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[진동·소음부문] 회전요소 베어링 상황감시를 위한 음향-진동 신호의 고차 통계해석
이해철(H.C.Lee),이준서(J.S.Lee),차경옥(K.O.Cha) 한국자동차공학회 1999 한국자동차공학회 춘 추계 학술대회 논문집 Vol.- No.-
This paper present a study on the application of sound pressure and vibration signals to detect the presence of defects in a rolling element bearing using a statistical analysis method. The well established statistical parameters such as the crest factor and the distribution of moments including kurtosis and skewless are utilized in this study. In addition. other statistical parameters derived from the beta distribution function are also used. A comparison study on the performance of the different types of parameter used is also performed. The statistical analysis is used because of its simplicity and quick computation. Under ideal conditions. the statistical method can be used to identify the different types of defect present in the bearing. In addition. the results also reveal that there is no significant advantages in using the beta function parameters when compared to using kurtosis and the crest factor for detecting and identifying defects in rolling element bearings from both sound and vibration signals.