CNC선반에서 연속절삭 및 단속절삭시 공구손상에 대한 음향방출신호 특성 연구

다국어 초록 (Multilingual Abstract)

Automatic monitoring of cutting process is one of the most important technology in machining. AE sensing technology has been applied to monitoring process and proved to be effective in detecting tool abnormalities such as tool wear and fracture. In this experimental study, AE signals were detected from the tool holder for continuous and interrupted cutting, which obtained from changing workpiece material configuration, under control of constant cutting speed from CNC lathe. From statistical and frequency analysis, the AE signals were analyzed to obtaining the characteristics of continuous and interrupted cutting conditions and tool failure. The Kurtosis values decreased but RMS voltages increased as the cutting speed increased, in both continuous and interrupted cutting. RMS voltage is suddenly increased but Kurtosis value is suddenly decreased when tool failure condition. Power spectrum density of AE signals when tool failure reaches extreme value around 0.065 cycles/μm.