• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Intelligent automation and soft computing >Motor current signatures and their envelopes as tools for fault diagnosis
【24h】

Motor current signatures and their envelopes as tools for fault diagnosis

机译：电动机电流信号及其包络线作为故障诊断的工具

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Induction motor inter-turn short circuit stator fault is identified using motor current signals with the help of Discrete Wavelet Transform along with Power Spectral Density. This methodology is adopted for motor current signals and their envelopes in order to identify a better tool for fault diagnosis. First, the analysis is performed using the original stator current signal, which has the fundamental frequency components along with the slip frequency and other harmonic/fault components. The fundamental component in the stator current can be eliminated by using the envelope of the signal. The transient in the wavelet decomposition can be suppressed by modifying the current envelope. This is done by pre-multiplying the original envelope with the Tukey window. The Power Spectral Density is calculated for both the signatures. Comparison of these two methods show that the proposed analysis based on modified envelope using Discrete Wavelet Transform along with Power Spectral Density offers better results compared to the original signal analysis.
机译：借助离散小波变换和功率谱密度，利用电动机电流信号来识别感应电动机匝间短路定子故障。电动机电流信号及其包络采用此方法，以便确定用于故障诊断的更好工具。首先，使用原始定子电流信号进行分析，该信号具有基本频率分量以及转差频率和其他谐波/故障分量。定子电流中的基本分量可以通过使用信号包络来消除。小波分解中的瞬变可以通过修改电流包络来抑制。这是通过将原始信封与Tukey窗口预乘。计算两个特征的功率谱密度。两种方法的比较表明，与原始信号分析相比，基于使用离散小波变换和功率谱密度的改进包络的分析方法提供了更好的结果。

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