• 한국음향학회:학술대회논문집
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• 한국음향학회 2002년도 하계학술발표대회 논문집 제21권 1호
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• pp.25-28
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• 2002

Voice activity detection is important Problem in the speech recognition and communication. This paper introduces feature parameter which is reconstructed by the spectral entropy of information theory for the robust voice activity detection in the noise environment, analyzes and compares it with the energy method of voice activity detection and performance. In experiment, we confirmed that the spectral entropy is more feature parameter than the energy method for the robust voice activity detection in the various noise environment.

• Journal of Magnetics
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• 제21권2호
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• pp.204-208
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• 2016

This paper demonstrates the key parameter detection for smelting of submerged arc furnace (SAF) based on magnetic field radiation. A magnetic field radiation model for the inner structure of SAF is established based on relative theory of electromagnetic field. A simple equipment of 3D magnetic field detection system is developed by theoretical derivation and simulation. The experiments are carried out under the environment of industrial field and AC magnetic field generated by electrode currents and molten currents in the furnace is reflected outside of the furnace. The experimental results show that the key parameters of smelting including the position of electrode tip, the length of electric arc, and the liquid level of molten bath can be achieved. The computed tomography for SAF can be realized by the detection for smelting.

• 비파괴검사학회지
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• 제33권1호
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• pp.14-19
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• 2013

금속 재료의 비선형 파라미터는 고유한 물성치로서 기본주파수의 음압의 크기($A_1$)과 2차고조파의 음압의 크기($A_2$)을 측정하면 산정할 수 있다. 하지만, 실험적으로 $A_1$과 $A_2$를 측정하는 것은 매우 복잡한 변환 과정이 필요하기 때문에 현재 많은 연구자들이 비선형 파라미터의 절대값을 측정하지 않고, 전압 변화를 관찰하는 비선형 파라미터의 상대값을 측정하고 있다. 하지만, 비선형 파라미터 상대값으로는 재료의 물성치를 대변할 수가 없기 때문에, 열화도에 따른 시편 측정에만 사용할 수 있는 제약이 있다. 따라서 본 연구에서는 정전용량 측정기법(capacitive detector)보다는 비용이 적게 소모되고 현장 적용이 가능한 압전형 수신기법(piezoelectric detection)을 이용하여 비선형 파라미터의 절대값을 측정하기 위한 시스템을 구축하였다. $A_1^2vsA_2$ 그래프로 시스템의 선형성을 검증하고 시험편인 fused silica와 Al2024-T4에 대한 비선형 파라미터를 측정하였다.

• 응용통계연구
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• 제22권4호
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• pp.735-744
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• 2009

이 논문에서는 장기억 과정에서의 변화점을 빨리 검출하는 베이지안 추론방법에 대해 알아본다. 장기억 과정에서의 베이지안 추정은 장기억 모수값에 따라 전체 자료에 대한 부분차분을 계산해야 하기 때문에 수행시간이 많이 걸린다는 문제가 있다. 이 논문에서는 이러한 문제를 해결하고자 장기억 모수공간을 그룹화하여 순서형으로 범주화시킨 후 설명력이 가장 높은 범주의 대표값을 선택하게 하였다. 이 방법은 초기단계에서 범주의 대표값에 대해 한번씩만 부분차분을 계산하면 되기 때문에, 매번 계산해야 하는 추정하는 방법보다, 특히 시계열자료의 수가 많은 경우, 상대적으로 빠른 베인지안 추론이 가능하다. 또한 장기억 모수공간이 (0,0.5) 이기 때문에 모수공간을 적절하게 그룹화한다면 장기억 모수를 선택하는 것이 모수를 추정하는 것에 비해 큰 차이가 없다. 이 논문에서는 나일강 수위자료 실증분석을 통해 제안된 방법의 타당성을 확인해본다.

• 자동차안전학회지
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• 제13권4호
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• pp.129-143
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• 2021

This paper proposes actuator fault detection and adaptive fault-tolerant control algorithms using performance index and human-like learning for longitudinal autonomous vehicles. Conventional longitudinal controller for autonomous driving consists of supervisory, upper level and lower level controllers. In this paper, feedback control law and PID control algorithm have been used for upper level and lower level controllers, respectively. For actuator fault-tolerant control, adaptive rule has been designed using the gradient descent method with estimated coefficients. In order to adjust the control parameter used for determination of adaptation gain, human-like learning algorithm has been designed based on perceptron learning method using control errors and control parameter. It is designed that the learning algorithm determines current control parameter by saving it in memory and updating based on the cost function-based gradient descent method. Based on the updated control parameter, the longitudinal acceleration has been computed adaptively using feedback law for actuator fault-tolerant control. The finite window-based performance index has been designed for detection and evaluation of actuator performance degradation using control error.

