Study On Thermal Analysis And Thermal Error Modeling Of Gear Continuous Generating Machine Tools

At present,continuous tooth surface generating is the mainstream technology of gear manufacturing industry.Gear continuous generating machine tools mainly include gear hobbing machine and worm wheel grinding machine,which determines the core competitiveness of gear manufacturing enterprises.The accuracy of gear making machine directly determines the quality of gear processing.However,accuracy of gear continuous generating machine tool is greatly affected by the thermal deformation,the law of thermal deformation of machine tools is unclear,and the lack of thermal error modeling method and other problems urgently needs to be solved.Although gear hobbing machine and worm grinding wheel gear grinding machine are used for rough and finish machining respectively,their structures are similar and their principles are the same.Therefore,based on the common characteristics of the structure and technology of gear continuous generating machine tool,this paper studies the Thermal Analysis and thermal error modeling.The main research contents are as following:(1)Aiming at the problem that the thermal deformation law of gear continuous generating machine tool is not clear,the thermal characteristics of the machine tool are analyzed.Based on the common features of hobbing machine and worm wheel grinding machine in structure and technology,the heat source distribution and thermal deformation trend are analyzed.Then,under the influence of different heat sources,the finite element analysis of the two kinds of machine tools is carried out,and the steady-state temperature field distribution and thermal deformation nephogram are obtained,so as to realize the preliminary understanding of the thermal deformation law of gear continuous generating machine tools,and provide theoretical support for the experimental of thermal error collection.(2)Aiming at the problems of thermal error acquisition and temperature measurement point optimization of gear continuous generating machine tool,the experiment of thermal error acquisition is designed,and the temperature measurement point optimization method based on improved k-means clustering method is proposed.The temperature and displacement measurement system are designed,and thermal error acquisition experiments under different working conditions are carried out respectively.The temperature thermal error data of gear continuous generating machine tool are obtained,which provides data basis for thermal error modeling.In the K-means clustering method,the mutual information method is introduced to realize the optimization of temperature measuring points,and the multiple regression modeling is introduced to determine the optimal clustering number,so as to realize the optimization of temperature measuring points.The effectiveness of the improved k-means clustering method in the optimization of temperature measurement points of gear continuous generating machine tool is verified by comparing with the modeling of ordered clustering,grey correlation degree and fuzzy clustering method.(3)Aiming at the problem of thermal error modeling of gear continuous generating machine tool,the thermal error modeling method based on convolution neural network(CNN)is studied.Combined with the principle of the convolution neural network,the algorithm structure is designed,and thermal error modeling of gear hobbing machine and worm grinding wheel gear grinding machine is carried out.Compared with multiple regression model and GA-BP neural network model,convolution neural network has higher prediction performance in thermal error modeling of gear continuous generating machine tool.It provides modeling method support for the subsequent thermal error compensation research of the project.