Detection of Main Spindle Bearing Conditions in Machine Tool via Neural Network Methodolog

신경회로망을 이용한 공작기계 주축용 베어링의 고장검지

This paper presents a method of detecting localized defects on tapered roller bearing in main spindle of machine tool system. The statistical parameters in time-domain processing technique have been calculated to extract useful features from bearing vibration signals. These features are used by the input feature of an artificial neural network to detect and diagnose bearing defects. As a results, the detection of bearing defect conditions could be successfully performed by using an artificial neural network with statistical parameters of acceleration signals.