• Water for future
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• v.29 no.1
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• pp.141-150
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• 1996

Steady state analysis of pressure and flow in water supply piping systems is a problem of great importance in hydraulic engineering. The basic equations consist of continuity equation and energy equation. The network equations are solved iteratively by using linear solution method. The resulting linear simultaneous equations are solved by frontal method. Frontal method, which is suitable to sparse matrix, gathers only non-zero entries in coefficient matrix. The suggested methodology can analyze faster than the existing routines by using smaller computer memory. The model presented in this study shows accurate and efficient results for various piping systems.

• Industrial Engineering and Management Systems
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• v.13 no.3
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• pp.319-329
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• 2014

Supply chain management is a subject that has an increasing importance due to the developments in the global markets and technology. In this paper, a fuzzy multi-objective linear programming model is developed for the supply chain of a company dealing with procurement, storage, filling, and distribution of liquefied petroleum gas (LPG) in Turkey. The model intends to determine the quantities of LPG to be procured, stored, filled to cylinders, and transported between the plants and demand centers for six planning periods. In this model, which aims to minimize both total costs (sum of procurement, storage, filling, and transportation costs) and total transportation distances, demand quantities of the main demand centers and decision maker's aspiration levels about objective functions are fuzzy. After comparing the results obtained from the model with those obtained by using different methods, it is concluded that the proposed method can be applied to real world problems practically and it may be used in this type of problems in order to generate an efficient solution.

• Journal of Korea Water Resources Association
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• v.34 no.5
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• pp.567-575
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• 2001

A methodology is developed for designing the minimum-cost water distribution network. The method is based on network simulations and an optimization scheme using genetic algorithms. Being a stochastic optimization scheme, genetic algorithms have advantages over the conventional search algorithms in solving network problems known for their nonlinearities and herculean computational costs. While existing methods focus on the design of either entirely new or parallel augmentation of network systems, the proposed method can be applied to problems having both new branches of tree-type and paralle augmentation in loops. The applicability of the method was shown through a case study for Baekryeon water supply system. The optimized design resulted in the maximum 5.37% savings compared to the conventional design without optimization, while meeting the hydraulic constraints.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.61-68
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• 1997

The algorithm of customer demand decomposition suggested by this study is a reconstruction method of distribution network under the allowance of same level supply. Regional distribution center(RDC) distributes additional inventories of some of the supplying items to retailers under its charge to reduce the time needed for emergency delivery to neighborhood retailer where backlog happened. This also restrict the purpose of the inventories held by RDC as only regular supply. All of which leads to the creation of more realistic method allowing the affiliation of closing related RDC with one in the vicinity. In this study, the role of RDC is restricted only as supplying items regularity and the conruction of distribution system processing through the closing by consideration of the possibility of supplying retailers from the RDC in the vicinity is discussed.

• Smart Structures and Systems
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• v.28 no.6
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• pp.811-825
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• 2021

High-voltage isolating switches play a paramount role in ensuring the safety of power supply systems. However, their exposure to outdoor environmental conditions may cause serious physical defects, which may result in great risk to power supply systems and society. Image processing-based methods have been used for anomaly detection. However, their accuracy is affected by numerous uncertainties due to manually extracted features, which makes the anomaly detection of isolating switches still challenging. In this paper, a vision-based anomaly detection method for isolating switches, which uses the rotational angle of the switch system for more accurate and direct anomaly detection with the help of deep learning (DL) and image processing methods (Single Shot Multibox Detector (SSD), improved frame differencing method, and Hough transform), is proposed. The SSD is a deep learning method for object classification and localization. In addition, an improved frame differencing method is introduced for better feature extraction and a hough transform method is adopted for rotational angle calculation. A number of experiments are conducted for anomaly detection of single and multiple switches using video frames. The results of the experiments demonstrate that the SSD outperforms the You-Only-Look-Once network. The effectiveness and robustness of the proposed method have been proven under various conditions, such as different illumination and camera locations using 96 videos from the experiments.

