轴承
軸承
축승
BEARING
2014年
9期
48-50,51
,共4页
滚动轴承%故障诊断%奇异值分解%Winger分布%支持向量机
滾動軸承%故障診斷%奇異值分解%Winger分佈%支持嚮量機
곤동축승%고장진단%기이치분해%Winger분포%지지향량궤
rolling bearing%fault diagnosis%singular value decomposition%Winger distribution%support vector ma-chine
提出了一种基于振动信号Winger分布和奇异值分解相结合的轴承故障诊断方法。首先将振动信号进行Winger分布分析；然后将得到的Winger谱矩阵进行奇异值分解，得到反映机械故障状态特征的特征序列；最后将振动信号的Winger谱奇异值作为特征向量，使用支持向量机进行故障诊断。
提齣瞭一種基于振動信號Winger分佈和奇異值分解相結閤的軸承故障診斷方法。首先將振動信號進行Winger分佈分析；然後將得到的Winger譜矩陣進行奇異值分解，得到反映機械故障狀態特徵的特徵序列；最後將振動信號的Winger譜奇異值作為特徵嚮量，使用支持嚮量機進行故障診斷。
제출료일충기우진동신호Winger분포화기이치분해상결합적축승고장진단방법。수선장진동신호진행Winger분포분석；연후장득도적Winger보구진진행기이치분해，득도반영궤계고장상태특정적특정서렬；최후장진동신호적Winger보기이치작위특정향량，사용지지향량궤진행고장진단。
A fault diagnosis method for bearings is proposed based on Winger distribution of vibration signals and SVD (singular value decomposition).Firstly,the Winger distribution analysis is carried out for vibration signals,then the singular value decomposition is done for Winger spectrum matrix,the characteristic sequence reflecting mechanical fail-ure state characteristics is obtained.Finally,the Winger spectrum singular values are used as the feature vector and the support vector machine is used to diagnose the faults.
