CAJ | 학술논문

针对风电机组调心滚子轴承故障振动信号非平稳、非线性的特点,提出了基于固有时间尺度分解（ITD）的轴承故障特征提取方法。ITD方法可以将复杂信号分解成若干个固有旋转分量和一个趋势分量之和,能准确地展示非平稳信号的动态特性,有较高的拆解效率和频率分辨率。分析结果表明,ITD方法能有效地提取风电机组轴承故障特征,可用于在线故障诊断。
침대풍전궤조조심곤자축승고장진동신호비평은、비선성적특점,제출료기우고유시간척도분해（ITD）적축승고장특정제취방법。ITD방법가이장복잡신호분해성약간개고유선전분량화일개추세분량지화,능준학지전시비평은신호적동태특성,유교고적탁해효솔화빈솔분변솔。분석결과표명,ITD방법능유효지제취풍전궤조축승고장특정,가용우재선고장진단。
According to the non-stationary and nonlinear characteristics of the spherical roller bearing fault vibration signals in wind turbine,a bearing fault feature extraction method of wind turbine based on intrinsic time-scale decomposition（ITD） is presented.The ITD method can decompose a complex signal into several proper rotation components and a trend component.It can also reveal the dynamic characteristics of non-stationary signals,has higher decomposition efficiency and frequency resolution.The diagnosis results show that the ITD method can effectively extract the bearing fault characteristics of wind turbine and can be applied to online fault diagnosis.