New Methods Of Thermal Reeor Modeling For NC Machine Tools And Their Researchment And Application

Based on the analysis and summarization of the study status on thermal errors compensation field, this dissertation carries on deeper studies on the following key techniques in this field: the optimization of thermal key points and machine tools thermal errors modeling method. Conclusions from this dissertation are all testified by experiment application from machining center of NC machine tools, which will effectively improve machining precision of machine tools.The main contributions of this dissertation are shown as follows:(1)Aimed at the influence of temperature field distribution of machine tool on the thermal error modeling, a new method about optimizing points of thermal sensors is brought forth. The study on the optimizing points of thermal sensors using the grey correlation model was carried out according to statistical data series measured on the spot. Grey correlation model analyses importance of each of influencing factors in the temperature field of machine tools, gives synthetical performance appraisal of these influencing factors and relative arrangement of performance. Finally, the most key points of temperature sensors are selected, and the disposal of temperature sensors on machine tools is optimized, which can analyze the thermal error of machine tool easily and increases the robustness of thermal error modeling.(2)The basic principle and method of time series analysis and its application in thermal error modeling on NC machine tools have been presented briefly. How to utilize the thermal error serials surveyed to identify, model and predict was discussed in detail, and finally feasibility and validity of time series analysis in the application of thermal error modeling on NC machine tools through computational analysis for many group datum observed in succession from turning centre have been proved.(3)The basic principle and method of grey system model and its application in thermal error modeling on machine tools have been presented briefly. How to utilize the thermal error serials surveyed for modeling and prediction is discussed in detail through modeling of grey system theory. Besides, a new prediction model based on improved grey system was proposed. In this model, the degree of smoothness of the data sequence was improved by function transform, then metabolic method was used to improve the deficiency of traditional GM (1,1), namely metabolic GM (1,1) was capable of dynamic refreshment of input data.(4)A kind of combining prediction model, synthesizing advantages of time series analysis and grey system theory, was applied to the trend prediction of thermal errors in a spot NC turning center. It first improves smoothness degree of primary data sequence by function transform method and uses again new data sequence obtained to establish GM(1,1) model; second, time series analysis model is established by remnant sequence of GM(1,1) model to amend the precision of GM(1,1) model. Through the prediction study on thermal error modeling in a spot NC turning center, testing results showed that combining prediction model can highly improve machine tool's prediction precision.(5)The definition and content of measurement uncertainty is introduced firstly, the calculating approach of dynamic uncertainty of measurement system is mainly discussed by applying Grey System Theory. Through the analysis of testing data obtained from the self-developed real-time measurement system of machine tool, the expression of dynamic uncertainty of measurement system is put forward. Compared with static uncertainty, the precision of dynamic uncertainty is farther enhanced through remnant correction. Hence, the importance and usefulness of dynamic uncertainty for scientific judge of measurement system and validity enhancement of measurement system is fully testified.(6)Experiment research for robust modeling of thermal error is carried, and real-time compensation of thermal error is applied for turning center. Firstly, heat root analysis, thermal error mode analysis and ideal setting place of temperature sensors are performed to find out main heat root and key temperature points impacting machining precision; secondly, many methods of machine tool thermal error modeling are used to check and test thermal error; finally, thermal error compensation system will be obtained and proved to be right through practical manufacturing process.