• Tribology and Lubricants
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• v.28 no.3
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• pp.130-135
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• 2012

This study presents a new methodology for realtime tool breakage detection by sensor fusion concept of two hall sensor and an acoustic emission (AE) sensor. Spindle induction motor torque of CNC Lathe during machining is estimated by two hall sensor. Estimated motor torque instead of a tool dynamometer was used to measure the cutting torque and tool breakage detection. A burst of AE signal was used as a triggering signal to inspect the cutting torque. A significant drop of cutting torque was utilized to detect tool breakage. The algorithm was implemented on a NI DAQ (Data Acquisition) board for in-process tool breakage detection. The result of experiment showed an excellent monitoring capability of the proposed tool breakage detection system. This system is available tool breakage monitoring through internet also provides this system's user with current cutting torque of induction motor.

• Transactions of the Korean Society of Mechanical Engineers
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• v.9 no.6
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• pp.757-766
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• 1985

Both in-process quality control and high reliability of the weld is one of the major concerns in applying friction welding to the economical and qualified mass-production. No reliable nondestructive monitoring method is available at present to determine the real-time evaluation of automatic production quality control for friction welding machine. This paper, so that, presents the experimental examinations and statistical quantitative analysis of the correlation between the initial cumulative counts of acoustic emission(AE) occurring during plastic deformation period of the welding and the tensile strength of the welded joints as well as the various welding variables, as a new approach which attempts finally to develop an on-line (or real-time) quality monitoring system and a program for the process of real-time friction welding quality evaluation by initial AE cumulative counts. As one of the important results, it was well confirmed that the initial AE cumulative counts were quantitatively and cubically correlated with reliability of 95% confidence level to the joint strength of the welds, bar-to-bar (SCM4 to SUM31, SCM4 to SUM24L) and that an AE technique using initial AE counts can be reliably applied to real-time strength evaluation of the welded joints, and that such a program of the system was well developed resulting in practical possibility of real-time quality control more than 100% joint efficiency showing good weld with no micro-structural defects.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.695-696
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• 2010

• Journal of the Korean Society for Precision Engineering
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• v.12 no.3
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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.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.67-71
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• 2003

A hot press method was used to create the optimal fabrication condition for a Shape Memory Alloy(SMA) composite. The bonding strength between the matrix and the reinforcement within the SMA composite by the hot press method was more increased by cold rolling. In this study, the objective was to develop an on-line monitoring system in order to prevent the crack initiation and propagation by shape memory effect in SMA composite. Shape memory effect was used to prevent the SMA composite from crack propagation. For this system an optimal AE parameter should be determined according to the degree of damage and crack initiation. When the SMA composite was heated by the plate heater attached at the composite, the propagating cracks could be controlled by the compressive force of SMA.

• 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.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.5
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• pp.118-123
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• 2004

The compressor has one of important roles in refrigeration cycle and it determines refrigeration efficiency and quality This paper aims to monitor rotary compressors for room air conditioners by using Acoustic Emission(AE) technique. The reliability of rotary compressors has been evaluated through visual inspection on them after long term test. This paper describes methods for acquisition and processing AE raw signal to monitor the state of rotary compressor. A detecting method of abnormal compressor in real time is suggested and special-purpose monitoring system which can be applied to automatic manufacturing line is developed using one-chip microprocessor at low cost.

• IEMEK Journal of Embedded Systems and Applications
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• v.5 no.2
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• pp.46-56
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• 2010

This study proposes a monitoring system by cooperating the image information and the sensor information in a sensor network system. The monitoring system proposed in this study is divided into internal spaces, such as offices and laboratories, and external spaces including other various spaces. In the internal spaces, motions in objects are detected through cameras while some peripherals like lights are controlled by analyzing some temperature, humidity, and illuminance data detected by sensor nodes. In the external spaces, it is to watch certain intruders to the internal spaces through the interested region for exceptional time by installing cameras, motion detectors, and body detectors in such interested regions. In the results of the test that was applied to a practically limited environment by implementing some interfaces for the proposed system, it was considered that it is possible to watch surroundings effectively using the image information obtained from cameras and sensor information acquisited from sensor nodes.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.26-33
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• 1999

Automatic monitoring of cutting process is one of the most important technologies for increasing the stability and the reliability of unmanned manufacturing system. In this study, basic methods which use the acoustic emission (AE) signals and cutting forces were proposed to monitor flank wear (width of flank wear) quantiatively. First, in order to detect flank wear, it was investigated that the influence of cutting conditions, that is, cutting velocity, feed and depth of cut, on AE signals (${AE_rms}$) and cutting forces. Furthermore, the relation between flank wear and the measured signals (${AE_rms}$, cutting force) was discussed.

• Journal of Ocean Engineering and Technology
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• v.9 no.1
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• pp.47-56
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• 1995

This study is aimed to have a database of system development for the prediction, monitoring, analyzing, and evaluation of tensile strength and damage characteristics through AE technique for CFRP. Therefore the correlations between impact characteristics (such as impact velocity, impact energy, delamination area etc) and AE signals for CFRP laminates were investigated. And also it were accomplished the evaluation of tensile strength and the investigation on correlation with AE signals for impact damaged specimen of CFRP laminates.