절삭력과 음향방출 신호를 이용한 밀링공구의 파손 검출 = Fracture Detection of Milling Cutter Using Cutting Force and Acoustic Emission Signals

다국어 초록 (Multilingual Abstract)

An on-line monitoring system of endmill failure such as weal, chipping, and fracture is developed using AE, cutting force Characteristic variations of AE and cutting force signals due to endmill failure are identified as follows. When endmill fracture occurs, AE count rate shows a rapid Increase in conjunction with a subsequent decrease while a standard deviation of the principal cutting force Increases significantly. The increase of AE count rate precedes the Increase of standard deviation of principal cutting force. Chipping results in relatively small increase and decrease of AE count rate without any significant variation of the cutting force Gradual increase of AE count rate and mean principal cutting force are Identified to be related with the wear of cutter. A cutter fracture detection algorithm is developed based on the present results. The signals me normalized to enhance the applicability of the algorithm to Wide those of fresh cutters, and qualitative characteristics of AE signals encountered at the moment of fracture are employed. It is demonstrated that the algorithm can detect the cutter fracture successfully.