• Journal of the Korean Society for Marine Environment & Energy
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• v.4 no.4
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• pp.61-69
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• 2001

Recently, according to the rapid development of computer and electronic technology, most crude oil carriers adopt automated cargo handling system. But an excessive automation makes system so complicate that it could increase the Possibility of accidents due to human error. Although a cargo handling process is done by an expert, the potential of accidents by human factor lies through the whole cargo handling procedure and the current automated system lacks of the functionality to prevent a mis-operation and diagnose the abnormal status of the system. Because the oil concerned accident could be almost a disaster, the primary goal of system development should not be a fully automated system but be a perfectly safe system. This paper deals with the analysis and design of an expert system which can provide mariner with the operational guidance and the facility of crisis management by monitoring system's abnormal condition and human's mis-operation.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.2043-2048
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• 2011

According to the statistical report from National Emergency Management Agency (NEMA) in Korea, the accident rate of closed switchboards in power systems occupies over 40%. In this paper, an integrated sensor module for monitoring the condition of closed switchboards is described. The sensor module monitors electro-magnetic (EM) wave, ultra-violet (UV) ray, heat and smoke generated by electrical discharges or insulation breakdown. The effective detection ranges were decided from experiment results; 100 kHz~10 MHz for EM wave, 220 nm~395 nm for UV ray and 0~$150^{\circ}C$ for heat, respectively. The prototype sensor module includes all functions above-mentioned in one device.

• Smart Media Journal
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• v.6 no.4
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• pp.9-16
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• 2017

The railway point machine is an especially important component that changes the traveling direction of a train. Failure of the point machine may cause a serious railway accident. Therefore, early detection of failures is important for the management of railway condition monitoring systems. In this paper, we propose a noise-robust anomaly detection method in railway condition monitoring systems using sound data. First, we extract feature vectors from the spectrogram image of sound signals and convert it into modulation feature to ensure robust performance, and lastly, use the support vector machine (SVM) as an early anomaly detector of railway point machines. By the experimental results, we confirmed that the proposed method could detect the anomaly conditions of railway point machines with acceptable accuracy even under noisy conditions.

• Nuclear Engineering and Technology
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• v.46 no.4
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• pp.557-568
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• 2014

This paper presents the results of an analysis of wind characteristics and atmosphere dispersion modeling that are based on computational simulation and part of a preliminary study evaluating environmental radiation monitoring system (ERMS) positions within the Barakah nuclear power plant (BNPP). The return period of extreme wind speed was estimated using the Weibull distribution over the life time of the BNPP. In the annual meteorological modeling, the winds from the north and west accounted for more than 90 % of the wind directions. Seasonal effects were not represented. However, a discrepancy in the tendency between daytime and nighttime was observed. Six variations of cesium-137 ($^{137}Cs$) dispersion test were simulated under severe accident condition. The $^{137}Cs$ dispersion was strongly influenced by the direction and speed of the main wind. A virtual receptor was set and calculated for observation of the $^{137}Cs$ movement and accumulation. The results of the surface roughness effect demonstrated that the deposition of $^{137}Cs$ was affected by surface condition. The results of these studies offer useful information for developing environmental radiation monitoring systems (ERMSs) for the BNPP and can be used to assess the environmental effects of new nuclear power plant.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.5
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• pp.38-48
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• 2010

Adverse weather (e.g. strong winds, snow and ice) will probably appear as a more serious and frequent threat to road traffic than in clear climate. Another consequence of climate change with a natural disastrous on road traffic is respond to traffic accident more the large and high-rise bridge zone, tunnel zone, inclined plane zone and de-icing zone than any other zone, which in turn calls for continuous adaption of monitoring procedures. Accident mitigating measures against this accident category may consist of intense winter maintenance, the use of road weather information systems for data collection and early warnings, road surveillance and traffic control. While hazard from reduced road friction due to snow and ice may be eliminated by snow removal and de-icing measures, the effect of strong winds on road traffic are not easily avoided. The purpose of the study described here, was to design of amber information the relationship between traffic safety, weather, user information on road weather and driving conditions in local-scale Geographic. The most applications are the optimization of the amber information definition, improvements to road surveillance, road weather monitoring and improved accuracy of user information delivery. Also, statistics on wind gust, surface condition, vehicle category and other relevant parameters for wind induced accidents provide basis for traffic control, early warning policies and driver education for improved road safety at bad weather-exposed locations.

