摘要
针对在强噪声干扰环境下提取往复压缩机故障特征以及VMD算法参数设置对先验知识的过度依赖的问题,提出了融合趋势评估VMD算法和MSSE_(2D)的往复压缩机故障诊断方法。本文选取往复压缩机的气阀故障数据作为研究对象,首先通过应用经过频谱趋势评估优化的VMD技术对信号进行深入分析与处理,然后使用MSSE_(2D)进行分析计算,最后使用支持向量机进行验证测试,实验结果表明此方法相较于其他方法可以有效提取往复压缩机气阀故障特征,能够快速的对气阀各种状态进行精确的诊断与区分。
Aiming at the problems of extracting the fault features of reciprocating compressors under the strong noise interference environment and the over-reliance on the a priori knowledge in the parameter setting of the VMD algorithm,a reciprocating compressor fault diagnosis method that integrates the VMD algorithm of trend evaluation and MSSE_(2D)is proposed.In this paper,the valve fault data of reciprocating compressor is selected as the research object,firstly,the signal is analyzed and processed in depth by applying the VMD technique optimized by spectral trend evaluation,then the MSSE_(2D)is used for analysis and calculation,and finally the support vector machine is used for validation test,and the experimental results show that this method can extract the fault characteristics of the reciprocating compressor valve efficiently compared with other methods,and it can quickly and accurately diagnose the various states of the valve,the results show that this method can effectively extract the fault characteristics of reciprocating compressor valves compared with other methods,and can quickly and accurately diagnose and distinguish between various states of valves.
作者
李颖
杨宝凯
孙国涵
巴鹏
马小英
Li Ying;Yang Baokai;Sun Guohan;Ba Peng;Ma Xiaoying(School of Mechanical Engineering,Shenyang Ligong University,Shenyang 110159,China)
出处
《电子测量技术》
北大核心
2024年第17期180-190,共11页
Electronic Measurement Technology
基金
国家自然科学基金(51934002)
辽宁省属本科高校基本科研业务费专项资金(LJ212410144039)
辽宁省教育厅青年科技人才“育苗”项目(LJKZ0259)资助。
