首页> 外文会议>International Conference on Smart Grid and Electrical Automation >A Novel Bearing Fault Diagnosis Method Based on Slice Spectrum and Wiener Process
【24h】

A Novel Bearing Fault Diagnosis Method Based on Slice Spectrum and Wiener Process

机译:基于切片谱和维纳过程的轴承故障诊断新方法

获取原文

摘要

This paper focused on weak fault feature extraction and reliability assessment for bearings and proposed a novel fault diagnosis method based on slice spectrum analysis and Wiener process. Firstly, we conducted slice spectrum analysis on the acquired vibration signals and extracted the characteristic value of early weak fault, based on the variation tendency of fault characteristic values, a reliability assessment model was established using Wiener degradation process. A case study on the bearing of the lubricating oil pump verifies that the proposed slice spectrum analysis method can effectively extract the modulated information of early weak fault and suppressed the inference of Gaussian noise on the vibration signals. The present study can provide some new ideas for the extraction of weak fault features from the mechanical products vibration signals and the prediction of fault development tendency.
机译:本文重点研究轴承的弱故障特征提取和可靠性评估,提出了一种基于切片频谱分析和维纳过程的新型故障诊断方法。首先,对采集到的振动信号进行切片频谱分析,提取早期弱断层的特征值,根据断层特征值的变化趋势,利用维纳退化过程建立可靠性评估模型。以润滑油泵轴承为例,验证了所提出的切片频谱分析方法能够有效地提取早期弱故障的调制信息,并抑制了高斯噪声对振动信号的干扰。本研究为从机械产品振动信号中提取弱故障特征和预测故障发展趋势提供了新的思路。

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