• Journal of the Korea institute for structural maintenance and inspection
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• v.9 no.2
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• pp.103-112
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• 2005

This study examines the stability of Sungsu bridge which was issued nine years ago because of its collapse accident and now is on the progress of extension work in each construction stage by construction monitoring system. From this study, the measured value in each construction stage of anchorage truss and suspended truss shows the agreement with the analytical values up to 60~110 percents, and the elements' stresses emanating from the pre-loading stage, are also similar to the analytical value. Regarding these results, it is expected that each member has enough stiffness and the construction condition is satisfactory. In addition, it is expected that the transverse members and sway bracing bolts integrate completely the existing truss and new attached truss as a one body from the result of the vibration test to find out the integration rates.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.05a
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• pp.230-231
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• 2019

This study is a development on condition based maintenance(CBM) technology which is a core item of future autonomous ships. It is developing to design & installation of condition monitoring system and acquisition & processing of data from ongoing ships for fault prediction & prognosis of engine in operation. The ultimate goal of this study is to develop a predicts and decision support software for marine engine faults. To do this, the FMEA and fault tree analysis of the main engine should be accompanied by the analysis of classification of system, identification of the components, the type of faults, and the cause and phenomenon of the failure. Finally, the CBM system solution software could predict and diagnose the failure of main engine through integrated analysis for bid-data of ongoing ships and engineering knowledge. Through this study, it is possible to pro-actively cope with abnormal signals of engine and to manage efficiently, and as a result, expected that marine accident and ship operation loss during navigation will be prevented in advance.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.1 s.106
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• pp.27-33
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• 2006

Fault diagnosis and condition monitoring for rotating machines are important for efficiency and accident prevention. The process of fault diagnosis is to extract the feature of signals and to classify each state. Conventionally, fault diagnosis has been developed by combining signal processing techniques for spectral analysis and pattern recognition, however these methods are not able to diagnose correctly for certain rotating machines and some faulty phenomena. In this paper, we add a minimum detection error algorithm to the previous method to reduce detection error rate. Vibration signals of the induction motor are measured and divided into subband signals. Each subband signal is processed to obtain the RMS, standard deviation and the statistic data for constructing the feature extraction vectors. We make a study of the fault diagnosis system that the feature extraction vectors are applied to K-means clustering algorithm and minimum detection error algorithm.

• Smart Media Journal
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• v.11 no.9
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• pp.30-38
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• 2022

It is important to grasp biometric data in real time for prompt action in the event of a safety accident at a work site where the risk of safety accidents exists. Among them, blood oxygen saturation is the most important factor in maintaining human life, so real-time oxygen saturation measurement and monitoring is necessary according to the situation as a preemptive response for worker safety management. By receiving real-time bio-signals from workers wearing health and life-risk protective clothing, and sharing and analyzing the worker's risk status in an external system, it is possible to diagnose the worker's current condition and efficiently respond to emergencies that may occur to the worker. In this paper, we propose a wearable oxygen saturation measurement platform technology that can monitor the risk of harmful gases and oxygen saturation of the wearer in real time and ensure the wearer's activity and safety in order to cope with emergency situations at the scene of an accident. If we overcome the limitations identified through the results of the proposed system later and apply improved biodata such as motion correction to the platform, we expect that it will be usable not only in hazardous gas environments, but also in hospitals and homes for emergency patients.

• Journal of Navigation and Port Research
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• v.45 no.1
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• pp.9-15
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• 2021

According to IMO, MASS is defined as a vessel operated at various levels independent of human interference. The safety navigation support service for MASS is designed to improve the safety and efficiency of MASS by developing public services on shore for ship arrivals/departures and for cargo handling. The safety navigation support service consists of a total of six types of services: autonomous operation, berthing/unberthing/mooring, cargo handling and ship arrival/departure service, PSC inspection, condition monitoring, and accident response support services. In order to support accident response service, the relative importance of a bridge navigational equipment was assessed by stratifying the navigation system to provide safe and efficient support services by objective judgment through specific and quantitative methods using AHP, one of decision-making methods used by an expert group. The survey was conducted by dividing the bridge navigational equipment into depth, location, and speed information. As a result of applying the AHP method, the importance of depth, location, and speed information was assessed. The relative importance of each equipment for providing location information was also assessed in order of Radar, DGPS, ECDIS, Gyro compass, Autopilot, and AIS. This was similar to survey results on the utilization of each operator's preference and its impact on marine accidents.