• Transactions of the Korean Society of Machine Tool Engineers
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• v.11 no.2
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• pp.103-111
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• 2002

Out of all metal-cutting process, the hole-making process is the most widely used. It is estimated to be more than 30% of the total metal-cutting process. It is therefore desirable to monitor and detect drill wear during the hole-drilling process. One important aspect in controlling the drilling process is monitoring drill wear status. There are two systems, Basic system and Online system, to detect the drill wear. Basic system comprised of spindle rotational speed, feed rates, thrust torque and flank wear measured by tool microscope. Outline system comprised of spindle rotational speed feed rates, AE signal, flank wear area measured by computer vision, On-line monitoring system does not need to stop the process to inspect drill wear. Backpropagation neural networks (BPNs) were used for on-line detection of drill wear. The output was the drill wear state which was either usable or failure. This paper deals with an on-line drill wear monitoring system to fit the detection of the abnormal tool state.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.452-455
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• 2005

The cutting characteristics of hardened steel by a PCBN tool is investigated with respect to workpiece surface roughness, cutting force and tool flank wear of the vision system. Backpropagation neural networks (BPNs) were used for detection of tool wear. The neural network consisted of three layers: input, hidden and output. The input vectors comprised of spindle rotational speed, feed rates, vision flank wear, and thrust force signals. The output was the tool wear state which was either usable or failure. Hard turning experiments with various spindle rotational speed and feed rates were carried out. The learning process was performed effectively by utilizing backpropagation. The detection of the abnormal states using BPNs achieved 96.4% reliability even when the spindle rotational speed and feedrate were changed.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.4 no.2
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• pp.38-45
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• 1995

The diagnosis and monitoring system of abnormal cutting condition is necessary to realize precision machining proces and factory automation, which are final goal of metal cutting in order to develop this system, theimage processing technique has been investigated in machining process. In theis paper, the measurement system of tool wear using computer vision is designed to detect the wear pattern by non-contact and direct method and get the realiable wear information about cutting tool. We measured the area of the side and front part of the diamond core dril which is used in 40kHz ultrasonic vibration machine.

• Journal of the korean Society of Automotive Engineers
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• v.10 no.1
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• pp.33-41
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• 1988

A turning (facing) test on Glass Fiber Reinforced Plastics was performed with several tool materials, e.g., cemented carbides, cermet and ceramic, and the wear patterns and wear rate were analyzed to clarify the relation between physical(mechanical) properties and flank wear of cutting tool. The main results are obtained as follows: (1) When cutting speed is increased, the flank wear in every tool material grows the abnormal wear in the shape of triangle at a certain speed, i.e., a critical speed. (2) When cutting speed is increased, the wear rate in experimental tool material starts to increase remarkably at a critical speed. (3) The thermal conductivity among the properties of the tool material and the thermal crack coefficient of it are almost in proportion to the critical speed. (4) The order of performance in tool materials for cutting GFRP is K 10, M10, P20, TiC, CB.

• Journal of the Korean Ceramic Society
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• v.35 no.2
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• pp.163-171
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• 1998

Continuously contacting with camshaft the face of Valve Lifter made of cast iron brings about abnormal wear such as unfairwear or earlywear because it is heavily loaded in the valve train systems as the engine gets more powered. This abnormal wear becomes a defet namely over-clearance when the valve is lifting so that the fuel gas imperfectly combusted by unsuitable open or close aaction of the engine valve in the combustion chamber. The imperfect combustion in the end results in the major cause of air pollution and combustion chamber. The imperfectly combusted by unsuitable open or close action of the engine valve in the combustion chamber. The imperfect combustion in the end results in the major causes of air pollution and decrease of the engine output. Consequently to prevent this wear this study was to develop the valve lifter which is joined by brazing process with SCM435H and a tip by manufacturing the face as a superhardened which is joined by brazing process with SCM435H and a tip by manufacturing the face as a superhardened ceramics alloy which has high wear resistance. Having the excellent surface hardness with Hv1100-1200 the sintered body developed with superhardened alloy(WC) can endure the severe face loading in the valve train system. We experienced with various brazing alloys and obtained the excellent joining strength to the joint had 150MPa shear strength. Interface analysis and microstructure in a joint were examined through SEM & EDS Optical microscope. Also 2,500 hours high speed(3,000-4,000 rpm) and continuous (1step 12hr) engine dynamo testing was carried out to casting valve liter and ceramics-metal joint valve lifter so that the abnormal wears were compared and evaluated.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.401-402
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• 2002

