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MOTION ERROR ESTIMATION OF 5-AXIS MACHINING CENTER USING DBB METHOD 被引量:3
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作者 CHEN Huawei ZHANG Dawei +1 位作者 TIAN Yanling ICHIR0 Hagiwara 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2006年第2期276-281,共6页
In order to estimate the motion errors of 5-axis machine center, the double ball bar (DBB) method is adopted to realize the diagnosis procedure. The motion error sources of rotary axes in 5-axis machining center com... In order to estimate the motion errors of 5-axis machine center, the double ball bar (DBB) method is adopted to realize the diagnosis procedure. The motion error sources of rotary axes in 5-axis machining center comprise of the alignment error of rotary axes and the angular error due to various factors, e.g. the inclination of rotary axes. From sensitive viewpoints, each motion error is possible to have a particular sensitive direction in which deviation of DBB error trace arises from only some specific error sources. The model of the DBB error trace is established according to the spatial geometry theory. Accordingly, the sensitive direction of each motion error source is made clear through numerical simulation, which is used as the reference patterns for rotational error estimation. The estimation method is proposed to easily estimate the motion error sources of rotary axes in quantitative manner. To verify the proposed DBB method for rotational error estimation, the experimental tests are carried out on a 5-axis machining center M-400 (MORISEIKI). The effect of the mismatch of the DBB is also studied to guarantee the estimation accuracy. From the experimental data, it is noted that the proposed estimation method for 5-axis machining center is feasible and effective. 展开更多
关键词 5-axis NC machine tool Double ball bar(DBB) Motion errors of rotary axes
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Adaptive Subspace Predictive Control with Time-varying Forgetting Factor 被引量:3
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作者 Li Zhang Shan-Zhi Xu Hong-Tao Zhao 《International Journal of Automation and computing》 EI CSCD 2014年第2期205-209,共5页
Aiming at the time-varying characteristics of industrial process, this paper introduces an adaptive subspace predictive control(ASPC) strategy with time-varying forgetting factor based on the original subspace predict... Aiming at the time-varying characteristics of industrial process, this paper introduces an adaptive subspace predictive control(ASPC) strategy with time-varying forgetting factor based on the original subspace predictive control algorithm(SPC). The new method uses model matching error to calculate the variable forgetting factor, and applies it to constructing Hankel data matrix.This makes the data represent the changes of system information better. For eliminating the steady state error, the derivation of the incremental control is made. Simulation results on a rotary kiln show that this control strategy has achieved a good control effect. 展开更多
关键词 Subspace predictive control time-varying forgetting factor model matching error adaptive rotary kiln.
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