• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.14-19
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• 2000

A machine tool has some serous stability problem in the from of tool chatter during the cutting process. Chatter vibration deteriorates the surface finish, reduce tool and machine life, accelerate machine tool system component wear, and may lead to an unacceptable noise sound in the working environment. In this study, in order to moni색 of the chatter vibration on the cutting process, the behavior of spectral density of AE signal and principal cutting force signal has been investigated. Furthermore, its reliability from obtained the results has been studied to evaluate and confirm the proposed method with the application procedure and the experimental results.

• Journal of Ocean Engineering and Technology
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• v.13 no.1 s.31
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• pp.88-93
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• 1999

This paper presents the experimental examinations and statistical quantitative analysis of the correlation between the cumulative counts of acoustic emission(AE) during plastic deformation periods of the welding and the tensile strength and other properties of the bar-to-bar welded joints of O.D. 16mm shaft(SM40C) as well as the various welding variables. And this is a new approach which attempts finally to develop real-time quality monitoring system for friction welding. The results lead to a practical possibility of real-time quality control more than 100% joint efficiency showing good weld with no micro structural defects.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.1
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• pp.7-13
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• 2003

A hot press method was use for the optimal manufacturing condition for a shape memory alloy(SMA) composite. The bonding between the matrix and the reinforcement within the SMA composite by the hot press method was strengthened by cold rolling. In this study, the objective was to develop an on-line monitoring system for the prevention of the crack initiation and propagation by shape memory effort of SMA composite. Shape memory effect was used to prevent the SMA composite from cracking. For the system to be developed, an optimal hE parameter should be determined based on the degree of damage and crack initiation. When the SHA composite was heated by the plate heater attached at the composite, the propagating cracks appeared to be controlled by the compressive force of SMA.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.1
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• pp.77-85
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• 2008

The objective of the study is to construct a sensor fusion system for tool-condition monitoring (TCM) that will lead to a more efficient and economical drill usage. Drill-wear monitoring has an important attribute in the automatic machining processes as it can help preventing the damage of tools and workpieces, and optimizing the drill usage. In this study, we present the architectures of a multi-layer feed-forward neural network with Levenberg-Marquardt training algorithm based on sensor fusion for the monitoring of drill-wear condition. The input features to the neural networks were extracted from AE, vibration and current signals using the wavelet packet transform (WPT) analysis. Training and testing were performed at a moderate range of cutting conditions in the dry drilling of steel plates. The results show good performance in drill- wear monitoring by the proposed method of sensor fusion and neural network analysis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.4
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• pp.803-808
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• 2000

This paper presents development of a different substance monitoring system base reliable detection between the conveyer belt and hopper used for materials transport line of steel company. Conventional detection method of a piece of iron separation system is losed the confidence, because of the place with bad surroundings of measurement so much that materials production line are completely exposed to dust, moisture and vibration. For the solution of this problem, we developed a different substance detection system using the acoustic emittion sensor and one chip microprocessor which is available for bad surroundings and inexpensive. The reliability of the system was estimated by experiment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.741-742
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• 2010

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.3 no.3
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• pp.24-31
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• 2004

A successful on-line monitoring system for conventional machining operations has the potential to reduce cost, guarantee consistency of product quality, improve productivity and provide a safer environment for the operator. In fine-shape machining, typical signs of tool problems such as vibration, noise, chip flow characteristics and visual signs are almost unnoticeable without the use of special equipment. These characteristics increase the importance of automatic monitoring in fine-shape machining, however, sensing and interpretation of signals ar more complex. In addition, the shafts of the mini-tools break before the typical extensive cutting edge of the tool gets damaged. In this study, the existence of a relationship between the characteristics of the cutting force and tool usage was investigated, and tool breakage detection algorithm by LabVIEW was developed and the following results are obtained. It was possible to use a relative error compare which mainly used in established experiment and investigated tool breakage detection algorithm in time domain which can detect AE and cutting force signals more effective and accurate.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.3
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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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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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.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.6
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• pp.509-519
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• 2007

This paper presents new techniques under development for monitoring the health and vibration of the active components in nuclear power plants, The purpose of this study is to develop an automated system for condition classification of a check valve one of the components being used extensively in a safety system of a nuclear power plant. Acoustic emission testing for a check valve under controlled flow loop conditions was performed to detect and evaluate disc movement for valve failure such as wear and leakage due to foreign object interference in a check valve, It is clearly demonstrated that the evaluation of different types of failure types such as disc wear and check valve leakage were successful by systematically analyzing the characteristics of various AE parameters, It is also shown that the leak size can be determined with an artificial neural network.