• Journal of the Korean Society of Environmental Restoration Technology
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• v.11 no.4
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• pp.1-11
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• 2008

This paper analyzed the status of contaminated soils in order to manage it efficiently in Incheon using Geographic Information System (GIS) and investigated the concepts and techniques of the GIS and interpolation method. GIS technique is applied to the analysis of soil quality monitoring data. The purposes of this research are to assess the soil contamination of Incheon metropolitan area and to analyze the existing contents of heavy metals (Cd, Cu, As, Hg, Pb, $Cr^{+6}$) and pH in soil. The samples had been collected from year 1998 to year 2002 by the Soil Contamination Monitoring Network. The soil quality monitoring results were imported with the geographical information of the monitoring programs in capital area. It is found that currently available GIS technique has a great extend of potential for soil quality management. From the analysis of soil quality monitoring results, the GIS application demonstrates the poor soil quality in the central capital area and the it is improved as it travels down to the suburb area. Concerning about the data interpolation, the discrepancy caused by applying different method was ignorable, although Kriging method is further developed.

• Nuclear Engineering and Technology
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• v.47 no.5
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• pp.624-632
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• 2015

A self-diagnostic monitoring system is a system that has the ability to measure various physical quantities such as temperature, pressure, or acceleration from sensors scattered over a mechanical system such as a power plant, in order to monitor its various states, and to make a decision about its health status. We have developed a self-diagnostic monitoring system for an air-operated valve system to be used in a nuclear power plant. In this study, we have tried to improve the self-diagnostic monitoring system to increase its reliability. We have implemented three different machine learning algorithms, i.e., logistic regression, an artificial neural network, and a support vector machine. After each algorithm performs the decision process independently, the decision-making module collects these individual decisions and makes a final decision using a majority vote scheme. With this, we performed some simulations and presented some of its results. The contribution of this study is that, by employing more robust and stable algorithms, each of the algorithms performs the recognition task more accurately. Moreover, by integrating these results and employing the majority vote scheme, we can make a definite decision, which makes the self-diagnostic monitoring system more reliable.

• Smart Structures and Systems
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• v.12 no.3_4
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• pp.465-482
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• 2013

Recently, a novel stress sensor, which utilizes the elasto-magnetic (EM) effect of ferromagnetic materials, has been developed to measure stress in steel cables and wires. In this study, the effectiveness of this EM based stress sensors for monitoring of the cable tension force of a real scale cable-stayed bridge was investigated. Two EM stress sensors were installed on two selected multi-strand cables in Hwa-Myung Bridge, Busan, South Korea. Conventional lift-off test was conducted to obtain reference cable tension forces of two test cables. The reference forces were used to calibrate and validate cable tension force measurements from the EM sensors. Tension force variations of two test cables during the second tensioning work on Hwa-Myung Bridge were monitored using the EM sensors. Numerical simulations were conducted to compare and verify the monitoring results. Based on the results, the effectiveness of EM sensors for accurate field monitoring of the cable tension force of cable-stayed bridge is discussed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.230-235
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• 1997

During laser welding, a laser induced matal vapour and plasuma is formed. The plasma shows strong fluctuation combined with acoustic sound emission. On-line monitoring of the process is possible by measuring and analysing the plasma and acoustic sound emission. This paper introduce the method of on line process monitoring in the laser beam welding and analysis being monitoring signal. The results show the complementary information on the process.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.2002-2007
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• 2010

The objective of this study is the developement monitoring measurement using global positioning digital datalogger system for monitoring measurement of railway construction sites. For the replacement of current passive data communication, Global positioning digital datalogger system using active communication is studied for the first time with in a country. Therefore data communication method and analyzing program of automatic measurement data is developed for the global positioning automatic digital datalogger system. The results of this study will be using real time automatic monitoring measurement of railway structures.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2012.06a
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• pp.119-120
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• 2012

In the various industry plant, it need a condition monitoring system for an active machine that used an detachable wireless sensors. In this paper, IEEE802.15.4 standard based detachable wireless sensor monitoring system configure results will be introduced.

