• Title/Summary/Keyword: updating

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Progressive damage detection of thin plate structures using wavelet finite element model updating

  • He, Wen-Yu;Zhu, Songye;Ren, Wei-Xin
    • Smart Structures and Systems
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    • v.22 no.3
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    • pp.277-290
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    • 2018
  • In this paper, wavelet finite element model (WFEM) updating technique is employed to detect sub-element damage in thin plate structures progressively. The procedure of WFEM-based detection method, which can detect sub-element damage gradually, is established. This method involves the optimization of an objective function that combines frequencies and modal assurance criteria (MAC). During the damage detection process, the scales of wavelet elements in the concerned regions are adaptively enhanced or reduced to remain compatible with the gradually identified damage scenarios, while the modal properties from the tests remains the same, i.e., no measurement point replacement or addition are needed. Numerical and experimental examples were conducted to examine the effectiveness of the proposed method. A scanning Doppler laser vibrometer system was employed to measure the plate mode shapes in the experimental study. The results indicate that the proposed method can detect structural damage with satisfactory accuracy by using minimal degrees-of-freedoms (DOFs) in the model and minimal updating parameters in optimization.

Updating Policy of Indoor Moving Object Databases for Location-Based Services: The Kalman Filter Method (위치기반서비스를 위한 옥내 이동객체 데이터베이스 갱신전략: 칼만 필터 방법)

  • Yim, Jae-Geol;Joo, Jae-Hun;Park, Chan-Sik;Gwon, Ki-Young;Kim, Min-Hye
    • The Journal of Information Systems
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    • v.19 no.1
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    • pp.1-17
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    • 2010
  • This paper proposes an updating policy of indoor moving object databases (IMODB) for location-based services. our method applies the Ka1man filter on the recently collected measured positions to estimate the moving object's position and velocity at the moment of the most recent measurement, and extrapolate the current position with the estimated position and velocity. If the distance between the extrapolated current position and the measured current position is within the threshold, in other words if they are close then we skip updating the IMODB. When the IMODB needs to know the moving object's position at a certain moment T, it applies the Kalman filter on the series of the measurements received before T and extrapolates the position at T with the estimations obtained by the Kalman filter. In order to verify the efficiency of our updating method, we performed the experiments of applying our method on the series of measured positions obtained by applying the fingerprinting indoor positioning method while we are actually walking through the test bed. In the analysis of the test results, we estimated the communication saving rate of our method and the error increment rate caused by the communication saving.

Learning Input Shaping Control with Parameter Estimation for Nonlinear Actuators (비선형 구동기의 변수추정을 통한 학습입력성형제어기)

  • Kim, Deuk-Hyeon;Sung, Yoon-Gyung;Jang, Wan-Shik
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.35 no.11
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    • pp.1423-1428
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    • 2011
  • This paper proposes a learning input shaper with nonlinear actuator dynamics to reduce the residual vibration of flexible systems. The controller is composed of an estimator of the time constant of the nonlinear actuator dynamics, a recursive least squares method, and an iterative updating algorithm. The updating mechanism is modified by introducing a vibration measurement function to cope with the dynamics of nonlinear actuators. The controller is numerically evaluated with respect to parameter convergence and control performance by using a benchmark pendulum system. The feasibility and applicability of the controller are demonstrated by comparing its control performance to that of an existing controller algorithm.

ANN based on forgetting factor for online model updating in substructure pseudo-dynamic hybrid simulation

  • Wang, Yan Hua;Lv, Jing;Wu, Jing;Wang, Cheng
    • Smart Structures and Systems
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    • v.26 no.1
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    • pp.63-75
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    • 2020
  • Substructure pseudo-dynamic hybrid simulation (SPDHS) combining the advantages of physical experiments and numerical simulation has become an important testing method for evaluating the dynamic responses of structures. Various parameter identification methods have been proposed for online model updating. However, if there is large model gap between the assumed numerical models and the real models, the parameter identification methods will cause large prediction errors. This study presents an ANN (artificial neural network) method based on forgetting factor. During the SPDHS of model updating, a dynamic sample window is formed in each loading step with forgetting factor to keep balance between the new samples and historical ones. The effectiveness and anti-noise ability of this method are evaluated by numerical analysis of a six-story frame structure with BRBs (Buckling Restrained Brace). One BRB is simulated in OpenFresco as the experimental substructure, while the rest is modeled in MATLAB. The results show that ANN is able to present more hysteresis behaviors that do not exist in the initial assumed numerical models. It is demonstrated that the proposed method has good adaptability and prediction accuracy of restoring force even under different loading histories.

Application of meta-model based parameter identification of a seismically retrofitted reinforced concrete building

  • Yu, Eunjong
    • Computers and Concrete
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    • v.21 no.4
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    • pp.441-449
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    • 2018
  • FE models for complex or large-scaled structures that need detailed modeling of structural components are usually constructed using commercial analysis softwares. Updating of such FE model by conventional sensitivity-based methods is difficult since repeated computation for perturbed parameters and manual calculations are needed to obtain sensitivity matrix in each iteration. In this study, an FE model updating procedure avoiding such difficulties by using response surface (RS) method and a Pareto-based multiobjective optimization (MOO) was formulated and applied to FE models constructed with a commercial analysis package. The test building is a low-rise reinforced concrete building that has been seismically retrofitted. Dynamic properties of the building were extracted from vibration tests performed before and after the seismic retrofits, respectively. The elastic modulus of concrete and masonry, and spring constants for the expansion joint were updated. Two RS functions representing the errors in the natural frequencies and mode shape, respectively, were obtained and used as the objective functions for MOO. Among the Pareto solutions, the best compromise solution was determined using the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) procedure. A similar task was performed for retrofitted building by taking the updating parameters as the stiffness of modified or added members. Obtained parameters of the existing building were reasonably comparable with the current code provisions. However, the stiffness of added concrete shear walls and steel section jacketed members were considerably lower than expectation. Such low values are seemingly because the bond between new and existing concrete was not as good as the monolithically casted members, even though they were connected by the anchoring bars.

