往复压缩机气阀故障混合诊断方法研究

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摘要由于往复压缩机气阀振动信号呈现强非线性和非平稳性特点，目前应用较好的三次样条EEMD（S-EEMD）方法仍然存在模态混叠及包络不准确问题。针对此情况提出一种基于四次Hermite插值EEMD（QH-EEMD）与功率谱熵（PSE）相结合的分析方法。结合四次Hermite插值保形性、可调性与EEMD提高信号在不同分解尺度上连续性的优点改善插值曲线的逼近精度，减少模态混叠，通过对振动信号进行分解，得到IMF分量。通过与S-EEMD-PSE（S-EEMD结合PSE）算法、QH-EEMD-SE（S-EEMD结合样本熵）算法比较，验证了QH-EEMD-PSE（QH-EEMD结合PSE）方法的优越性。以往复压缩机常见故障为研究对象，基于QH-EEMD-PSE方法提取故障特征实现了常见故障的准确诊断。

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关键词 ： EEMD, 功率谱熵, 往复压缩机, 故障诊断

Abstract：For the strong nonlinear and non-stationary characteristics of reciprocating compressor valve vibration signal, the cubic spline interpolation EEMD (S-EEMD) method which was well utilized still had the shortage of mode mixing and envelop inaccurate. According to the above mentioned state, the combined analysis method of EEMD based on quartic Hermite interpolation (QH-EEMD) with the power spectrum entropy (PSE) was proposed. The original signals were decomposed into a set of IMF components by quartic Hermite method which had the advantages of shape-preserving and tunable properties combined with EEMD promoting the signal stable in different decomposing scale, whose union ameliorated the approximation of interpolation curve and decreased the mode mixing. The advantages of QH-EEMD combined with PSE （QH-EEMD with PSE） analysis method was testified comparing with S-EEMD-PSE（S-EEMD with PSE） and QH-EEMD-SE(QH-EEMD with Sample Entropy) method. Taken common faults of reciprocating compressor as research objects, feature vectors of faults were extracted based on QH-EEMD-PSE method and the faults were diagnosed accurately.

Key words： EEMD power spectrum entropy (PSE) reciprocating compressor fault diagnosis

收稿日期: 2015-04-09 出版日期: 2016-05-25

引用本文:

张思阳1,2，徐敏强1，李永波1，赵海洋1，王日新1. 往复压缩机气阀故障混合诊断方法研究[J]. 振动与冲击, 2016, 35(11): 167-173.
Zhang Siyang1、2, Xu Minqiang1, Li Yongbo1, Zhao Haiyang1, Wang Rixin1,. Valve Fault Diagnosis of the Reciprocating Compressor Based on Hybrid Method. JOURNAL OF VIBRATION AND SHOCK, 2016, 35(11): 167-173.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2016/V35/I11/167

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