• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.150-160
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• 2020

In this paper, we introduce a pilot's scheduling model which is able to maintain and balance their capabilities for each relevant skill level in military helicopter squadron. Flight scheduler has to consider many factors related pilot's flight information and spends a lot of times and efforts for flight planning without scientific process depending on his/her own capability and experience. This model reflected overall characteristics that include pilot's progression by basis monthly and cumulative flight hours, operational recent flight data and quickly find out a pinpoint areas of concern with respect to their mission subjects etc. There also include essential several constraints, such as personnel qualifications, and Army helicopter training policy's constraints such as regulations and guidelines. We presented binary Integer Programming (IP) mathematical formulation for optimization and demonstrated its effectiveness by comparisons of real schedule versus model's solution to several cases experimental scenarios and greedy random simulation model. The model made the schedule in less than 30 minutes, including the data preprocessing process, and the results of the allocation were more equal than the actual one. This makes it possible to reduce the workload of the scheduler and effectively manages the pilot's skills. We expect to set up and improve better flight planning and combat readiness in Korea Army aviation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.217-228
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• 2020

The ROK Army must detect the enemy's location and the type of artillery weapon to respond effectively at wartime. This paper proposes a radar positioning model by applying a scenario-based robust optimization method i.e., binary integer programming. The model consists of the different types of radar, its available quantity and specification. Input data is a combination of target, weapon types and enemy position in enemy's attack scenarios. In this scenario, as the components increase by one unit, the total number increases exponentially, making it difficult to use all scenarios. Therefore, we use partial scenarios to see if they produce results similar to those of the total scenario, and then apply them to case studies. The goal of this model is to deploy an artillery locating radar that maximizes the detection probability at a given candidate site, based on the probability of all possible attack scenarios at an expected enemy artillery position. The results of various experiments including real case study show the appropriateness and practicality of our proposed model. In addition, the validity of the model is reviewed by comparing the case study results with the detection rate of the currently available radar deployment positions of Corps. We are looking forward to enhance Korea Artillery force combat capability through our research.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1168-1182
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• 2017

In the past decades, various image regularization methods have been introduced. Among them, total variation model has drawn much attention for the reason of its low computational complexity and well-understood mathematical behavior. However, regularization parameter estimation of total variation model is still an open problem. To deal with this problem, a novel adaptive regularization parameter selection scheme is proposed in this paper, by means of using the local spectral response, which has the capability of locally selecting the regularization parameters in a content-aware way and therefore adaptively adjusting the weights between the two terms of the total variation model. Experiment results on simulated and real noisy image show the good performance of our proposed method, in visual improvement and peak signal to noise ratio value.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1306-1313
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• 2018

The randomness and incipient nature of certain faults in reactor systems warrant a robust and dynamic detection mechanism. Existing models and methods for fault diagnosis using different mathematical/statistical inferences lack incipient and novel faults detection capability. To this end, we propose a fault diagnosis method that utilizes the flexibility of data-driven Support Vector Machine (SVM) for component-level fault diagnosis. The technique integrates separately-built, separately-trained, specialized SVM modules capable of component-level fault diagnosis into a coherent intelligent system, with each SVM module monitoring sub-units of the reactor coolant system. To evaluate the model, marginal faults selected from the failure mode and effect analysis (FMEA) are simulated in the steam generator and pressure boundary of the Chinese CNP300 PWR (Qinshan I NPP) reactor coolant system, using a best-estimate thermal-hydraulic code, RELAP5/SCDAP Mod4.0. Multiclass SVM model is trained with component level parameters that represent the steady state and selected faults in the components. For optimization purposes, we considered and compared the performances of different multiclass models in MATLAB, using different coding matrices, as well as different kernel functions on the representative data derived from the simulation of Qinshan I NPP. An optimum predictive model - the Error Correcting Output Code (ECOC) with TenaryComplete coding matrix - was obtained from experiments, and utilized to diagnose the incipient faults. Some of the important diagnostic results and heuristic model evaluation methods are presented in this paper.

• Smart Structures and Systems
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• v.23 no.1
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• pp.45-60
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• 2019

This paper is devoted to proposing a new approach for damage detection of structures. In this technique, the biconjugate gradient method (BCG) is employed. To remedy the noise effects, a new preconditioning algorithm is applied. The proposed preconditioner matrix significantly reduces the condition number of the system. Moreover, based on the characteristics of the damage vector, a new direct search algorithm is employed to increase the efficiency of the suggested damage detection scheme by reducing the number of unknowns. To corroborate the high efficiency and capability of the presented strategy, it is applied for estimating the severity and location of damage in the well-known 31-member and 52-member trusses. For damage detection of these trusses, the time history responses are measured by a limited number of sensors. The results of numerical examples reveal high accuracy and robustness of the proposed method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.6
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• pp.4137-4146
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• 2015

