• Journal of Sensor Science and Technology
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• v.24 no.6
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• pp.368-372
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• 2015

In this paper, we proposed a post-processing technique for improving classification performance of electronic nose (E-Nose) system which may be occurred drift signals from sensor array. An adaptive radial basis function network using stochastic gradient (SG) and singular value decomposition (SVD) is applied to process signals from sensor array. Due to drift from sensor's aging and poisoning problems, the final classification results may be showed bias and fluctuations. The predicted classification results with drift are quantized to determine which identification level each class is on. To mitigate sharp fluctuations moving-averaging (MA) technique is applied to quantized identification results. Finally, quantization and some edge correction process are used to decide levels of the fluctuation-smoothed identification results. The proposed technique has been indicated that E-Nose system was shown correct odor identification results even if drift occurred in sensor array. It has been confirmed throughout the experimental works. The enhancements have produced a very robust odor identification capability which can compensate for decision errors induced from drift effects with sensor array in electronic nose system.

• Journal of applied mathematics & informatics
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• v.4 no.1
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• pp.135-135
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• 1997

Times series modeling plays an important role in the field of engineering, Statistics, Biomedicine etc. Model identification is one of crucial steps in the modeling of an AutoRegreesive Moving Average(ARMA(p, q)) process for real world problems. Many techniques have been developed in the literature (Salas et al., McLeod et al. etc.) for the identification of an ARMA(p, q) Model. In this paper, a new technique called The Generalised Parameters Technique is formulated for seasonal and non-seasonal ARMA model identification. This technique is very simple and can e applied to any given time series. Initial estimates of the AR parameters of the ARMA model are also obtained by this method. This model identification technique is validated through many theoretical and simulated examples.

• Journal of the Korean Society of Safety
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• v.29 no.3
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• pp.79-84
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• 2014

Human error is one of the major contributors to the accidents. A lot of risk assessment techniques have been developed for prevention of accidents. Nevertheless, most of them were interested in physical factors, because quantitative evaluation of human errors was difficult quantitatively. According to lack of risk assessment techniques about human errors, most of industrial risk assessment for human errors were based on data of accident analysis. In order to develop an effective countermeasure to reduce the risk caused by human errors, a systematic analysis is needed. Generally, risk assessment system is composed of 5 step(classification of work activity, identification of hazards, risk estimation, evaluation and improvement). This study aimed to develop a risk identification technique for human errors that could mainly be applied to industrial fields. In this study, Ergo-HAZOP and Comprehensive Human Error Analysis Technique were used for developing the risk identification technique. In the proposed risk identification technique, Ergo-HAZOP was used for broad-brush risk identification. More critical risks were analysed by Comprehensive Human Error Analysis Technique. In order to verify applicability, the proposed risk identification technique was applied to the work of pile head cutting. As a consequence, extensive hazards were identified and fundamental countermeasures were established. It is expected that much attention would be paid to prevent accidents by human error in industrial fields since safety personnel can easily fint out hazards of human factors if utilizing the proposed risk identification technique.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.153-156
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• 1999

The technique is reported of identifying parameters in off-line process. The technique demands that closed-loop system consists of a reference and two-degree-of-freedom controllers (TDFC) in real process. A model process is the same as the real process except their parameters. Deviations are differences between the reference and the output of the plant or the model. The technique is based on minimizing identification error between the two deviations. The parameter differences between the plant and the model are characterized of mean value and of variance which are derived from the identification error. Consequently, the algorithm which identifies the unknown plant parameters is shown by minimizing the mean value and the variance, respectively, within double convergence loops. The technique is applied to course change of a ship. The plant deviation at the first trial is shown to occur in replacing the nominal parameters by the default parameters. The plant deviation at the second trial is shown to not occur in replacing the nominal parameters by the identified parameters. Hence, the identification technique is confirmed to be feasible in the real field.

• Wind and Structures
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• v.9 no.2
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• pp.159-178
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• 2006

For the slender and flexible cable supported bridges, identification of all the flutter derivatives for the vertical, lateral and torsional motions is essential for its stability investigation. In all, eighteen flutter derivatives may have to be considered, the identification of which using a three degree-of-freedom elastic suspension system has been a challenging task. In this paper, a system identification technique, known as covariance-driven stochastic subspace identification (COV-SSI) technique, has been utilized to extract the flutter derivatives for a typical bridge deck. This method identifies the stochastic state-space model from the covariances of the output-only (stochastic) data. All the eighteen flutter derivatives have been simultaneously extracted from the output response data obtained from wind tunnel test on a 3-DOF elastically suspended bridge deck section-model. Simplicity in model suspension and measurements of only output responses are additional motivating factors for adopting COV-SSI technique. The identified discrete values of flutter derivatives have been approximated by rational functions.

