• 한국철도학회:학술대회논문집
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• 한국철도학회 2005년도 춘계학술대회 논문집
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• pp.97-102
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• 2005

As the railroad-base is an important factor to maintenance the rolling stocks, it is essential to improve the current problems of the environment pollution, nose, vibration, welfare, work condition and to applicate the performance betterment cases to the new base construction and pre-base maintenance. When the new base construction and pre-base maintenance is proceeded, it is necessary to construct the optimized system which includes the user's opinions enough to prevent the waste of the budget ,in that some part of the budget is spent to improve convenience, work condition, and the fault of base system after the construction. Therefore, this research intends to present the problem of the pre-constructed facilities, the testing operators' opinions, the analysis and the investigation of facilities' improvement, thorough the indication of provisions and the analysis of the result of the survey of testing operators.

• Nuclear Engineering and Technology
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• 제46권6호
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• pp.737-752
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• 2014

As condition-based maintenance (CBM) has risen as a new trend, there has been an active movement to apply information technology for effective implementation of CBM in power plants. This motivation is widespread in operations and maintenance, including monitoring, diagnosis, prognosis, and decision-making on asset management. Thermal efficiency analysis in nuclear power plants (NPPs) is a longstanding concern being updated with new methodologies in an advanced IT environment. It is also a prominent way to differentiate competitiveness in terms of operations and maintenance costs. Although thermal performance tests implemented using industrial codes and standards can provide officially trustworthy results, they are essentially resource-consuming and maybe even a hind-sighted technique rather than a foresighted one, considering their periodicity. Therefore, if more accurate performance monitoring can be achieved using advanced data analysis techniques, we can expect more optimized operations and maintenance. This paper proposes a framework and describes associated methodologies for in-situ thermal performance analysis, which differs from conventional performance monitoring. The methodologies are effective for monitoring, diagnosis, and prognosis in pursuit of CBM. Our enabling techniques cover the intelligent removal of random and systematic errors, deviation detection between a best condition and a currently measured condition, degradation diagnosis using a structured knowledge base, and prognosis for decision-making about maintenance tasks. We also discuss how our new methods can be incorporated with existing performance tests. We provide guidance and directions for developers and end-users interested in in-situ thermal performance management, particularly in NPPs with large steam turbines.

• 한국실내디자인학회논문집
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• 제17권5호
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• pp.40-50
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• 2008

This article examined the applicability of spatial configuration to Escher's works through configurative logics and rules and studied the contrasting relations among the unit elements in Escher's works and their characteristics and the creative process of the characteristics. As the results of the study on the bases to maintain and create the partial elements revealed as the characteristics, it was shown that Escher's sequential transformative works demonstrated diverse expressive characteristics as a creative process of Inter-complementary contrasting relations based on the independence of the unit elements. It was also shown that the creative process of the unit elements was actualized through the maintenance base of the fixed and absolute characteristic as the logic for the creation and the creation base of the dynamic and relative characteristic. Therefore, it was interpreted that by applying the logics for creation to Escher's unit elements through the spatial interpretation of the maintenance base and the creation base as well as by configuring the units created in such a way according to the characteristics of Escher's works, spatial possibility canbe derived out from Escher's contrasting tessellation works. The process of spatial configuration is the process to make a balance between various conditions, artists own understanding of the space and his/her intention of the space. From this viewpoint, the logics for maintenance base and for creation base seem to have the potentiality as a spatial configuration to consistently meet the given conditions as well as to derive out novelty through the transformation to maintain the fixed and absolute condition(base) and the characteristics of the independent(additional) transformation arising together with the implicit relations among the transformative units.

• 한국정밀공학회지
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• 제12권11호
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• pp.82-90
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• 1995

This paper pressents a condition-based maintenance (CBM) method through bibration analysis. The well known frequency analysis is employed for performing machine fault diagnosis. The statistical control chart is also applied for analyzing the trend of the bearing wear. Vibration sensors are attached to prototype machine and signals are continuously monitored. The sampled data are utilized to evaluate how well the fast fourier transform(FFT) and the statistical control chart techniques could be used to identify defects of machine and to analyze the machine degradation. Experimental results show that the propowed approach could classify every mal-function and could be utilized for real machine diagnosis system.

• Computers and Concrete
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• 제14권6호
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• pp.727-743
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• 2014

The management of existing concrete bridges has become a major social concern in many developed countries due to the large number of bridges exhibiting signs of significant deterioration. This problem has increased the demand for effective maintenance and renewal planning. In order to implement an appropriate management procedure for a structure, a wide array of corrective strategies must be evaluated with respect to not only the condition state of each defect but also safety, economy and sustainability. This paper describes a new performance evaluation system for existing concrete bridges. The system evaluates performance based on load carrying capability and durability from the results of a visual inspection and specification data, and describes the necessity of maintenance. It categorizes all girders and slabs as either unsafe, severe deterioration, moderate deterioration, mild deterioration, or safe. The technique employs an expert system with an appropriate knowledge base in the evaluation. A characteristic feature of the system is the use of neural networks to evaluate the performance and facilitate refinement of the knowledge base. The neural network proposed in the present study has the capability to prevent an inference process and knowledge base from becoming a black box. It is very important that the system is capable of detailing how the performance is calculated since the road network represents a huge investment. The effectiveness of the neural network and machine learning method is verified by comparing diagnostic results by bridge experts.

