首页> 外文会议>2011 International Conference on Process Automation, Control and Computing >Detection of Broken Rotor Bars in Induction Motor Using Derivative Free Kalman Filters
【24h】

Detection of Broken Rotor Bars in Induction Motor Using Derivative Free Kalman Filters

机译:使用导数自由卡尔曼滤波器检测感应电动机中的转子条损坏

获取原文

摘要

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.
机译:本文研究了联合无味卡尔曼滤波器(JUKF)和双无味卡尔曼滤波器(DUKF)的设计和实现,用于在仿真研究中检测和监测感应电动机的转子杆故障。损坏的转子条实质上导致感应电动机的转子电阻增加。所使用的方法基本上是基于模型的故障检测,其中问题被视为参数变化的检测和估计之一。进行了广泛的蒙特卡洛模拟研究,以评估两种过滤器在各种操作条件下的相对性能。仿真研究结果表明,DUKF在宽范围的调节参数下对转子电阻变化更为敏感,在检测和估计转子电阻方面优于JUKF。但是,DUKF还显示出对负载干扰的高度敏感性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号