• Structural Monitoring and Maintenance
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• v.1 no.3
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• pp.249-271
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• 2014

This paper presents a unique study of Structural Health Monitoring (SHM) for the maintenance decision making about a real life movable bridge. The mechanical components of movable bridges are maintained on a scheduled basis. However, it is desired to have a condition-based maintenance by taking advantage of SHM. The main objective is to track the operation of a gearbox and a rack-pinion/open gear assembly, which are critical parts of bascule type movable bridges. Maintenance needs that may lead to major damage to these components needs to be identified and diagnosed timely since an early detection of faults may help avoid unexpected bridge closures or costly repairs. The fault prediction of the gearbox and rack-pinion/open gear is carried out using two types of Artificial Neural Networks (ANNs): 1) Multi-Layer Perceptron Neural Networks (MLP-NNs) and 2) Fuzzy Neural Networks (FNNs). Monitoring data is collected during regular opening and closing of the bridge as well as during artificially induced reversible damage conditions. Several statistical parameters are extracted from the time-domain vibration signals as characteristic features to be fed to the ANNs for constructing the MLP-NNs and FNNs independently. The required training and testing sets are obtained by processing the acceleration data for both damaged and undamaged condition of the aforementioned mechanical components. The performances of the developed ANNs are first evaluated using unseen test sets. Second, the selected networks are used for long-term condition evaluation of the rack-pinion/open gear of the movable bridge. It is shown that the vibration monitoring data with selected statistical parameters and particular network architectures give successful results to predict the undamaged and damaged condition of the bridge. It is also observed that the MLP-NNs performed better than the FNNs in the presented case. The successful results indicate that ANNs are promising tools for maintenance monitoring of movable bridge components and it is also shown that the ANN results can be employed in simple approach for day-to-day operation and maintenance of movable bridges.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.4
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• pp.169-176
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• 2000

Longitudinal and lateral forces acting on tires are known to be closely related to the tract-ability braking characteristics handling stability and maneuverability of ground vehicles. In thie paper in order to develop tire force monitoring systems a monitoring model is proposed utilizing not only the vehicle dynamics but also the roll motion. Based on the monitoring model three monitoring systems are developed to estimate the tire force acting on each tire. Two monitoring systems are designed utilizing the conventional estimation techniques such as SMO(Sliding Mode Observer) and EKF(Extended Kalman Filter). An additional monitoring system is designed based on a new SKFMEC(Scaled Kalman Filter with Model Error Compensator) technique which is developed to improve the performance of EKF method. Tire force estimation performance of the three monitoring systems is compared in the Matlab simulations where true tire force data is generated from a 14 DOF vehicle model with the combined-slip Magic Formula tire model. The built in our Lab. simulation results show that the SKFMEC method gives the best performance when the driving and road conditions are perturbed.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.4
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• pp.230-242
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• 2010

In this paper, an environmental monitoring and diagnosis system based on ubiquitous computing technology, shortly u-Eco Monitoring System, is proposed. u-Eco Monitoring System is designed to: 1) Collect information from the manufacturing processes via ubiquitous computing technology, 2) Analyze the current status, 3) Identify the cause of problem if detected by rule-based and case-based reasoning, and 4) Provide the results to the operator for proper decision making. Based on functional modeling, a generic architecture is derived, followed by application to a manufacturing system in iron and steel making industry. Finally, to show the validity of the proposed method, a prototype is developed and tested. The developed methods can be used as a conceptual framework for designing environmental monitoring and diagnosis system for industrial practices by which monitoring accuracy and response time for abnormal status can be significantly enhanced, and relieving operator pressure from manual monitoring and error-prone decision making.

• International Journal of Contents
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• v.9 no.4
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• pp.22-29
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• 2013

In this paper, we propose a integrated real-time monitoring system for recycling agriculture resourcing based on USN. We design and implement the monitoring system so that we can integrate the quality control of farmyard and liquid manures, barn environment monitoring, and positioning information control into a total management system performing recycling of excrement and manure. Selection of sensors and sensor-node construction and requirements, structure of wire/wireless communication networks, and design of monitoring program are also presented. As a result of operating our system, we can get over various drawbacks of conventional separated system and promote the proper circulation of excrement up to the farmyard. We confirm that these advanced effects arise from the effective management of the total system integrating quality control of farmyard/liquid manure, barn/farmhouse information, and vehicle moving monitoring information etc. Moreover, this monitoring system is able to exchange real-time information throughout communication networks so that we can construct a convenient information environment for agricultural community by converging IT technology with farm and stockbreeding industries. Finally we present some results of processing using our monitoring system. Sensing data and their graphs are processed in real-time, positioning information on the v-world map offers various moving paths of vehicles, and statistical analysis shows all the procedure from excrement occurrence to recycling and resourcing.