CAJ | 학술논문

针对旋转机械故障特征提取的问题,以干式真空泵为研究对象,将自回归(AR)模型应用于其滚动轴承故障检测,针对其时域信号建立自回归模型,确定出模型最佳阶次,并计算出其AR功率谱,进而判断轴承的工作状态.实验结果表明:采用该方法能有效地提取轴承故障的特征频率,对于干式真空泵的故障检测是一种有效的方法.
침대선전궤계고장특정제취적문제,이간식진공빙위연구대상,장자회귀(AR)모형응용우기곤동축승고장검측,침대기시역신호건립자회귀모형,학정출모형최가계차,병계산출기AR공솔보,진이판단축승적공작상태.실험결과표명:채용해방법능유효지제취축승고장적특정빈솔,대우간식진공빙적고장검측시일충유효적방법.
@@@@Aiming at the problem of fault feature extraction of rotating machinery,dry vacuum pump was regarded as the research object. AR model was applied to fault detection of rolling bearings. The AR model for time-domain signal was established,and the optimum order was determined. The AR power spectrum was calculated. The condition of the rolling bearing was identified. The ex-perimental results show that the method can be used to extract fault feature frequency effectively. It is a valid method for fault detection of dry vacuum pump.