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基于多领域耦合建模的轴向柱塞泵故障诊断方法

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针对轴向柱塞泵传统单一领域建模方法存在的建模困难、仿真精度低以及故障诊断所需故障样本不足的问题,开展基于多领域耦合建模的轴向柱塞泵故障诊断方法.利用Simscape构建轴向柱塞泵多领域耦合模型,并对柱塞泄漏、主轴轴承磨损以及组合故障3种常见的故障进行模拟,再通过故障注入技术和MATLAB快速重启功能获取多种工况、不同故障程度下的压力和流量数据;随后从时域和频域对故障数据进行特征提取,同时利用单因素方差分析对故障特征进行选择;最后利用得到的特征对K邻近、朴素贝叶斯、决策树、神经网络、支持向量机等5种故障诊断算法进行训练,得到故障诊断准确率最高的算法,其平均诊断准确率为98.5%.该方法提高了轴向柱塞泵多领域耦合建模的精确性,实现了对轴向柱塞泵的有效故障诊断.
Fault Diagnosis Method of Axial Piston Pump Based on Multi-domain Coupling Modeling
In order to solve the problems of modeling difficulties,low simulation accuracy and insufficient fault samples required for fault diagnosis in the traditional single-domain modeling method of axial piston pump,a fault diagnosis method based on multi-do-main coupling modeling was carried out for the axial piston pump.The multi-domain coupling model of the axial piston pump was con-structed by Simscape,and three common faults of plunger leakage,spindle bearing wear and combined fault were simulated,then the pressure and flow data under various working conditions and different fault degrees were obtained by fault injection technology and MATLAB fast restart function.The fault data were extracted from time domain and frequency domain,and the fault features were selected by one-way ANOVA.Finally,the obtained features were used to train five fault diagnosis algorithms,including K-nearest neighbor,na-ive Bayes,decision tree,neural network and support vector machine,and the algorithm with the highest accuracy of fault diagnosis was obtained,with an average diagnostic accuracy of 98.5%.The method improves the accuracy of multi-domain coupling modeling of axial piston pumps,and realizes effective fault diagnosis of axial piston pumps.

axial piston pumpmulti-domain coupling modelfault injectmachine learningfault diagnosis

唐宏宾、李志祥、董晋阳、陈思源

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长沙理工大学汽车与机械工程学院,湖南长沙 410114

湖南省特种设备检验检测研究院,湖南长沙 410114

轴向柱塞泵 多领域耦合模型 故障注入 机器学习 故障诊断

湖南省教育厅重点项目长沙理工大学专业学位研究生实践创新与创业能力提升计划

22A0222CLSJCX22059

2024

机床与液压
中国机械工程学会 广州机械科学研究院有限公司

机床与液压

CSTPCD北大核心
影响因子:0.32
ISSN:1001-3881
年,卷(期):2024.52(15)