• Title/Summary/Keyword: Model Update Method

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Bayesian model update for damage detection of a steel plate girder bridge

  • Xin Zhou;Feng-Liang Zhang;Yoshinao Goi;Chul-Woo Kim
    • Smart Structures and Systems
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    • v.31 no.1
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    • pp.29-43
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    • 2023
  • This study investigates the possibility of damage detection of a real bridge by means of a modal parameter-based finite element (FE) model update. Field moving vehicle experiments were conducted on an actual steel plate girder bridge. In the damage experiment, cracks were applied to the bridge to simulate damage states. A fast Bayesian FFT method was employed to identify and quantify uncertainties of the modal parameters then these modal parameters were used in the Bayesian model update. Material properties and boundary conditions are taken as uncertainties and updated in the model update process. Observations showed that although some differences existed in the results obtained from different model classes, the discrepancy between modal parameters of the FE model and those experimentally obtained was reduced after the model update process, and the updated parameters in the numerical model were indeed affected by the damage. The importance of boundary conditions in the model updating process is also observed. The capability of the MCMC model update method for application to the actual bridge structure is assessed, and the limitation of FE model update in damage detection of bridges using only modal parameters is observed.

Automatic Local Update of Triangular Mesh Models Based on Measurement Point Clouds (측정된 점데이터 기반 삼각형망 곡면 메쉬 모델의 국부적 자동 수정)

  • Woo, Hyuck-Je;Lee, Jong-Dae;Lee, Kwan-H.
    • Korean Journal of Computational Design and Engineering
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    • v.11 no.5
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    • pp.335-343
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    • 2006
  • Design changes for an original surface model are frequently required in a manufacturing area: for example, when the physical parts are modified or when the parts are partially manufactured from analogous shapes. In this case, an efficient 3D model updating method by locally adding scan data for the modified area is highly desirable. For this purpose, this paper presents a new procedure to update an initial model that is composed of combinatorial triangular facets based on a set of locally added point data. The initial surface model is first created from the initial point set by Tight Cocone, which is a water-tight surface reconstructor; and then the point cloud data for the updates is locally added onto the initial model maintaining the same coordinate system. In order to update the initial model, the special region on the initial surface that needs to be updated is recognized through the detection of the overlapping area between the initial model and the boundary of the newly added point cloud. After that, the initial surface model is eventually updated to the final output by replacing the recognized region with the newly added point cloud. The proposed method has been implemented and tested with several examples. This algorithm will be practically useful to modify the surface model with physical part changes and free-form surface design.

FE-model Update for System Identification of PSC Girde (민감도 분석을 통한 프리스트레스 콘크리트 거더의 유한요소모델 개선)

  • Ho, Duc-Duy;Lee, So-Young;Kim, Jeong-Tae
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2009.04a
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    • pp.425-428
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    • 2009
  • This paper presents a sensitivity-based finite element (FE)-model update procedure for prestressed concrete (PSC) girder bridge model using vibration test results. Firstly, the stiffness parameters of the structure such as flexural rigidity of concrete and flexural rigidity of tendon are chosen as updating parameters. Next, the numerical frequencies of first two bending modes are calculated using a three-dimensional FE model which is established for the PSC girder. Then, the corresponding experimental frequencies which are obtained from forced vibration tests are selected. In order to perform the model update, the eigensensitivity-based method is employed. Finally, the effect of prestress-loss on the stiffness parameters is evaluated.

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An Optimal Denormalization Method in Relational Database with Response Time Constraint (관계형 데이터베이스에서 응답시간에 제약이 있는 경우 최적 역정규화 방법)

  • 장영관
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.26 no.3
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    • pp.1-9
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    • 2003
  • Databases are central to business information systems and RDBMS is most widely used for the database system. Normalization was designed to control various anomalies (insert, update, delete anomalies). However, normalized database design does not account for the tradeoffs necessary for performance. In this research, I model a database design method considering denormalization of duplicating attributes in order to reduce frequent join processes. This model considers response time for processing each select, insert, update, delete transaction, and for treating anomalies. A branch and bound method is proposed for this model.

Probability-Based Context-Generation Model with Situation Propagation Network (상황 전파 네트워크를 이용한 확률기반 상황생성 모델)

  • Cheon, Seong-Pyo;Kim, Sung-Shin
    • The Journal of Korea Robotics Society
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    • v.4 no.1
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    • pp.56-61
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    • 2009
  • A probability-based data generation is a typical context-generation method that is a not only simple and strong data generation method but also easy to update generation conditions. However, the probability-based context-generation method has been found its natural-born ambiguousness and confliction problems in generated context data. In order to compensate for the disadvantages of the probabilistic random data generation method, a situation propagation network is proposed in this paper. The situation propagating network is designed to update parameters of probability functions are included in probability-based data generation model. The proposed probability-based context-generation model generates two kinds of contexts: one is related to independent contexts, and the other is related to conditional contexts. The results of the proposed model are compared with the results of the probabilitybased model with respect to performance, reduction of ambiguity, and confliction.

