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Online prediction and control method for compensation regulation value in grinding processes

为在磨进程的赔偿规定价值的联机预言和控制方法

作     者:Zheng, Peng Liu, Dong-liang Tian, Xue-hao Zhi, Zhan-xin Zhang, Lin-na 

作者机构:Zhengzhou Univ Sch Mech Engn 100 Kexue Rd Zhengzhou 450001 Henan Peoples R China 

出 版 物:《ADVANCES IN MECHANICAL ENGINEERING》 (机械工程进展)

年 卷 期:2019年第11卷第3期

核心收录:

学科分类:08[工学] 0807[工学-动力工程及工程热物理] 0802[工学-机械工程] 

基  金:National Science Foundation of China Natural Science Foundation of Henan Province 

主  题:Grinding compensation regulation value error correction support vector machine convex hull algorithm 

摘      要:In any grinding process, compensation regulation value is a crucial factor for maintaining precision during the batch processing of workpieces. Geometric characteristics, buffing allowance, temperature, wheel speed, and workpiece speed are the main factors that affect compensation regulation value in any grinding process. In this article, a novel prediction method for compensation regulation value is proposed based on incremental support vector machine and mixed kernel function. The support vectors for the prediction model are extracted using the convex hull vertex optimization algorithm, and the speed of the operation can be increased effectively. In addition, the parameters of the model are optimized using cross-validation optimization method to improve the accuracy of the prediction model. Then, the feedback control strategy of compensation regulation value for the grinding process is also proposed. Single-factor and multi-factor experiments are implemented respectively using the proposed method. The results verify the feasibility and effectiveness of the proposed method. It is also noted that the machining accuracy is improved significantly in comparison with the machining without prediction and compensation control. Moreover, by applying the prediction compensation control of compensation regulation value to the active measurement and control of the grinding process, a feedback system is formed, and then the intelligentization of the grinding system can be realized.

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