Method for predicting thermal error of spindle of computer numerical control machine tool based on twin feature transferring of virtual-real prototype

A method for predicting a thermal error of a spindle of a computer numerical control (CNC) machine tool based on twin feature transferring of a virtual-real prototype, comprising:

• S1:
• building a spindle physical prototype experiment table, uniformly arranging a plurality of measuring points outside a physical prototype spindle, screening and obtaining first temperature sensitive points outside the physical prototype spindle from the plurality of measuring points, and establishing a thermal error autoregressive distributed lag model;
• S2:
• determining temperature synchronization lag points on the physical prototype spindle corresponding to the first temperature sensitive points outside the physical prototype spindle, establishing a first temperature relationship between the first temperature sensitive points outside the physical prototype spindle and the temperature synchronization lag points on the physical prototype spindle according to a grey system theory, and obtaining a thermal error analysis model of the physical prototype spindle with temperatures of the temperature synchronization lag points on the physical prototype spindle as a thermal error feature according to the first temperature relationship;
• S3:
• establishing a virtual prototype model of the CNC machine tool, taking the temperature synchronization lag points on the physical prototype spindle as a twin feature and transferring and mapping the temperature synchronization lag points to an virtual prototype spindle of the CNC machine tool to obtain temperature transferring points of the virtual prototype spindle, and then determining second temperature sensitive points outside the virtual prototype spindle with a same thermal hysteresis effect as the temperature transferring points on the virtual prototype spindle by a binary search method, and then establishing a second temperature relationship between the temperature transferring points on the virtual prototype spindle and the second temperature sensitive points outside the virtual prototype spindle according to the grey system theory;
• and by integrating a twin coupling relationship between the physical prototype spindle and the virtual prototype spindle, the thermal error analysis model of the physical prototype spindle and the second temperature relationship, obtaining a thermal error prediction model of the spindle of the CNC machine tool based on twin feature transferring of the virtual-real prototype;
• S4:
• adjusting parameters of a physical prototype experiment table to keep running in a same working condition as the CNC machine tool all the time, fusing a thermal error of the physical prototype spindle measured by a displacement sensor with the twin coupling relationship in S3 to obtain a real value of the thermal error of the spindle of the CNC machine tool;
• arranging temperature sensors at corresponding positions outside the spindle of the CNC machine tool according to the second temperature sensitive points outside the virtual prototype spindle, inputting acquired temperature data into the thermal error prediction model of the spindle of the CNC machine tool in real time to obtain a predicted value of the thermal error of the spindle of the CNC machine tool;
• finally, calculating prediction accuracy according to the real value and the predicted value of the thermal error of the spindle of the CNC machine tool, and optimizing the prediction model of the thermal error of the spindle of the CNC machine tool according to the prediction accuracy, so as to obtain a more accurate predicted value of the thermal error of the spindle of the CNC machine tool.