• Computers and Concrete
• /
• v.2 no.6
• /
• pp.481-498
• /
• 2005

A wavelet based approach is proposed for structural damage detection in beams, plate and delamination of composite plates. Wavelet theory is applied here for crack identification of a beam element with a transverse on edge non-propagating open crack. Finite difference method was used for generating a general displacement equation for the cracked beam in the first example. In the second and third example, damage is detected from the deformed shape of a loaded simply supported plate applying the wavelet theory. Delamination in composite plate is identified using wavelet theory in the fourth example. The main concept used is the breaking down of the dynamic signal of a structural response into a series of local basis function called wavelets, so as to detect the special characteristics of the structure by scaling and transformation property of wavelets. In the light of the results obtained, limitations of the proposed method as well as suggestions for future work are presented. Results show great promise of wavelet approach for damage detection and structural health monitoring.

• Structural Engineering and Mechanics
• /
• v.55 no.6
• /
• pp.1223-1239
• /
• 2015

A method for structural damage identification based on Chaotic Artificial Bee Colony (CABC) algorithm is presented. ABC is a heuristic algorithm with simple structure, ease of implementation, good robustness but with slow convergence rate. To overcome the shortcoming, the tournament selection mechanism is chosen instead of the roulette mechanism and chaotic search mechanism is also introduced. Residuals of natural frequencies and modal assurance criteria (MAC) are used to establish the objective function, ABC and CABC are utilized to solve the optimization problem. Two numerical examples are studied to investigate the efficiency and correctness of the proposed method. The simulation results show that the CABC algorithm can identify the local damage better compared with ABC and other evolutionary algorithms, even with noise corruption.

• Journal of the Architectural Institute of Korea Structure & Construction
• /
• v.35 no.6
• /
• pp.93-100
• /
• 2019

Modern society is transforming into an extreme climate environment. This is fatal to humans and ecosystems and is expected to cause large-scale damage. As this spokesman, natural disasters are increasing as this global average temperature rises. Social and economic damage by this tendency is also increasing. In addition, the frequency and scale of social disasters are increasing. Damage to the living area due to the damage of the infrastructure due to the increased reliance on infrastructure has been increasingly enlarged. In this research, various disasters such as natural disasters and social disasters analyze the impact on urban safety. A local autonomous entity K Priority Management Establish a kind of disaster, prepare crisis management manual, and use it as a basic material of education / training.

• Smart Structures and Systems
• /
• v.28 no.6
• /
• pp.799-810
• /
• 2021

When monitoring the structural integrity of a bridge using data collected through accelerometers, identifying the profile of the load exerted on the bridge from the vehicles passing over it becomes a crucial task. In this study, the speed and location of vehicles on the deck of a bridge is reconfigured using real-time video to implicitly associate the load applied to the bridge with the response from the bridge sensors to develop an image-based deep learning network model. Instead of directly measuring the load that a moving vehicle exerts on the bridge, the intention in the proposed method is to replace the correlation between the movement of vehicles from CCTV images and the corresponding response by the bridge with a neural network model. Given the framework of an input-output-based system identification, CCTV images secured from the bridge and the acceleration measurements from a cantilevered beam are combined during the process of training the neural network model. Since in reality, structural damage cannot be induced in a bridge, the focus of the study is on identifying local changes in parameters by adding mass to a cantilevered beam in the laboratory. The study successfully identified the change in the material parameters in the beam by using the deep-learning neural network model. Also, the method correctly predicted the acceleration response of the beam. The proposed approach can be extended to the structural health monitoring of actual bridges, and its sensitivity to damage can also be improved through optimization of the network training.

• Journal of Navigation and Port Research
• /
• v.43 no.3
• /
• pp.209-218
• /
• 2019

Coastal cities suffer a great deal of storm and wind damage. The storm and wind characteristics vary between cities. Therefore, a storm and wind damage management system suited for specific characteristics is required for each coastal city. In this study, we analyze the current situation and establish the problem of storm and wind damage management system in regards to urban management, coastal management and disaster management. We also review the storm and wind damage management system for the USA and Japan. We consequently propose a plan to improve the storm and wind damage management system. As a result of the study, in terms of city management, we recommend the compulsory identification of disaster prevention districts, implementation of the integrated coastal city management plan, designation of natural disaster risk mitigation area as disaster prevention district, the division of disaster prevention district into wind damage prevention district, storm damage prevention district, erosion damage prevention district, the building of restrictions at the disaster prevention district by ordinance, etc. In regards to coastal management, we suggest the delegation of authority to delegate coastal erosion management area to the local government, the subdivision of coastal erosion management area into erosion serious area, erosion progress area, erosion concern area, the building restrictions at coastal erosion management area by ordinance, development of erosion prediction chart, etc. In relation to disaster management, we recommend the integration of "countermeasures against natural disasters act" and "disasters and safety management basic act", the local government-led disaster prevention system, the local disaster management network, and the customized local disaster prevention plan, etc.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 1996.04a
• /
• pp.119-126
• /
• 1996

