• Journal of Mechanical Science and Technology
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• v.19 no.10
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• pp.1891-1901
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• 2005

Recently the authors tried to find damage position only using measured frequency response functions. According to their work, it seems that the algorithm is very practical since it needs only measured frequency responses while other methods require exact analytic model. But when applying the method to a real structure, it requires lots of experiment. The authors, in this time, propose a method to reduce its experimental load by detecting damage within a substructure. This method searches damages not within an entire structure but within substructures. In addition, damage severity was treated in this paper since it is worthy to know damage severity. Optimization technique is used to estimate damage level using measured responses and damage model. Two test examples, a plate and a jointed structure, are chosen to verify the suggesting method.

• Structural Engineering and Mechanics
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• v.33 no.3
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• pp.325-337
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• 2009

Structural damage detection, damage localization and severity estimation of jacket platforms, based on calculating modal strain energy is presented in this paper. In the structure, damage often causes a loss of stiffness in some elements, so modal parameters; mode shapes and natural frequencies, in the damaged structure are different from the undamaged state. Geometrical location of damage is detected by computing modal strain energy change ratio (MSECR) for each structural element, which elements with higher MSECR are suspected to be damaged. For each suspected damaged element, by computing cross-modal strain energy (CMSE), damage severity as the stiffness reduction factor -that represented the ratios between the element stiffness changes to the undamaged element stiffness- is estimated. Numerical studies are demonstrated for a three dimensional, single bay, four stories frame of the existing jacket platform, based on the synthetic data that generated from finite element model. It is observed that this method can be used for damage detection of this kind of structures.

• Structural Engineering and Mechanics
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• v.26 no.3
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• pp.315-341
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• 2007

A sudden change of stiffness in a structure, associated with the events such as weld fracture and brace breakage, will cause a discontinuity in acceleration response time histories recorded in the vicinity of damage location at damage time instant. A new damage index is proposed and implemented in this paper to detect the damage time instant, location, and severity of a structure due to a sudden change of structural stiffness. The proposed damage index is suitable for online structural health monitoring applications. It can also be used in conjunction with the empirical mode decomposition (EMD) for damage detection without using the intermittency check. Numerical simulation using a five-story shear building under different types of excitation is executed to assess the effectiveness and reliability of the proposed damage index and damage detection approach for the building at different damage levels. The sensitivity of the damage index to the intensity and frequency range of measurement noise is also examined. The results from this study demonstrate that the damage index and damage detection approach proposed can accurately identify the damage time instant and location in the building due to a sudden loss of stiffness if measurement noise is below a certain level. The relation between the damage severity and the proposed damage index is linear. The wavelet-transform (WT) and the EMD with intermittency check are also applied to the same building for the comparison of detection efficiency between the proposed approach, the WT and the EMD.

• Journal of Communications and Networks
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• v.11 no.4
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• pp.350-358
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• 2009

In a wireless sensor network (WSN) setting, this paper presents a distributed decision-making framework and illustrates its application in an online structural health monitoring (SHM) system. The objective is to recover a damage severity vector, which identifies, localizes, and quantifies damages in a structure, via distributive and collaborative decision-making among wireless sensors. Observing the fact that damages are generally scarce in a structure, this paper develops a nonlinear 0-norm minimization formulation to recover the sparse damage severity vector, then relaxes it to a linear and distributively tractable one. An optimal algorithm based on the alternating direction method of multipliers (ADMM) and a heuristic distributed linear programming (DLP) algorithm are proposed to estimate the damage severity vector distributively. By limiting sensors to exchange information among neighboring sensors, the distributed decision-making algorithms reduce communication costs, thus alleviate the channel interference and prolong the network lifetime. Simulation results in monitoring a steel frame structure prove the effectiveness of the proposed algorithms.

• Structural Engineering and Mechanics
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• v.64 no.3
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• pp.353-360
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• 2017

This study presents the Big Bang and Big Crunch (BB-BC) optimization algorithm for detection of structure damage in large severity. Local damage is represented by a perturbation in the elemental stiffness parameter of the structural finite element model. A nonlinear objective function is established by minimizing the discrepancies between the measured and calculated acceleration responses (AR) of the structure. The BB-BC algorithm is utilized to solve the objective function, which can localize the damage position and obtain the severity of the damage efficiently. Numerical simulations have been conducted to identify both single and multiple structural damages for beam, plate and European Space Agency Structures. The present approach gives accurate identification results with artificial measurement noise.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.3
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• pp.333-342
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• 2003

The objective of this paper is to present an algorithm to locate and size damage in a beam structure. The method uses the changes in the modal strain energy distribution. A damage index, utilized to identify possible location and corresponding severity of local damage, is formulated and expressed in terms of modal displacements that can be obtained from mode shapes of the undamaged and the damaged structures. The possible damage locations in the structure arc determined by the application of damage indicator according to previously developed decision rules. The robustness and effectiveness of the method arc demonstrated using numerical examples of beam structures with simulated damage.

