中国机械工程
中國機械工程
중국궤계공정
CHINA MECHANICAl ENGINEERING
2014年
21期
2912-2917,2924
,共7页
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
多呎度高階奇異譜熵%基于變量預測模型分類識彆%遺傳算法%轉子繫統%故障診斷
다척도고계기이보적%기우변량예측모형분류식별%유전산법%전자계통%고장진단
multi _ scale high order singular spectrum entropy (MSHOSSE)%variable predictive model based class discriminate(VPMCD)%genetic algorithm(GA)%rotor system%fault diagnosis
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。
首先，針對轉子故障振動信號的非高斯、非線性特徵，提齣瞭多呎度高階奇異譜熵的概唸，併將其用于轉子故障特徵提取；然後，針對新的小樣本多分類識彆方法---基于變量預測模型分類識彆的模型選擇問題，結閤融閤診斷思想和遺傳算法，提齣瞭 GA-VPMCD 分類識彆方法。最後提齣瞭基于多呎度高階奇異譜熵和 GA-VPMCD 的轉子故障診斷方法。試驗結果驗證瞭該方法的有效性和優越性。
수선，침대전자고장진동신호적비고사、비선성특정，제출료다척도고계기이보적적개념，병장기용우전자고장특정제취；연후，침대신적소양본다분류식별방법---기우변량예측모형분류식별적모형선택문제，결합융합진단사상화유전산법，제출료 GA-VPMCD 분류식별방법。최후제출료기우다척도고계기이보적화 GA-VPMCD 적전자고장진단방법。시험결과험증료해방법적유효성화우월성。
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 subjec-tivity.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 ap-plied for rotor fault diagnosis.The experimental results show its effectiveness and superiority.
