• Structural Engineering and Mechanics
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• v.39 no.1
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• pp.77-91
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• 2011

A simply structural damage detection software is developed to identification damage in beams. According to linear fracture mechanics theory, the localized additional flexibility in damage vicinity can be represented by a lumped parameter element. The damaged beam is modeled by wavelet-based elements to gain the first three frequencies precisely. The first three frequencies influencing functions of damage location and depth are approximated by means of surface-fitting techniques to gain damage detection database of forward problem. Then the first three measured natural frequencies are employed as inputs to solve inverse problem and the intersection of the three frequencies contour lines predict the damage location and depth. The DLL (Dynamic Linkable Library) file of damage detection method is coded by C++ and the corresponding interface of software is coded by virtual instrument software LabVIEW. Finally, the software is tested on beams and shafts in engineering. It is shown that the presented software can be used in actual engineering structures.

• Earthquakes and Structures
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• v.22 no.4
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• pp.345-353
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• 2022

The configuration of an open ground floor (pilotis) is a common and very critical irregularity observed in multistory reinforced concrete frame structures. The characteristics and the geometrical formation of the beams of the first story proved to be a critical parameter for the overall seismic behavior of this type of Reinforced Concrete (RC) structures. In this work the combination of open ground floor (pilotis) morphology with very strong perimetrical beams at the level of the first story is studied. The observation of the seismic damages and the in situ measurements of the fundamental period of four buildings with this morphology and Π-shaped plan view are presented herein. Further analytical results of a pilotis type Π-shaped RC structure are also included in the study. From the measurements and the analytical results yield that the open ground floor configuration greatly influences the fundamental period whereas this morphology in combination with strong beams can lead to severe local shear damages in the columns of the ground floor. The structural damage was limited in the columns of the ground floor and yet based on the changes of the in situ measured fundamental period the damaged level is assessed as DI=88%. Furthermore, due to the Π-shape of the plan view the tendency of the parts of the building to move independently strongly influences the distribution of the damages over the ground floor vertical elements.

• ETRI Journal
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• v.15 no.2
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• pp.35-51
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• 1993

This paper presents function approximation based on nonparametric estimation. As an estimation model of function approximation, a three layered network composed of input, hidden and output layers is considered. The input and output layers have linear activation units while the hidden layer has nonlinear activation units or kernel functions which have the characteristics of bounds and locality. Using this type of network, a many-to-one function is synthesized over the domain of the input space by a number of kernel functions. In this network, we have to estimate the necessary number of kernel functions as well as the parameters associated with kernel functions. For this purpose, a new method of parameter estimation in which linear learning rule is applied between hidden and output layers while nonlinear (piecewise-linear) learning rule is applied between input and hidden layers, is considered. The linear learning rule updates the output weights between hidden and output layers based on the Linear Minimization of Mean Square Error (LMMSE) sense in the space of kernel functions while the nonlinear learning rule updates the parameters of kernel functions based on the gradient of the actual output of network with respect to the parameters (especially, the shape) of kernel functions. This approach of parameter adaptation provides near optimal values of the parameters associated with kernel functions in the sense of minimizing mean square error. As a result, the suggested nonparametric estimation provides an efficient way of function approximation from the view point of the number of kernel functions as well as learning speed.

• Journal of Welding and Joining
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• v.11 no.4
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• pp.44-56
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• 1993

The arc welding processes are substantially nonlinear, in addition to being highly coupled multivariable systems, Frequently, not all the variables affecting the welding quality are known, nor may they be easily quantified. From this point of view, decoupling between the welding parameters from the welding quality is very difficult, which makes it also difficult to control the welding parameters for obtaining the desired welding quality. In this study, a neural network based on the backpropagation algorithm was implemented and adopted for the selection of gas metal arc welding parameters of the fillet joint, that is, welding current, arc voltage and welding speed. The performance of the neural network for modeling the relationship between the welding quality and welding parameters was presented and evaluated by using the actual welding data. To obtain the optimal neural network structure, various types of the neural network structures were tested with the experimental data. It was revealed that the neural network can be effectively adopted to select the appropriate gas metal arc welding parameter of fillet joints for a given weld quality.