• 한국환경복원기술학회지
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• 제16권4호
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• pp.15-26
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• 2013

In recent years, river maintenance projects using natural methods have been continuously implemented in urban areas and methods emphasizing ecology are being developed and constructed in revetment areas. However, there is insufficient technical review on the hydraulic stability of those revetment methods during the event of flood. Therefore, a hydraulic analysis is necessary for the stream where revetments are applied. This study was conducted to develop an objective test method for the hydraulic stability of green revetment media. For this purpose, hydraulic model tests were performed for the green base materials for revetments. Tests were conducted using experimental devices for the hydraulic model which were installed to simulate the rapid current during the flood. Loss of soil by the hydraulic condition was compared and analyzed with that of dry green revetment media, and the evaluations were made on the corrosion resistance, tractive force, and contractile force. Test results showed that green revetment media had higher corrosion resistance in non-vegetation condition compared to dry green revetment media, and the loss of base materials by the rooting of vegetation showed significant reduction by the vegetation. In addition, results of the allowable tractive force of the base material indicated it is relatively stable in vegetation condition but scouring can occur in non-vegetation condition. Therefore, the development of vegetation in revetment areas is anticipated to be effective for the stability of revetment areas by reducing external forces interacting with the corrosion resistance and stream bank. The green revetment media in expected to contribute to the stability of revetment areas.

• 한국추진공학회지
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• 제17권1호
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• pp.80-88
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• 2013

최근 개발되는 엔진 진단 시스템들은 현장에서 일하는 엔진 정비사들이 이들 시스템들의 복잡성, 비실용성, 공학적 이해부족으로 사용하기가 매우 어렵다. 따라서 실용성 있는 엔진 진단시스템이 요구된다. 본 연구는 작동중인 온라인 성능진단 자료와 기본엔진 성능모델에 의해 계산된 초기고장이 없는 엔진 성능자료와의 비교를 통한 소형엔진의 실용적 성능진단 시스템 개발에 관한 것이다. 또한 제안된 성능진단 시스템은 성능이 저하되거나 고장이 난 엔진으로 간주되는 작동 중 엔진과 고장이 없는 엔진으로 간주되는 기본 엔진 성능모델 사이의 구성품 성능특성을 비교함으로서 가스경로 구성품의 온라인 진단을 확인할 수 있다. 개발된 상태진단시스템은 실제 적용을 용이하게 하기위해 SIMULINK와 LabVIEW프로그램을 이용하여 사용자조건의 GUI형 프로그램으로 작성하였다.

• Journal of Advanced Marine Engineering and Technology
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• 제30권2호
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• pp.247-252
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• 2006

Almost ship monitoring systems are event driven alarm system which warn only when the measurement value is over or under set point. These kinds of system cannot warn until signal is growing to abnormal state that the signal is over or under the set point. therefore cannot play a role for preventive maintenance system. This paper proposes fault diagnosis method which is able to diagnose and forecast the fault from present operating condition by analyzing monitored signals with present ship monitoring system without any additional sensors. By analyzing the data with high correlation coefficient(CC), correlation level of interactive data can be defined. Knowledge base of abnormal detection can be built by referring level of CC(Fault Detection CC. FDCC) to detect abnormal data among monitored data from monitoring system and knowledge base of diagnosis built by referring CC among interactive data for related machine each other to diagnose fault part.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2005년도 전기학술대회논문집
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• pp.281-286
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• 2005

Almost ship monitoring systems are event driven alarm system which warn only when the measurement value is over or under set point. These kinds of system cannot warn while signal is growing to abnormal state until the signal is over or under the set point and cannot play a role for preventive maintenance system. This paper proposes fault diagnosis method which is able to diagnose and forecast the fault from present operating condition by analyzing monitored signals with present ship monitoring system without additional sensors. By analyzing this data having high correlation coefficient(CC), correlation level of interactive data can be understood. Knowledge base of abnormal detection can be built by referring level of CC(Fault Detection CC, FDCC) to detect abnormal data among monitored data from monitoring system and knowledge base of diagnosis built by referring CC among interactive data for related machine each other to diagnose fault part.

• Structural Monitoring and Maintenance
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• 제6권4호
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• pp.317-346
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• 2019

Performance assessment of pavements proves useful, in terms of handling the ride quality, controlling the travel time of vehicles and adequate maintenance of pavements. Roughness profiles provide a good measure of the deteriorating condition of the pavement. For the accurate estimates of pavement roughness from dynamic vehicle responses, vehicle parameters should be known accurately. Information on vehicle parameters is uncertain, due to the wear and tear over time. Hence, condition monitoring of pavement requires the identification of pavement roughness along with vehicle parameters. The present study proposes a scheme which estimates the roughness profile of the pavement with the use of accurate estimates of vehicle parameters computed in parallel. Pavement model used in this study is a two-layer Euler-Bernoulli beam resting on a nonlinear Pasternak foundation. The asphalt topping of the pavement in the top layer is modeled as viscoelastic, and the base course bottom layer is modeled as elastic. The viscoelastic response of the top layer is modeled with the help of the Burgers model. The vehicle model considered in this study is a half car model, fitted with accelerometers at specified points. The identification of the coupled system of vehicle-pavement interaction employs a coupled scheme of an unbiased minimum variance estimator and an optimization scheme. The partitioning of observed noisy quantities to be used in the two schemes is investigated in detail before the analysis. The unbiased minimum variance estimator (MVE) make use of a linear state-space formulation including roughness, to overcome the linearization difficulties as in conventional nonlinear filters. MVE gives estimates for the unknown input and fed into the optimization scheme to yield estimates of vehicle parameters. The issue of ill-posedness of the problem is dealt with by introducing a regularization equivalent term in the objective function, specifically where a large number of parameters are to be estimated. Effect of different objective functions is also studied. The outcome of this research is an overall measure of pavement condition.