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机构地区:[1]江苏工业学院,常州213016
出 处:《中国机械工程》2008年第1期120-125,共6页China Mechanical Engineering
基 金:江苏省"六大人才高峰"资助项目(06-D-040);常州市科技计划项目(CE2006063)
摘 要:介绍了以德国为主的欧洲工业国在并联运动机械(PKM)误差建模及校正技术方面的研究成果与最新进展,包括基于统计的方法、冗余校正方法、最小线性组合法、神经网络法、固定点法、自我校正方法等新的运动学建模与参数识别方法,以及最新研制的实用测量装置或元件。目前,全世界共有40余种PKM获得成功应用,主要应用于以德国为主的欧洲工业国的模具制造、航空制造、汽车及成形技术等领域。由于机械加工误差、安装误差等因素的影响,PKM必须进行标定校正,以达到较好的工作精度;较高的制造安装精度是PKM获得有效工作空间、良好工作精度以及动力学性能的前提,减小误差及标定校正是其成功应用的技术保证。The latest achievements and development of Parallel Kinematic Machine (PKM) in error analysis modeling and calibration in Germany were overviewed, including the statistical approach , redundant measurement method, minimal linear combination method, neural network error identification method, the fixed point method and the total self--calibration approach and some new measurement devices or elements. Up till now, there were about 40 PKM models or prototypes in the world which had found practical use successfully in the Europe countries in die making, aerospace, automobile and modeling industry. There were always some errors between ideal parameters and practical ones because of the manufacturing and assembling errors. Manufacturing precision was an important index of the PKM performance, which was the basis to obtain effective workspace and better position precision as well as dynamic performance. Therefore, error-reducing and calibration are the key technical measures, which is necessary for successful applications of PKMs.
分 类 号:TH112[机械工程—机械设计及理论] TP242[自动化与计算机技术—检测技术与自动化装置]
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