Analysis Of Thermal Error Mechanism And Real-time Error Compensation Of Gantry Rail Grinder

This article is sponsored by the National Natural Science Foundationof China (No.51275305), Doctoral Program of Higher SpecializedResearch Fund (No.20110073110041), National Science and TechnologyMajor Project (No.2011ZX04015-031) support for Shanghai HeavyMachine Tool Plant MK5225A heavy CNC gantry rail Researchconducted grinder. This paper focuses on modal analysis Grinder to find alarge amount of deformation and regional machine, analyze themechanism to establish the finite element model and error analysis andstructural optimization. We try to find the strength and variation of strainvariation by temperature field and thermal deformation field, build errormodel and compensation, and ultimately to reduce errors and improveprocessing accuracy purposes.The main contents include the following aspects,1As the grinder bed structure is large, it is necessary to carry outusing ANSYS simplified finite element model of the structure when thepre-treatment, omitting machine errors on less important parts. W Finally,the temperature field and the whole deformation field are calculated.2Due to the finite element analysis to simplify the structure of themachine and is not precise enough to handle the load, we need to do atargeted analysis. Based on the results of finite element analysis machine,spindle system of beams is analyzed. Considering some of the majorbeam stress and strain of the situation, we analyzed on some of the majorconsiderations spindle thermal modals. 3Error detections, modeling and compensation grinder are madethrough the main measure of geometric errors and grinder spindle thermaldrift errors, including geometric error measured using a laserinterferometer, spindle thermal drift errors using API dynamic measuringinstrument measured. Based on measured data, the machine’s integratedmodeling errors are compensated.4GSA based on BP neural network optimized thermal error modelingmethod is proposed. Compared with modeling method of least squares,this proposal was proven of the advantages. Using this method, we areable to jump out of the limitations of the best local optimum solution,which is more robust with higher accuracy.