首页> 外文期刊>Mechanical systems and signal processing >Diagnosis Of Subharmonic Faults Of Large Rotating Machinery Based On Emd
【24h】

Diagnosis Of Subharmonic Faults Of Large Rotating Machinery Based On Emd

机译:基于Emd的大型旋转机械次谐波故障诊断。

获取原文
获取原文并翻译 | 示例

摘要

The vibration signals always carry the abundant dynamic information of a machine and are very useful for the feature extraction and fault diagnosis. In practice, most subharmonic signals have a close relationship to time variables and can manifest large amplitude fluctuation, transient vibration, or modulation signals in time domain. In view of this, this paper describes an effective method to search the features of subharmonic faults of large rotating machinery based on empirical mode decomposition (EMD). Case study on some actual vibration signals of machine parts shows that EMD is an adaptive and unsupervised method in feature extraction and it provides an attractive alternative to the traditional diagnostic methods.
机译:振动信号始终承载着机器的丰富动态信息,对于特征提取和故障诊断非常有用。实际上,大多数次谐波信号与时间变量具有密切关系,并且在时域中可能表现出较大的幅度波动,瞬态振动或调制信号。有鉴于此,本文提出了一种基于经验模态分解(EMD)的大型旋转机械次谐波故障特征搜索方法。通过对机械零件实际振动信号的案例研究表明,EMD是一种自适应的,无监督的特征提取方法,它为传统的诊断方法提供了一种有吸引力的替代方法。

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