• Title/Summary/Keyword: Structure Identification

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Wavelet based system identification for a nonlinear experimental model

  • Li, Luyu;Qin, Han;Niu, Yun
    • Smart Structures and Systems
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    • v.20 no.4
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    • pp.415-426
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    • 2017
  • Traditional experimental verification for nonlinear system identification often faces the problem of experiment model repeatability. In our research, a steel frame experimental model is developed to imitate the behavior of a single story steel frame under horizontal excitation. Two adjustable rotational dampers are used to simulate the plastic hinge effect of the damaged beam-column joint. This model is suggested as a benchmark model for nonlinear dynamics study. Since the nonlinear form provided by the damper is unknown, a Morlet wavelet based method is introduced to identify the mathematical model of this structure under different damping cases. After the model identification, earthquake excitation tests are carried out to verify the generality of the identified model. The results show the extensive applicability and effectiveness of the identification method.

A New Identification Method for a Fuzzy Model (퍼지모델의 새로운 설정 방법)

  • 박민기;지승환;박민용
    • Journal of the Korean Institute of Intelligent Systems
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    • v.5 no.2
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    • pp.70-78
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    • 1995
  • The identification of a fuzzy model using input-output data consists of two parts :Structure identification and parameter identification. In this paper an algorithm to identify those parameters and structures is suggested to solve the problems of the conventional methods. Given a set of input-output data, the consequent parameters are identified by the Hough transform and clustering method, each of which considers the linearity and continuity respectively. The gradient descent algorithm is used to fine-tune parameters of a fuzzy model. Finally, it is shown that this method is useful for the identification of a fuzzy model by simulation, where we only consider a single input and single output system.

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Identification of Chinese Personal Names in Unrestricted Texts

  • Cheung, Lawrence;Tsou, Benjamin K.;Sun, Mao-Song
    • Proceedings of the Korean Society for Language and Information Conference
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    • 2002.02a
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    • pp.28-35
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    • 2002
  • Automatic identification of Chinese personal names in unrestricted texts is a key task in Chinese word segmentation, and can affect other NLP tasks such as word segmentation and information retrieval, if it is not properly addressed. This paper (1) demonstrates the problems of Chinese personal name identification in some If applications, (2) analyzes the structure of Chinese personal names, and (3) further presents the relevant processing strategies. The geographical differences of Chinese personal names between Beijing and Hong Kong are highlighted at the end. It shows that variation in names across different Chinese communities constitutes a critical factor in designing Chinese personal name Identification algorithm.

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Hybrid evolutionary identification of output-error state-space models

  • Dertimanis, Vasilis K.;Chatzi, Eleni N.;Spiridonakos, Minas D.
    • Structural Monitoring and Maintenance
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    • v.1 no.4
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    • pp.427-449
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    • 2014
  • A hybrid optimization method for the identification of state-space models is presented in this study. Hybridization is succeeded by combining the advantages of deterministic and stochastic algorithms in a superior scheme that promises faster convergence rate and reliability in the search for the global optimum. The proposed hybrid algorithm is developed by replacing the original stochastic mutation operator of Evolution Strategies (ES) by the Levenberg-Marquardt (LM) quasi-Newton algorithm. This substitution results in a scheme where the entire population cloud is involved in the search for the global optimum, while single individuals are involved in the local search, undertaken by the LM method. The novel hybrid identification framework is assessed through the Monte Carlo analysis of a simulated system and an experimental case study on a shear frame structure. Comparisons to subspace identification, as well as to conventional, self-adaptive ES provide significant indication of superior performance.

Determination of flutter derivatives by stochastic subspace identification technique

  • Qin, Xian-Rong;Gu, Ming
    • Wind and Structures
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    • v.7 no.3
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    • pp.173-186
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    • 2004
  • Flutter derivatives provide the basis of predicting the critical wind speed in flutter and buffeting analysis of long-span cable-supported bridges. In this paper, one popular stochastic system identification technique, covariance-driven Stochastic Subspace Identification(SSI in short), is firstly presented for estimation of the flutter derivatives of bridge decks from their random responses in turbulent flow. Secondly, wind tunnel tests of a streamlined thin plate model and a ${\Pi}$ type blunt bridge section model are conducted in turbulent flow and the flutter derivatives are determined by SSI. The flutter derivatives of the thin plate model identified by SSI are very comparable to those identified by the unifying least-square method and Theodorson's theoretical values. As to the ${\Pi}$ type section model, the effect of turbulence on aerodynamic damping seems to be somewhat notable, therefore perhaps the wind tunnel tests for flutter derivative estimation of those models with similar blunt sections should be conducted in turbulent flow.

