• 전산구조공학
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• 제11권4호
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• pp.135-146
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• 1998

대형 시스템의 건전성 평가를 위한 동적 재하시험에 있어서 변위를 측정하는 것보다 가속도를 측정하는 것이 수월하나 대부분의 공학적 기준은 응력과 비례관계를 지니는 변화를 기준으로 하고 있다. 본 연구에서는 시스템의 재하시험시 측정된 가속도신호를 이용하여 변위응답을 산정하는데 그 목적을 두고 적분을 위한 신호처리시 발생되는 문제점을 정상상태 및 천이영역에 대하여 규명하였다. 기존의 연구에서 고려하지 못하였던 초기조건의 항을 도입함으로써 시간영역의 적분과 주파수영역의 적분결과가 일치함을 해석적으로 입증하였으며 이동하중을 받는 보의 동적거동에 대하여 제시된 타당성을 검증하였다.

• International Journal of Railway
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• 제2권4호
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• pp.180-186
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• 2009

High speed railway challenge the design, construction and maintaining of traditional railway, many traditional design concepts have been changed. Transition of railway and bridge has two main problems. one is that different lines have different ability of resisting distortion in area of trial load, which was known that problem of smooth transition of stiffness, the other is that differential settlement between artificial structure and earth structure cause bending of railway. The two problems have effect on train moving. The principle of processing transition of railway and bridge is same in world, but it is difficult to find relationship between design standard of transition, vehicle performance, line standard, design speed and so on form documentation and data reports. Based on mechanics, the paper analyzed dynamic performance of transition of high speed railway, studied various rough elements which is effective to train moving, built mathematical model of interaction of train and transition of high speed railway and developed numerical simulation software. In various different work conditions, we did great quantity of numerical simulation, comprehensive analysis and performance analysis.

• 한국해양공학회지
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• 제21권6호
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• pp.42-46
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• 2007

The impact of a single wave generated by a dam break with a tall structure is modeled with a three-dimensional version of the Moving particle semi-implicit (MPS) method. The particle method is more feasible and effective than methods based on grid connection problems involving violent free surface motions. In the present study, the Tsunami impact load and the change of longitudinal velocity component around the structure, which are obtained from the numerical simulation, are compared to those from experiments.

• Smart Structures and Systems
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• 제24권5호
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• pp.617-630
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• 2019

Currently most of the vision-based structural identification research focus either on structural input (vehicle location) estimation or on structural output (structural displacement and strain responses) estimation. The structural condition assessment at global level just with the vision-based structural output cannot give a normalized response irrespective of the type and/or load configurations of the vehicles. Combining the vision-based structural input and the structural output from non-contact sensors overcomes the disadvantage given above, while reducing cost, time, labor force including cable wiring work. In conventional traffic monitoring, sometimes traffic closure is essential for bridge structures, which may cause other severe problems such as traffic jams and accidents. In this study, a completely non-contact structural identification system is proposed, and the system mainly targets the identification of bridge unit influence line (UIL) under operational traffic. Both the structural input (vehicle location information) and output (displacement responses) are obtained by only using cameras and computer vision techniques. Multiple cameras are synchronized by audio signal pattern recognition. The proposed system is verified with a laboratory experiment on a scaled bridge model under a small moving truck load and a field application on a footbridge on campus under a moving golf cart load. The UILs are successfully identified in both bridge cases. The pedestrian loads are also estimated with the extracted UIL and the predicted weights of pedestrians are observed to be in acceptable ranges.

• Structural Engineering and Mechanics
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• 제54권1호
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• pp.55-67
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• 2015

Taking the mid-span/center-point of the structure as the reference point of capturing the maximum dynamic response is very customary in the available literature of the moving load problems. In this article, the absolute maximum dynamic response of an Euler-Bernoulli beam subjected to a moving mass is widely investigated for various boundary conditions of the base beam. The response of the beam is obtained by utilizing a robust numerical method so-called OPSEM (Orthonormal Polynomial Series Expansion Method). It is underlined that the absolute maximum dynamic response of the beam does not necessarily take place at the mid-span of the beam and thus the conventional analysis needs modifications. Therefore, a comprehensive parametric survey of the base beam absolute maximum dynamic response is represented in which the contribution of the velocity and weight of the moving inertial objects are scrutinized and compared to the conventional version (maximum at mid-span).

