APPLICATION OF THE FULL VECTOR SPECTRUM BASED ON EMD IN FAULT DIAGNOSIS OF BEARINGS

CHEN Chao; MENG YaJun; DU YunLong; HUANG ChuanJin

doi:10.16579/j.issn.1001.9669.2015.05.015

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APPLICATION OF THE FULL VECTOR SPECTRUM BASED ON EMD IN FAULT DIAGNOSIS OF BEARINGS

更新时间：2022-09-22

- APPLICATION OF THE FULL VECTOR SPECTRUM BASED ON EMD IN FAULT DIAGNOSIS OF BEARINGS
- Journal of Mechanical Strength Vol. 37, Issue 5, Pages: 806-811(2015)
- 作者机构：
  
  1. 郑州机械研究所
  2. 中州大学机电与汽车工程学院
- 作者简介：
- 基金信息：
- DOI：10.16579/j.issn.1001.9669.2015.05.015
  CLC：
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CHEN Chao, MENG YaJun, DU YunLong, et al. APPLICATION OF THE FULL VECTOR SPECTRUM BASED ON EMD IN FAULT DIAGNOSIS OF BEARINGS. [J]. 37(5):806-811(2015)
DOI：

CHEN Chao, MENG YaJun, DU YunLong, et al. APPLICATION OF THE FULL VECTOR SPECTRUM BASED ON EMD IN FAULT DIAGNOSIS OF BEARINGS. [J]. 37(5):806-811(2015) DOI： 10.16579/j.issn.1001.9669.2015.05.015.

摘要

针对基于单源信息的EMD故障诊断的局限性和根据传统全矢谱分析故障的缺点,提出了基于EMD的全矢谱故障特征提取新方法。该方法对采集于同一截面上的互相垂直的两个传感器上的振动信号,运用EMD将其分别分解为若干IMF分量之和。根据IMF频率及其能量特点,通过全矢谱技术融合特定的IMF分量,得到基于EMD的全矢谱,进而进行故障诊断。仿真结果显示,该方法获取的故障特征更全面、准确。某额定功率为3000k W的TRT发电机组轴瓦振动故障诊断结果进一步表明了该方法的可行性和有效性。

Abstract

Aiming at the deficiency of the analysis of single channel signal EMD and dual channel signal traditional full vector spectrum analysis,this paper presents the full vector spectrum extraction based on EMD.The method of vibration signals collected from the same cross section of the two perpendicular on the sensor,then use EMD on each signal respectively,so that the two signals are decomposed into several IMF components.By the fusion of the IMF component,we can get the full vector spectrum based on obtained EMD.The simulation results show that,the method of obtaining fault characteristics is more comprehensive,accurate.The analysis results of bearing fault vibration signals of TRT generating units in a power rating of3000 KW,further shows the feasibility and effectiveness of the method.

关键词

EMD全矢谱TRT发电机故障诊断同源信息融合滑动轴承

Keywords

Empirical mode decompositionFull vector spectrumTRT generatorFault diagnosisHomologous information fusionSliding bearing

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