• 한국공작기계학회논문집
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• 제10권1호
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• pp.1-9
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• 2001

The development of flexible automation in the manufacturing industry is concerned with production activities performed by unmanned machining system A major topic relevant to metal-cutting operations is monitoring toll wear, which affects process efficiency and product quality, and implementing automatic toll replacements. In this paper, the measurement of the cutting force components has been found to provide a method for an in-process detection of tool wear. The static com-ponents of cutting force have been used to detect flank wear. To eliminate the influence of variations in cutting conditions, tools, and workpiece materials, the force modeling is performed for various cutting conditions. The normalized force dis-parities are defined in this paper, and the relationships between normalized disparity and flank were are established. Final-ly, artificial neural network is used to learn these relationships and detect tool wear. According to proposed method, the static force components could provide the effective means to detect flank wear for varying cutting conditions in turning operation.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2009년도 춘계학술대회 논문집
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• pp.1059-1060
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• 2009

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.89-94
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• 1995

A16061, SB41 and SM45C was used for developing tool wear monitoring system in face milling. First of all, Neural networks of which input are 8 $_{th}$ order AR morel parameters, frequency band energies, cutting conditions was used to monitor tool wear for each material. Finally, A unified neural network, which has tensile strengths of each material as an additional input, was constructed to consider the effect three materials on the features of tool wear. It was verified that tensile strength is the one of properties of workpiece materials.s.

• 한국정밀공학회지
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• 제12권3호
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• pp.5-14
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• 1995

In recent years, the automization of cutting machine tools has been developed very fast. Hance, the in-process detection of cutting condition is very important for automatic manufacturing system in factory. Acoustic Emission(AE) has been widely used in monitoring the cutting conditions, because of high sensitivity of AE signal and low cost of AE equipment. This experimental study deals with the relations between AE signal, cutting force charcteristics and tool wear in the machining of SUS304. Face milling operation is used for the analysis between tool wear and AE signal.

• 한국정밀공학회지
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• 제16권9호
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• pp.62-67
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• 1999

In milling, cutting tool ins directly attached to spindle and this tells that spindle can provide very useful information on the cutting tool condition such as wear or breakage. Since spindle is rotating at a high speed, measuring spindle velocity using a noncontacting measurement system gives the best information which can be obtained. Due to the force applied to spindle through cutting tool, velocity of spindle changes. And any change in cutting tool condition affects cutting force and consequently spindle vibration. With the intent of continuously monitoring cutting tool condition in intermittent machining operations in a benign manner, a noncontacting velocity measurement system using a laser Doppler velocimeter was assembled to measure spindle torsional vibration. Spindle vibration was measured and analysis of it in the frequency domain yielded a measure which corresponded to amount of cutting tool wear in milling.

• 한국공작기계학회논문집
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• 제12권3호
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• pp.8-16
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• 2003

Monitoring of the drill wear :md hole quality change is conducted during the drilling process. Cutting force measured by tool dynamometer is a evident feature estimating abnormal state of drilling. One major difficulty in using tool dynamometer is that the work-piece must be mounted on the dynamometer, and thus the machining process is disturbed and discontinuous. Acoustic transducer do not disturb the normal machining process and provide a relatively easy way to monitor a machining process for industrial application. for this advantage, AE signal is used to estimate the abnormal fate. In this study vision system is used to detect flank wear tendency and hole quality, there are many formal factors in hole quality decision circularity, cylindricity, straightness, and so of but these are difficult to measure in on-line monitoring. The movement of hole center and increasement of hole diameter is presented to determine hole quality. As the results of this experiment AE RMS signal and measurements by vision system are shorn the similar tendency as abnormal state of drilling.

• 한국정밀공학회지
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• 제7권3호
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• pp.75-82
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• 1990

Automatic monitoring of the cutting conditions is one of the most improtant technologies in machining. In this study, the feasibility in applying acoustic emission(AE) signals for the in-process detection of endmill wear and fracture has been investigated by performing experimental test on the NC vertical milling machine with SM45C for specimen. As the results of detecting and analyzing AE signals on various cutting conditions, the followings have confirmed. (1) The RMS value of acoustic emission is related sensitively to the cutting velocity, but is not affected largely by feed rate. (2) The burst type AE signals of high level have been observed when removing chips distorderly and discontinuously. (3) When the RMS value grows up rapidly due to the increase of wear the endmill are generally broken or fractured, but when the endmills fracture at the conditions of smooth chip-flow or built-up-edge(BUE) occurred frequently, the rapid change of the RMS arenot found. And it is expected that this technigue will be quite useful for in-process sensing of tool wear and fracture.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.1038-1042
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• 2002

Monitoring of the drill wear and hole quality change is conducted during the drilling process. Cutting force measured by tool dynamometer is a evident feature estimating abnormal state of drilling. One major difficulty in using tool dynamometer is that the work piece must be mounted on the dynamometer, and thus the machining process is disturbed and discontinuous. Acoustic transducer do not disturb the normal machining process, and provide a relatively easy way to monitor a machining process for industrial application. For this advantage, AE signal is used to estimate the abnormal state. In this study vision system is used to detect flank wear tendency and hole quality, there are many formal factors in hole quality decision circularity, cylindricity, straightness, and so on, but these are difficult to measure in on-line monitoring. The movement of hole center and increasement of hole diameter is presented to determine hole quality As the results of this experiment, AE RMS signal and measurements by vision system are shown the similar tendency as abnormal state of drilling. And detection of the abnormal states using BPNs was achieved 96.4% reliability.

• Tribology and Lubricants
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• 제11권5호
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• pp.40-46
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• 1995

This study concerns the design and development of the non-vibrating capacitance probe which could be used as a non-contact sensor for tribological wear. This device detects surface charge through temporal variation in the work function of a material. Experiments are performed to demonstrate the operation of the probe on a roating aluminum shaft. The reference electrode of the probe, made of lead, is placed adjacent (< 1.25-mm distance) to the shaft. Both surfaces which are electrically connected, form a capacitor. An artificial spatial variation in the work function is imposed on the shaft surface by coating a segment along the shaft circumference with a colloidal silver paint. As the shaft rotates, the reference electode senses changing contact potential difference with the shaft surface, owing to compositional variation. Temporal variation in the contact potential difference induces a current through the electrical connection. This current is amplified and converted to a voltage signal by an electoronic circuit with an operational amplifier. The magnitude of the signal decreases asymptotically with the electrode-shaft distance and increases linearly with the rotational frequency. These results are consistent with the theoretical model. Potential applications of the probe on wear monitoring are proposed.

• 한국정밀공학회지
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• 제10권4호
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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.