• Smart Structures and Systems
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• 제13권1호
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• pp.155-171
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• 2014

Various monitoring techniques are now available for structural health monitoring and Acoustic Emission (AE) is one of them. One of the major advantages of the AE technique is its capability to locate active cracks in structural members. AE crack locating approaches are affected by the signal attenuation and dispersion of elastic waves due to inhomogeneity and geometry of reinforced concrete (RC) members. In this paper, a novel technique is described based on signal processing and sensor arrangement to process multisensory AE data generated by the onset and propagation of cracks and is validated with experimental results from an in-situ load test. Considering the sources of uncertainty in the AE crack location process, a methodology is proposed to capture and locate events generated by cracks. In particular, the relationship between AE events and load is analyzed, and the feasibility of using the AE technique to evaluate the cracking behavior of two RC slab strips during loading to failure is studied.

• 제어로봇시스템학회논문지
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• 제6권3호
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• pp.256-262
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• 2000

This paper proposes a new sliding mode controller combined with a multi-layer neural network using the error back propagation learning algorithm,, The network acts as a compensator of the conventional sliding mode controller to improve the control performance when initial assumptions of uncertainty bounds of system parameters are violated. The proposed controller can reduce th steady state error of conventional sliding mode controller with the boundary layer technique Computer simulation results show that the proposed method is effective to control dynamic systems with unexpectably large uncertainties.

• 제어로봇시스템학회논문지
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• 제6권4호
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• pp.305-312
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• 2000

This paper presents a new control scheme using a sliding mode controller with a multilayer neural network for the robot manipulator operating under the sea which has large uncertainties such as the buoyancy and the added mass/moment of inertia. The multilayer neural network using the error back propagation loaming algorithm acts as a compensator of the conventional sliding mode controller to improve the control performance when the initial assumptions of uncertainty bounds are not valid. Computer simulation results show that the proposed control scheme gives an effective path way to cope with the unexpected large uncertainties in the underwater robot manipulator.

• 한국생산제조학회지
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• 제19권6호
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• pp.804-811
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• 2010

The fatigue crack propagation is stochastic in nature, because the variables affecting the fatigue behavior are random and have uncertainty. Therefore, the fatigue life prediction is critical for the design and the maintenance of many structural components. In this study, fatigue experiments are conducted on the specimens of magnesium alloy AZ31 under various conditions such as thickness of specimen, the load ratio and the loading condition. The probability distribution fit to the fatigue failure life are investigated through a probability plot paper by these conditions. The probabilities of failure at various conditions are also estimated. The fatigue design life is predicted by using the Weibull distribution.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.819-821
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• 1998

This paper deals with a method or a residual generation for fault isolation in a centrifugal pump with a water circulation system, driven by a speed controlled dc motor. It is based on parity relations derived from the moving-average model of the system and is used to identify sensor faults and two possible brush and impeller faults, where the former is dealt with additive faults, while the latter characterized as discrepancies between the nominal and actual plant parameters of the system is modelled by multiplicative faults. We will represent the propagation of this uncertainty to the model matrices by the approximate handling of partial derivatives of polynomials. With multiplicative faults, the transformation matrix implemented in the residual generator are calculated on-line. The simulation studies demonstrate that small changes of the system can be detected and diagnosed by using the method.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
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• pp.219-222
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• 1996

During the navigation of mobile robot, one of the essential task is to determination the absolute location of mobile robot. In this paper, we proposed a method to determine the position of the camera from a landmark through the visual image of a quadrangle typed landmark using neural network. In determining the position of the camera on the world coordinate, there is difference between real value and calculated value because of uncertainty in pixels, incorrect camera calibration and lens distortion etc. This paper describes the solution of the above problem using BPN(Back Propagation Network). The experimental results show the superiority of the proposed method in comparison to conventional method in the performance of determining camera position.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 춘계학술대회 학술발표 논문집
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• pp.165-170
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• 1997

During the navigation of mobile robot, one of the essential task if to determine the absolute position of mobile robot. In this paper, a method to determine the position of the camera using a vanishing point and neural networks without landmark if proposed. In determining the position of the camera on the world coordinate, there are differences between the real value and the calculated value because of uncertainty in pixels, incorrect camera calibration and lens distortion etc. This paper describes the solution of the above problem using BPNN(Back Propagation Neural Network) and experimental results show the capability to adapt for a mobile robot.

• 대한공간정보학회지
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• 제3권2호
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• pp.91-100
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• 1995

본 논문은 위성탐사 이미지의 분류에서 한 화소(SPOT HRV의 밴드 1-3의 경우 $200{\times}20m$)에 포함된 혼합된 정보의 분류를 시도한다. 먼저 기존의 분류기법에서 발생되는 정보의 손실과 혼합화소에 내포된 정보의 불확실성에 대해 알아보고 이를 해결하기 위한 방법으로 피지 시그모이드 함수와 역전파 신경망을 이용한 기법을 제안하며, 이를 실험하고 비교 분석한다.

• Structural Engineering and Mechanics
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• 제56권5호
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• pp.767-785
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• 2015

The stochastic finite element method is employed to obtain a stochastic dynamic model of angled beams subjected to impact loads when uncertain material properties are described by random fields. Using the perturbation technique in conjunction with a precise time integration method, a random analysis approach is developed for efficient analysis of random elastic waves. Formulas for the mean, variance and covariance of displacement, strain and stress are introduced. Statistics of displacement and stress waves is analyzed and effects of bend angle and material stochasticity on wave propagation are studied. It is found that the elastic wave correlation in the angled section is the most significant. The mean, variance and covariance of the stress wave amplitude decrease with an increase in bend angle. The standard deviation of the beam material density plays an important role in longitudinal displacement wave covariance.

• IEIE Transactions on Smart Processing and Computing
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• 제4권4호
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• pp.216-223
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• 2015

The autonomous underwater vehicle (AUV) is being widely researched in order to achieve superior performance when working in hazardous environments. This research focuses on using image processing techniques to estimate the AUV's egomotion and the changes in orientation, based on image frames from different time frames captured from a single high-definition web camera attached to the bottom of the AUV. A visual odometry application is integrated with other sensors. An internal measurement unit (IMU) sensor is used to determine a correct set of answers corresponding to a homography motion equation. A pressure sensor is used to resolve image scale ambiguity. Uncertainty estimation is computed to correct drift that occurs in the system by using a Jacobian method, singular value decomposition, and backward and forward error propagation.