Pattern recognition of machine tool faults with a fuzzy mathematics algorithm

摘要

The accuracy and precision of CNC machine tools directly affect the quality of machined parts. Automatic diagnosis of faults can improve the maintenance efficiency of CNC machine tools, and thus increase production uptime and improve product quality. In this study, the typical fault categories of CNC machine tools, such as cyclic, backlash, scale mismatch, etc., are taken as refer- ence patterns and recognized by the fuzzy mathematics algorithm with the machine contouring trajectory measured by an inspection device.