作者：吴漫1,2, 冯早1,2, 黄国勇1,2, 牟竹青1,2
作者单位：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
关键词：单向阀;VMD;Wigner-Ville;早期故障诊断
摘要：
针对大型往复式机械设备高压隔膜泵单向阀早期故障难以识别的问题，该文提出基于变分模态分解（variational mode decomposition，VMD）和Wigner -Ville的单向阀早期故障诊断方法。首先，利用VMD将原始振动信号分解成有限个IMF分量，基于观察中心频率法筛选富含故障信息的IMF分量；然后，利用魏格纳-维利分布（Wigner -Ville distribution，WVD）对筛选后的IMF分量计算，得到每个分量的Wigner -Ville分布；最后，将各项结果线性求和得到信号的WVD分布。经仿真与工程实验分析，该方法能较好表征出振动信号中所蕴含的单向阀早期故障特征信息，能实现高压隔膜泵单向阀早期故障诊断。
Early fault diagnosis of check valve based on variational mode decomposition and Wigner-Ville
WU Man1,2, FENG Zao1,2, HUANG Guoyong1,2, MU Zhuqing1,2
1. Faculty of Information Engineering & Automation, Kunming University of Science and Technology, Kunming 650500, China;
2. Engineering Research Center for Mineral Pipeline Transportation. YN, Kunming 650500, China
Abstract: In view of the difficult identification of the early failure of large reciprocating mechanical equipment high pressure diaphragm pump check valve, an early fault diagnosis method of it that based on variational mode decomposition(VMD) and Wigner -Ville is proposed. Firstly, the original vibration signal is decomposed into a finite number of IMF components by VMD, and the IMF components rich in fault information are screened based on the observing center frequency method. Then the screened IMF components are calculated by Wigner-Ville distribution (WVD), and the Wigner-Ville distribution of each component is obtained. Finally, the results are linearly summed and the WVD distribution of the signal is obtained to extract the characteristics of the fault vibration signal. Through simulation and engineering experiment analysis, this method can better characterize the early fault characteristic information of the check valve that contained in the vibration signal, and can realize the early fault diagnosis of the high pressure diaphragm pump check valve.
Keywords: check valve;variational mode decomposition;Wigner -Ville;early fault diagnosis
2019, 45(4):116-122 收稿日期: 2018-04-19;收到修改稿日期: 2018-06-12
基金项目: 国家自然科学基金资助项目（61663017）
作者简介: 吴漫(1993-),女,广东湛江市人,硕士研究生,专业方向为机械设备的故障诊断
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