电子学报 ›› 2018, Vol. 46 ›› Issue (11): 2696-2704.DOI: 10.3969/j.issn.0372-2112.2018.11.017

• 学术论文 • 上一篇    下一篇

相关系数SVD增强随机共振的单向阀故障诊断

张丹威1,2, 王晓东1,2, 黄国勇1,2   

  1. 1. 昆明理工大学信息工程与自动化学院, 云南昆明 650500;
    2. 云南省矿物管道输送工程技术研究中心, 云南昆明 650500
  • 收稿日期:2018-01-04 修回日期:2018-04-23 出版日期:2018-11-25 发布日期:2018-11-25
  • 通讯作者: 王晓东
  • 作者简介:张丹威 男,1992年生,河南商丘人,2015年毕业于郑州大学电力系统及其自动化专业,2016年就读于昆明理工大学信息工程与自动化学院控制工程专业,现为硕士研究生,研究方向为信号处理、故障诊断.E-mail:1263469369@qq.com
  • 基金资助:
    国家自然科学基金(No.61663017)

Check Valve Fault Diagnosis with Correlation Coefficient SVD Enhanced Stochastic Resonance

ZHANG Dan-wei1,2, WANG Xiao-dong1,2, HUANG Guo-yong1,2   

  1. 1. Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, Yunnan 650500, China;
    2. Yunnan Province Engineering Technology Research Center for Mineral Pipeline Transportation, Kunming, Yunnan 650500, China
  • Received:2018-01-04 Revised:2018-04-23 Online:2018-11-25 Published:2018-11-25

摘要: 针对大型往复式高压隔膜泵关键部件单向阀的磨损击穿故障通常遭受强噪声污染,故障难以检测的问题,从单向阀振动信号分析入手,提出一种相关系数SVD增强随机共振的单向阀故障诊断方法.该方法首先将含有噪声的单向阀振动信号进行奇异值分解(SVD),然后利用相关系数法筛选出包含故障特征信息最多的分量信号,再将其输入到随机共振系统中进行处理,达到检测强噪声背景下单向阀磨损击穿故障的目的.仿真结果表明,提出方法解决了强噪声背景下故障特征提取困难的问题;实测数据表明,该方法能够有效检测单向阀磨损击穿故障.

关键词: 单向阀, 相关系数, 奇异值分解(SVD), 随机共振, 强噪声

Abstract: For the key components of the large reciprocating high pressure diaphragm pump,the wear breakdown of one way valve usually suffers from strong noise pollution and it is difficult to detect the fault.Starting with the analysis of the vibration signal of the check valve,a method of single directional valve fault diagnosis with the correlation coefficient SVD enhanced random resonance is proposed.In this method,the singular value decomposition(SVD) of the check valve vibration signal with noise is first carried out,then the component signal which contains the most information of the fault features is selected by the correlation coefficient method,and then input into the stochastic resonance system,the purpose of detecting the wear breakdown fault of the check valve under the strong noise background is achieved.The simulation results show that the proposed method solves the problem of difficult fault feature extraction under the strong noise background,and the measured data show that the method can effectively detect the wear breakdown fault of the check valve.

Key words: check valve, correlation coefficient, singular value decomposition(SVD), stochastic resonance, strong noise

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