A Study On Identification Of A Linear Discrete System When The Statistical Characteristics Of Observation Noise Are Unknown (측정잡음의 통계적 성질이 미지인 경우의 선형 이산치형계통의 동정에 관한 연구)

  • 하주식;박장춘
    • 전기의세계
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    • v.22 no.4
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    • pp.17-24
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    • 1973
  • In the view point of practical engineering the identification problem may be considered as a problem to determine the optimal model in the sense of minimizing a given criterion function using the input-output records of the plant. In the system identification the statistical approach has been known to be very effective when the topological structure of the system and the statistical characteristics of the observation noises are known a priori. But in the practical situation there are many cases when the inforhation about the observation noises or the system noises are not available a priori. Here, the authors propose a new identification method which can be used effectively even in the cases when the variances of observation noises are unknown a priori. In the method, the identification of unknown parameters of a linear diserete system is achieved by minimizing the improved quadratic criterion function which is composed of the term of square equation errors and the term to eliminate the affection of observation noises. The method also gives the estimate of noise variance. Numerical computations for several examples show that the proposed procedure gives satisfactory results even when the short time observation data are provided.

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On parameter identification algorithm using VSS theory (가변구조이론에 의한 파라미터 identification 알고리즘)

  • 심귀보;한동균;전홍태
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10a
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    • pp.927-930
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    • 1992
  • VSS identification approach is based on following concept, i.e. while in sliding motion, the switching of control inputs refects system uncertainites. Therefore, if there exist some operations that make the information form the switiching control inputs be achievable, then the unknown parameters can be actually identification mechanisms which can fully make use of the available information. Two different types of VSS identifiers are taken into consideration. The first type uses adjustable model whose structure is similar to that of identified systems. From the viewpoint of contro, this type of VSS identifiers may be regraded as direct identifier vecause the identified system is handled as an open loop. On the other hand, if the identified system is controlable in the sense of VSS(sliding mode can be generated through chosing control inputs), the second type of VSS identifier, the indirect VSS identifier, can be constructed according to the linerized system strucutre while staying in sliding mode. Therefroe it can be applied to some nonlinear systems which are not linear in parametric space by general identification algorithms, whereas linear in parametric space when sliding mode is existed.

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Modeling for M/C tools structure using system identification (System Identification을 이용한 공작기계구조물의 모델화에 관한 연구)

  • Hah, B.H.;Ro, S.H.;Kim, K.H.
    • Journal of the Korean Society for Precision Engineering
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    • v.10 no.1
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    • pp.142-146
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    • 1993
  • The vibrations of the main spindle of the M/C tools are most important in the consideration of the dymamic performance of the M/C tools. In order to resolve and predict the dynamic behaviour of the main syindle it is necessary to have the mathematical model of the system. The system identification is the procedure to provide us with the mathematical model of the procedure of the system identification of the main spindle of the M/C tools to predict the dynamic behaviour of the machine and further to have the basis for the design of M/C tools.

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Structural damage identification using cloud model based fruit fly optimization algorithm

  • Zheng, Tongyi;Liu, Jike;Luo, Weili;Lu, Zhongrong
    • Structural Engineering and Mechanics
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    • v.67 no.3
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    • pp.245-254
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    • 2018
  • In this paper, a Cloud Model based Fruit Fly Optimization Algorithm (CMFOA) is presented for structural damage identification, which is a global optimization algorithm inspired by the foraging behavior of fruit fly swarm. It is assumed that damage only leads to the decrease in elementary stiffness. The differences on time-domain structural acceleration data are used to construct the objective function, which transforms the damaged identification problem of a structure into an optimization problem. The effectiveness, efficiency and accuracy of the CMFOA are demonstrated by two different numerical simulation structures, including a simply supported beam and a cantilevered plate. Numerical results show that the CMFOA has a better capacity for structural damage identification than the basic Fruit Fly Optimization Algorithm (FOA) and the CMFOA is not sensitive to measurement noise.

Identification of Damages within a Plate Structure (평판 구조물의 손상규명)

  • Kim, Nam-In;Lee, U-Sik
    • Proceedings of the KSME Conference
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    • 2000.11a
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    • pp.671-675
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    • 2000
  • In this study, an FRF-based structural damage identification method (SDIM) is proposed for plate structures. The present SDIM is derived from the partial differential equation of motion of the damaged plate, in which damage is characterized by damage distribution function. Various factors that might affect the accuracy of the damage identification are investigated. They include the number of modal data used in the analysis and the damage-induced modal coupling. In the present SDIM, an efficient iterative damage self-search method is introduced. The iterative damage search method efficiently reduces the size of problem by searching out and then by removing all damage-free zones at each iteration of damage identification analysis. The feasibility of the present SDIM is studied by some numerically simulated tests.

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