• Journal of the Korea Safety Management & Science
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• 제6권3호
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• pp.303-309
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• 2004

Many system devices for fluoroscopic and general X-ray studies in diagnostic radiographic system have been being changed from analog mode to digital mode. In addition, among diagnostic imaging and radiologic examinations, fluoroscopic studies that requires functional diagnosis is being widely used. The video recording method of fluoroscopic studies has been useful in functional image diagnosis and dynamic image observation, but the utility of its image quality is being reduced because of limitation in setting play segments of the video player, inconvenience of play, difficulties in preserving reproduced images, the change of image quality, etc. In order to complement these shortages, it is necessary to facilitate access to patient diagnosis information such as storing, editing and sharing functional diagnosis images in response to the trend of the digitalization of digital radiographic & fluoroscopic system(DRF). Thus this study designed and implemented a device of storing functional dynamic images real time using a computer rather than existing video recording, aiming at contribution to functional image diagnosis.

• Journal of the Korea Safety Management & Science
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• 제12권2호
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• pp.65-73
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• 2010

In an automated industry PLC plays a central role to control the manufacturing system. Therefore, fault free operation of PLC controlled manufacturing system is essential in order to maximize a firm's productivity. On the contrary, distributed nature of manufacturing system and growing complexity of the PLC programs presented a challenging task of designing a rapid fault finding system for an uninterrupted process operation. Hence, designing an intelligent monitoring, and diagnosis system is needed for smooth functioning of the operation process. In this paper, we propose a method to continuously acquire a stream of PLC signal data from the normal operational PLC-based manufacturing system and to generate diagnosis model from the observed PLC signal data. Consequently, the generated diagnosis model is used for distinguish the possible abnormalities of manufacturing system. To verify the proposed method, we provided a suitable case study of an assembly line.

• Journal of the Korea Safety Management & Science
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• 제2권4호
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• pp.59-70
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• 2000

To keep enterprise's competitiveness on condition of the automatic manufacturing system such as FA, FMS and CIM, all the maintenance problems should be considered seriously in not only production and maintenance but also related industrial safety. As we analyze in the surveys for the maintenance management of domestic enterprises and the causes of Industrial accident, there will be necessity of drawing up countermeasures for prevention of industrial accidents and for ensuring expertise maintenance technologies. Based on these analyses, this study studied the safety information system, maintenance management information system, and the machinery condition diagnosis technique by using of the knowledge-based system under the internet environment. This web based knowledge-based diagnosis system can easily provide not only the knowledge of expert about deterioration phenomenon of industrial robot, but also the knowledge of relating safety and facility on everywhere, everytime. Therefore, when we use this system, it is expected to improve the efficiency of business processes in the production and safety.

• Journal of the Korea Safety Management & Science
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• 제10권3호
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• pp.19-27
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• 2008

Since 1995, the facility of class 1 and 2, classified by law had been subject to system of post maintenance management where periodic safety inspection and diagnosis to identify any problems and to take appropriate measures as a matter of urgency. Although the standards and systems had been revised many times for continuous improvement due to surrounding environmental factors, the technical factors and other factors for improvements, continuous researches and efforts are needed to ensure even higher effectiveness. Furthermore, the consciousness of the management body that executes and implements such improvements for facility management is most important. Therefore in this study, through such analysis, more realistic management consciousness review was performed. Also the direction for improvements is proposed, to carry out more effective facility safety management systems implementation.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 한국조명전기설비학회 2009년도 춘계학술대회 논문집
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• pp.59-62
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• 2009

When happen the electrical facilities accident the one's diagnosis system of fault cause was constructed by FMEA method Cable accident cause is given by accident cause that can happen in each one's diagnosis and accident probability value. From the verification of system, the one's diagnosis system agreed well with result that analyzed actual state. Thus, the system is judged to be used effectively examine for accident cause of electrical facilities.

• Journal of the Korea institute for structural maintenance and inspection
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• 제22권4호
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• pp.37-41
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• 2018

Recently, interest in the safety and maintenance of the structures is growing. However, due to the low-cost order placed by the ordering organization, the safety diagnosis specialized institution becomes insolvent and many problems have arisen due to insufficient inspection and diagnosis. Therefore, in this study, the current status of bid cost was examined through the survey of the practitioners and case analysis. As a result, Precision safety inspection is deemed that it is necessary to increase the efficiency of the criteria cost and to strengthen the rigidity of the criteria cost rather than adjusting the criteria cost. Precision safety diagnosis, the criteria cost for structures with a floor area of less than $10,000m^2$ is lowered to 80 % from the current standard. For structures larger than that, the current criteria cost are applied, but it is deemed necessary to strengthen the rigidity of the criteria cost.

