• Smart Structures and Systems
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• 제23권3호
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• pp.263-278
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• 2019

Moving train load parameters, including train speed, axle spacing, gross train weight and axle weights, are identified based on strain-monitoring data. In this paper, according to influence line theory, the classic moving force identification method is enhanced to handle time-varying velocity of the train. First, the moments that the axles move through a set of fixed points are identified from a series of pulses extracted from the second derivative of the structural strain response. Subsequently, the train speed and axle spacing are identified. In addition, based on the fact that the integral area of the structural strain response is a constant under a unit force at a unit speed, the gross train weight can be obtained from the integral area of the measured strain response. Meanwhile, the corrected second derivative peak values, in which the effect of time-varying velocity is eliminated, are selected to distribute the gross train weight. Hence the axle weights could be identified. Afterwards, numerical simulations are employed to verify the proposed method and investigate the effect of the sampling frequency on the identification accuracy. Eventually, the method is verified using the real-time strain data of a continuous steel truss railway bridge. Results show that train speed, axle spacing and gross train weight can be accurately identified in the time domain. However, only the approximate values of the axle weights could be obtained with the updated method. The identified results can provide reliable reference for determining fatigue deterioration and predicting the remaining service life of railway bridges.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 춘계학술대회 논문집
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• pp.346-350
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• 1996

This paper presents a Neural Network Identification (NNI) method for modeling of highly complicated nonlinear and time varing human system with a pneumatically driven mock circulation system of Left Ventricular Assist Device(LVD). This system consists of electronic circuits and pneumatic driving circuits. The initation of systole and the pumping duration can be determined by the computer program. The line pressure from a pressure transducer inserted in the pneumatic line was recorded. System modeling is completed using the adaptively trained backpropagation learning algorithms with input variables, Heart Rate(HR), Systole-Diastole Rate(SDR), which can vary state of system, and preload, afterload, which indicate the systemic dynamic characteristics and output parameters are preload, afterload.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 A
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• pp.308-310
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• 1992

Adaptive noise cancelling using system identification techniques for cancelling power line interference in the electrocardiogram (ECG) is presented. This method is sensitive and self-adjusting to both slow and abrupt changes in the AC interference amplitude and frequency. Computer simulation were done to compare this method with the Lekov's method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국내학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.511-517
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• 1988

Movement order program of robot operating program is generally made by teach-in method. Therefore in most cases it is sufficient as long as the robot system shows a reguired repeatability for the working conditions. But the trend in the robot application moves to the automatic generation of the working programs. A mathematical robot model similar to the reality is necessary for the analysis of the kinematic transformation of the robot system. The purposes of this paper are to make a better describing form and to suggest an automatic algorithm for kinematic parameter identification.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1998년도 추계학술대회 논문집
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• pp.54-59
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• 1998

In order to minimize straightness error of deflected shafts, a automatically bending process control system is designed, fabricated, and studied. The multi-step straightening process and the three-point bending process are developed for the geometric adaptive straightness control. Load-deflection relationship, on-line identification of variations of material properties, on-line springback prediction, and studied for the three-point bending processes. Selection of a loading point supporting condition are derved form fuzzy inference and fuzzy self-learning method in the multi-step straighternign process. Automatic straightening machine is fabricated by using the develped ideas. Validity of the proposed system si verified through experiments.

• 한국식품영양학회지
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• 제1권2호
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• pp.31-36
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• 1988

An adaptive on-line optimization method has been applied to test the ability to maximize the cellular productivity of a continuous methylotroph culture system which was simulated by a variable yield Monod-type model. Optimum dilution rate and productivity were successively obtained and maintained at all times by the algorithm that utilizes steepest descent technique as optimization method and recursive least-square method with forgetting factor as dynamic model identification.

• ETRI Journal
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• 제28권3호
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• pp.383-385
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• 2006

A new meander-line antenna consisting of two open-ended strips is proposed for a compact and broadband UHF radio frequency identification tag. An equivalent circuit model for the proposed antenna is derived and used to perform a simple and wideband impedance match to an arbitrary complex impedance of a tag chip without any additional matching network. The performance of the proposed antenna is validated by comparing calculated and measured results, which show good agreement.

• 말소리와 음성과학
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• 제5권1호
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• pp.91-98
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• 2013

This paper investigated Korean prosody as it relates to graded internal structure in an identification function. Within Korean prosody, variants regarded as dialectal variations can appear as different prosodic scales, which contain the range of within-category variations. The current experiment was intended to show how the prosodic scale corresponding to the range of within-category differences relates to f0 contours for speakers of two Korean dialects, North Kyungsang and South Cholla. In an identification task, participants responded by selecting an item from two answer choices. The probability of choosing the correct response from the two choices was computed by a logistic regression analysis using intercepts and slopes. That is, the correct response between two choices was used to show a linear line with an s-shape presentation. In this paper, to investigate the graded internal structure of labeling, 25%, 50%, and 75% of predicted probability were assessed. Listeners from North Kyungsang showed progressive variations, whereas listeners from South Cholla revealed random patterns in the internal structure of the identification function. In this paper, the results were plotted using scatterplot graphs, applying the range of within-category variation and predicted probability obtained from the logistic regression analyses. The scatterplot graphs showed the different degree of the responses for f0 scales (i.e., variations within categories). The results demonstrate that the gradient structures of native pitch accent users become more progressive in response to f0 scales.

• 대한기계학회논문집A
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• 제29권12권
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• pp.1586-1596
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• 2005

In this paper, a structural damage identification method (SDIM) is developed to identify the line crack-like directional damages generated within a cylindrical shell. First, the equations of motion for a damaged cylindrical shell are derived. Based on a theory of continuum damage mechanics, a small material volume containing a directional damage is represented by the effective orthotropic elastic stiffness, which is dependent of the size and the orientation of the damage with respect to the global coordinates. The present SDIM is then derived from the frequency response function (FRF) directly solved from the equations of motion of a damaged shell. In contrast with most existing SDIMs which require the modal parameters measured in both intact and damaged states, the present SDIM may require only the FRF-data measured at damaged state. By virtue of utilizing FRF-data, one may choose as many sets of excitation frequency and FRF measurement point as needed to acquire a sufficient number of equations for damage identification analysis. The numerically simulated damage identification tests are conducted to study the feasibility of the present SDIM.

• Smart Structures and Systems
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• 제11권1호
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• pp.19-34
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• 2013

The objective of this paper is to develop on-line system parameter estimation and damage detection technique from the response measurements through using the Recursive Covariance-Driven Stochastic Subspace identification (RSSI-COV) approach. To reduce the effect of noise on the results of identification, discussion on the pre-processing of data using recursive singular spectrum analysis (rSSA) is presented to remove the noise contaminant measurements so as to enhance the stability of data analysis. Through the application of rSSA-SSI-COV to the vibration measurement of bridge during scouring experiment, the ability of the proposed algorithm was proved to be robust to the noise perturbations and offers a very good online tracking capability. The accuracy and robustness offered by rSSA-SSI-COV provides a key to obtain the evidence of imminent bridge settlement and a very stable modal frequency tracking which makes it possible for early warning. The peak values of the identified $1^{st}$ mode shape slope ratio has shown to be a good indicator for damage location, meanwhile, the drastic movements of the peak of $2^{nd}$ mode slope ratio could be used as another feature to indicate imminent pier settlement.