• Nuclear Engineering and Technology
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• v.36 no.1
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• pp.12-23
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• 2004

In the present study a new measurement technique has been developed, which uses an ultrasonic transmission signal in order to identify the vertical two phase flow pattern. The ultrasonic measurement system developed in the present study not only provides the information required for the identification of vertical two phase flow patterns but also makes real time identification possible. Various vertical two phase flow patterns such as bubbly, slug, churn, annular flow etc. have been accurately identified with the present ultrasonic measurement system under atmospheric condition. In addition, the present test apparatus can practically simulate the ultrasonic propagation characteristics under high temperature and high pressure systems. Therefore, it is expected that the present ultrasonic flow pattern identification technique could be applicable to the vertical two phase flow systems under high temperature and high pressure conditions.

• Structural Engineering and Mechanics
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• v.22 no.1
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• pp.53-70
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• 2006

The paper summarizes the dynamic-based assessment of a reinforced concrete arch bridge, dating back to the 50's. The outlined approach is based on ambient vibration testing, output-only modal identification and updating of the uncertain structural parameters of a finite element model. The Peak Picking and the Enhanced Frequency Domain Decomposition techniques were used to extract the modal parameters from ambient vibration data and a very good agreement in both identified frequencies and mode shapes has been found between the two techniques. In the theoretical study, vibration modes were determined using a 3D Finite Element model of the bridge and the information obtained from the field tests combined with a classic system identification technique provided a linear elastic updated model, accurately fitting the modal parameters of the bridge in its present condition. Hence, the use of output-only modal identification techniques and updating procedures provided a model that could be used to evaluate the overall safety of the tested bridge under the service loads.

• Journal of Ocean Engineering and Technology
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• v.24 no.1
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• pp.123-132
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• 2010

This paper presents a prestress-loss monitoring technique for prestressed concrete (PSC) girder structures that uses a vibration-based system identification method. First, the theoretical backgrounds of the prestress-loss monitoring technique and the system identification technique are presented. Second, vibration tests are performed on a lab-scaled PSC girder for which the modal parameter was measured for several prestress-force cases. A numerical modal analysis is performed by using an initial finite element (FE) model from the geometric, material, and boundary conditions of the lab-scaled PSC girder. Third, a vibration-based system identification is performed to update the FE model by identifying structural parameters since the natural frequency of the FE model became identical to the experimental results. Finally, the feasibility of the prestress-loss monitoring technique is evaluated for the PSC girder model by using the experimentally measured natural frequency and numerically identified natural frequency for several prestress-force cases.

• Journal of Positioning, Navigation, and Timing
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• v.3 no.2
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• pp.45-51
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• 2014

GNSS has the disadvantage of being vulnerable to jamming, and thus, the necessity of jamming countermeasure techniques has gradually increased. Jamming countermeasure techniques can be divided into an anti-jamming technique and a jammer localization technique. Depending on the type of a jammer, applicable techniques and performance vary significantly. Using an appropriate jamming countermeasure technique, the effect of jamming on a GNSS receiver can be attenuated, and prompt action is enabled when estimating the location of a jammer. However, if an inappropriate jamming countermeasure technique is used, a GNSS receiver may not operate in the worst case. Therefore, jammer identification is a technique that is essential for proper action. In this study, a technique that identifies a jammer based on template matching was proposed. For template matching, analysis of a received jamming signal is required; and the signal analysis was performed using a spectral correlation function. Based on a simulation, it was shown that the proposed identification of jamming signals was possible at various JNR.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.10a
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• pp.109-116
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• 2001

An integrated damage identification system (IDIS) and system identification (SID) technique using modal information to detect damage in structures is presented. The objective is to detect damages in cracked model plate-girder without baseline modal parameters. The theory of damage localization and system identification is outlined. Experiments on a model plate-girder was described and a baseline model representing the experimental modal characteristics of the model plate-girder is updated using the system identification technique. Finally, damage inflicted in the model plate-girder is predicted using the IDIS software.