The scale and required functionality of modern systems have increased and become more complicated. To successfully carry out the systems development projects, appropriate systems engineering (SE) and project management (PM) activities are required for the underlying process. In a system development organization, it is an effort to secure the SE & PM capability by adopting the CMMI is an evaluation model of improvement and ability of SE&PM process. To achieve the goal each organization establishes and uses its own organizational standard process, which satisfies the business characteristics. However, in practice, due to the lack of sufficient understanding on the interrelationship among different CMMI process areas, there still exist some difficulties with constructing organization processes. In systems development, the activities of SE are closely related with those of PM. Thus, the processes of SE and PM need to be fully integrated and explicitly linked to each other in order to complete the projects successfully. In this paper, we propose a SE&PM integration process architecture of organization that can be utilized in the system development organization is referenced in the construction of CMMI-based organizational process.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.142-148
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• 2015

Due to advancements in technology and manufacturing capability, it is not uncommon that life tests yield no or few failures at low stress levels. In these situations it is difficult to analyse lifetime data and make meaningful inferences about product or system reliability. For some products or systems whose performance characteristics degrade over time, a failure is said to have occurred when a performance characteristic crosses a critical threshold. The measurements of the degradation characteristic contain much useful and credible information about product or system reliability. Degradation measurements of the performance characteristics of an unfailed unit at different times can directly relate reliability measures to physical characteristics. Reliability prediction based on physical performance measures can be an efficient and alternative method to estimate for some highly reliable parts or systems. If the degradation process and the distance between the last measurement and a specified threshold can be established, the remaining useful life is predicted in advance. In turn, this prediction leads to just in time maintenance decision to protect systems. In this paper, we describe techniques for mapping product or system which has degrading performance parameter to the associated classical reliability measures in the performance domain. This paper described a general modeling and analysis procedure for reliability prediction based on one dominant degradation performance characteristic considering pseudo degradation performance life trend model. This pseudo degradation trend model is based on probability modeling of a failure mechanism degradation trend and comparison of a projected distribution to pre-defined critical soft failure point in time or cycle.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.111-118
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• 2004

In this paper, we present a novel approach for the structure of Fuzzy Neural Network(FNN) based on wavelet function and apply this network structure to the solution of the tracking problem for mobile robots. Generally, the wavelet fuzzy model(WFM) has the advantage of the wavelet transform by constituting the fuzzy basis function(FBF) and the conclusion part to equalize the linear combination of FBF with the linear combination of wavelet functions. However, it is very difficult to identify the fuzzy rules and to tune the membership functions of the fuzzy reasoning mechanism. Neural networks, on the other hand, utilize their learning capability for automatic identification and tuning. Therefore, we design a wavelet based FNN structure(WFNN) that merges these advantages of neural network, fuzzy model and wavelet transform. The basic idea of our wavelet based FNN is to realize the process of fuzzy reasoning of wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. And our network can automatically identify the fuzzy rules by modifying the connection weights of the networks via the gradient descent scheme. To verify the efficiency of our network structure, we evaluate the tracking performance for mobile robot and compare it with those of the FNN and the WFM.

• Journal of Magnetics
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• v.21 no.2
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• pp.239-243
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• 2016

High temperature superconductor (HTS) magnet systems usually employ metal current leads which bridge between the cryogenic environment and room temperature. Such current leads are the dominant heat load for these magnet systems due to a combination of electrical resistance and heat conduction. HTS flux pumps enable large currents to be injected into a HTS magnet circuit without this heat load. We present results from an axial-type HTS mechanically rotating flux pump which employs a ferromagnetic circuit and a Cu-stabilized coated conductor (CC) HTS stator. We show the device can be described by a simple circuit model which was previously used to describe barrel-type flux pumps, where the model comprises an internal resistance due to dynamic resistance and a DC voltage source. Unlike previously reported devices, we show the internal resistance and DC voltage in the flux pump are not exactly proportional to frequency, and we ascribe this to the presence of eddy currents. We also show that this axial-type flux pump has superior current injection capability over barrel-type flux pumps which do not incorporate a magnetic circuit.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.13-20
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• 2013

Currently, SEAMCAT has been widely used as a tool to evaluate the effects of interference among wireless communication systems. In the previous work, we have incorporated the ITU-R P.526 pathloss model to the existing SEAMCAT in order to support the capability of interference evaluation taking into account any specific terrain characteristics. Along with this, we have implemented a terrain display function based on the Google map. However, the two-dimensional Google map based display is not effective in helping users to figure out some terrain features including the elevation variation in a given region. In order to alleviate this difficulty, we have incorporated the three-dimensional terrain display using the API of the Google earth to the existing SEAMCAT and provided the capability of viewing the positions of the associated communication systems, the variation of the carrier intensity and interference intensity in location, shadow region indication, and line-of-sight analysis and presented an example of interference evaluation.