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Update Cycle Detection Method of Control Limits using Control Chart Performance Evaluation Model (관리도 성능평가모형을 통한 관리한계선 갱신주기 탐지기법)

  • Kim, Jongwoo;Park, Cheong-Sool;Kim, Jun Seok;Kim, Sung-Shick;Baek, Jun-Geol
    • Journal of Korean Institute of Industrial Engineers
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    • v.40 no.1
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    • pp.43-51
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    • 2014
  • Statistical process control (SPC) is an important technique for monitoring and managing the manufacturing process. In spite of its easiness and effectiveness, some problematic sides of application exist such that the SPC techniques are hardly reflect the changes of the process conditions. Especially, update of control limits at the right time plays an important role in acquiring a reasonable performance of control charts. Therefore, we propose the control chart performance evaluation index (CPEI) based on count data model to monitor and manage the performance of control charts. The CPEI could indicate the degree of control chart performance and be helpful to detect the proper update cycle of control limits in real time. Experiments using real manufacturing data show that the proper update intervals are made by proposed method.

Study on Nonlinear Filter Using Unscented Transformation Update (무향변환을 이용한 비선형 필터에 대한 연구)

  • Yoon, Jangho
    • Journal of Aerospace System Engineering
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    • v.10 no.1
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    • pp.15-20
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    • 2016
  • The optimal estimation of a general continuous-discrete system can be achieved through the solution of the Fokker-Planck equation and the Bayesian update. Due the high nonlinearity of the equation of motion of the system and the measurement model, it is necessary to linearize the both equation. To avoid linearization, the filter based on Fokker-Planck equation is designed. with the unscented transformation update mechanism, in which the associated Fokker-Planck equation was solved efficiently and accurately via discrete quadrature and the measurement update was done through the unscented transformation update mechanism. This filter based on the Direct Quadrature Moment of Method(DQMOM) and the unscented transformation update is applied to the bearing only target tracking problem. The proposed filter can still provide more accurate estimation of the state than those of the extended Kalman filter especially when measurements are sparse. Simulation results indicate that the advantages of the proposed filter based on the DQMOM and the unscented transformation update make it a promising alternative to the extended Kalman filter.

A Study on the GaAs MESFET Model Parameter Extraction (GaAs MESFET 모델 매개변수 추출에 관한 연구)

  • 박의준;박진우
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.16 no.7
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    • pp.628-639
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    • 1991
  • A new efficient method for GaAs MESFET model parameter extraction is proposed, which is based on the bias dependance of each parameter characteristics derved from the analytic model. The requiremnts of the method are only small-signal S-parameter measurements under the three bias variations. Fixation of the linear model parameter values in the optimization process is made using the sensitivity information of the model parameter obtained by the weighted Broyden update method, it is to improve the uniqueness and reliablility of the solution. The validity of the extracted values of the FET model parameters is confirmed by comparing the simulation results with the experimental data.

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A new optimization method for improving the performance of neural networks for optimization (최적화용 신경망의 성능개선을 위한 새로운 최적화 기법)

  • 조영현
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.34C no.12
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    • pp.61-69
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    • 1997
  • This paper proposes a new method for improving the performances of the neural network for optimization using a hyubrid of gradient descent method and dynamic tunneling system. The update rule of gradient descent method, which has the fast convergence characteristic, is applied for high-speed optimization. The update rule of dynamic tunneling system, which is the deterministic method with a tunneling phenomenon, is applied for global optimization. Having converged to the for escaping the local minima by applying the dynamic tunneling system. The proposed method has been applied to the travelling salesman problems and the optimal task partition problems to evaluate to that of hopfield model using the update rule of gradient descent method.

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Indoor Localization of a Mobile Robot Using External Sensor (외부 센서를 이용한 이동 로봇 실내 위치 추정)

  • Ko, Nak-Yong;Kim, Tae-Gyun
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.5
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    • pp.420-427
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    • 2010
  • This paper describes a localization method based on Monte Carlo Localization approach for a mobile robot. The method uses range data which are measured from ultrasound transmitting beacons whose locations are given a priori. The ultrasound receiver on-board a robot detects the range from the beacons. The method requires several beacons, theoretically over three. The method proposes a sensor model for the range sensing based on statistical analysis of the sensor output. The experiment uses commercialized beacons and detector which are used for trilateration localization. The performance of the proposed method is verified through real implementation. Especially, it is shown that the performance of the localization degrades as the sensor update rate decreases compared with the MCL algorithm update rate. Though the method requires exact location of the beacons, it doesn't require geometrical map information of the environment. Also, it is applicable to estimation of the location of both the beacons and robot simultaneously.