仪器仪表学报
儀器儀錶學報
의기의표학보
CHINESE JOURNAL OF SCIENTIFIC INSTRUMENT
2014年
8期
1789-1795
,共7页
徐玉秀%赵晓清%杨文平%郭威
徐玉秀%趙曉清%楊文平%郭威
서옥수%조효청%양문평%곽위
行星齿轮传动系统%混沌特征参数%多测点%支持向量机%故障诊断
行星齒輪傳動繫統%混沌特徵參數%多測點%支持嚮量機%故障診斷
행성치륜전동계통%혼돈특정삼수%다측점%지지향량궤%고장진단
planetary gear transmission system%chaotic characteristic parameter%multiple measuring points%support vector machine%fault diagnosis
为了找到多级行星齿轮传动系统复杂故障诊断的合适方法,对三级齿轮传动系统进行故障模拟和振动信号测试。针对行星齿轮传动系统振动信号的非线性和非平稳性、故障特征信号难以提取等特点,采用关联维数、最大Lyapunov指数、样本熵3个混沌特征参数作为故障辨识特征量。用不同测点和不同混沌特征参数的信息融合,通过支持向量机分类方法建立信息融合故障诊断模型及6种不同故障状态的训练集,实现对三级齿轮传动系统复杂故障类型的识别与诊断。分析结果表明:多测点信息融合或不同混沌特征参数融合,均能不同程度提高故障分类准确率。而经多测点与多混沌特征参数的信息融合后,通过支持向量机的故障分类准确率最高。
為瞭找到多級行星齒輪傳動繫統複雜故障診斷的閤適方法,對三級齒輪傳動繫統進行故障模擬和振動信號測試。針對行星齒輪傳動繫統振動信號的非線性和非平穩性、故障特徵信號難以提取等特點,採用關聯維數、最大Lyapunov指數、樣本熵3箇混沌特徵參數作為故障辨識特徵量。用不同測點和不同混沌特徵參數的信息融閤,通過支持嚮量機分類方法建立信息融閤故障診斷模型及6種不同故障狀態的訓練集,實現對三級齒輪傳動繫統複雜故障類型的識彆與診斷。分析結果錶明:多測點信息融閤或不同混沌特徵參數融閤,均能不同程度提高故障分類準確率。而經多測點與多混沌特徵參數的信息融閤後,通過支持嚮量機的故障分類準確率最高。
위료조도다급행성치륜전동계통복잡고장진단적합괄방법,대삼급치륜전동계통진행고장모의화진동신호측시。침대행성치륜전동계통진동신호적비선성화비평은성、고장특정신호난이제취등특점,채용관련유수、최대Lyapunov지수、양본적3개혼돈특정삼수작위고장변식특정량。용불동측점화불동혼돈특정삼수적신식융합,통과지지향량궤분류방법건립신식융합고장진단모형급6충불동고장상태적훈련집,실현대삼급치륜전동계통복잡고장류형적식별여진단。분석결과표명:다측점신식융합혹불동혼돈특정삼수융합,균능불동정도제고고장분류준학솔。이경다측점여다혼돈특정삼수적신식융합후,통과지지향량궤적고장분류준학솔최고。
In order to find the appropriate method of multistage planetary gear transmission system complex fault diagnosis,fault simulation and vibration signal test were carried out on three stage gear transmission system.Aiming at the nonlinear and non-sta-tionary characteristics of the vibration signals of the planetary gear transmission system and the difficultly in picking up the fault fea-ture signals,3 chaotic characteristic parameters,including the correlation dimension,maximum Lyapunov exponent and sample entropy were adopted as fault identification features.The information of different measuring points and different chaotic characteris-tic parameters was fused;and the information fusion fault diagnosis model and the training set for 6 kinds of different fault states were established based on the classification method of support vector machine,then the recognition and diagnosis of the three stage gear transmission system with complex fault types were achieved.Analysis results show that the multiple measurement information fusion or different chaotic characteristic parameter fusion both can improve the accuracy of fault classification at different degrees. After the information fusion of multipoint and multiple chaotic characteristic parameters,and using support vector machine,the ob-tained fault classification accuracy rate is the highest.