Vibration-based tool wear estimation by using non-stationary Functional Series TARMA (FS-TARMA) models
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, cilt.93, ss.1431-1442, 2017 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 93
- Basım Tarihi: 2017
- Doi Numarası: 10.1007/s00170-017-0576-7
- Dergi Adı: INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Sayfa Sayıları: ss.1431-1442
- Anahtar Kelimeler: Tool wear, FS-TARMA, Non-stationary, Vibration, AR metric, Damping ratio, ADAPTIVE-OBSERVER, FAULT-DIAGNOSIS, SENSOR FUSION, TIME-SERIES, ONLINE, PERFORMANCE
- Orta Doğu Teknik Üniversitesi Adresli: Evet
Özet
Inverse problem of tool wear estimation using vibration signals is considered via non-stationary functional series time-dependent autoregressive moving average (FS-TARMA) model in this paper. The estimation procedure of FS-TARMA models is presented and through the obtained models, dynamics of the tool-holder system is identified. For finding a relationship between wear and the models, two wear sensitive features are used. First, the models are clustered considering autoregressive (AR) distance as a feature and then, damping ratios of tool-holder bending modes are used as another feature for correlating tool wear with the vibrations. The AR metric provides a parsimonious parametric way for comparison of the structures generating the time series. The obtained wear-AR distance curves possess extremums at critical wear stage. Moreover, in wear-damping ratio curves, which are obtained first time in this paper, extremums appear in the vicinity of critical wear point. These extremums can be used as a measure for tool change policy. The results of the study demonstrate the good accuracy of FS-TARMA models in prediction of tool non-stationary signals and the effectiveness of the selected features for estimation of tool major flank wear.