Abstract
Error modeling and compensation is the most effective way to reduce thermal errors. In this paper, a novel approach to predict the thermal error of machine tool based on M-RAN is presented, clustering analysis is used to select the temperature variables, and then an easy and economical measurement system is applied to measure the temperature variables and thermal shift of CNC machining center. The thermally induced errors are estimated in real-time using the trained M-RAN network. The proposed approach is verified through error compensation test.
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