• Journal of the Korea Society of Computer and Information
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• v.20 no.9
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• pp.121-128
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• 2015

In this paper, we proposed and implemented the effective automatic foreground motion detection algorithm that detect the foreground motion by analyzing the digital video data that captured by the network camera. We classified the background as moving background, fixed background and normal background based on the standard deviation of background and used it to detect the foreground motion. According to the result of experiment, our algorithm decreased the fault detection of the moving background and increased the accuracy of the foreground motion detection. Also it could extract foreground more exactly by using the statistic information of background in the phase of our foreground extraction.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.956-958
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• 1995

This paper presents the automatic construction of fuzzy rule-based systems for diagnosing the faults of complex systems. Generally, fuzzy systems work well when we can use expert's experience to articulate fuzzy IF-THEN rules and memberships for fuzzy sets. When we cannot do this, we should generate the fuzzy rules and membership functions for fuzzy sets directly from experimental data. In this paper, we propose a new method on how to extract fuzzy sets and fuzzy rules. We also introduce an efficient fine-tunning algorithm of the parameters of membership functions.

• Journal of KIISE:Software and Applications
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• v.35 no.5
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• pp.335-346
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• 2008

Causal relations in ontology should be defined based on the inference types necessary to solve problems specific to application as well as domain. In this paper, we present a model to define and extract causal relations for application ontology for Question-Answering (QA) on fault-diagnosis of electronic devices. Causal categories are defined by analyzing generic patterns of QA application; the relations between concepts in the corpus belonging to the causal categories are defined as causal relations. Instances of casual relations are extracted using lexical patterns in the concept definitions of domain, and extended incrementally with information from thesaurus. On the evaluation by domain specialists, our model shows precision of 92.3% in classification of relations and precision of 80.7% in identifying causal relations at the extraction phase.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2002.11a
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• pp.155-159
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• 2002

Wire ropes are used in a myriad of various industrial applications such as elevator, mine hoist, construction machinery, lift, and suspension bridge. Especially, wire rope of crane is important component to container transfer. If it happens wire rope failures in operating, it may lead to safety accident, economic power loss by productivity decline, competitive power decline of container terminal and so on. To solve this problem, we developed wire rope fault detecting system as a portable instrument, and this system is consisted of 3 parts that fault detecting part using hall sensor, permanent magnets and analog unit, and digital signal processing part using data acquisition card, monitoring part using wavelet transform, denoising method. In this paper, a wire rope is scanned by this system after makes several broken parts on the surface of wire rope artificially. All detected signal has external noise or disturbance according to circumstances. So, we applied to discrete wavelet transform to extract a signal from noisy data that was used filter. In practical applications of denoising, it is shown that wavelet pursue it with little information loss and smooth signal display. It is verified that the detecting system by denoising has good efficiency for inspecting faults of wire ropes in service. As a result, by developing this system, container terminal could reduce expense because of extension of wire ropes exchange period and could competitive power. Also, this system is possible to apply in several fields like that elevator, lift and so on.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2843-2845
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• 2000

A lane detection based on a road model or feature all need correct acquirement of information on the lane in a image, It is inefficient to implement a lane detection algorithm through the full range of a image when being applied to a real road in real time because of the calculating time. This paper defines two searching range of detecting lane in a road, First is searching mode that is searching the lane without any prior information of a road, Second is recognition mode, which is able to reduce the size and change the position of a searching range by predicting the position of a lane through the acquired information in a previous frame. It is allow to extract accurately and efficiently the edge candidates points of a lane as not conducting an unnecessary searching. By means of removing the perspective effect of the edge candidate points which are acquired by using the inverse perspective transformation, we transform the edge candidate information in the Image Coordinate System(ICS) into the plane-view image in the World Coordinate System(WCS). We define linear approximation filter and remove the fault edge candidate points by using it This paper aims to approximate more correctly the lane of an actual road by applying the least-mean square method with the fault-removed edge information for curve fitting.

