• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.2
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• pp.7-15
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• 2017

Recently, an electricity sensor system has been installed and operated to prevent failures and accidents by identifying whether a transformer is normal in advance of failure. This electricity sensor system is able to both measure and monitor the transformer's power and voltage remotely and send information to a manager when unusual operation is discovered. However, a battery is required to operate power detection devices, and battery systems need ongoing management such as regular replacement. In addition, at a maintenance cost, occasional human resources and worker safety problems arise. Accordingly, we apply a linear electromagnetic generator using vibration energy from a transformer for an electric sensor system's drive in this research and we conduct optimal design to maximize the linear electromagnetic generator's power. We consider design variables using the provided design method from Process Integration, Automation, and Optimization (PIAnO), which is common tool from process integration and design optimization (PIDO). In addition, we analyze the experiment point from the design of the experiments using "MAXWELL," which is a common electromagnet analysis program. We then create an approximate model and conduct accuracy verification. Finally, we determine the optimal model that generates the maximum power using the proven approximate kriging model and evolutionary optimization algorithm, which we then confirm via simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.7
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• pp.813-820
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• 2010

The vertical roller mill is important for machine grinding and mixing various crude materials in the process of producing Portland cement. A vertical roller mill is subjected to cyclic bending stress because of the roller load. Because of the cyclic bending stress, only $4{\times}10^6-8{\times}10^6$ cycles are achieved instead of $4{\times}10^7$ cycles. The stress also causes fractures at the edge of grinding path of the outer roller. The expenses incurred in repairing the grinding path amounts to 30% of the total maintenance cost. Therefore, it is desirable to redesign the vertical roller mill in order to reduce the expenses incurred in repairing the roller. In this study, artificial neural networks (ANNs) were applied in order to solve the multiobjective optimization problem for vertical roller mills by using the function approximation ability of ANNs. To learn and generalize ANNs, the maximum and minimum stresses were estimated from the results of the finite-element analysis of a vertical roller mill. Thus, ANNs could be applied to solve the multiobjective optimization problem.

• The Journal of the Korea Contents Association
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• v.6 no.1
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• pp.160-169
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• 2006

This paper describes the data structure for program analysis and optimization of bytecode level. First we create an extended CFG(Control Flow Graph). Because of the special properties of bytecode, we must adaptively extend the existing control flow analysis techniques. We build basic blocks to create the CFG and create various data that can be used for optimization. The created CFG can be tested for comprehension and maintenance of Java bytecode, and can also be used for other analyses such as data flow analysis. This paper implements CTOC's CTOC-BR(CTOC-Bytecode tRanslator) for control flow analysis of bytecode level. CTOC(Classes To Optimized Classes) is a Java bytecode framework for optimization and analysis. This paper covers the first part of the CTOC framework. CTOC-BR is a tool that converts the bytecode into tree form for easy optimization and analysis of bytecode in CTOC.

• Proceedings of the KSR Conference
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• 1999.11a
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• pp.46-53
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• 1999

As of July 1999, i,185 lomocotives(excluding metropolitan area electric locomotives) are in Korean National Railroad(KNR). With this limited number of resources assigning locomotives to each trains of timetable is very important in the entire railway management point of view because schedule can be regarded as goods in transportation industry. On a simple rail network, it is rather easier to assign proper locomotives to trains with the experience of operating experts and get optimal assignment solution. However, as the network is getting bigger and complicated, the number of trains and corresponding locomotives will be dramatically increased to rover all the demands required to service all of the trains in timetable. There will be also numerous operational constraints to be considered. Assigning proper locomotives to trains and building optimal cyclic rotations of locomotive routings will result in increasing efficiency of schedule and giving a guarantee of more profit. The purpose of this study is two fold: (1) we consider a planning-level locomotive scheduling problem with the objective of minimizing the wasting cost under various practical constraints and (2) development of implementation prototype program of its assigning result. Not like other countries, i.e. Canada, Sweden, Korean railroad operates on n daily schedule basis. The objective is to find optimal assignment of locomotives of different types to each trains, which minimize the wasting cost. This problem is defined on a planning stage and therefore, does not consider operational constraints such as maintenance and emergency cases. Due to the large scale of the problem size and complexity, we approach with heuristic methods and column generation to find optimal solution. The locomotive scheduling prototype consists of several modules including database, optimization engine and diagram generator. The optimization engine solves MIP model and provides an optimal locomotive schedule using specified optimization algorithms. A cyclic locomotive route diagram can be generated using this optimal schedule through the diagram generator.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.387-390
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• 2008

The importance of the life cycle cost analysis for construction projects of bridge has been recognized over the last decades. Accordingly, theoretical models, guidelines, and supporting softwares have been developed for the life cycle cost analysis of bridges. However, it is difficult to predict life cycle cost considering uncertainties precisely. This paper presents methodology for optimal design of substructure for a steel box bridge. Total life cycle cost for the service life is calculated as sum of initial cost, damage cost considering uncertainty, maintenance cost, repair and rehabilitation cost. The optimization method is applied to design of a bridge substructure with minimal cost, in which the objective function is set to life cycle cost and constraints are formulated on the basis of Korean Bridge Design Specification. Initial cost is calculated based on standard costs of the Korea Construction Price Index and damage cost on the damage probabilities to consider the uncertainty of load and resistance. An advanced first-order second moment method is used as a practical tool for reliability analysis using damage probability. Maintenance cost and cycle is determined by a stochastic method and user cost includes traffic operation costs and time delay costs.

