• 지질공학
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• 제28권3호
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• pp.349-365
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• 2018

The strain and acoustic emission (AE) signals of Pocheon granite were measured during uniaxial compression tests to investigate microcrack formation and damage. Crack closure, initiation, and damage stresses of each sample were determined through an analysis of the crack volumetric strain and stiffness. The samples experienced four damage stages according to stress levels: stage 1 = crack closure stage; stage 2 = elastic stage; stage 3 = crack initiation stage; stage 4 = crack damage stage. At least 75% of all AE signals occurred in stages 3 and 4, and different AE parameters were detected in the four stress stages. Rise time, count, energy, and duration clearly showed a tendency to gradually increase with the damage stress stage. In particular, the rise time, energy, and duration increased by at least 95% in stage 4 as compared with stage 1. However, the maximum amplitude showed a smaller increase, and the average frequency decreased slightly at higher stages. These results indicate that as the degree of rock damage increases, the crack size grows larger. The crack types corresponding to the AE signals were determined using the relationship between RA (Rise time / Amplitude) values and average frequencies. Tension cracking was dominant in all stress stages. Shear cracking was rare in stages 1 and 2, but increased in stages 3 and 4. These results are consistent with previous studies that reported cracking begins after samples have already been damaged. Our study shows that the state of rock damage can be investigated solely through an analysis of AE parameters when rocks are under compressive stress. As such, this methodology is suitable for understanding and monitoring the stress state of bedrock.

• Smart Structures and Systems
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• 제25권3호
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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.

• Smart Structures and Systems
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• 제5권1호
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• pp.1-21
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• 2009

A two-stage damage detection method is proposed and demonstrated for structural health monitoring. In the first stage, the subset selection method is applied for the identification of the multiple damage locations. In the second stage, the damage severities of the identified damaged elements are determined applying SSGA to solve the optimization problem. In this method, the sensitivities of residual force vectors with respect to damage parameters are employed for the subset selection process. This approach is particularly efficient in detecting multiple damage locations. The SEREP is applied as needed to expand the identified mode shapes while using a limited number of sensors. Uncertainties in the stiffness of the elements are also considered as a source of modeling errors to investigate their effects on the performance of the proposed method in detecting damage in real-life structures. Through a series of illustrative examples, the proposed two-stage damage detection method is demonstrated to be a reliable tool for identifying and quantifying multiple damage locations within diverse structural systems.

• Smart Structures and Systems
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• 제17권2호
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• pp.347-361
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• 2016

A two-stage method for damage detection in truss systems is proposed. In the first stage, a modal residual vector based indicator (MRVBI) is introduced to locate the potentially damaged elements and reduce the damage variables of a truss structure. Then, in the second stage, a differential evolution (DE) based optimization method is implemented to find the actual site and extent of damage in the structure. In order to assess the efficiency of the proposed damage detection method, two numerical examples including a 2D-truss and 3D-truss are considered. Simulation results reveal the high performance of the method for accurately identifying the damage location and severity of trusses with considering the measurement noise.

• Steel and Composite Structures
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• 제36권1호
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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.

• 한국습지학회지
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• 제5권1호
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• pp.41-52
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• 2003

The flood damage reduction studies have been performed by the channel improvement plan and the levee has mainly constructed with the freeboard concept. However, the freeboard concept might be an inappropriate choice as a safety factor of the levee because many uncertainties are involved in the procedure of the channel improvement plan studies. So, we considered the uncertainties In the discharge-probability, stage-discharge, and stage-damage functions and estimate the expected annual damage. The Monte Carlo technique for uncertainty analysis is used. As our results, the expected annual damage with uncertainty shows the larger value than without uncertainty. Since the expected annual damage with uncertainty already considers the safety factor it is the proper result. However, the expected annual damage without uncertainty does not consider the safety factor yet. Thus, if the expected annual damage without uncertainty considers the freeboard concept, it could be compared with the expected annual damage with uncertainty for the evaluation of the overestimation or underestimation of the levee construction.

• Smart Structures and Systems
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• 제11권1호
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• pp.69-86
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• 2013

An efficient methodology using static test data and changes in natural frequencies is proposed to identify the damages in structural systems. The methodology consists of two main stages. In the first stage, the Damage Signal Match (DSM) technique is employed to quickly identify the most potentially damaged elements so as to reduce the number of the solution space (solution parameters). In the second stage, a particle swarm optimization (PSO) approach is presented to accurately determine the actual damage extents using the first stage results. One numerical case study by using a planar truss and one experimental case study by using a full-scale steel truss structure are used to verify the proposed hybrid method. The identification results show that the proposed methodology can identify the location and severity of damage with a reasonable level of accuracy, even when practical considerations limit the number of measurements to only a few for a complex structure.

• Smart Structures and Systems
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• 제21권2호
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• pp.235-248
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• 2018

An efficient method utilizing the multi-stage improved differential evolution algorithm (MSIDEA) as an optimization solver is presented here to detect the multiple-damage of structural systems. Natural frequency changes of a structure are considered as a criterion for damage occurrence. The structural damage detection problem is first transmuted into a standard optimization problem dealing with continuous variables, and then the MSIDEA is utilized to solve the optimization problem for finding the site and severity of structural damage. In order to assess the performance of the proposed method for damage identification, an experimental study and two numerical examples with considering measurement noise are considered. All the results demonstrate the effectiveness of the proposed method for accurately determining the site and severity of multiple-damage. Also, the performance of the MSIDEA for damage detection compared to the standard differential evolution algorithm (DEA) is confirmed by test examples.

• Earthquakes and Structures
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• 제8권4호
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• pp.821-841
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• 2015

This paper proposes a two-stage imaging approach for quantitative inspection of damages in metallic plates using the fundamental anti-symmetric mode of ($A_0$) Lamb wave. The proposed approach employs a number of transducers to transmit and receive $A_0$ Lamb wave pulses, and hence, to sequentially scan the plate structures before and after the presence of damage. The approach is applied to image the corrosion damages, which are simplified as a reduction of plate thickness in this study. In stage-one of the proposed approach a damage location image is reconstructed by analyzing the cross-correlation of the wavelet coefficient calculated from the excitation pulse and scattered wave signals for each transducer pairs to determine the damage location. In stage-two the Lamb wave diffraction tomography is then used to reconstruct a thickness reduction image for evaluating the size and depth of the damage. Finite element simulations are carried out to provide a comprehensive verification of the proposed imaging approach. A number of numerical case studies considering a circular transducer network with eight transducers are used to identify the damages with different locations, sizes and thicknesses. The results show that the proposed methodology is able to accurately identify the damage locations with inaccuracy of the order of few millimeters of a circular inspection area of $100mm^2$ and provide a reasonable estimation of the size and depth of the damages.

• Smart Structures and Systems
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• 제15권1호
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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.