• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.234-239
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• 1990

A neural controller for process control was proposed that combines a simple feedback controller with a neural network. This control was applied to distillation control. The feedback error learning technique was used for on-line learning. Important characteristics on neural controller were analyzed. The proposed neural controller can cope well with strong interactions, significant time delays, sudden changes in process dynamics without any prior knowledge of the process. It was shown that the neural controller has good features such as fault tolerance, interpolation effect and random learning capability

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.792-793
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• 2005

Circuit testing process is very important in IC Manufacturing there are two ways in research for circuit testing improvement. These are ATPG Tool Design and Test simulation application. We are interested in how to use parallel technique such as one-side communication, parallel IO and dynamic Process with data partition for circuit testing improvement and we use one-side communication technique in this paper. The parallel ATPG Tool can reduce the test pattern sets of the circuit that is designed in laboratory for make sure that the fault is not occur. After that, we use result for parallel circuit test simulation to find fault between designed circuit and tested circuit. From the experiment, We use less execution time than non-parallel Process. And we can set more parameter for less test size. Previous experiment we can't do it because some parameter will affect much waste time. But in the research, if we use the best ATPG Tool can optimize to least test sets and parallel circuit testing application will not work. Because there are too little test set for circuit testing application. In this paper we use a standard sequential circuit of ISCAS89.

• Journal of the Korean earth science society
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• v.23 no.1
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• pp.87-96
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• 2002

Aeromagnetic and gravity data were analyzed to delineate the subsurface structure of the Yeongdong basin and its related fault movement in the Okcheon fold belt. The aeromagnetic data of the total intensity (KIGAM, 1983) were reduced to the pole and three dimensional inverse modeling, which considers topography of the survey area in the modeling process, were carried out. The apparent susceptibility map obtained by three dimensional magnetic inversion, as well as the observed aeromagnetic anomaly itself, show clearly the gross structural trend of the Yeongdong basin in the direction on between $N30^{\circ}E$ and $N45^{\circ}E$. Gravity survey was carried out along the profile, of which the length is about 18.2 km across the basin. Maximum relative Bouguer anomaly is about 7 mgals. Both forward and inverse modeling were also carried out for gravity analysis. The magnetic and gravity results show that the Yeongdong basin is developed by the force which had created the NE-SW trending the magnetic anomalies. The susceptibility contrast around Yeongdong fault is apparent, and the southeastern boundary of the basin is clearly defined. The basement depth of the basin appears to be about 1.1 km beneath the sea level, and the width of the basin is estimated to be 7 km based on the simultaneous analysis of gravity and magnetic profiles. There exists an unconformity between the sedimentary rocks and the gneiss at the southeastern boundary, which is the Yeongdong fault, and granodiorite is intruded at the northwestern boundary of the basin. Our results of gravity and magnetic data analysis support that the Yeongdong basin is a pull-apart basin formed by the left-stepping sinistral strike-slip fault, which formed the Okcheon fold belt.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.78-83
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• 2014

Recently, a rapid growth of wind power system as a leading renewable energy source has compelled a number of companies to develop intelligent monitoring and diagnostic system. Such systems can detect early mechanical faults, which prevents from costly repairs. Generally, fault diagnostic system for wind turbines is based on vibration and process signal analysis. In this work, different type of mechanical faults such as mass unbalance and shaft misalignment which can always happen in wind turbine system is considered. The proposed intelligent fault diagnostic algorithm utilizes artificial neural network and Wavelet transform. In order to verify the feasibility of the proposed algorithm, mechanical fault generation experimental system manufactured by Gaon corporation is utilized.

• The KIPS Transactions:PartA
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• v.8A no.4
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• pp.319-330
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• 2001

In virtual memory system, when a process attempts to access a page that is not resident in memory, the system generates and handles a page fault that causes unpredictable delay. So virtual memory system is not appropriate for the real-time system, because it can increase the deadline miss ratio of real-time task. In multimedia system, virtual memory system may degrade the QoS(quality of service) of multimedia application. Furthermore, in general-purpose operating system, whenever a new task is dynamically loaded, virtual memory system suffers from extensive page fault that cause transient overloading state. In this paper, we present efficient overloading control mechanism called RBPFH (Rate-Based Page Fault Handling). A significant feature of the RBPFH algorithm is page fault dispersion that keeps page fault ratio from exceeding available bound by monitoring current system resources. Furthermore, whenever the amount of available system resource is changed, the RBPFH algorithm dynamically adjusts the page fault handling rate. The RBPFH algorithm is implemented in the Linux operating system and its performance measured. The results demonstrate RBPFH\`s superior performance in supporting multimedia applications. Experiment result shows that RBPFH could achieve 10%∼20% reduction in deadline miss ratio and 50%∼60% reduction in average delay.

