• IE interfaces
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• v.11 no.1
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• pp.175-182
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• 1998

The maintainability prediction of an underwater military system is considered. A general and parctical prediction method for maintainability using MIL-HDBK-472 is presented. We develop a computer program to predict MTTR of an underwater military system. A case study is made to explain the proposed maintainability prediction method.

• Journal of Internet of Things and Convergence
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• v.8 no.6
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• pp.55-63
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• 2022

In recent years, with the rapid development of large and medium-sized urban rail transit in China, the total operating mileage of high-speed railway and the total number of EMUs(Electric Multiple Units) are rising. The system complexity of high-speed EMU is constantly increasing, which puts forward higher requirements for the safety of equipment and the efficiency of maintenance.At present, the maintenance mode of high-speed EMU in China still adopts the post maintenance method based on planned maintenance and fault maintenance, which leads to insufficient or excessive maintenance, reduces the efficiency of equipment fault handling, and increases the maintenance cost. Based on the intelligent operation and maintenance technology of PHM(prognostics and health management). This thesis builds an integrated PHM platform of "vehicle system-communication system-ground system" by integrating multi-source heterogeneous data of different scenarios of high-speed EMU, and combines the equipment fault mechanism with artificial intelligence algorithms to build a fault prediction model for traction motors of high-speed EMU.Reliable fault prediction and accurate maintenance shall be carried out in advance to ensure safe and efficient operation of high-speed EMU.

• Magazine of the Korea Institute for Structural Maintenance and Inspection
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• v.19 no.4
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• pp.52-55
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• 2015

• Magazine of the Korea Institute for Structural Maintenance and Inspection
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• v.19 no.2
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• pp.19-23
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• 2015

• Korean Journal of Construction Engineering and Management
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• v.21 no.6
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• pp.46-55
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• 2020

The maintenance cost for highway pavement is gradually increasing due to the continuous increase in road extension as well as increase in the number of old routes that have passed the public period. As a result, there is a need for a method of minimizing costs through preventative grievance Preventive maintenance requires the establishment of a strategic plan through accurate prediction old Highway pavement. herefore, in this study, the XGBoost among machine learning classification-based models was used to develop a highway pavement damage prediction model. First, we solved the imbalanced data issue through data sampling, then developed a predictive model using the XGBoost. This predictive model was evaluated through performance indicators such as accuracy and F1 score. As a result, the over-sampling method showed the best performance result. On the other hand, the main variables affecting road damage were calculated in the order of the number of years of service, ESAL, and the number of days below the minimum temperature -2 degrees Celsius. If the performance of the prediction model is improved through more data accumulation and detailed data pre-processing in the future, it is expected that more accurate prediction of maintenance-required sections will be possible. In addition, it is expected to be used as important basic information for estimating the highway pavement maintenance budget in the future.

• Journal of the Semiconductor & Display Technology
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• v.19 no.1
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• pp.1-5
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• 2020

In this paper, a predictive maintenance of the robot trouble using the machine learning method, so called MT(Mahalanobis Taguchi), was studied. Especially, 'MD(Mahalanobis Distance)' was used to compare the robot arm motion difference between before the maintenance(bearing change) and after the maintenance. 6-axies vibration sensor was used to detect the vibration sensing during the motion of the robot arm. The results of the comparison, MD value of the arm motions of the after the maintenance(bearing change) was much lower and stable compared to MD value of the arm motions of the before the maintenance. MD value well distinguished the fine difference of the arm vibration of the robot. The superior performance of the MT method applied to the prediction of the robot trouble was verified by this experiments.

• Proceedings of the KIEE Conference
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• 2005.07e
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• pp.31-33
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• 2005

The accelerating of industrial development causes electricity demand to increase. By that power equipments need high power, multi function and intelligence. Also consumers demand for guarantee power supplying of good quality and reasonable operating equipment. Also they require for reliance and stabilization of power facility. Therefore preventive maintenance of electric installation must be developed and improvement of domestic technical level is needed in the maintenance management of equipment. The diagnosis of trouble existence is technique that compares steady state with unusual condition, whereas the prediction technique makes a diagnosis of remaining equipments life. It is difficult for us to diagnose trouble existence of electric installation and to develop prediction method in building because of a wide scope for electric installation in building. And in this paper we will investigate diagnosis and prediction method for only switch part of electric installation in building.

• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.4
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• pp.71-78
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• 2007

Schmidt hammer and ultra-sonic method are commonly used for crushed sand concrete compressive strength test in a construction field. At present, various of equations for prediction of strength are present, which have been used in a construction field. The purpose of this study is to evaluate the correlation between prediction strength by presentation equations and destructive strength to test specimen, and find out which is a suitable equation for the construction site. In this study, a strength test was carried out destructive test by means of core sampling and traditional test. The experimental parameter were concrete age, curing condition, and strength level.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.486-493
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• 2007

In the field of maintenance of domestic high-speed railroad which has cost a great deal more than any other fields since it was opened; 1) We found out the conditions of current domestic railroad by understanding the status of track maintenance and analyzing operative processes of track maintenance. 2) The main factors in track maintenance of high-speed railroad, that is, the elements for success to help decision-support in track maintenance were derived from a research on literature about the condition of railroad R&D in these days and about the prediction of the irregular progresses of track. 3) We derived the order of priority and weights from AHP analysis which was based on the survey regarding elements for success.

• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.5
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• pp.81-88
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• 2007

Among deteriorations of concrete due to environmental exposure, carbonation problems of concrete structures have increased in urban and underground structures. But conventional carbonation-prediction equations that were proposed by foreign references, can not be applied directly to the prediction of carbonation for domestic concrete structures. The purpose of this study is to propose a prediction equation of carbonation depth by considering domestic exposure conditions of concrete structures. For the derivation of the equation, conventional carbonation-prediction equations are analyzed. Through considering the relationship between results of prediction equation and those of various domestic field survey data, the so-called correction factors for different domestic exposure condition of concrete structures are derived. Finally, a carbonation-prediction equation of concrete structures under domestic exposure conditions is proposed with consideration for concrete strength in core and correction factors.