• 한국정밀공학회지
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• 제15권5호
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• pp.100-109
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• 1998

In order to increase productivity through unmanned machining in CNC milling process, in-process tool fracture detection is required. In this paper, a new algorithm for tool fracture detection using cutting load variations was developed. For this purpose, developed were tool condition vector which is dimensionless indicator of cutting load and tool fracture index (TFI) which represents magnitude of tool fracture. Through cutting force simulation, tool fracture index was shown to be independent of tool run-outs and cutting condition variations. Using tool fracture index, the ratio of the tool fracture to feed per tooth could be indentified.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권12호
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• pp.5073-5086
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• 2015

The rock fracture detection by image analysis is significant for fracture measurement and assessment engineering. The paper proposes a novel image segmentation algorithm for the centerline tracing of a rock fracture based on Hessian Matrix at Multi-scales and Steger algorithm. A traditional fracture detection method, which does edge detection first, then makes image binarization, and finally performs noise removal and fracture gap linking, is difficult for images of rough rock surfaces. To overcome the problem, the new algorithm extracts the centerlines directly from a gray level image. It includes three steps: (1) Hessian Matrix and Frangi filter are adopted to enhance the curvilinear structures, then after image binarization, the spurious-fractures and noise are removed by synthesizing the area, circularity and rectangularity; (2) On the binary image, Steger algorithm is used to detect fracture centerline points, then the centerline points or segments are linked according to the gap distance and the angle differences; and (3) Based on the above centerline detection roughly, the centerline points are searched in the original image in a local window along the direction perpendicular to the normal of the centerline, then these points are linked. A number of rock fracture images have been tested, and the testing results show that compared to other traditional algorithms, the proposed algorithm can extract rock fracture centerlines accurately.

• 한국정밀공학회지
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• 제15권8호
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• pp.116-125
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• 1998

In this paper, main target is to select parameters for prediction of tool wear and detection of tool fracture. The research about choosing parameter for prediction of tool wear is done by using force ratios. Also current sensor, tool-dynamometer, and accelerometer are used for researching detection method of tool fracture. Experiment is done using Taguchi's method in medium machining conditions. Parameter which is best for prediction of tool wear and detection of tool fracture by deviation analysis is selected. In this paper, tool wear means flank wear.

• 한국재료학회:학술대회논문집
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• 한국재료학회 2007년도 추계학술발표대회 및
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• pp.104.2-104.2
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• 2007

• 오토저널
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• 제8권3호
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• pp.28-36
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• 1986

This study was investigated the feasibility of AE application on in-process detection of tool fracture and chipping. Carbon steel SM45C workpiece with longitudinal slots was turned interruptedly on a lathe. AE RMS signal at tool fracture was observed and also the tangential force and the feed observed at the time of tool fracture, the levels of tangential force and the feed force at the time of fracture decrease considerably. In chipping, high level AE signal was observed but there were no changes of cutting force. Peak AE RMS squared is proportional to the area of tool fracture and resultant force. Fracture model of tool fracture is proposed as $V_{p}$ = $C_{1}$ $E_{1}$F(.DELTA. A)$_{0.5}$ and peak AE RMS shows strong correlation with the fracture parameter F(.DELTA.A)$^{0.5}$.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 춘계학술대회 논문집
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• pp.881-888
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• 1997

A new algorithm for detection of tool fracture in milling process was developed. The variation of the peak-to-valley value of cutting load was used in this algorithm. Various kinds of vectors representing the condition of tool, such as tool condition vector, reference tool condition vector, tool condition variation vector were defined. Using these vectors, tool fracture index which represents the magnitude of tool fracture and is independent of tool run-outs is developed. Small and large tool fracture and chipping under various cutting condition could be detected using proposed tool fracture index, which was proved with cutting force model and experiments.

• 대한기계학회논문집
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• 제16권4호
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• pp.707-722
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• 1992

본 연구에서는 공구의 큰 파손에서 부터 공구의 기하학적 형태가 크게 변하지 않는 작은 파손등 파손의 크기와 파손부위에 따른 신호의 형태를 조사하고자 한다. 그 방법으로서 가공재료로서는 SM45C강(steel)과 열처리한 SM45C강을 이용하였다. 공구파손에 따른 AE신호와 절삭력신호의 변화를 분석하기 위하여, AE신호의 경우는 RMS값을 택하고 그 진폭의 갑작스런 변화와 평균 레벨의 변화를 이용하여 파손의 순간 을 감지하였고, 절삭력의 경우에는 절삭력의 주분력, 이송분력 그리고 배분력의 변화 형태를 이용하여 공구의 이상상태를 알 수 있었으며, 이 두 신호의 변화를 동시에 관 찰함으로써 임의의 가공조건에서 공구의 파손을 감지할 수 있는 알고리즘 개발의 기준 을 마련할 수 있었다.

• 한국정밀공학회지
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• 제15권5호
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• pp.110-119
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• 1998

Dynamic cutting force variations in milling process were measured indirectly using spindle motor current. Magnitude of the spindle motor current is independent of cutting direction. Quasi-static sensitivity of the spindle motor current is higher than that of the feed motor current. Dynamic sensitivity of the spindle motor current is lower but cutting force was correctly represented by spindle RMS current in rough milling. In rough milling, chipping and tool fracture were well detected by the proposed tool fracture index using spindle motor current.

• 한국정밀공학회지
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• 제12권4호
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• pp.67-77
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• 1995

In modern industry the requirement of automation of manufacturing process increases so that unmanned system has been popular as an ultimate goal of modern manufacturing process. In unmanned manufacturing process the tool fracture is a very serious problem because it results in the damage of workpieces and can stop the operation of whole manufa- turing system. In this study, image processing technique is used to detect the fracture of insert tip of face milling using multi-point-tool. In order to acquire the image information of fracture shape of rotation insert tip. We set up the optical system using a light beam chopper. In this system we can reduce the image degradation generated from stopped image of rotating insert tip using image restoration technique. We calculated the mean square error to diagnose the condition of tool fracture, and determind the criteria of tool fracture using experimental and staticstical method. From the results of this study we've developed non- contact detection technique of tool fracture using image processing method and proposed the fracture direction of automation and unmanned system considering the optimal time of tool change milling.

• 한국정밀공학회지
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• 제28권11호
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• pp.1330-1338
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• 2011

Social activities of the elderly have been increasing as our society progresses toward an aging society. As their activities increase, so does the occurrence of falls that could lead to fractures. Falls are serious health hazards to the elderly. Therefore, development of a device that can detect fall accidents and prevent fracture is essential. In this study, we developed a portable fall detection system for the fracture prevention system of the elderly. The device is intended to detect a fall and activate a second device such as an air bag deployment system that can prevent fracture. The fall detection device contains a 3-axis acceleration sensor and two 2-axis tilt sensors. We measured acceleration and tilt angle of body during fall and activities of daily(ADL) living using the fall detection device that is attached on the subjects'. Moving mattress which is actuated by a pneumatic system was used in fall experiments and it could provide forced falls. Sensor data during fall and ADL were sent to computer and filtered with low-pass filter. The developed fall detection device was successful in detecting a fall about 0.1 second before a severe impact to occur and detecting the direction of the fall to provide enough time and information for the fracture preventive device to be activated. The fall detection device was also able to differentiate fall from ADL such as walking, sitting down, standing up, lying down, and running.