• Structural Engineering and Mechanics
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• v.17 no.3_4
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• pp.483-492
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• 2004

This paper presents an efficient algorithm for the estimation of damage location and severity in bridge structures using Probabilistic Neural Network (PNN). Generally, the Back Propagation Neural Network (BPNN)-based damage detection methods need a lot of training patterns for neural network learning process and the optimum architecture of a BPNN is selected by trial and error. In this paper, the PNN instead of the conventional BPNN is used as a pattern classifier. The modal properties of damaged structure are somewhat different from those of undamaged one. The basic idea of proposed algorithm is that the PNN classifies a test pattern which consists of the modal characteristics from damaged structure, how close it is to each training pattern which is composed of the modal characteristics from various structural damage cases. In this algorithm, two PNNs are sequentially used. The first PNN estimates the damage location using mode shape and the results of the first PNN are put into the second PNN for the damage severity estimation using natural frequency. The proposed damage assessment algorithm using the PNN is applied to a cable-stayed bridge to verify its applicability.

• Steel and Composite Structures
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• v.36 no.1
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• pp.31-45
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• 2020

The purpose of this study is to develop an effective iterative two-stage method (ITSM) for structural damage identification of offshore platform structures. In each iteration, a new damage index, Modal Energy-Based Damage Index (MEBI), is proposed to help effectively locate the potential damage elements in the first stage. Then, in the second stage, the beetle antenna search (BAS) algorithm is used to estimate the damage severity of these elements. Compared with the well-known particle swarm optimization (PSO) algorithm and genetic algorithm (GA), this algorithm has lower computational cost. A modal energy based objective function for the optimization process is proposed. Using numerical and experimental data, the efficiency and accuracy of the ITSM are studied. The effects of measurement noise and spatial incompleteness of mode shape are both considered. All the obtained results show that under these influences, the ITSM can accurately identify the true location and severity of damage. The results also show that the objective function based on modal energy is most suitable for the ITSM compared with that based on flexibility and weighted natural frequency-mode shape.

• Steel and Composite Structures
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• v.25 no.4
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• pp.485-496
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• 2017

In this paper, damage detection has been introduced as an optimization problem and a two-step method has been proposed that can detect the location and severity of damage in truss structures precisely and reduce the volume of computations considerably. In the first step, using the residual force vector concept, the suspected damaged members are detected which will result in a reduction in the number of variables and hence a decrease in the search space dimensions. In the second step, the precise location and severity of damage in the members are identified using the genetic algorithm and the results of the first step. Considering the reduced search space, the algorithm can find the optimal points (i.e. the solution for the damage detection problem) with less computation cost. In this step, the Efficient Correlation Based Index (ECBI), that considers the structure's first few frequencies in both damaged and healthy states, is used as the objective function and some examples have been provided to check the efficiency of the proposed method; results have shown that the method is innovatively capable of detecting damage in truss structures.

• Smart Structures and Systems
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• v.2 no.2
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• pp.127-140
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• 2006

In this study, a wavelet-based covariance-driven system identification technique is proposed for damage assessment of structures under ambient excitation. Assuming the ambient excitation to be a white-noise process, the covariance computation is shown to be able to separate the effect of random excitation from the response measurement. Wavelet transform (WT) is then used to convert the covariance response in the time domain to the WT magnitude plot in the time-scale plane. The wavelet coefficients along the curves where energy concentrated are extracted and used to estimate the modal properties of the structure. These modal property estimations lead to the calculation of the stiffness matrix when either the spectral density of the random loading or the mass matrix is given. The predicted stiffness matrix hence provides a direct assessment on the possible location and severity of damage which results in stiffness alteration. To demonstrate the proposed wavelet-based damage assessment technique, a numerical example on a 3 degree-of-freedom (DOF) system and an experimental study on a three-story building model, which are all under a broad-band excitation, are presented. Both numerical and experimental results illustrate that the proposed technique can provide an accurate assessment on the damage location. It is however noted that the assessment of damage severity is not as accurate, which might be due to the errors associated with the mode shape estimations as well as the assumption of proportional damping adopted in the formulation.