首页> 外文期刊>Magnetics, IEEE Transactions on >Static, Dynamic, and Mixed Eccentricity Faults Diagnosis in Switched Reluctance Motors Using Transient Finite Element Method and Experiments
【24h】

Static, Dynamic, and Mixed Eccentricity Faults Diagnosis in Switched Reluctance Motors Using Transient Finite Element Method and Experiments

机译:瞬态有限元法和实验法在开关磁阻电动机中的静态,动态和混合偏心故障诊断

获取原文
获取原文并翻译 | 示例
           

摘要

This paper presents a new method for noninvasive diagnosis of static, dynamic, and mixed eccentricity faults in switched reluctance motors (SRMs). This method makes it possible to precisely determine the eccentricity fault features. The proposed signature in this algorithm is based on the analysis of produced current with a particular variation pattern. It is theoretically shown that the occurrence and growth of the fault level cause an increase in amplitude of the produced current signature (PCS), which can be employed to diagnose the fault and extract its details. In this method, first, occurrence of the fault and its location are detected by utilizing eccentricity level detection pattern. Afterward, a new index to precisely determine the fault level is introduced. Then, a novel strategy based on the proposed pattern and index is offered to detect the type of eccentricity as well as the exact location of the faulty phase. For this purpose, an SRM under eccentricity fault is modeled using three dimensional transient finite element method (TFEM). This precise model considers all complex motor geometry, nonlinear characteristics of the motor, end effects and axial fringing effects. A test bed in the laboratory is established to perform various measurements on the eccentric motor with different fault levels. The experimental results validate the numerical analysis outcomes. Fault detection and analysis in SRM demonstrate that the algorithm presented can assure the reliability of detection as well as the sensitivity of eccentricity fault in a SRM.
机译:本文提出了一种用于开关磁阻电机(SRM)的静态,动态和混合偏心故障的非侵入式诊断的新方法。这种方法可以精确地确定偏心故障特征。该算法中建议的签名基于对具有特定变化模式的产生电流的分析。从理论上讲,故障级别的发生和增长会导致所产生的电流信号(PCS)的幅度增加,可用于诊断故障并提取其详细信息。在该方法中,首先,利用偏心度检测模式来检测故障的发生及其位置。此后,引入了一个新索引来精确确定故障级别。然后,基于提出的模式和指标提供了一种新颖的策略来检测偏心率的类型以及故障相的确切位置。为此,使用三维瞬态有限元方法(TFEM)对偏心故障下的SRM进行建模。这个精确的模型考虑了所有复杂的电动机几何形状,电动机的非线性特性,端效应和轴向边缘效应。在实验室中建立了一个试验台,以对具有不同故障级别的偏心电动机执行各种测量。实验结果验证了数值分析结果。 SRM中的故障检测和分析表明,所提出的算法可以确保SRM中检测的可靠性以及偏心故障的敏感性。

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