• Earthquakes and Structures
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• v.22 no.5
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• pp.503-515
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• 2022

This paper presents the development of seismic fragility curves for a precast reinforced concrete bridge instrumented with a structural health monitoring (SHM) system. The bridge is located near an active seismic fault in the Dominican Republic (DR) and provides the only access to several local communities in the aftermath of a potential damaging earthquake; moreover, the sample bridge was designed with outdated building codes and uses structural detailing not adequate for structures in seismic regions. The bridge was instrumented with an SHM system to extract information about its state of structural integrity and estimate its seismic performance. The data obtained from the SHM system is integrated with structural models to develop a set of fragility curves to be used as a quantitative measure of the expected damage; the fragility curves provide an estimate of the probability that the structure will exceed different damage limit states as a function of an earthquake intensity measure. To obtain the fragility curves a digital twin of the bridge is developed combining a computational finite element model and the information extracted from the SHM system. The digital twin is used as a response prediction tool that minimizes modeling uncertainty, significantly improving the predicting capability of the model and the accuracy of the fragility curves. The digital twin was used to perform a nonlinear incremental dynamic analysis (IDA) with selected ground motions that are consistent with the seismic fault and site characteristics. The fragility curves show that for the maximum expected acceleration (with a 2% probability of exceedance in 50 years) the structure has a 62% probability of undergoing extensive damage. This is the first study presenting fragility curves for civil infrastructure in the DR and the proposed methodology can be extended to other structures to support disaster mitigation and post-disaster decision-making strategies.

• Journal of Korean Society for Geospatial Information Science
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• v.6 no.2 s.12
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• pp.133-141
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• 1998

Terrain modelling is composed of a method using the rectangular grid and another using the triangulated irregular network. The method using the triangulated irregular network is most widely used because it can express the characteristics of the terrain well with only a small amount of information on the terrain and also reduces the rendering time. The process of extracting the surface-specific point and a triangular process is needed to construct such triangulated irregular network. This paper concentrates on the process of extracting the surface-specific point. The 8-direction neighborhood method and other transformed methods of the former method are frequently used to extract the surface-specific point. Another method which eliminates the unnecessary points using the Polygon reduction method is also suggested However, the 8-direction neighborhood method has a big fault of also drawing out some unnecessary points. To resolve such problem, we suggest a method of extracting the surface-specific point using the cross section of the terrain. This method reduces the time to extract the surface-specific point and enables a more precise extraction with less terrain information.

• Journal of the Korean Society for Nondestructive Testing
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• v.19 no.4
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• pp.270-276
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• 1999

Fourier transform has been one of the most commonly used tools in study of frequency characteristics of signal. However, based on the Fourier transform. it is hard to tell whether a signal's frequency contents evolve in time or not. Recently, to overcome Fourier transform fault. not to represent non-stationary signal, time-frequency analysis methods are developed and those can represent informations of signal's time and frequency at the same time. In this study we analysed ultrasonic signal for degraded SUS 316 with time-frequency analysis method. In particular the methods such as short time Fourier(STFT) and Wigner-Ville distribution(WVD) were used to extract frequency contents and characteristics from ultrasonic signals.

• 한국신재생에너지학회:학술대회논문집
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• 2007.06a
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• pp.395-399
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• 2007

Renewable energy sources such as wind energy is copiously available without any limitation. Wind turbines are used to tap the potential of wind energy which is available in millions of megawatt. Reliability of wind turbine is critical to extract this maximum amount of energy from the wind. We reviewed different techniques, methodologies, and algorithms developed to monitor the performance of wind turbine as well as for an early fault detection to keep away the wind turbines from catastrophic conditions due to sudden breakdowns. To keep the wind turbine in operation, implementation of Condition Monitoring System (CMS) is paramount, and for this purpose ample knowledge of these types of system is mandatory. So, an attempt has been made in this direction to review maximum approaches related to CMS in this piece of writing.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.05c
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• pp.170-176
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• 2002

In this papers, we proposed the feature extraction method due to partial discharge type of transformers. For wavelet transform, Daubechie's filter is used, we can obtain wavelet coefficients which is used to extract feature of statistical parameters (maximum value, average value, dispersion, skewness, kurtosis) about acoustic emission signal generated from each partial discharge type. The defects which could occur in a transformer were simulated by using needle-plane electrode, IEC electrode and Void electrode. Also, these coefficients are used to identify signal of partial discharge type electrode fault in transformer. As a result, from compare of acoustic emission amplitude and acoustic average value, we are obtained results of IEC electrode> Void electrode> Needle-Plane electrode. otherwise, In case of skewness and kurtosis, we are obtained results of Needle-Plane electrode electrode> Void electrode> IEC electrode.