机械科学与技术2024，Vol.43Issue(5)：756-764,9.DOI:10.13433/j.cnki.1003-8728.20220293
单向阀微弱内泄漏故障征提取与模式识别研究
Research on Feature Extraction and Pattern Recognition of Tiny Internal Leakage of Check Valve
摘要
Abstract
Check valves are widely used in hydraulic systems of construction machinery,agricultural machinery and military vehicles,the leakage is a common fault of check valves.This paper proposes a fault diagnosis method of check valve tiny internal leakage based on multi-source,multi-domain,multi-scale feature extraction and machine learning.First of all,the empirical mode decomposition(EEMD)is performed on the vibration signals and pressure signals of the four types of leakage failures.Secondly,the singular value,form factor,entropy and other methods from time domain,frequency domain and time-frequency domain are used to extract features and construct fault feature vector.Finally,the particle swarm-support vector machine algorithm are adopted to classify the leakage fault patterns.Experimental results show that the method can effectively detect leakage and the pattern recognition accuracy of leakage is over 90%.This paper laid a foundation for the research on the leakage rate prediction of the internal leakage of check valves,which has a good engineering application prospect.关键词
单向阀/内泄漏/经验模态分解/支持向量机/模式识别Key words
check valves/internal leakage/empirical mode decomposition/support vector machines/pattern recognition分类
机械制造引用本文复制引用
熊力,刘宁,童成彪,程军圣..单向阀微弱内泄漏故障征提取与模式识别研究[J].机械科学与技术,2024,43(5):756-764,9.基金项目
湖南省自然科学基金项目(2020JJ4045)与湖南省重点研发计划(2022NK2028) （2020JJ4045）
