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A Study on the Tool Fracture Detection Algorithm Using System Identification
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 Title & Authors
A Study on the Tool Fracture Detection Algorithm Using System Identification
Sa, Seung-Yun; Yu, Eun-Lee; Ryu, Bong-Hwan;
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 Abstract
The demands for robotic and automatic system are continually increasing in manufacturing fields. There have been many studies to monitor and predict the system, but they have mainly focused upon measuring cutting force, and current of motor spindle, and upon using acoustic sensor, etc. In this study, digital image of time series sequence was acquired by taking advantage of optical technique. Mean square error was obtained from it and was available for useful observation data. The parameter was estimated using PAA(parameter adaptation algorithm) from observation data. AR(auto regressive) model was selected for system model and fifth order was decided according to parameter estimation. Uncorrelation test was also carried out to verify convergence of parameter. Through the proceedings, it was found that there was a system stability.
 Keywords
System Identification;Parameter Estimation;Digital Image of Time Series;Observation Data;A Posteriori Prediction Error;
 Language
Korean
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