also shows high sensitivity towards load disturbances.
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