• Journal of the Society of Naval Architects of Korea
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• v.40 no.5
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• pp.43-52
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• 2003

Two methods which estimate manoeuvring derivatives in the model of hydrodynamic force and moment acting on a manoeuvring ship using sea trial data were compared. One is the widely used parameter estimation method by using the Extended Kalman Filter (EKF), which estimates state variables of linearized state space model at every instant after dealing with the coefficients as the augmented state variables. The other one is the Estimation-Before-Modeling (EBM) technique, so called the two-step method. In the first step, hydrodynamic force of which dynamic model is assumed the third-order Gauss-Markov process is estimated along with motion variables by the EKF and the modified Bryson-Frazier smoother. Then, in the next step, manoeuvring derivatives are identified through the regression analysis. If the exact structure of hydrodynamic force could be known, which was an ideal case, the EKF method would be regarded as being more superior compared to the EBM technique. However the EBM technique was more robust than the EKF method from a realistic point of view where the assumed model structure was slightly different from the real one.

• The Korean Journal of Applied Statistics
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• v.29 no.3
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• pp.463-470
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• 2016

In analysing a time series on the frequency domain, the spectral estimator (or periodogram) is a very useful statistic to identify the periods of a time series. However, the spectral estimator is very sensitive in nature to outliers, so that the spectral estimator in terms of M-estimation has been studied by some researchers. Pak (2001) proposed an empirical method to choose a tuning parameter for the Huber's M-estimating function. In this article, we try to implement Pak's estimation proposal in the spectral estimator. We use the Korean housing price index as an example data set for comparing various M-estimating results.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.10
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• pp.34-43
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• 1990

An improved parameter adaptation and control law for robot manipulator are proposed based on a linearized parametric system equation and augmented error vectors. In view of the modeling error and parasitics with small time constants which inevitably introduced during modelling process, their effects on the robustness of the system performance are reviewed and as an conutermearsure, adaptation mechanism with low pass filter is proposed. Proposed parameter adaptation and control low assure the stability of the robot manipulator in the large without further assumption. Computer simulation shows its effectiveness of the proposed adaptation mechanism to improve the robustness of the system in presence of the parasitics in the system and superior performance for high speed operations make it an attractive option in application of the adaptive control field for robot manipulator.

• Journal of the Ergonomics Society of Korea
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• v.7 no.2
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• pp.31-44
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• 1988

If an error occurs in the automatic mode when the advanced teleoperator system performs a task in hostile environment then the automatic mode changes into the manual mode. The operation by the control program and the operation by a human recover the error in the manual mode. The system resumes the automatic mode and continues the given task. It is necessary to improve the manual mode in order to make the best use of a man-robot system, as a part of the human interface technique. Therefore, the error recovery task is performed by combining the operation by the control program representing autonomy of a robot and the operation by a human representing versatility of a human operator effectively in the view point of human factors engineering. The geometric inverse kinematics is used for the calculation of the robot joint values in the operation by the control program. The singularity operation error and the parameter operation error often occur in this procedure. These two operation errors increase the movement time of the robot and the coordinate reading time, during the error recovery task. A singularity algorithm, parameter algorithm and fuzzy control are studied so as to remove the disadvantages of geometric inverse kinematics. And the geometric straight line motion is studied so as to improve the disadvantages of the operation by a human.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.3 no.2
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• pp.11-17
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• 2004

In this paper we propose a new conceptual system for a network clock in which all node clocks are simultaneously synchronized to the national standard by intermediation parameter of satellite time. Experiments have shown the possibility of its adoption by real networks. The new proposed method has various structural benefits, in particular all node clocks can be kept at the same hierarchical quality in contrast to the existing method. The measurement results show that the accuracy of the experimental slave clock system can be kept within a few parts In 1012 and the MTIE (Maximum Time Interval Error) sufficiently meets ITU-T G.811 for the primary reference clock. A prototype system with fully automatic operational functions has been realized at present and is expected to be directly used for communication network synchronization in the near future.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.3
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• pp.146-152
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• 2013

In this paper, we have proposed and experimentally demonstrated an intensity-based self-referencing fiber optic sensor. The proposed fiber optic sensor consists of a broadband light source (BLS), fiber Bragg grating (FBG), tunable Fabry-Perot (F-P) filter, and LabVIEW program. We define the measurement parameter (X) and the calibration parameter (${\beta}$) to determine the transfer function(H) of the self-referencing fiber optic sensor, and the validity of the theoretical analysis is confirmed by experiments. The self-referencing characteristic for the proposed system has been validated by showing that the measurement parameter (X) is invariant for BLS optical power attenuations of 0 dB, 3 dB, and 6 dB. Also, the measured result is irrelevant to the FBGs with different characteristics. This means that the proposed fiber optic sensor offers the flexibility for determining the FBGs needed for implementation. Experimental results for the proposed fiber optic sensor are in good agreement with a theoretical analysis for BLS optical power attenuations and for three FBG pairs with different characteristics. So, the proposed fiber optic sensor has several benefits, including the self-referencing characteristic and the flexibility to determine the FBGs.