Thermal error prediction and optimal design of cooling structure for oscillating head housing

Abstract

The thermal error of machine tool has always been an important reason affecting the accuracy of machine tool. In modern methods to reduce thermal error, thermal error compensation method and thermal error isolation method are two methods with high operability. Thermal error compensation method emphasizes predicting deformation in advance and then compensating in advance. Thermal error isolation method emphasizes the reduction of numerical value in thermal error propagation path. In this paper, the machine tool swing head is taken as the research object, and the above two methods are innovatively combined; Build an experimental platform and a simulation model to ensure the accuracy of the experiment through mutual verification; The POA-LSTM prediction model is established to predict the expansion of the swing head shell structure caused by thermal load accumulation, and compared with the LSTM prediction model. The results show that the prediction accuracy of the POA-LSTM prediction model in Z direction and X direction is 98.89 % and 98.38 %, respectively, which is higher than that of LSTM's 89.33 % and 89.47 %. The experiment for shell structure optimization is designed to reduce the thermal expansion of the pendulum and improve the machining accuracy. As a result, the thermal expansion inhibition effect on the whole pendulum is 26.14 %, and the thermal expansion inhibition effects on the X-direction, Y-direction and Z-direction are 34.93 %, 33.35 % and 30.24 % respectively.

Keywords

• machine tool
• thermal error
• prediction model
• Reasonable optimization
• Inhibition effect