A novel method for fast identification of a machine tool selected point temperature rise based on an adaptive unscented Kalman filter
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Chen-hui Xia, Jian-zhong Fu, Yue-tong Xu, Zi-chen Chen. A novel method for fast identification of a machine tool selected point temperature rise based on an adaptive unscented Kalman filter[J]. Journal of Zhejiang University Science A, 2014, 15(10): 761-773.
@article{title="A novel method for fast identification of a machine tool selected point temperature rise based on an adaptive unscented Kalman filter",
author=" Chen-hui Xia, Jian-zhong Fu, Yue-tong Xu, Zi-chen Chen",
journal="Journal of Zhejiang University Science A",
volume="15",
number="10",
pages="761-773",
year="2014",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A1400074"
}
%0 Journal Article
%T A novel method for fast identification of a machine tool selected point temperature rise based on an adaptive unscented Kalman filter
%A Chen-hui Xia
%A Jian-zhong Fu
%A Yue-tong Xu
%A Zi-chen Chen
%J Journal of Zhejiang University SCIENCE A
%V 15
%N 10
%P 761-773
%@ 1673-565X
%D 2014
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A1400074
TY - JOUR
T1 - A novel method for fast identification of a machine tool selected point temperature rise based on an adaptive unscented Kalman filter
A1 - Chen-hui Xia
A1 - Jian-zhong Fu
A1 - Yue-tong Xu
A1 - Zi-chen Chen
J0 - Journal of Zhejiang University Science A
VL - 15
IS - 10
SP - 761
EP - 773
%@ 1673-565X
Y1 - 2014
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A1400074
Abstract: A novel method is presented for fast identification of a machine tool selected point temperature rise, based on an adaptive unscented Kalman filter. The major advantage of the method is its ability to predict the selected point temperature rise in a short period of measuring time, like 30 min, instead of 3 to 6 h in conventional temperature rise tests. A fast identification algorithm is proposed to predict the selected point temperature rise and the steady-state temperature. An adaptive law is applied to adjust parameters dynamically by the actual measured temperature, which can effectively avoid the failure of prediction. A vertical machining center was used to validate the effectiveness of the presented method. Taking any selected point, we could identify the temperature rise at that point in 28 min. However, if the method was not used, it took 394 min to obtain the temperature rise curve from the start-up of the machine tool to the time when it reached a steady-state temperature. The root mean square error (RMSE) between the estimated and measured temperatures in the period of 394 min was 0.1291 °C, and the error between the estimated and measured steady-state temperatures was 0.097 °C. Therefore, this method can effectively and quickly identify a machine tool selected point temperature rise.
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