• Smart Structures and Systems
• /
• v.11 no.1
• /
• pp.69-86
• /
• 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.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 1996.10a
• /
• pp.138-146
• /
• 1996

The presence of a damage, such as a crack, in a structure increases the flexibility and damping in the structure. Most of methods to detect damage or damage location uses stiffness matrix of the structural system. The modification of stiffness matrix, however, has complicated procedures to identify structural. system in the basis of finite element model and has too many degree of freedom to calculate. Identification of changes of flexibility of structure can offer damage information immediately and simple procedure can employ real time continuous monitoring system. To identify changes of the flexibility, vibration mode shapes and natural frequencies are usually used. In this paper, a procedure for damage location in continuous girder bridges using vibration data is described. The effectiveness and sensitivity of the presented method to measurement errors in mode shapes and natural frequencies are investigated using analytical results from finite element models. It is shown that the errors in the first mode shape and first natural frequency demonstrate much larger influence than those in the higher mode shapes and modal frequencies.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.27 no.6
• /
• pp.938-945
• /
• 2003

In the present study, the inverse perturbation method is applied to the structural damage detection in conjunction with a system condensation technique. The system condensation technique is adopted to r esolve the problem due to the incomplete measurement of the degrees-of-freedom (DOFs) in a natural mode. However, the numerical difficulty may arise in the system condensation when the DOFs to be measured are not properly selected. Thus, the issue of sensor placement for structural damage detection, in the framework of the condensation technique-based inverse perturbation method, is considered in this study. Also, a methodology to measure the number of sensors required to obtain reliable damage detection is proposed and then verified through some illustrative example problem.

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

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

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

• Structural Monitoring and Maintenance
• /
• v.2 no.3
• /
• pp.237-252
• /
• 2015

This paper addresses the issue of reliability and performance in wireless sensor networks (WSN) based structural health monitoring (SHM), particularly with decentralized damage identification techniques. Two decentralized damage identification algorithms, namely, the autoregressive (AR) model based damage index and the Wiener filter method are developed for structural damage detection. The ambient and impact testing have been carried out on the steel beam structure in the laboratory. Seven wireless sensors are installed evenly along the steel beam and seven wired sensor are also installed on the beam to monitor the dynamic responses as comparison. The results showed that wireless measurements performed very much similar to wired measurements in detecting and localizing damages in the steel beam. Therefore, apart from the usual advantages of cost effectiveness, manageability, modularity etc., wireless sensors can be considered a possible substitute for wired sensors in SHM systems.

• Journal of the Korean Society of Safety
• /
• v.36 no.3
• /
• pp.40-49
• /
• 2021

This study surveyed damage to small and medium-sized RC slab bridges, the largest in number in Korea. Four common types of damage were identified, and their static and dynamic structural behaviors were examined through structural analysis. The degree of damage was selected as an analysis parameter for three superstructures of RC slab bridges. After structural analysis, a damage assessment process was proposed that can be used as the basis for establishing maintenance yplans for these bridges. The results of the present study can be used for the safety management of RC slab bridges, classified as bridges suspected of safety flaws or requiring maintenance in load-carrying capacity tests.

• Structural Engineering and Mechanics
• /
• v.44 no.2
• /
• pp.179-196
• /
• 2012

An eigenspace projection clustering method is proposed for structural damage detection by combining projection algorithm and fuzzy clustering technique. The integrated procedure includes data selection, data normalization, projection, damage feature extraction, and clustering algorithm to structural damage assessment. The frequency response functions (FRFs) of the healthy and the damaged structure are used as initial data, median values of the projections are considered as damage features, and the fuzzy c-means (FCM) algorithm are used to categorize these features. The performance of the proposed method has been validated using a three-story frame structure built and tested by Los Alamos National Laboratory, USA. Two projection algorithms, namely principal component analysis (PCA) and kernel principal component analysis (KPCA), are compared for better extraction of damage features, further six kinds of distances adopted in FCM process are studied and discussed. The illustrated results reveal that the distance selection depends on the distribution of features. For the optimal choice of projections, it is recommended that the Cosine distance is used for the PCA while the Seuclidean distance and the Cityblock distance suitably used for the KPCA. The PCA method is recommended when a large amount of data need to be processed due to its higher correct decisions and less computational costs.

• Earthquakes and Structures
• /
• v.18 no.4
• /
• pp.507-517
• /
• 2020

This study aims to present new frequency-related seismic intensity parameters (SIPs) based on the Hilbert-Huang Transform (HHT) analysis. The proposed procedure is utilized for the processing of several seismic accelerograms. Thus, the entire evaluated Hilbert Spectrum (HS) of each considered seismic velocity time-history is investigated first, and then, a delimited area of the same HS around a specific frequency is explored, for the proposition of new SIPs. A first application of the suggested new parameters is to reveal the interrelation between them and the structural damage of a reinforced concrete frame structure. The index of Park and Ang describes the structural damage. The fundamental frequency of the structure is considered as the mentioned specific frequency. Two statistical methods, namely correlation analysis and multiple linear regression analysis, are used to identify the relationship between the considered SIPs and the corresponding structural damage. The results confirm that the new proposed HHT-based parameters are effective descriptors of the seismic damage potential and helpful tools for forecasting the seismic damages on buildings.