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中文摘要：
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。
英文摘要：
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.
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