In this paper, a method of substructural identification is presented for the estimation of localized structural parameters. for this purpose, an auto-regressive and moving average with stochastic input (ARMAX) model is derived for the substructure to process the measurement data impaired by noises. The sequential prediction error method is used fer the estimation of unknown localized parameters. Using the substructural method, the number of unknown parameters can be reduced and the convergence and accuracy of estimation can be improved. For some substructures, the effect of the input excitation is expressed in terms of the responses at the inferences with the main structure, and substructural identification may be carried out without measuring the actual input excitation to the whole structure. Example analysis is carried out for idealized structural models of a multistory building and a truss bridge. The results indicate that the present method is effective and efficient for local damage estimation of complex structures.

• International Journal of Railway
• /
• v.2 no.1
• /
• pp.18-21
• /
• 2009

The basis of modem risk-based safety management is to focus on what might happen and ensure it is designed out of the system by robust hazard identification and risk analysis. However, in the real world things go wrong and it is essential to be prepared for the worst so that the response can minimise harm and loss of property and damage to the environment. Whilst some hazard mitigation measures are aimed at preventing incidents, others are venting escalation. The results of the tests concluded that the most effective means by the control room, both with and without, local station staff assistance using directive public address announcements and CCTV surveillance.

• Structural Engineering and Mechanics
• /
• v.34 no.3
• /
• pp.351-366
• /
• 2010

A novel system identification and structural health assessment procedure of steel framed structures with semi-rigid connections is presented in this paper. It is capable of detecting damages at the local element level under normal operating conditions; i.e., serviceability limit state. The procedure is a linear time-domain system identification technique in which the structure responses are required, whereas the dynamic excitation force is not required to identify the structural parameters. The procedure tracks changes in the stiffness properties of all the elements in a structure. It can identify damage-free and damaged structural elements very accurately when excited by different types of dynamic loadings. The method is elaborated with the help of several numerical examples. The results indicate that the proposed algorithm identified the structures correctly and detected the pre-imposed damages in the frames when excited by earthquake, impact, and harmonic loadings. The algorithm can potentially be used for structural health assessment and monitoring of existing structures with minimum disruption of operations. Since the procedure requires only a few time points of response information, it is expected to be economic and efficient.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.6 no.6
• /
• pp.7-15
• /
• 2002

In this paper, the nonlinear parameter estimation method using the estimated hysteresis of each structural members was studied for the purpose of efficient seismic damage prediction and estimation of MDOF nonlinear structural model in the shaking table test. The hysteresis of each structural members can be obtained by the conversion of measured response histories into relative motions of each structural members and member forces. These hysteresis can be used to evaluate various kinds of damage indices of each structural members. The MDOF nonlinear structural model for further analysis(re-analysis) can be easily reconstructed using estimated nonlinear structural parameters of each structural members. To demonstrate the proposed techniques, several numerical and experimental example analyses are carried out. The results indicate that the proposed method can be very useful to assess local seismic damages of structures.

• Smart Structures and Systems
• /
• v.5 no.4
• /
• pp.469-482
• /
• 2009

The emerging sensor-based structural health monitoring (SHM) technology has a potential for cost-effective maintenance of aging civil infrastructure systems. The author proposes to integrate continuous and global monitoring using on-structure sensors with targeted local non-destructive evaluation (NDE). Significant technical challenges arise, however, from the lack of cost-effective sensors for monitoring spatially large structures, as well as reliable methods for interpreting sensor data into structural health conditions. This paper reviews recent efforts and advances made in addressing these challenges, with example sensor hardware and health monitoring software developed in the author's research center. The hardware includes a novel fiber optic accelerometer, a vision-based displacement sensor, a distributed strain sensor, and a microwave imaging NDE device. The health monitoring software includes a number of system identification methods such as the neural networks, extended Kalman filter, and nonlinear damping identificaiton based on structural dynamic response measurement. These methods have been experimentally validated through seismic shaking table tests of a realistic bridge model and tested in a number of instrumented bridges and buildings.