• Structural Engineering and Mechanics
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• 제8권3호
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• pp.285-297
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• 1999

A method is presented to find the location and magnitude of damage in a structure using data from dynamic tests. The test data include a combination of natural frequency measurements, taken before and after the occurrence of damage, and response measurements taken after damage. An algorithm is developed to identify localized increases in the flexibility of the structural members. Increases in flexibility are attributed to damage. The algorithm uses the sensitivity of the flexibility matrix to changes in the natural frequencies of the structure to identify the damage. A set of under determined equations is solved using an objective function which is derived from measurements of the system moments. Damage ranging from 10 to 60% increase in the flexibility of a member was successfully identified in a 50 d.o.f. structure, using a small number of natural frequency and velocity measurements.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2010년도 추계 학술발표회 3차
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• pp.86-95
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• 2010

Ground movements during tunnelling have the potential for major impact on nearby buildings, utilities and streets. The impacts on buildings are assessed by linking the magnitude of ground loss at the source of ground loss around tunnel to the lateral and vertical displacements on the ground surface, and then to the lateral strain and angular distortion, and resulting damage in the building. To prevent or mitigate the impacts on nearby buildings, it is important to understand the whole mechanism from tunnelling to building damage. This paper discusses tunneling-induced ground movements and their impacts on nearby buildings, including the importance of the soil-structure interactions. In addition, a building damage criterion, which is based on the state of strain, is presented and discussed in detail and the overall damage assessment procedure is provided for the estimation of tunnelling-induced building damage considering the effect of soil-structure interaction.

• Smart Structures and Systems
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• 제9권3호
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• pp.253-271
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• 2012

Finite element (FE) model updating is a useful tool for global damage detection technique, which identifies the damage of the structure using measured vibration data. This paper presents the application of a finite element model updating method to detect the damage of a small-scale reinforced concrete building structure using measured acceleration data from shaking table tests. An iterative FE model updating strategy using the least-squares solution based on sensitivity of frequency response functions and natural frequencies was provided. In addition, a side constraint to mitigate numerical difficulties associated with ill-conditioning was described. The test structure was subjected to six El Centro 1942 ground motion histories with different Peak Ground Accelerations (PGA) ranging from 0.06 g to 0.5 g, and analytical models corresponding to each stage of the shaking were obtained using the model updating method. Flexural stiffness values of the structural members were chosen as the updating parameters. In model updating at each stage of shaking, the initial values of the parameter were set to those obtained from the previous stage. Severity of damage at each stage of shaking was determined from the change of the updated stiffness values. Results indicated that larger reductions in stiffness values occurred at the slab members than at the wall members, and this was consistent with the observed damage pattern of the test structure.

• 한국소음진동공학회논문집
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• 제22권7호
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• pp.667-675
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• 2012

A damage estimation method for support structure of offshore wind turbine using modal parameters is presented for effective structural health monitoring. Natural frequencies and mode shapes for a support structure with monopile of an offshore wind turbine were calculated considering soil condition and added mass. A neural network was learned based on training patterns generated by the changes of natural frequency and mode shape due to various damages. Natural frequencies and mode shapes for 10 prospective damage cases were input to the trained neural network for damage estimation. The identified damage locations and severities agreed reasonably well with the accurate damages. Multi-damage cases could also be successfully estimated. Enhancement of estimation result using another parameters as input to neural network will be carried out by further study. Proposed method could be applied to other type of support structure of offshore wind turbine for structural health monitoring.

• 한국군사과학기술학회지
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• 제15권3호
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• pp.266-271
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• 2012

The rescue methods for the marine casualties are limited due to the characteristics of operation environment of the vessel. Especially the most of marine accidents have been occurred at the bow structure of ship. Moreover the failure of bow structure may lead to catastrophic mishaps. In this paper, the extents of damage of a bow structure fracture subject to collision accident was investigated by using numerical method. The computer simulation approach by using Finite Element Method was employed to accomplish this goal. A finite element model, a 3D model of ship, has been utilized to evaluate damage of bow structure according to collision scenario. In conclusion, we have demonstrated that the plastic deformation occurred at the bow structure. Also it was shown that the collision angle clearly plays a role in determining amount of damage of ship structures.

