• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.152-154
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• 2005

This paper proposes new methods which are used for trouble detecting and tolerance of IED in IEC61850 based Substation Automation System. There are three point devices for construction of this system: Trouble Detection IED, Backup IED and Engineering Unit. Trouble Detection IED tests trouble of Bay IED and sends the result to Engineering Unit. And then Engineering Unit is able to control the system. When fault occurs in Bay IED, Backup IED will be substitute the troubled Bay IED. If this proposed scheme can be used in this system, the reliability of the Power System would be greatly improved.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.131-137
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• 1994

Detection of grinding trouble occuring during the grinding process is classified into two types, i.e, based on the quantitative and qualitative knowledge. But, since the grinding operation is especially related with a large amount of functional parameters, it is actually defficult to cope with the grinding troubles occuring during process. Therefore, grinding trouble-shooting has difficulty in satisfying the requirement from the user. To cope with the grinding troubles occuring during the process, the application of neural network is on effective way. In this study, we identify the four parameters derived from the AE(Acoustic Emission) signals and present the grinding trouble-shooting system utilizing a back-propagation model of the neural network.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.8
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• pp.351-356
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• 2014

Typical trouble patterns in solar thermal systems include working fluid leakage and freezing other than breakdown of pump. A fluid sensor for measuring electric resistance of fluid was developed and installed at the top of the collector piping in order to check the fault of solar system. Working fluid level in the pipe was determined by measuring electric resistance from a fluid sensor. On the base of this, it was confirmed that the fluid sensor diagnoses leakage of fluid. Electric resistance of propylene glycol aqueous solution was measured in the range of $0{\sim}70^{\circ}C$ and 0~40% of concentration. The response surface analysis was performed by using a central composite design, and the regression equation was derived from the relationship between electric resistance, temperature, and concentration. Through the experiment in a real solar system, we can estimate a concentration of working fluid when a pump is not operating and predict a possibility of freezing. Finally, an effective algorithm for trouble shooting was proposed to operate and maintain the solar system.

• Transactions of the Korean Society of Mechanical Engineers
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• v.11 no.6
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• pp.1014-1025
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• 1987

This paper proposes an approach of building an expert system for designing gear drives. In terms of gear drives the relationship between expert systems and data base systems is explained and a data base system for design, failure detection, and trouble-shooting of gear drives is built on a personal computer by the data manipulation language of dBASE III. This paper proposes a method how to build a data base system and what to consider to build a data base system for gear drives and two kinds of data base systems of design and failure detection of gear drives and trouble-shooting for noise and vibration of gear drives are built. The two data base systems are very effective for the retrieval of information for the gear design, and they will be considerably helpful for the gear design.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.11a
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• pp.575-578
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• 2003

Recently, because GIS equipment has problems on confidence according to long-time usage, development of diagnosis technique has been importantly recognized. Therefore. measurement and analysis of PD has been generally used much equipment of GIS. But, in case of measurement of PD at field, real trouble signals are difficult to classify noise. Accordingly, a variety of trouble conditions for DS were simulated, and detected signals were analyzed by the application of electrical and mechanical methods. For this analysis, detected signals were accumulated according to phase-magnitude with the application of Induction sensor, and then we analyzed the characteristics. For the simulation experiment, we made DS for 170kV GIS and analyzed the characteristics of detected singals with the application of neural network algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.11
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• pp.57-63
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• 1996

Monitoring of grinding troble occurring during the process is classified into the quantitative data which depends upon a sensor and the qualitative knowledge which relies upon an empirical knowledge. Since grinding operation is highly related with a large amount of functional parameters, it is actually deficulty in copying wiht the grinding troubles through the process. To cope with grinding trouble, it is an effective monitoring systems when occurring the grinding process. The use of neural networks is an effective method of detection and/or monitroing on the grinding trouble. In this paper, four parameters which are derived from the AE(Acoustic Emission) signatures are identified, and grinding monitoring system utilized a back propagation learning algorithm of PDP neural networks is presented.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.05d
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• pp.29-32
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• 2003

Recently, the development of diagnosis technique with high confidence is important on power equipment, for this reason is to use for measurement and analysis of PD with prior appearance of insulation breakdown In this paper, we presents the analysis of trouble signal to use both method of general analysis of $\Phi$-Q-N in PD and statistical parameter by this interpretation Equipment of simulation has made independently DS for 170kV GIS of one phase with same on field. The detected signal through the sensor of Induction and Acoustic Emission is classified which used to characteristic neural network algorithm and then it is analysis.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.20-27
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• 2000

A chatter vibration and a workpiece burn are the main phenomena to be monitored in modern grinding processes. This study describes a trouble diagnosis of the cylindrical plunge grinding process using the power and acoustic emission (AE) signals. The raw signals of the power and the AE occurred during the grinding operation were sampled and analyzed to determine the relationship between each fault and change of signals. A neural network that has a high success rate of the fault detection was used. Furthermore, an analysis on the influence of parameters to the chatter vibration and the grinding burn was conducted.

• Corrosion Science and Technology
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• v.10 no.4
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• pp.151-155
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• 2011

The iron oxide particles could be resulted from the corrosion of the circulating water system of a power plant. Because it may be one of the trouble materials which affect the power generation efficiency due to the deposition on steam generator tube and turbine blade, the continuous observation of its concentration is very important. The laser induced break-down detection (LIBD) technology was applied to monitor continuously the concentration of corrosion products with the detection limit of ppb level. The measurement system consists of a Nd:YAG pulsed laser, a polarizing beam splitter, a flow-type sample cell, an acoustic emission sensor, a high speed data acquisition board, a personal computer, etc.. The performance test results confirmed that this technology can be effective to monitor the corrosion product concentration of the circulating water system of a power plant.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.1A
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• pp.1-6
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• 2008

TDM-PON has a disadvantage that entire PON system gets into trouble when only one ONU is out of order and sends optical signal constantly. This paper suggests a scheme to find the fault location. TDMA is impossible when upstream traffic is interrupted by continuous wave signal from a troubled ONU. Therefore, CDMA coding is introduced in separating fault ONUs, and detection algorithm is verified.