• Tribology and Lubricants
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• v.18 no.4
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• pp.285-290
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• 2002

Integrated condition monitoring is required to monitor effectively the machine conditions since machine failures could not be monitored accurately by any single measurement parameter. Application of various condition monitoring techniques is therefore preferred in many cases in order to diagnosis the machine condition. However it inevitably requires lots of maintenance cost and sometimes it could be proved to over-maintenance unnecessarily. This could happen especially when one measurement parameter closely correlates to another. Therefore correlation analysis of various monitoring parameters has to be performed to improve the reliability of diagnosis. In this work, Pearson correlation coefficient was used to analyze the correlation between condition monitoring parameters of an over-loaded machine system where the vibration, wear and temperature were monitored simultaneously. The result showed that Pearson correlation coefficient could be regarded as a good measure for evaluating the availability of condition monitoring technology.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2001.11a
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• pp.252-259
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• 2001

Integrated condition monitoring is required to monitor effectively the machine conditions since machine failures could not be monitored accurately by any single measurement parameter. Application of various condition monitoring techniques is therefore preferred in many cases in order to diagnosis the machine condition. However it inevitably requires lots of maintenance cost and sometimes it could be proved to over-maintenance unnecessarily. This could happen especially when one measurement parameter closely correlates to another. Therefore correlation analysis of various monitoring parameters has to be performed to improve the reliability of diagnosis. In this work, Pearson correlation coefficient was used to analyze the correlation between condition monitoring parameters of an over-loaded machine system where the vibration, wear and temperature were monitored simultaneously. The result showed that Pearson correlation coefficient could be regarded as a good measure for evaluating the availability of condition monitoring technology.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.10 no.1
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• pp.37-43
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• 2014

Nuclear power plants(NPPs) are consisted of power production functions and safety functions preventing leakage of radiation. Operators working in NPPs shall maintain these functions during an operation period through various activities such as improvement & modification, corrective maintenance, preventive maintenance and surveillance test. According to the performance of these work activities, there are configuration changes in NPPs systems. Its changes cause the increase of safety risks(CDF) and plant trip risks. Recently, the importance of risk management is increasing gradually in the operation process of NPPs. Therefore, this paper presents the work management methods using the various risk monitoring systems during power operation and overhaul period. Also this paper suggests the optimum application ways of risk systems for work management.

• Convergence Security Journal
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• v.19 no.4
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• pp.143-150
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• 2019

Recently, As ICT technology develops, cyber attacks are becoming more intelligent and advanced. In order to cope with such cyber attacks, the security control system must be maintained 24 hours a day, 365 days a year. Security personnel should be able to respond in real time to cyber attacks through shift work for 24 hours, but the workforce law was revised in 2018 to affect manpower and security control work systems. Therefore, in this paper, we propose an effective security control work system by reducing 52 working hours per week.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.54.1-54
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• 2002

1. Introduction 2. Related Work 3. Secure Data Transmission on web-based monitoring and control System 3.1 Requirement facts with the Security for the Secure Data Transmission 3.2 Architecture for the Secure Data Transmission 4. Conclusions and Further Research

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.374-379
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• 2016

On-line process monitoring schemes are designed to give early warnings of process faults. In the artificial intelligence and machine learning fields, reliable approaches have been utilized, such as kernel-based nonlinear techniques. This work presents a kernel-based empirical monitoring scheme with a small sample problem. The measurement data of normal operations are easy to collect, whereas special events or faults data are difficult to collect. In such situations, noise filtering techniques can be helpful in enhancing the process monitoring performance. This can be achieved by the preprocessing of raw process data and eliminating unwanted variations of data. In this work, the performance of several monitoring schemes was demonstrated using three-dimensional batch process data. The results showed that the monitoring performance was improved significantly in terms of the detection success rate.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.625-631
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• 2002

In the previous study, a polishing robot system was developed to automate the polishing process and to cope with the shortage of skilled workers. This polishing robot system has several advantages: reduced time for setting polishing work, decreased labor costs, effective operation, continuous polishing work without an operator, improved machine accuracy, and the ability to polish a free curved surface die. However, still the problem remains that a worker must stay to monitor the polishing process in the poor working conditions for a long time. Nowadays some advanced manufacturing companies need to find a way to check the performance of their production equipments and plants from remote sites. Thus, this study constructed the communication network and developed the monitoring programs (a servo program and a client program) to operate the polishing robot from remote sites. Using these programs, workers are able to monitor and control the polishing robot on the web page, in any place where internet service is possible. To guarantee a stable operation in spite of a variable computer operating environment, the monitoring system is implemented in Java. The experimental results showed that the developed monitoring programs provided a stable communication.

• Nuclear Engineering and Technology
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• v.51 no.4
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• pp.1132-1141
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• 2019

Steel-concrete-steel (SCS) sandwich structures have important advantages over conventional concrete structures, however, bond-slip between the steel plate and concrete may lead to a loss of composite action, resulting in a reduction of stiffness and fatigue life of SCS sandwich structures. Due to the inaccessibility and invisibility of the interface, the interfacial performance monitoring and debonding detection using traditional measurement methods, such as relative displacement between the steel plate and core concrete, have proved challenging. In this work, two methods using piezoelectric transducers are proposed to detect the bond-slip between steel plate and core concrete during the test of the beam. The first one is acoustic emission (AE) method, which can detect the dynamic process of bond-slip. AE signals can be detected when initial micro cracks form and indicate the damage severity, types and locations. The second is electromechanical impedance (EMI) method, which can be used to evaluate the damage due to bond-slip through comparing with the reference data in static state, even if the bond-slip is invisible and suspends. In this work, the experiment is implemented to demonstrate the bond-slip monitoring using above methods. Experimental results and further analysis show the validity and unique advantage of the proposed methods.

• Safety and Health at Work
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• v.9 no.4
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• pp.479-485
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• 2018

The aim of this study is to validate an integrated air monitoring approach for assessing airborne formaldehyde (FA) in the workplace. An active sampling by silica gel impregnated with 2,4-dinitrophenylhydrazine, a passive solid phase microextraction technique using O-(2,3,4,5,6-pentafluorobenzyl)hydroxylamine as on-fiber derivatization reagent, an electrochemical direct-reading monitor, and an enzyme-based badge were evaluated and tested over a range of 0.020-5.12 ppm, using dynamically generated FA air concentrations. Simple linear regression analysis showed the four methods were suitable for evaluating airborne FA. Personal and area samplings in 12 anatomy pathology departments showed that the international occupational exposure limits in the GESTIS database were frequently exceeded. This monitoring approach would allow a fast, easy-to-use, and economical evaluation of both current work practices and eventual changes made to reduce FA vapor concentrations.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4751-4758
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• 2022

Two-phase flow may almost exist in every branch of the energy industry. For the corresponding engineering design, it is very essential and crucial to monitor flow patterns and their transitions accurately. With the high-speed development and success of deep learning based on convolutional neural network (CNN), the study of flow pattern identification recently almost focused on this methodology. Additionally, the photographing technique has attractive implementation features as well, since it is normally considerably less expensive than other techniques. The development of such a two-phase flow pattern online monitoring system is the objective of this work, which seldom studied before. The ongoing preliminary engineering design (including hardware and software) of the system are introduced. The flow pattern identification method based on CNNs and transfer learning was discussed in detail. Several potential CNN candidates such as ALexNet, VggNet16 and ResNets were introduced and compared with each other based on a flow pattern dataset. According to the results, ResNet50 is the most promising CNN network for the system owing to its high precision, fast classification and strong robustness. This work can be a reference for the online monitoring system design in the energy system.