• Structural Engineering and Mechanics
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• v.31 no.3
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• pp.333-347
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• 2009

Due to structural complicacy, structural health monitoring for civil engineering needs more accurate and effectual methods of damage identification. This study aims to import multi-source information fusion (MSIF) into structural damage diagnosis to improve the validity of damage detection. Firstly, the essential theory and applied mathematic methods of MSIF are introduced. And then, the structural damage identification method based on multi-mode information fusion is put forward. Later, on the basis of a numerical simulation of a concrete continuous box beam bridge, it is obviously indicated that the improved modal strain energy method based on multi-mode information fusion has nicer sensitivity to structural initial damage and favorable robusticity to noise. Compared with the classical modal strain energy method, this damage identification method needs much less modal information to detect structural initial damage. When the noise intensity is less than or equal to 10%, this method can identify structural initial damage well and truly. In a word, this structural damage identification method based on multi-mode information fusion has better effects of structural damage identification and good practicability to actual structures.

• Smart Structures and Systems
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• v.15 no.1
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• pp.57-80
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• 2015

Extended Kalman Filter (EKF) has been widely used for structural identification and damage detection. However, conventional EKF approaches require that external excitations are measured. Also, in the conventional EKF, unknown structural parameters are included as an augmented vector in forming the extended state vector. Hence the sizes of extended state vector and state equation are quite large, which suffers from not only large computational effort but also convergence problem for the identification of a large number of unknown parameters. Moreover, such approaches are not suitable for intelligent structural damage detection due to the limited computational power and storage capacities of smart sensors. In this paper, a two-stage and two-step algorithm is proposed for the identification of structural damage as well as unknown external excitations. In stage-one, structural state vector and unknown structural parameters are recursively estimated in a two-step Kalman estimator approach. Then, the unknown external excitations are estimated sequentially by least-squares estimation in stage-two. Therefore, the number of unknown variables to be estimated in each step is reduced and the identification of structural system and unknown excitation are conducted sequentially, which simplify the identification problem and reduces computational efforts significantly. Both numerical simulation examples and lab experimental tests are used to validate the proposed algorithm for the identification of structural damage as well as unknown excitations for structural health monitoring.

• Proceedings of the KSR Conference
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• 2004.10a
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• pp.121-126
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• 2004

In this paper, a nonlinear structural damage identification algorithm is derived by taking into account the structurally damped spectral element model thinking over a real situation. The structural damage identification analyses are conducted by using the Newton-Raphson method. It is found that, in general Structural Damage Identification by using the Structurally Damped Spectral Element Model provides the same exact damage identification results when compared with the results obtained by the structurally undamped spectral model.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.789-797
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• 2017

Recently, some integrated structural identification/damage detection and reliability evaluation of structures with uncertainties have been proposed. However, these techniques are applicable for off-line synthesis of structural identification and reliability evaluation. In this paper, based on the recursive formulation of the extended Kalman filter, an on-line integration of structural identification/damage detection and reliability evaluation of stochastic building structures is investigated. Structural limit state is expanded by the Taylor series in terms of uncertain variables to obtain the probability density function (PDF). Both structural component reliability with only one limit state function and system reliability with multi-limit state functions are studied. Then, it is extended to adopt the recent extended Kalman filter with unknown input (EKF-UI) proposed by the authors for on-line integration of structural identification/damage detection and structural reliability evaluation of stochastic building structures subject to unknown excitations. Numerical examples are used to demonstrate the proposed method. The evaluated results of structural component reliability and structural system reliability are compared with those by the Monte Carlo simulation to validate the performances of the proposed method.

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.921-926
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• 2004

In this paper, a nonlinear structural damage identification algorithm is derived by taking into account the non-linearity of damage. The structural damage identification analyses are conducted by using the direct method and the Newton-Raphson method. It is found that, the Newton-Raphson method in general provides the better damage identification results when compared with the results obtained by the direct method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.837-840
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• 1997

This paper provides an experimental verification of an FRF-based structural damage identification method (SDIM) developed by the authors for beam structures. The FRF-based SDIM requires the following data : (1) natural frequencies and mode shapes measured at the intact state and (2) the FRF-data measured at the damaged state. Experiments are conducted for the cantilevered beam with one slot and three slots. It is shown that the FRF-based SDIM developed by the authors provide very successful damage identification results which agree well with true damage state.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.3
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• pp.178-188
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• 2005

This paper introduces a structural damage identification method to identify 4he multiple directional damages generated within a cylindrical shell by using the measured frequency response function (FRF). The equations of motion for a damaged cylindrical shell are derived. by using a theory of continuum damage mechanics in which a small material volume containing a directional damage is represented by the effective orthotropic elastic stiffness. In contrast with most existing vibration-based structural damage identification methods which require the modal Parameters measured in both intact and damaged states, the present method requires only the FRF-data measured at damaged state. Numerically simulated damage identification tests are conducted to verify the feasibility of the Proposed structural damage identification method.

• Proceedings of the KSME Conference
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• 2001.11a
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• pp.635-640
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• 2001

This paper introduces a frequency-domain method of structural damage identification. It is formulated in a general form from the dynamic stiffness equation of motion for a structure and then applied to a beam structure. The appealing features of the present damage identification method are: (1) it requires only the frequency response functions experimentally measured from damaged structure as the input data, and (2) it can locate and quantify many local damages at the same time. The feasibility of the present damage identification method is tested through some numerically simulated damage identification analyses and then experimental verification is conducted for a cantilevered beam with damage caused by introducing three slots.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.6
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• pp.559-565
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• 2003

A spectral element model-based structural damage identification method (SDIM) was derived in the previous study by using the damage-induced changes in frequency response functions. However the previous SDIM often provides poor damage identification results because the nonlinear effect of damage magnitude was not taken into account. Thus, this paper improves the previous SDIM by taking into account the nonlinear effect of damage magnitude. Accordingly an iterative solution method is used in this study to solve the nonlinear matrix equation for local damages distribution. The present SDIM is evaluated through the numerically simulated damage identification tests.

• 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.