Research On Dynamic Error Analysis And Compensation Technology Of Coordinate Measuring Machine

Coordinate measuring machines(CMMs),called as the intelligent precision measuring equipment,provide a significantly important condition for the development of manufacturing industry towards intellectualization.Coordinate measuring machines can be integrated with manufacturing equipment under today's shop floor to meet the needs of efficient on-line or in-situ measurement.Thus,how to improve the accuracy of CMMs while improving the efficiency of CMMs has become a key scientific issue in the field of precision measurement.However,the measurement speed and accuracy of the CMMs are the contradiction.In order to analyse the relationship between them,improve the measuring speed and compensate the dynamic error,the specific work of this paper is as follows.In order to make the research results typical and representative,this paper takes moving bridge coordinate measuring machine widely used in industry as the research object,analyses the composition system and structural characteristics of the measuring machine,and discusses the key dynamic error sources affecting the dynamic characteristics of the measuring machine,such as geometric error of the mechanism,systematic error of the probe,structural error of the air-bearing guideway,etc.The relationship between dynamic error sources is deeply studied,the common error factors are extracted,and the speed is determined to be the key factor affecting the accuracy of dynamic measurement.In this paper,the dynamic error separation platform of the CMM is established to research the dynamic measurement process under the high-speed operation of the measuring machine.Based on the quasi-static measurement process,four dynamic parameters reflecting the dynamic characteristics of the measuring machine are analyzed and refined,namely maximum positioning error(MPE),residual positioning error(RPE)and maximum approximation error.(MAE)and Residual Approximation Error(RAE).By means of multiple experiments to calibrate dynamic errors,the method of analysis of variance is used to analyze the influence degree of factors(location speed,location distance,approximation speed and approximation distance)of dynamic error sources on these four dynamic parameters,so as to consolidate the foundation for establishing dynamic parameter error model.Based on fully understanding the relationship between the influence factors of dynamic error sources and dynamic parameter errors,the BP neural network and fuzzy neural network are used to establish dynamic parameter error prediction models,and the validity of the models are verified through a variety of measurement data.By comparing the advantages of the two methods,the experiment results show that the four dynamic parameter errors in the dynamic measurement process of CMM can be reduced by more than 70% and 90% respectively after compensation,which proves the superiority of the fuzzy neural network compensation model,lays a foundation for dynamic error compensation of CMM,and provides guarantee for improving dynamic accuracy of CMM,shortening measuring period and improving measuring efficiency of CMM.