• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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• pp.930-933
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• 2000

Experimental study was conducted for finding the characteristics of machining precision according to the change of feedrate when ball endmilling of semisphere shape. The values of tool deflection and cutting force were measured simultaneously by the systems of eddy-current sensor and dynamometer. The machining precision was analyzed by roundness values, which were deeply relating with tool deflection and forces. the roundness was decreased in down-milling than in up-milling for each feedrate. As the cutting edge is moved to radius direction on the tool path, the tool deflection and the cutting force were seemed to be decreased. As the tool path was moved downward, the values of roundness, cutting force and tool deflection were obtained better ones. When compared the values of roundness, cutting force and tool deflection for different feedrate, the best machining accuracy was obtained at feed rate of 90mm/min in down-milling.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.3
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• pp.130-143
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• 1995

This paper presents a new methodology for on-line tool breadage detection by sensor fusion of an acoustic emission (AE) sensor and a built-in force sensor. A built-in piezoelectric force sensor, instead of a tool dynamometer, was used to measure the cutting force without altering the machine tool dynamics. The sensor was inserted in the tool turret housing of an NC lathe. FEM analysis was carried out to locate the most sensitive position for the sensor. A burst of AE signal was used as a triggering signal to inspect the cutting force. A sighificant drop of cutting force was utilized to detect tool breakage. The algorithm was implemented on a DSP board for in-process tool breakage detection. Experiental works showed an excellent monitoring capability of the proposed tool breakage detection system.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.12
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• pp.78-85
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• 2002

The wavelet transform is a popular tool fer studying intermittent and localized phenomena in signals. In this study the wavelet transform of cutting force signals was conducted for the detection of a tool failure in turning process. We used the Daubechies wavelet analyzing function to detect a sudden change in cutting signal level. A preliminary stepped workpiece which had intentionally a hard condition was cut by the inserted cermet tool and a tool dynamometer obtained cutting force signals. From the results of the wavelet transform, the obtained signals were divided into approximation terms and detailed terms. At tool failure, the approximation signals were suddenly increased and the detailed signals were extremely oscillated just before tool failure.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.68-71
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• 2000

A tool holder system has been designed to measure cutting forces in diamond turning. This system includes a 3-component piezo-electric tranducer. In this research, tool holder system is modeled by considering the element dividing, material properties, and boundary conditions using MSC/PATRAN. Mode and frequency analysis of structure is simulated by MSC/NASTRAN, for the purpose of developing the effective design. In addition, tool holder system is verified by vibration test using accelerometer. This system will aid to the development of Fast Tool Servo.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.9 no.5
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• pp.1-6
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• 2010

The wavelet transform is a popular tool for studying intermittent and localized phenomena in signals. In this study the wavelet transform of cutting force signals was conducted for the detection of a tool failure in turning process. We used the Daubechies wavelet analyzing function to detect a sudden change in cutting signal level. A preliminary stepped workpiece which had intentionally a hard condition was cut by the inserted cermet tool and a tool dynamometer obtained cutting force signals. From the results of the wavelet transform, the obtained signals were divided into approximation terms and detailed terms. At tool failure, the approximation signals were suddenly increased and the detailed signals were extremely oscillated just before tool failure.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.617-618
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• 2007

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.4
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• pp.1216-1224
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• 1996

In the use of glass fiber reinforced plastics it is often necessary to cutting the components, but the cutting GFRP is often made difficult by the delamination of composites and the short tool life. In this paper, the machinability of GFRP by mean of tool materials and type was experimentally investigated. By proper selection of cutting tool material and type excellent machining of this workpiece is achieved. The surface quality relate closely with the feed rate and cutting tools.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.12
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• pp.48-55
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• 1997

A useful method to detect tool breakage suing neural network of cutting force signal is porposed and implemented in a basic cutting process. Cutting signal is gathered by tool dynamometer and normalized as a preprocessing. The cutting force signal level is continually monitored and compared with the predefined level. The neural network has been trained normalized sample data of the normal operation and cata-strophic tool failure using backpropagation learning process. The develop[ed system is verified to be very effective in real-time usage with minor modification in conventional cutting processes.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.84-87
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• 2001

The high speed machining which cam improve the production and quality has been remarkable in die/mold industry with the growth of parts and materials industries. The speed of machine tool increases, but on the other hand, the response of sensors I not being improved. Therefore, the condition monitoring techniques for the machine too, tool and workpiece in high speed machining are incomplete. In this study, characteristics of the tool edge roughness were verified from the high frequency components of cutting force signals acquired by the high speed dynamometer. Also, the experimental evaluation technique for the machinability and condition monitoring in high speed machining was established by analyzing the cutting force, acceleration and surface roughness.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.11
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• pp.93-101
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• 1997

Ever since the nonlinearity of machine tool dynamics was established, researchers attempted to make use of this fact to devise better monitoring, diagnostics and control system, which were hitherto based on linear models. Theory of chaos which explains many nonlinear phenomena comes handy for furthering the analysis using nonlinear model. In this study, measuring system will be constructed using multi-sensor (Tool Dynamometer, Acoustic Emission) in end milling process. Then, it will be verified that cutting force is low-dimensional chaos by calculating Lyapunov exponents. Fractal dimension, embedding dimension. And it will be investigated that the relation between characteristic parameter calculated from sensor signal and tool wear.