• The Journal of Engineering Geology
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• v.20 no.2
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• pp.183-189
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• 2010

Fault gouge samples were collected from the fault cores of the boundary faults between the Cretaceous Basement and the Tertiary Waeup Basin. Fractal dimensions (D) were obtained by using survivor grains which were analysed from six thin sections of the gouges under the optical microscope. The elliptical survivor grains show a shape preferred orientation almost parallel to clay foliation in matrix, suggesting that it was formed by the rotation of the survivor grains in abundant fine-grained matrix during repeated fault slips. The size distributions of the survivor grains follow power-laws with fractal dimensions in the 2.40-3.02 range. D values of all samples but one are higher than a specific D value equal to 2.58 which predicts the self similarity of fragmentation process in constrained comminution model (Sammis et al., 1987), which indicates large fault slip and multiple faulting. Probably the higher D values than 2.58 mean the non-self-similar evolution of cataclastic rocks where fragmentation mechanism changed from constrained comminution to the grain abrasion accompanying selective fracture of larger grains.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.7A
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• pp.649-658
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• 2006

Recently, Software Development was applied to new-approach methods as a various form : client-server system and web-programing, object-orient concept, distributed development with a network environments. On the other hand, it be concerned about the distributed development technology and increasing of object-oriented methodology. These technology is spread out the software quality and improve of software production, reduction of the software develop working. Futures, we considered about the distributed software development technique with a many workstation. In this paper, we discussed optimal release problem based on a stochastic differential equation model for the distributed Software development environments. In the past, the software reliability applied to quality a rough guess with a software development process and approach by the estimation of reliability for a test progress. But, in this paper, we decided to optimal release times two method: first, SRGM with an error counting model in fault detection phase by NHPP. Second, fault detection is change of continuous random variable by SDE(stochastic differential equation). Here, we decide to optimal release time as a minimum cost form the detected failure data and debugging fault data during the system test phase and operational phase. Especially, we discussed to limitation of reliability considering of total software cost probability distribution.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.3
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• pp.205-216
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• 2024

Recently, seismic Probabilistic Safety Assessment (PSA) methods have been developed for process plants, such as gas plants, oil refineries, and chemical plants. The framework originated from the PSA of nuclear power plants, which aims to assess the risk of reactor core damage. The original PSA method was modified to adopt the characteristics of a process plant whose purpose is continuous operation without shutdown. Therefore, a fault tree, whose top event is shut down, was constructed and transformed into a Bayesian Network (BN), a probabilistic graph model, for efficient risk-informed decision-making. In this research, the fault tree-based BN from the previous research is further developed to consider the multi-hazard of earthquake-induced fire and explosion (EQ-induced F&E). For this purpose, an event tree describing the occurrence of fire and explosion from a release is first constructed and transformed into a BN. And then, this BN is connected to the previous BN model developed for seismic PSA. A virtual plot plan of a gas plant is introduced as a basis for the construction of the specific EQ-induced F&E BN to test the proposed BN framework. The paper demonstrates the method through two examples of risk-informed decision-making. In particular, the second example verifies how the proposed method can establish a repair and retrofit strategy when a shutdown occurs in a process plant.

• The Journal of Society for e-Business Studies
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• v.15 no.4
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• pp.303-317
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• 2010

In this paper, we propose a novel approach to fault prediction for real-time business process monitoring method using extended KNN imputation based LOF prediction. Existing rule-based approaches to process monitoring has some limitations like late alarm for fault occurrence or no indicators about real-time progress, since there exist unobserved attributes according to the monitoring phase during process executions. To improve these limitations, we propose an algorithm for LOF prediction by adopting the imputation method to assume unobserved attributes. LOF of ongoing instance is calculated by assuming next probable progresses after the monitoring phase, which is conducted during entire monitoring phases so that we can predict the abnormal termination of the ongoing instance. By visualizing the real-time progress in terms of the probability on abnormal termination, we can provide more proactive operations to opportunities or risks during the real-time monitoring.

• 한국초전도학회:학술대회논문집
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• 2007.07a
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• pp.68-68
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• 2007