• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.64-69
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• 1993

최근의 생산시스템은 FMS,FMC와 같은 고도로 자동화된 무인시스템으로 운용되고 있으며, 생산성 향상을 위한 무인운전의 필요성이 증대되고 있으나, 숙련된 작업자를 대신하여 작업상태를 감시하는 신뢰성 있는 감시 시스템의 부족으로 인해 곤란을 겪고 있다.따라서 작업자를 대신할수 있는 신뢰성있는 감시 시스템의 개발을 필요로 한다. 특히 공구파손,공구마멸과 같은 공구손상은 공작물 및 기계에 치명적 손상을 초래하고, 기계정지시간을 증가시키므로 공구파손 검출과 공구마멸의 실시간 센싱은 가공 프로세스의 자동화와 신뢰성을 증가시키는데 가장 중요한 역활을 수행한다. 본 연구에서는 드릴가공시 검출한 주축 및 Z축 모터전류를 기초로 하여 드릴마멸을 추정하는 모델을 개발하고자 한다.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.101-108
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• 1999

A reliable and practical monitoring of drill breakage is a crucial technique in automatic machining system. In this study, a real-time monitoring system was developed to predict drill breakage using both spindle and z-axis motor current. Drill breakage is monitored by detecting the level of residual motor current which is obtained through the moving average filter algorithm. The residual exhibits a feature of sharp decrease just before drill breakage. Therefore, drill breakage can be predicted by detecting this characteristic of residual component. Z-axis motor current is better to predict the drill breakage than spindle motor current, because the former is faster in response than the latter when drill breakage is occurred. The evaluation experiments have shown that the developed monitoring system works very well.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.04a
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• pp.216-222
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• 1992

현재의 가공 시스템에 있어서 가공 작업자체는 NC 공작기계, 머시닝 센터등에의해 자동적으로이루어 지고있으나, 작업 상태에 대한 감시 및 공구교환 시기의 결정은 주로 숙련된 작업자에 의해이루어 지고 있으므로완전 자동화, 무 인화에 큰장애가 되고 있다. 특히 공구 파손 및 공구 마멸에 대한 감시는 공구 교환 시점의 자동결정 뿐 아니라 가공 시스템의 무인 운전을 위해서 필수적인 것으로, 기계 정지 시간(down time)을 줄일 수 있고, 제품의 정밀도를 높일 수 있다. 본 연구에서는 이를 위한 기초 연구로, 가공상태를 나타내는 감시신호로 AC 주축 모터 전류와 주축대진동 신호 를 선정하여 엔드밀 공구와 드릴 공구를 이용한 작업에서의 공구 상태변화에 따른 감시신호의 성능을 조사하였다.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.5
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• pp.98-107
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• 1995

The in-process detection of drill wear and breakage is one of the most importnat technical problems in unmaned machining system. In this paper, the monitoring system is developed to monitor abnormal drilling states such as drill breakage, drill wear and unstable cutting using motor current. Drill breakage is detected by level monitoring. Tool wear is classified by fuzzy pattern recognition. The key feature for classification of tool wear is the estimated flank wear which is calculated by the proposed flank wear model. The characteristic of the model is not sensitive to the variation of cutting conditions but is sensitive to drill wear state. Unstable cutting states due to the unsmooth chip disposal and the overload are monitored by the variance/mean ratio of spindle motor current. Variance/mean ratio also includes the information about the prediction of drill wear and drill breakage. The evaluation experiments have shown that the developed system works very well.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.4
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• pp.142-151
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• 1993

An intelligent mulitiple monitoring system to monitor tool/machining states synthetically was proposed and developed. It consists of 2 fundamental subsystems : the multiple sensor detection unit and the intellignet integrated diagnosis unit. Three signals, that is, spindle motor current, Z-axis motor current, and machining sound were adopted to detect tool/machining states more reliably. Based on the multiple sensor information, the diagnosis unit judges either tool breakage or degree of tool wear state using fuzzy reasoning. Tool breakage is diagnosed by the level of spindle/z-axis motor current. Tool wear is diagnosed by both the result of fuzzy pattern recognition for motor currents and the result of pattern matching for machining sound. Fuzzy c-means algorithm was used for fuzzy pattern recognition. Experiments carried out for drill operation in the machining center have shown that the developed system monitors abnormal drill/states drilling very reliably.