• Journal of Korean Society of Water and Wastewater
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• v.12 no.4
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• pp.43-52
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• 1998

The purpose of this study is to establish a method of estimating the daily urban water demend using Backpropagation algorithm is part of ANN(Artificial Neural Network). This method will be used for the development of the efficient management and operations of the water supply facilities. The data used were the daily urban water demend, the population and weather conditions such as treperarture, precipitation, relative humidity, etc. Kwangju city was selected for the case study area. We adjusted the weights of ANN that are iterated the training data patterns. We normalized the non-stationary time series data [-1,+1] to fast converge, and choose the input patterns by statistical methods. We separated the training and checking patterns form input date patterns. The performance of ANN is compared with multiple-regression method. We discussed the representation ability the model building process and the applicability of ANN approach for the daily water demand. ANN provided the reasonable results for time series forecasting.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.12
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• pp.1113-1119
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• 2000

To operate a process plant safely and economically, process monitoring is very important. Process monitoring is the task to identify the state of the system from sensor data. Process monitoring includes data acquisition, regulatory control, data reconciliation, fault detection, etc. This research focuses on the data recon-ciliation using scale-space filtering and fault detection using functional-link associative neural networks. Scale-space filtering is a multi-resolution signal analysis method. Scale-space filtering can extract highest frequency factors(noise) effectively. But scale-space filtering has too large calculation costs and end effect problems. This research reduces the calculation cost of scale-space filtering by applying the minimum limit to the gaussian kernel. And the end-effect that occurs at the end of the signal of the scale-space filtering is overcome by using extrapolation related with the clustering change detection method. Nonlinear principal component analysis methods using neural network have been reviewed and the separately expanded functional-link associative neural network is proposed for chemical process monitoring. The separately expanded functional-link associative neural network has better learning capabilities, generalization abilities and short learning time than the exiting-neural networks. Separately expanded functional-link associative neural network can express a statistical model similar to real process by expanding the input data separately. Combining the proposed methods-modified scale-space filtering and fault detection method using the separately expanded functional-link associative neural network-a process monitoring system is proposed in this research. the usefulness of the proposed method is proven by its application a boiler water supply unit.

• Journal of Digital Convergence
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• v.10 no.1
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• pp.371-378
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• 2012

Through sensor nodes it can obtain behavior, condition, location of objects. Generally speaking, sensor nodes are very limited because they have a battery power supply. Therefore, for collecting sensor data, efficient energy management is necessary in order to prolong the entire network survival. In this paper, we propose a method that increases energy efficiency to be self-configuring by distributed sensor nodes per cluster. The proposed method is based on the ANTCLUST. After measuring the similarity between two objects it is method that determine own cluster. It applies a colonial closure model of ant. The result of an experiment, it showed that the number of alive nodes increased 27% than existing clustering methods.

• Journal of Information Technology Applications and Management
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• v.20 no.2
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• pp.147-160
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• 2013

Today, the management environments of intelligence firm are changing the way of production planning and logistics management, and are changing the process of supply chain management system. This paper shows the development of information system software for intelligence enterprises is used in supply chain management for robot engineering industry. Specifically, supply chain management system in this paper has been developed to analyze the impact of multi plant and multi distribution environment, showing the process analysis and system development of hierarchical assembly manufacturing industry. In this paper we consider a production planning and distribution management system of intelligence firm in the supply chain. We focus on a capacitated production resource and distribution volume allocation problem, develop a mixed integer programming model, and propose an efficient heuristic procedure using a genetic algorithm to solve it efficiently. This method makes it possible for the population to reach the feasible approximate solution easily. The proposed regeneration procedures, which evaluate each infeasible chromosome, makes the solution converge to the feasible approximate solution quickly.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.4
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• pp.86-97
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• 2006

For the design of DC traction power supply system at new Light Rail Transit(LRT) construction, it is very important to determine system configuration, location and power capacity of substation. However, a LRT system consists of a number of subsystems such as train movement, power supply and traction drives, which inevitably contains many complexities and diversities. The objective of this paper is to clarify and systematize the design procedure and its assessment for the electrification system of a LRT line. This paper discusses in detail our approach to system design and its assessment. The whole DC-feeding network configuration, characteristics of a train, and design method of substation arrangements is thoroughly investigated for the design. As a result of the investigations, the design procedure is clarified and systematized and a computer program for the design and evaluation of the system is developed using the most suitable iterative method with nodal equation. To verify the proposed design and its assessment procedure, case studies for the DC traction power supply system of a planed Korean LRT line are performed.