Study On Thermal Characteristics Of The Ball Screw In The Composite Type Boring-Milling Machining Center

With the development of the NC machine tool in the direction of high speed,high precision,intelligence and automation,the precision and reliability of the NC machine tools is required improving.Ball screw pair which has high positioning accuracy and high transmission efficiency,is an important components of NC machine tool feed system.However,high speed machine tool have the inevitable requirement of faster and faster feed speed.Ball screw pair generates plenty of friction heat because of high speed.Deformation of the ball screw caused by temperature increment,is one of the important factors that affect the feed system positioning accuracy.Improving the hot state characteristics of ball screw is very important to improve the machining precision of the NC machine tools.This thesis introduces the research status about thermal characteristics and error compensation technology of the NC machine tools.The ball screw of the TX1600G composite boring-milling machining center feed system was the research object.The characteristics of structure and the major heating source of feed system was studied.According to heat transfer theory and the finite element theory,the internal heat source and the boundary conditions of the ball screw system was analyzed.The finite element model of the ball screw system was established.Solidworks software was used to establish a three-dimensional model of ball screw system.The model was put into the finite element analysis software ANSYS.The thesis simulated the transient temperature field of the screw system through loading mobile thermal.Then the variation regularity of thermal deformation was proposed under the heat-structure coupling analysis.This thesis explored the different feed speed and convective heat transfer coefficient on the influence of the temperature field and thermal deformation of feed system.Thereby the effective measures to reduce the thermal deformation were obtained.According to the results of the finite element analysis,the fuzzy clustering analysis and clustering analysis method based on grey correlation was used to optimize the number of temperature measuring point.Then the most representative temperature measuring point position can be gained.The ball screw system solution of temperature field and thermal error collection experiment was confirmed on the basis of the structure characteristics of TX1600G feed system.Under a certain condition the temperature and screw position error of test spots on ball screw system was measured.The thermal error of the test spots was separated by using the theory of error separation.The temperature variation over time of the front bearing,rear bearing and the nut,and the relation between the thermal error of measuring points and the temperature was analyzed.The finite element analysis results was compared with the experiment results to prove the correctness of the results.Finally according to the actual situation,the structure of the BP neural network and training methods was confirmed.The BP neural network was used to predict thermal error of the ball screw.So ball screw error prediction model was established.The BP neural network model was easy to fall into local extremum and train time was long.Genetic algorithm was used to optimize the weights and threshold of the BP neural network algorithm,then the GA-BP neural network model was established.The accuracy of two kinds of modeling methods was compared.In conclusion,the thesis took the ball screw of TX1600G boring-milling machining center feed system as research object and studied the thermo-dynamic characteristics of ball screw.Then the thesis analyzed the influence on machine positioning accuracy under different working conditions and got the relationship between the ball screw temperature and rotational speed,the convective heat transfer coefficient,the relationship between the thermal deformation and temperature key point,nut position.This research illustrates that the thermal error of ball screw can be predicted effectively and it can provide the theoretical guiding significance for thermal error compensation of ball screw.