Self-Updating One-Time Password Mutual Authentication Protocol for Ad Hoc Network

  • Xu, Feng;Lv, Xin;Zhou, Qi;Liu, Xuan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.5
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    • pp.1817-1827
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    • 2014
  • As a new type of wireless network, Ad hoc network does not depend on any pre-founded infrastructure, and it has no centralized control unit. The computation and transmission capability of each node are limited. In this paper, a self-updating one-time password mutual authentication protocol for Ad hoc network is proposed. The most significant feature is that a hash chain can update by itself smoothly and securely through capturing the secure bit of the tip. The updating process does not need any additional protocol or re-initialization process and can be continued indefinitely to give rise to an infinite length hash chain, that is, the times of authentication is unlimited without reconstructing a new hash chain. Besides, two random variable are added into the messages interacted during the mutual authentication, enabling the protocol to resist man-in-the-middle attack. Also, the user's identity information is introduced into the seed of hash chain, so the scheme achieves anonymity and traceability at the same time.

Optimal solution search method by using modified local updating rule in Ant Colony System (개미군락시스템에서 수정된 지역 갱신 규칙을 이용한 최적해 탐색 기법)

  • Hong, Seok-Mi;Chung, Tae-Choong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.1
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    • pp.15-19
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    • 2004
  • Ant Colony System(ACS) is a meta heuristic approach based on biology in order to solve combinatorial optimization problem. It is based on the tracing action of real ants which accumulate pheromone on the passed path and uses as communication medium. In order to search the optimal path, ACS requires to explore various edges. In existing ACS, the local updating rule assigns the same pheromone to visited edge. In this paper, our local updating rule gives the pheromone according to the number of visiting times and the distance between visited cities. Our approach can have less local optima than existing ACS and find better solution by taking advantage of more informations during searching.

Damage Detection Using Finite Element Model Updating (유한요소 모델 개선기법을 이용한 손상추정)

  • Min, Cheon-Hong;Choi, Jong-Su;Hong, Sup;Kim, Hyung-Woo;Yeu, Tae-Kyeong
    • Journal of Ocean Engineering and Technology
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    • v.26 no.5
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    • pp.11-17
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    • 2012
  • In this study, a damage detection method that uses sensitivity-based finite (FE) element model updating with the natural frequency and zero frequency was proposed. The stiffness matrix for a structure was modified using the sensitivity-based FE model updating method. A sensitivity analysis was used to update the FE model, and the natural frequencies and zero frequencies were considered as target parameters to supplement the information on the vibration characteristics. The locations and values of the damages were estimated from the modified stiffness matrix. Several numerical examples were considered to verify the performance of the proposed method.

Vibration based damage identification of concrete arch dams by finite element model updating

  • Turker, Temel;Bayraktar, Alemdar;Sevim, Baris
    • Computers and Concrete
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    • v.13 no.2
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    • pp.209-220
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    • 2014
  • Vibration based damage detection is very popular in the civil engineering area. Especially, special structures like dams, long-span bridges and high-rise buildings, need continues monitoring in terms of mechanical properties of material, static and dynamic behavior. It has been stated in the International Commission on Large Dams that more than half of the large concrete dams were constructed more than 50 years ago and the old dams have subjected to repeating loads such as earthquake, overflow, blast, etc.,. So, some unexpected failures may occur and catastrophic damages may be taken place because of theloss of strength, stiffness and other physical properties of concrete. Therefore, these dams need repairs provided with global damage evaluation in order to preserve structural integrity. The paper aims to show the effectiveness of the model updating method for global damage detection on a laboratory arch dam model. Ambient vibration test is used in order to determine the experimental dynamic characteristics. The initial finite element model is updated according to the experimentally determined natural frequencies and mode shapes. The web thickness is selected as updating parameter in the damage evaluation. It is observed from the study that the damage case is revealed with high accuracy and a good match is attained between the estimated and the real damage cases by model updating method.

A Codebook Generation Algorithm Using a New Updating Condition (새로운 갱신조건을 적용한 부호책 생성 알고리즘)

  • 김형철;조제황
    • Journal of the Institute of Convergence Signal Processing
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    • v.5 no.3
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    • pp.205-209
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    • 2004
  • The K-means algorithm is the most widely used method among the codebook generation algorithms in vector quantization. In this paper, we propose a codebook generation algorithm using a new updating condition to enhance the codebook performance. The conventional K-means algorithm uses a fixed weight of the distance for all training iterations, but the proposed method uses different weights according to the updating condition from the new codevectors for training iterations. Then, different weights can be applied to generate codevectors at each iteration according to this condition, and it can have a similar effect to variable weights. Experimental results show that the proposed algorithm has the better codebook performance than that of K-means algorithm.

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