电子测量与仪器学报

钱恩丽,黄国勇,李锶宇,何冬.基于 CMFDE 的单向阀早期微弱故障诊断方法[J].电子测量与仪器学报,2021,35(4):169-176

基于 CMFDE 的单向阀早期微弱故障诊断方法

Method of CMFDE in check valve early weak fault diagnosis

DOI：

英文关键词:check valve early weak fault composite multiscale fluctuation dispersion entropy fluctuation dispersion entropy fault diagnosis

基金项目:国家自然科学基金(61663017)项目资助

作者	单位
钱恩丽	1. 昆明理工大学信息工程与自动化学院
黄国勇	1. 昆明理工大学信息工程与自动化学院，2. 昆明理工大学民航与航空学院
李锶宇	1. 昆明理工大学信息工程与自动化学院
何冬	1. 昆明理工大学信息工程与自动化学院

Author	Institution
Qian Enli	1. Faculty of Information Engineering and Automation, Kunming University of Science and Technology
Huang Guoyong	1. Faculty of Information Engineering and Automation, Kunming University of Science and Technology, 2. Faculty of Civil Aviation and Aeronautics, Kunming University of Science and Technology
Li Siyu	1. Faculty of Information Engineering and Automation, Kunming University of Science and Technology
He Dong	1. Faculty of Information Engineering and Automation, Kunming University of Science and Technology

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中文摘要:

对单向阀早期微弱故障进行诊断可预防高压隔膜泵因单向阀磨损击穿无法正常工作而造成经济损失及安全事故。针对往复式高压隔膜泵单向阀早期微弱故障特征不明显且受大量噪声干扰的问题,提出基于复合多尺度波动散布熵( composite multiscale fluctuation dispersion entropy, CMFDE)的单向阀早期微弱故障诊断方法。首先,用正切 S 型替换 CMFDE 方法中的正态分布函数映射,提高 CMFDE 的抗噪性;其次,计算振动信号的复合多尺度波动散布熵值,构建特征矩阵,并将其输入支持向量机(support vector machine, SVM)分类器中进行故障诊断;最后,利用单向阀实际工程数据验证该方法的有效性,并进行对比实验。实验结果与对比分析表明,不需对单向阀原始信号进行降噪,简化了诊断过程。复合多尺度波动散布熵可精确反映单

英文摘要:

The early weak fault diagnosis of check valve can prevent economic loss and safety accident caused by the failure of the high pressure diaphragm pump due to the wear and breakdown of check valve. Aiming at the problem that early weak fault feature of the check valve of the reciprocating high pressure diaphragm pump are not obvious and are disturbed by a lot of noise, Method: a method for early weak fault diagnosis of check valve based on composite multiscale fluctuation dispersion entropy (CMFDE) is proposed. First of all, replace the normal cumulative distribution function mapping in the CMFDE method with tangent sigmoid to improve the noise resistance of CMFDE. Then, calculate the composite multiscale fluctuation dispersion entropy of the vibration signal, and construct the feature matrix and input it into the support vector machine (SVM) classifier for fault diagnosis. Finally, the actual engineering data of the check valve is used to verify the effectiveness of the method, and a comparative experiment is carried out. The experimental results and comparative analysis show that it is not necessary to reduce the noise of the original signal of check valve, which simplifies the diagnosis process. The composite multiscale fluctuation dispersion entropy feature can accurately reflect the different signal characteristics of check valve, which improves the identification rate of the early weak fault diagnosis of check valve, and the fault diagnosis result is less affected by classifiers, with the identification accuracy reaching 96. 667%.

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