Sensor placement strategy based on reduced-order models for thermal error estimation in machine tools

Abstract

To compensate for thermal errors in machine tools, strategic sensor placement and rapid error calculation are crucial. This study addresses these challenges using model order reduction. A transfer function matrix and a sensitivity function were defined to optimize the number and locations of sensors without physically attaching them to the machine tool. This methodology was validated through experiments on a 3-axis machining center. The number of sensors was reduced by 50 %, and the calculations were performed instantaneously on a laptop. These results demonstrate the approach's effectiveness in advancing sensor placement strategies and real-time thermal displacement estimation.