• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.04a
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• pp.366-373
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• 2003

This paper introduces a frequency-domain method of structural damage identification. It is formulated in a general form to include the nonlinearity of damage magnitudes from the dynamic stiffness equation of motion for a beam structure. The appealing features of the present damage identification method are: (1) it requires only the frequency response functions 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 for a cantilevered beam with three piece-wise uniform damages.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.10a
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• pp.109-116
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• 2001

An integrated damage identification system (IDIS) and system identification (SID) technique using modal information to detect damage in structures is presented. The objective is to detect damages in cracked model plate-girder without baseline modal parameters. The theory of damage localization and system identification is outlined. Experiments on a model plate-girder was described and a baseline model representing the experimental modal characteristics of the model plate-girder is updated using the system identification technique. Finally, damage inflicted in the model plate-girder is predicted using the IDIS software.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.552-559
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• 2009

Most damage identification methods for structural health monitoring developed to date utilize modal domain responses which require postprocessing and inevitably contain errors in transforming the domain of responses. In this paper, the feasibility of a damage identification method based on dynamics responses from moving loads is experimentally verified. The experiment is performed via applying periodic and non-periodic moving loads to a steel beam and acceleration and displacement responses of the beam is measured. The moving loads is applied using steel balls and the damage of a structure is simulated by saw-cutting the beam. The damage identification results using the measured responses show that the moving load response based damage identification method successfully identify all damages in the beam.

• Structural Engineering and Mechanics
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• v.56 no.3
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• pp.409-422
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• 2015

In this paper, the Multi-Swarm Fruit Fly Optimization Algorithm (MFOA) is presented for structural damage identification using the first several natural frequencies and mode shapes. We assume damage only leads to the decrease of element stiffness. The differences on natural frequencies and mode shapes of damaged and intact state of a structure are used to establish the objective function, which transforms a damage identification problem into an optimization problem. The effectiveness and accuracy of MFOA are demonstrated by three different structures. Numerical results show that the MFOA has a better capacity for structural damage identification than the original Fruit Fly Optimization Algorithm (FOA) does.

• Advanced Composite Materials
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• v.16 no.2
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• pp.115-134
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• 2007

This study proposes two new approaches for identifying damage patterns in a holed CFRP cross-ply laminate using an embedded fiber Bragg grating (FBG) sensor. It was experimentally confirmed that the reflection spectrum from the embedded FBG sensor was significantly deformed as the damage near the hole (i.e. splits, transverse cracks and delamination) extended. The damage patterns were predicted using forward analysis (a damage analysis and an optical analysis) with strain estimation and the proposed damage-identification method as well as the forward analysis only. Forward analysis with strain estimation provided the most accurate damage-pattern estimation and the highest computational efficiency. Furthermore, the proposed damage identification significantly reduced computation time with the equivalent accuracy compared to the conventional identification procedure, by using damage analysis as the initial estimation.

• Smart Structures and Systems
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• v.25 no.3
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• pp.345-368
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• 2020

The present work proposes a self-controlled multi-stage optimization method for damage identification of structures utilizing standard particle swarm optimization (PSO) algorithm. Damage identification problem is formulated as an inverse optimization problem where damage severity in each element of the structure is considered as optimization variables. An efficient objective function is formed using the first few frequencies and mode shapes of the structure. This objective function is minimized by a self-controlled multi-stage strategy to identify and quantify the damage extent of the structural members. In the first stage, standard PSO is utilized to get an initial solution to the problem. Subsequently, the algorithm identifies the most damage-prone elements of the structure using an adaptable threshold value of damage severity. These identified elements are included in the search space of the standard PSO at the next stage. Thus, the algorithm reduces the dimension of the search space and subsequently increases the accuracy of damage prediction with a considerable reduction in computational cost. The efficiency of the proposed method is investigated and compared with available results through three numerical examples considering both with and without noise. The obtained results demonstrate the accuracy of the present method can accurately estimate the location and severity of multi-damage cases in the structural systems with less computational cost.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.394-399
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• 2005

In this paper, a structural damage identification method (SDIM) is developed to identify the line crack-like directional damages generated within a cylindrical shell. First, the equations of motion fur a damaged cylindrical shell are derived. Based on a theory of continuum damage mechanics, a small material volume containing a directional damage is represented by the effective orthotropic elastic stiffness, which is dependent of the size and the orientation of the damage with respect to the global coordinates. The present SDIM is then derived from the frequency response function (FRF) directly solved from the dynamic equations of the damaged cylindrical shell. In contrast with most existing SDIMs which require the modal parameters measured in both intact and damaged states, the present SDIM requires only the FRF-data measured in damaged state. By virtue of utilizing FRF-data, one may choose as many sets of excitation frequency and FRF measurement point as needed to acquire a sufficient number of equations fer damage identification analysis. The numerically simulated damage identification tests are conducted to study the feasibility of the present SDIM.

• Structural Monitoring and Maintenance
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• v.11 no.3
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• pp.203-217
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• 2024

Electro-mechanical impedance (EMI) technique is a low-cost structural damage detection method. It reflects structural damage through the change in admittance signal which contains the structural mechanical impedance information. The ambient temperature greatly affects the admittance signal, which hides the changes caused by structural damage and reduces the accuracy of damage identification. This study introduces a convolutional neural network to compensate for the temperature effect. The proposed method uses a framework that consists of a feature extraction network and a decoding network, and the original admittance signal with temperature information is used as the input. The output admittance signal is eliminated from the temperature effect, improving damage identification robustness. The admittance data simulated by the finite element model of the spatial grid structure is used to verify the effectiveness of the proposed method. The results show that the proposed method has advantages in identification accuracy compared with the damage index minimization method and the principal component analysis method.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.04a
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• pp.292-299
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• 2002

In this paper a new damage identification theory is developed in order to identify the locations, severities, and orientations of local damages, all together at a time, by using the frequency response functions measured from damaged plate. Finally, the effects of damage orientation on the vibration responses of a plate are numerically investigated, and the numerically simulated damage identification tests are conducted to verify the present damage identification theory.

• 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.