Diesel engines have many sliding parts with solid body contact. For example, a piston-ring and a cylinder bore, a valve and a valve-seat, a cam and a valve tappet. These parts have a severe wear problem. during engine life times. During these times, the valve tappet has abnormal wear such as scuffing and pitting due to a high hertzian contact stress between the cam and the tappet. Excessive wear problems frequently occur to both the cam and the tappet. To solve these problems, we developed an advanced wear resistant tappet. The developed tappet consisted of a hard-metal wear part and a steel body. To increase a bonding strength, those two parts, were directly bonded to each other. Also to decrease a bonding temperature, we developed the composition of Ni-binder materials in the hard metal. To estimate the wear characteristics of the newly developed tappet, we performed wear tests and engine dynamo tests in order to compare them with a conventional Fe-base tappet. As a result, the newly developed tappet has better wear characteristics than those of the conventional tappet. In addition, we performed a 100,000km field-test, and the newly developed tappet showed much improved wear resistance.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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• pp.613-616
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• 2000

This paper deals with monitoring of grinding wheel wear in surface grinding process. A laser scanning micrometer is used to measure the circumferential shape as well as the axial shape of grinding wheel. The monitoring system is applied to two kinds of grinding methods: plunge and traverse grinding. Through experiments, it is found that measurement of grinding wheel wear reveals information of roughness of ground surface and the adequate dressing time. In addition, monitoring of grinding wheel wear makes it possible to identify abnormal grinding conditions.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.3
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• pp.14-17
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• 2006

To diagnosis abnormal compressor conditions in an air-conditioner, the acoustic emission (AE) signal, which is derived from wear condition, compressed air, and assembly error, was analyzed experimentally. Burst and continuous type AE signals resulted from metal contact and compressed air, and the raw AE signal of compressors was acquired in the production line. After extracting samples using waveforms, the Early Life Test (ELT) was conducted and the waveform was classified as normal or abnormal. Efficient parameters in the waveform pattern were investigated in time and frequency domains and a diagnosis algorithm for air-conditioners using Neural Network estimation is suggested.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.11
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• pp.125-129
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• 2004

For the diagnosis of compressor abnormal condition in air-conditioner, AE signal which is derived from wear condition, compressed air and assembly error is analyzed experimentally. The burst and continuous type AE signal occurred by metal contact and compressed air and AE raw signal of compressors were directly acquired in production line. After extracting samples according to waveforms, Early Life Test(ELT) is conducted and classified to normal and abnormal waveform. The efficient parameters of waveform pattern are investigated in time and frequency domain and the diagnosis algorithm of air-conditioner by Neural Network estimation is suggested.

• Journal of Korea Foundry Society
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• v.14 no.6
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• pp.548-557
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• 1994

Grey iron containing a small amount of Cu and Mo to improve the effect of heat treatment and microstructures were poured in to the mold and them austenized at $900^{\circ}C$. After austenitizing the specimens of castings were austempered $210^{\circ}C$, $250^{\circ}C$, $300^{\circ}C$ and $350^{\circ}C$. The effects of matrix structures, mechanical properties and wear characteristics were investigated by austempering temperatures. Tensile strength and hardness of austempered grey iron are increased and the amount of retained austenite is decreased as austempering temperature is lower even though the amount of retained autenite in it only 4%. The amount of rolling wear loss are increased as rolling revolution is increased and wear loss of austempered grey iron under dry rolling condition is characterized by three models; initial wear, stationary wear and abnormal wear. It has been found that the amount of wear loss was increased with increasing maxium compressive stress and rolling revolution.