• Smart Structures and Systems
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• 제23권4호
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• pp.359-371
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• 2019

As part of a structural health monitoring system, the relative geometric relationship between a ship and bridge has been recognized as important for bridge authorities and ship owners to avoid ship-bridge collision. This study proposes a novel computer vision method for the real-time geometric parameter identification of moving ships based on a single shot multibox detector (SSD) by using transfer learning techniques and monocular vision. The identification framework consists of ship detection (coarse scale) and geometric parameter calculation (fine scale) modules. For the ship detection, the SSD, which is a deep learning algorithm, was employed and fine-tuned by ship image samples downloaded from the Internet to obtain the rectangle regions of interest in the coarse scale. Subsequently, for the geometric parameter calculation, an accurate ship contour is created using morphological operations within the saturation channel in hue, saturation, and value color space. Furthermore, a local coordinate system was constructed using projective geometry transformation to calculate the geometric parameters of ships, such as width, length, height, localization, and velocity. The application of the proposed method to in situ video images, obtained from cameras set on the girder of the Wuhan Yangtze River Bridge above the shipping channel, confirmed the efficiency, accuracy, and effectiveness of the proposed method.

• 대한전기학회논문지:전력기술부문A
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• 제48권3호
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• pp.270-277
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• 1999

This paper deals with the maneuver detection and target tracking problem in uncertain parameter systems using a robust{{{{ { H}_{ } }}}} FIR filter to improve the unacceptable tracking performance due to the parametr uncertainty. The tracking filter used in the current paper is based on the robust{{{{ { H}_{ } }}}} FIR filter proposed by Kwon et al. [1,2] to estimate the state signal in uncertain systems with parameter uncertainty, and the basic scheme of the proposed method is the input estimation approach. Tracking performance of the maneuver detection and target tracking method proposed is compared with other techniques, Bogler allgorithm [4] and FIR tracking filter [2], via some simulations to examplify the good tracking performance of the proposed method over other techniques.

• 대한건축학회논문집:구조계
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• 제34권1호
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• pp.27-32
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• 2018

This work provides the analytical methods to represent the updated form of stiffness or flexibility matrices using the measurements of the first few natural frequencies and the corresponding mode shapes. This study derives the mathematical forms on the variance of stiffness or flexibility matrices to minimize the performance index in the satisfaction of the eigen-function including the residual force depending on the measured data. The proposed methods can be utilized in detecting damage and updating the parameter matrices deviated from the analytical parameter matrices. The validity of the proposed methods is investigated in a numerical experiment of truss structure and the numerical results of stiffness-based and flexibility-based methods are compared. The sensitivity to the external noise is also examined for applying to the practical work.

• International Journal of Computer Science & Network Security
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• 제22권7호
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• pp.165-170
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• 2022

Lying is nuisance to all, and all liars knows it is nuisance but still keep on lying. Sometime people are in confusion how to escape from or how to detect the liar when they lie. In this research we are aiming to establish a dynamic platform to identify liar by using video analysis especially by calculating the ratio of changes in their appearance when they lie. The platform will be developed using a machine learning algorithm along with the dynamic classifier to classify the liar. For the experimental analysis the dataset to be processed in two dimensions (people lying and people tell truth). Both parameter of facial appearance will be stored for future identification. Similarly, there will be standard parameter to be built for true speaker and liar. We hope this standard parameter will be able to diagnosed a liar without a pre-captured data.

• Smart Structures and Systems
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• 제6권7호
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• pp.811-833
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• 2010

Vibration control and health monitoring of building structures have been actively investigated in recent years but treated separately according to the primary objective pursued. This paper presents a general approach in the time domain for integrating vibration control and health monitoring of a building structure to accommodate various types of control devices and on-line damage detection. The concept of the time-domain approach for integrated vibration control and health monitoring is first introduced. A parameter identification scheme is then developed to identify structural stiffness parameters and update the structural analytical model. Based on the updated analytical model, vibration control of the building using semi-active friction dampers against earthquake excitation is carried out. By assuming that the building suffers certain damage after extreme event or long service and by using the previously identified original structural parameters, a damage detection scheme is finally proposed and used for damage detection. The feasibility of the proposed approach is demonstrated through detailed numerical examples and extensive parameter studies.