Journal of the Korean Society for Precision Engineering (한국정밀공학회지)
- Volume 12 Issue 5
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- Pages.33-39
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- 1995
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- 1225-9071(pISSN)
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- 2287-8769(eISSN)
Detection of Main Spindle Bearing Conditions in Machine Tool via Neural Network Methodolog
신경회로망을 이용한 공작기계 주축용 베어링의 고장검지
- Oh, S.Y. (Dept.of Mechanical Engineering, Graduate School of Soongsil University) ;
- Chung, E.S. ;
- Lim, Y.H.
- Published : 1995.05.01
Abstract
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.
Keywords
- detection of bearing conditions;
- machine tool system;
- statistical parameters;
- time-domain processing techniques;
- acceleration signal;
- neural network