• 항공우주시스템공학회지
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• 제7권1호
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• pp.39-43
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• 2013

In this study, damage assesment and repair technique of aircraft adopted on Sandwich composite structure were performed. The sandwich composite structure were damaged by drop weight type impact test machine. The damaged sandwich composite structure was repaired using external patch repair method after removing damaged area. This study presents comparison results of the experimental investigation between the impact damaged and the repaired specimen.

• Structural Engineering and Mechanics
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• 제25권1호
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• pp.39-52
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• 2007

This paper describes an experimental study on structural health monitoring of a 1:3-scaled one-story concrete frame subjected to seismic damage and retrofit. The structure is tested on a shaking table by exerting successively enhanced earthquake excitations until severe damage, and then retrofitted using fiber-reinforced polymers (FRP). The modal properties of the tested structure at trifling, moderate, severe damage and strengthening stages are measured by subjecting it to a small-amplitude white-noise excitation after each earthquake attack. Making use of the measured global modal frequencies and a validated finite element model of the tested structure, a neural network method is developed to quantitatively identify the stiffness reduction due to damage and the stiffness enhancement due to strengthening. The identification results are compared with 'true' damage severities that are defined and determined based on visual inspection and local impact testing. It is shown that by the use of FRP retrofit, the stiffness of the severely damaged structure can be recovered to the level as in the trifling damage stage.

• Structural Engineering and Mechanics
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• 제30권2호
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• pp.135-146
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• 2008

This study utilizes the fine-tuning and small-digit characteristics of the successive zooming genetic algorithm (SZGA) to propose a method of structural damage detection in a continuum structure, where the differences in the natural frequencies of a structure obtained by experiment and FEM are compared and minimized using an assumed location and extent of structural damage. The final methodology applied to the structural damage detection is a kind of pseudo-discrete-variable-algorithm that counts the soundness variables as one (perfectly sound) if they are above a certain standard, such as 0.99. This methodology is based on the fact that most well-designed structures exhibit failures at some critical point due to manufacturing error, while the remaining region is free of damage. Thus, damage of 1% (depending on the given standard) or less can be neglected, and the search concentrated on finding more serious failures. It is shown that the proposed method can find out the exact structural damage of the monitored structure and reduce the time and amount of computation.

• Smart Structures and Systems
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• 제15권1호
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• pp.15-40
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• 2015

This paper proposes a structural damage identification approach based on the power spectral density transmissibility (PSDT), which is developed to formulate the relationship between two sets of auto-spectral density functions of output responses. The accuracy of response reconstruction with PSDT is investigated and the damage identification in structures is conducted with measured acceleration responses from the damaged state. Numerical studies on a seven-storey plane frame structure are conducted to investigate the performance of the proposed damage identification approach. The initial finite element model of the structure and measured acceleration measurements from the damaged structure are used for the identification with a dynamic response sensitivity-based model updating method. The simulated damages can be identified accurately without and with a 5% noise effect included in the simulated responses. Experimental studies on a steel plane frame structure in the laboratory are performed to further verify the accuracy of response reconstruction with PSDT and validate the proposed damage identification approach. The locations of the introduced damage are detected accurately and the stiffness reductions in the damaged elements are identified close to the true values. The identification results demonstrated the accuracy of response reconstruction as well as the correctness and efficiency of the proposed damage identification approach.

• Smart Structures and Systems
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• 제5권1호
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• pp.43-54
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• 2009

This study introduces a novel approach for locating damage in a structure using wireless sensor system with local level computational capability to alleviate data traffic load on the centralized computation. Smart wireless sensor systems, capable of iterative damage-searching, mimic an optimization process in a decentralized way. The proposed algorithm tries to detect damage in a structure by monitoring abnormal increases in strain measurements from a group of wireless sensors. Initially, this clustering technique provides a reasonably effective sensor placement within a structure. Sensor clustering also assigns a certain number of master sensors in each cluster so that they can constantly monitor the structural health of a structure. By adopting a voting system, a group of wireless sensors iteratively forages for a damage location as they can be activated as needed. Since all of the damage searching process occurs within a small group of wireless sensors, no global control or data traffic to a central system is required. Numerical simulation demonstrates that the newly developed searching algorithm implemented on wireless sensors successfully localizes stiffness damage in a plate through the local level reconfigurable function of smart sensors.