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제53권3호
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• pp.188-195
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• 2004

This paper presents neural load torque observer that is used to deadbeat load torque observer and gain compensation by parameter estimator As a result, the response of the PMSM(permanent magnet synchronous motor) follows that nominal plant. The load torque compensation method is composed of a neural deadbeat observer To reduce the noise effect, the post-filter implemented by MA(moving average) process, is adopted. The parameter compensator with RLSM (recursive least square method) parameter estimator is adopted to increase the performance of the load torque observer and main controller The parameter estimator is combined with a high performance neural load torque observer to resolve the problems. The neural network is trained in on-line phases and it is composed by a feed forward recall and error back-propagation training. During the normal operation, the input-output response is sampled and the weighting value is trained multi-times by error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. As a result, the proposed control system has a robust and precise system against the load torque and the Parameter variation. A stability and usefulness are verified by computer simulation and experiment.

• 대한산업공학회지
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• 제16권2호
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• pp.23-36
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• 1990

A unit-load automated guided vehicle system is considered in which a single vehicle is operated on a unidirectional path in a closed loop. The vehicle serves a manufacturing cell moving pallets from one station to another based on the "First-Encountered-First-Serve" dispatching rule. An approximation method is developed to compute the mean waiting time of an arbitrary pallet at each station. Extensive numerical experiments, performed for various problems, yield fairly good results in most of the cases compared with those obtained by simulation method.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 추계학술대회논문집
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• pp.760-765
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• 2003

This study is performed in order to determine a method to solve vibration-borne problems by isolating the vibration that is generated by vehicles in case a road passes through a building and also to verify its applicability and effect both theoretically and experimentally.

• 전력전자학회논문지
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• 제9권1호
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• pp.42-49
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• 2004

본 논문은 데드비트 외란 관측기를 사용한 외부 부하 외란 보상과 파라미터 추정기에 의한 보상 이득의 조정을 나타내고 있다. 결론적으로 PMSM의 응답은 지표 시스템을 따른다. 부하 토크 보상 방법은 데드비트 관측기로 구성된다. 노이즈 영향을 감소시키기 위해 MA 처리에 의해 구현된 후단 필터를 적용하였고, RLSM 파라미터 추정기를 가진 파라미터 보상기가 주어진 실제 시스템의 이득 계산시 사용된 파라미터로 가상 동작하여 이득이 오차가 없는 것처럼 동작하게 한다. 제안된 추정기는 문제를 풀기 위해 고성능 외란 관측기와 조합하여 사용한다. 제안된 제어 시스템은 부하토크와 파라미터 변화에 대해 강인하고 정밀한 시스템이 된다. 이상의 제안된 시스템의 안정성과 유용함이 컴퓨터 시뮬레이션과 실험을 통하여 확인되었다.

• Journal of Power Electronics
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• 제8권4호
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• pp.354-362
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• 2008

This paper presents neural load torque compensation method which is composed of a deadbeat load torque observer and gains compensation by a parameter estimator. As a result, the response of the PMSM (permanent magnet synchronous motor) obtains better precision position control. To reduce the noise effect, the post-filter is implemented by a MA (moving average) process. The parameter compensator with an RLSM (recursive least square method) parameter estimator is adopted to increase the performance of the load torque observer and main controller. The parameter estimator is combined with a high performance neural load torque observer to resolve problems. The neural network is trained in online phases and it is composed by a feed forward recall and error back-propagation training. During normal operation, the input-output response is sampled and the weighting value is trained multi-times by the error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. As a result, the proposed control system has a robust and precise system against load torque and parameter variation. Stability and usefulness are verified by computer simulation and experiment.