Research On The Thermal Error Prediction Of Heavy Type Milling Boring Machine Tool

During the process of machining, there are varieties of heat sources, such as the beating of bearing, the beating of motor and the beating of slide-way, they can lead to the thermal distortion the different structural elements. Under the action of superposition of various thermal distortions, the accuracy of the position of the tool is destroyed, as it is called thermal error. It has been shown that the thermal error of machine tool can account for 40～70 percents of the total machine error.The heavy NC machine tools which are widely applied in the field of aerospace and others are usually used on machining of heavy parts, which has the characteristic of large volume, heavy mass and long range of travel, and its thermal errors that are caused by thermal deformation cannot be ignored. Aiming at some heavy type milling boring ma-chine tool, the machine tool thermal errors are analyzed and forecasted in this disserta-tion. The main research achievement of this dissertation is as follows:The theory of heat transfer and the application of finite element is elaborated, and also the finite element model is modeled. After analyzing and calculating the heat and boundary conditions, this dissertation analyzed the temperature field and thermal defor-mation .The method of optimization selection of temperature sensor is researched. After ar-ranging the temperature sensors by experience on the machine tool, the thermal error ex-periment is conducted. By the use of strategy of optimization selection of temperature sensor, such as principal factor, mutually uncorrelated and maximum sensitivity, the crit-ical temperature points that are used for thermal error modeling are selected in three pro-cedures. Considering the impact on the selecting result, two different proposals are raised according to the strategy in the last procedure.The application of theory of the multiple linear regression on the thermal error mod-eling is analyzed. Aiming at the two proposals that are discussed, the regression variables are selected by stepwise weakening and the thermal error models are established in three directions. After analyzing and comparing the forecast precision of the results of the two models, the final thermal error model is recommended.