Temperature Measuring Point Optimization And Thermal Error Modeling Of Machining Center

The reliability and accuracy stability of flexible production line largely depend on the key equipment in the processing—machining center. So the processing accuracy of machining center determines the products’quality in the production line directly. Thermal error is one of the most important elements that effects its processing precision, it is generally able to account for the total error of the machine tool 40%-70%, the higher the accuracy of the machine, the greater the proportion. At present, the thermal error compensation technology is one of the effective methods to reduce or eliminate the machine tool’s thermal error and improve its machining accuracy. This technique has aroused wide attention from scholars both at home and abroad. This paper has researched the thermal error compensation technology based on the sub project of "the machine tool’s precision stability and reliability" from the project of "Xichai flexible machining production line demonstration project of heavy-duty diesel engine cylinder block, cylinder head" supported by the major national science and technology projects of "high-end CNC machine tools and basic manufacturing equipment". The main job contents are as follows:(1) This paper expounds the background and significance of the research, summarizes the research status of thermal error compensation technology in China and abroad, and puts forward the main content and research ideas of this paper.(2) In order to get the temperature field and each heat point’s temperature behavior, the thermal characteristics of the machining center during the processing are analyzed. The thermal analysis is carried out by using the finite element method, including establishing geometric model, setting engineering data (such as specific heat, thermal conduction coefficient, density), meshing, adding thermal load and boundary conditions. A finite element model is established at last and the whole temperature field and each heat point’s temperature behavior are achieved.(3) The thermal error composition of the machining center is analyzed, and the measures to reduce the thermal error of the spindle are introduced—error prevention and error compensation. The temperature and spindle thermal error test of machining center is introduced, a test system is built, the test scheme is designed, and the experiment is carried out. Then the experiment data is analyzed and provide a basis for the follow-up study.(4) A temperature measuring point optimization method is proposed, and the realization of the method is given. Relevance analysis method is used for the preliminary screening and the points whose correlation are larger with the thermal error will be reserved. Then the fuzzy clustering analysis and grey correlation degree analysis are carried out respectively. According to the results of the analysis, multiple linear regression models of different measuring points are established. The measuring points whose prediction model achieves the highest accuracy are screened. The result is verified by the experiment.(5) A spindle thermal error modeling method is proposed, and the realization of the method is given. The critical temperature measuring points and thermal error data are divided into different samples, then different multivariate linear regression models are set up. The models who have a higher prediction precision are screened out. The predicted results are seemed as inputs of BP neural network, and the thermal error data is seemed as an output. The thermal error compensation model is established eventually, and the prediction accuracy of the model is compared with other methods.