• Journal of the Korea institute for structural maintenance and inspection
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• v.1 no.2
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• pp.87-94
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• 1997

This research aims to develop an algorithm of optimal transducer placement using Kinetic Energy of the structural system. The structural vibration response-based health monitoring is considered one of the best for the system which requires a long-term, continuous monitoring. In its experimental modal testing, however, it is difficult to decide on the measurement locations and their number, especially for complex structures, which have a major influence on the quality of the results. In order to minimize the number of sensing operations and optimize the transducer location while maximizing the accuracy of results, this paper discusses about an optimum transducer placement criterion suitable for the identification of structural damage. As a criterion algorithm, it proposes the Kinetic Energy Optimization Technique (EOT), and then addresses the numerical issues which are subsequently applicable to actual experiment where a bridge model is used. By using the experimental data, it compares the EOT with the EIM (Effective Independence Method) which is generally used to optimize the transducer placement for the damage identification and control purposes. The comparison conclusively shows that the EOT algorithm proposed in this paper is preferable when a structure is to be instrumented with fewer sensors.

• Journal of the Korea institute for structural maintenance and inspection
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• v.6 no.2
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• pp.145-155
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• 2002

It is essential for health monitoring of a cable-stayed bridge to provide more accurate and enough information from the sensors. In experimental modal testing, the chosen measurement locations and the number of measurements have a major influence on the quality of the results. The choice is often difficult for complex structures like a cable-stayed bridge. It is extremely important a cable-stayed bridge to minimize the number of sensing operations required to monitor the structural system. In order to obtain the desired accuracy for the structural test, several issues must take into consideration. Two important issues are the number and location of response sensors. There are usually several alternative locations where different sensors can be located. On the other hand, the number of sensors might be limited due to economic constraints. Therefore, techniques such as methodologies, algorithms etc., which address the issue of limited instrumentation and its effects on resolution and accuracy in health monitoring systems are paramount to a damage diagnosis approach. This paper discusses an optimum sensor placement criterion suitable to the identification of structural damage for continuous health monitoring. A Kinetic Energy optimization technique and an Effective Independence Method are analyzed and numerical and theoretical issues are addressed for a cable-stayed bridge. Its application to a cable-stayed bridge is discussed to optimize the sensor placement for identification and control purposes.

• Nuclear Engineering and Technology
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• v.52 no.10
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• pp.2262-2273
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• 2020

Digital twin technology can provide significant value for the prognostics and health management (PHM) of critical plant components by improving insight into system design and operating conditions. Digital twinning of systems can be utilized for anomaly detection, diagnosis and the estimation of the system's remaining useful life in order to optimize operations and maintenance processes in a nuclear plant. In this regard, a conceptual framework for the application of digital twin technology for the prognosis of Control Element Drive Mechanism (CEDM), and a data-driven approach to anomaly detection using coil current profile are presented in this study. Health management of plant components can capitalize on the data and signals that are already recorded as part of the monitored parameters of the plant's instrumentation and control systems. This work is focused on the development of machine learning algorithm and workflow for the analysis of the CEDM using the recorded coil current data. The workflow involves features extraction from the coil-current profile and consequently performing both clustering and classification algorithms. This approach provides an opportunity for health monitoring in support of condition-based predictive maintenance optimization and in the development of the CEDM digital twin model for improved plant safety and availability.

• Journal of Information Technology Services
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• v.20 no.3
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• pp.1-12
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• 2021

Reactor Coolant Pump (RCP) is core part of nuclear power plant to provide the forced circulation of reactor coolant for the removal of core heat. Properly monitoring vibration of RCP is a key activity of a successful predictive maintenance and can lead to a decrease in failure, optimization of machine performance, and a reduction of repair and maintenance costs. Here, we developed real-time RCP Vibration Analysis System (VAS) that web based platform using NoSQL DB (Mongo DB) to handle vibration data of RCP. In this paper, we explain how to implement digital signal process of vibration data from time domain to frequency domain using Fast Fourier transform and how to design NoSQL DB structure, how to implement web service using Java spring framework, JavaScript, High-Chart. We have implement various plot according to standard of the American Society of Mechanical Engineers (ASME) and it can show on web browser based on HTML 5. This data analysis platform shows a upgraded method to real-time analyze vibration data and easily uses without specialist. Furthermore to get better precision we have plan apply to additional machine learning technology.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.1
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• pp.10-18
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• 2022

This report describes the development and stability evaluation of a seismic retrofit method to evaluate the seismic performance of existing school buildings by analyzing the earthquake waveforms that occurred in Korea. Currently, Facilities for seismic retrofit designed for excessive reinforcement are being applied. To compensate for this, optimised the retrofit mothod suitable for domestic situation considering the characteristics of the seismic region, generated a Korean-style artificial seismic wave that meets the seismic design criteria, which is less frequent than other countries.