• Journal of the Korea institute for structural maintenance and inspection
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• 제14권6호
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• pp.246-253
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• 2010

National major facilities have been rigorously investigated using regular safety inspections and precision safety diagnosis since the Special Law for Facilities Safety Management was made in 1995. However, the process of safety inspection and precision safety diagnosis could be doubted due to intervention of facility owner for safety level evaluation, competition to obtain low price order, and low technical skills of inspection companies. Although the management processes for evaluating the inspection companies were used for several years, the process should continue to improve in the safety inspection field. This study analyzed the recent evaluation system and the ratios of insufficient inspection. Estimation of national loss expenses to the insufficient safety inspection was investigated to recognize the necessity for the improvement of facility inspection process and evaluation system.

• Journal of the Korean Society of Safety
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• 제34권4호
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• pp.59-67
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• 2019

Since it is really hard to construct process models based on prior process knowledges, various statistical approaches have been employed to build fault diagnosis models. However, the crucial drawback of these approaches is that the solutions may vary according to the fault magnitude, even if the same fault occurs. In this study, the parameter monitoring approach is suggested. When a fault occurs in a chemical process, this leads to trigger the change of a process model and the monitoring parameters of process models is able to provide the efficient fault diagnosis model. A few important variables are selected and their predictive models are constructed by partial least square (PLS) method. The Euclidean norms of parameters of PLS models are estimated and a fault diagnosis can be performed as comparing with parameters of PLS models based on normal operational conditions. To improve the monitoring performance, cumulative summation (CUSUM) control chart is employed and the changes of model parameters are recorded to identify the type of an unknown fault. To verify the efficacy of the proposed model, Tennessee Eastman (TE) process is tested and this model can be easily applied to other complex processes.

• Journal of the Korean Society of Safety
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• 제19권1호
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• pp.23-30
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• 2004

Modern production systems are very complex by request of automation, and failure modes that occur in thisautomatic system are very various and complex. The efficient fault diagnosis for these complex systems is essential for productivity loss prevention and cost saving. Traditional fault diagnostic system which perforns sequential fault diagnosis can cause catastrophic failure during diagnosis when fault propagation is very fast. This paper describes the Real-time Intelligent Multiple Fault Diagnosis System (RIMFDS). RIMFDS assesses current machine condition by using sensor signals. This system deals with multiple fault diagnosis, comprising of two main parts. One is a personal computer for remote signal generation and transmission and the other is a host system for multiple fault diagnosis. The signal generator generates various faulty signals and image information and sends them to the host. The host has various modules and agents for efficient multiple fault diagnosis. A SUN workstation is used as a host for multiple fault modules and agents for efficient multiple fault diagnosis. A SUN workstation is used as a host for multiple fault diagnosis and graphic representation of the results. RIMFDS diagnoses multiple faults with fast fault propagation and complex physical phenomenon. The new system based on multiprocessing diagnoses by using Hierarchical Artificial Neural Network (HANN).

• Journal of the Korean Society of Safety
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• 제31권4호
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• pp.35-41
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• 2016

In order to guarantee the process safety and prevent accidents, the deviations from normal operating conditions should be monitored and their root causes have to be identified as soon as possible. The statistical theories-based method among various fault diagnosis methods has been gaining popularity, due to simplicity and quickness. However, according to fault magnitudes, the scalar value generated by statistical methods can be changed and this point can lead to produce wrong information. To solve this difficulty, this work employs PCA (Principal Component Analysis) based method with qualitative information. In the case study of our previous study, the number of assumed faults is much smaller than that of process variables. In the case study of this study, the number of predefined faults is 19, while that of process variables is 6. It means that a fault diagnosis becomes more difficult and it is really hard to isolate a single fault with a small number of variables. The PCA model is constructed under normal operation data in order to get a loading vector and the data set of assumed faulty conditions is applied with PCA model. The significant changes on PC (Principal Components) axes are monitored with CUSUM (Cumulative Sum Control Chart) and recorded to make the information, which can be used to identify the types of fault.