CAJ | 학술논문

根据滚动轴承故障信号的非平稳特点及振动信号的强噪声背景，提出一种基于固有时间尺度分解（ITD）和灰色关联度的轴承故障诊断方法。首先利用ITD法将轴承振动信号分解为若干个固有旋转分量，进而提取故障特征参数，然后通过计算标准故障模式与待识别样本的灰色关联度对轴承故障类型进行判断。实例表明， ITD法可较好地分解轴承故障振动信号，结合灰色关联度可成功用于轴承故障在线监测与诊断，有效识别轴承工作状态。
근거곤동축승고장신호적비평은특점급진동신호적강조성배경，제출일충기우고유시간척도분해（ITD）화회색관련도적축승고장진단방법。수선이용ITD법장축승진동신호분해위약간개고유선전분량，진이제취고장특정삼수，연후통과계산표준고장모식여대식별양본적회색관련도대축승고장류형진행판단。실례표명， ITD법가교호지분해축승고장진동신호，결합회색관련도가성공용우축승고장재선감측여진단，유효식별축승공작상태。
According to the strong noise background of vibration signals and the non-stationary characteristics of fault signals for rolling bearings,a fault diagnosis method for bearings is proposed based on intrinsic time-scale decomposi-tion(ITD)and grey incidence degree.Firstly,the vibration signals for bearings is decomposed into a finite number of proper rotation components to extract fault feature parameter using the ITD method,then fault type of bearings is judged by calculating the grey incidence degree between unknown sample and standard fault pattern.The results show that ITD method can effectively decompose fault vibration signals for bearings and this method which combined with grey inci-dence degree can be successfully applied in the on-line monitoring and diagnosis of fault for bearings to identify work-ing conditions of bearings effectively.