多尺度高阶奇异谱熵和GA-VPMCD方法在转子故障智能诊断中的应用

摘要/Abstract

摘要：

首先,针对转子故障振动信号的非高斯、非线性特征，提出了多尺度高阶奇异谱熵的概念，并将其用于转子故障特征提取；然后,针对新的小样本多分类识别方法——基于变量预测模型分类识别的模型选择问题，结合融合诊断思想和遗传算法，提出了GA-VPMCD分类识别方法。最后提出了基于多尺度高阶奇异谱熵和GA-VPMCD的转子故障诊断方法。试验结果验证了该方法的有效性和优越性。

关键词: 多尺度高阶奇异谱熵, 基于变量预测模型分类识别, 遗传算法, 转子系统, 故障诊断

Abstract:

Firstly, according to nongaussian and nonlinear characteristics of rotor fault vibration signals, combining higher order statistics analysis,singular spectrum analysis, information entropy and multi-scale analysis, a conception of MSHOSSE was presented and applied to rotor fault feature extraction. Secondly, VPMCD was a new class discriminate approach, which was of excellent learning ability for small samples and multi_classification, however, the choice of model type existed subjectivity. Thus, an improved class discriminate method based on GA and VPMCD (GA_VPMCD) was presented in the course of rotor fault diagnosis using VPMCD by the global optimization performance of genetic algorithm (GA) and fusion diagnosis method. Finally, a novel intelligent fault diagnosis method based on MSHOSSE and GA_VPMCD was put forward. Simultaneously, the method was applied for rotor fault diagnosis. The experimental results show its effectiveness and superiority.

Key words: multi_scale high order singular spectrum entropy(MSHOSSE), variable predictive model based class discriminate(VPMCD), genetic algorithm(GA), rotor system;fault diagnosis

中图分类号:

罗颂荣, 程军圣, 杨宇. 多尺度高阶奇异谱熵和GA-VPMCD方法在转子故障智能诊断中的应用[J]. 中国机械工程, 2014, 25(21): 2912-2917,2924.

Luo Songrong, Cheng Junsheng, Yang Yu. Intelligent Fault Diagnosis for Rotor Using MSHOSSE and GA-VPMCD Method[J]. China Mechanical Engineering, 2014, 25(21): 2912-2917,2924.

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http://www.cmemo.org.cn/CN/Y2014/V25/I21/2912

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