scholarly journals Charged System Search Algorithm Utilized for Structural Damage Detection

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Zahra Tabrizian ◽  
Gholamreza Ghodrati Amiri ◽  
Morteza Hossein Ali Beigy

This paper presents damage detection and assessment methodology based on the changes in dynamic parameters of a structural system. The method is applied at an element level using a finite element model. According to continuum damage mechanics, damage is represented by a reduction factor of the element stiffness. A recently developed metaheuristic optimization algorithm known as the charged system search (CSS) is utilized for locating and quantifying the damaged areas of the structure. In order to demonstrate the abilities of this method, three examples are included comprising of a 10-elements cantilever beam, a Bowstring plane truss, and a 39-element three-story three-bay plane frame. The possible damage types in structures by considering several damage scenarios and using incomplete modal data are modeled. Finally, results are obtained from the CSS algorithm by detecting damage in these structures and compared to the results of the PSOPC algorithm. In addition, the effect of noise is shown in the results of the CSS algorithm by suitable diagrams. As is illustrated, this method has acceptable results in the structural detection damage with low computational time.

2013 ◽  
Vol 20 (4) ◽  
pp. 633-648 ◽  
Author(s):  
Zahra Tabrizian ◽  
Ehsan Afshari ◽  
Gholamreza Ghodrati Amiri ◽  
Morteza Hossein Ali Beigy ◽  
Seyed Mohammad Pourhoseini Nejad

The present paper aims to explore damage assessment methodology based on the changes in dynamic parameters properties of vibration of a structural system. The finite-element model is used to apply at an element level. Reduction of the element stiffness is considered for structural damage. A procedure for locating and quantifying damaged areas of the structure based on the innovative Big Bang-Big Crunch (BB-BC) optimization method is developed for continuous variable optimization. For verifying the method a number of damage scenarios for simulated structures have been considered. For the purpose of damage location and severity assessment the approach is applied in three examples by using complete and incomplete modal data. The effect of noise on the accuracy of the results is investigated in some cases. A great unbraced frame with a lot of damaged element is considered to prove the ability of proposed method. More over BB-BC optimization method in damage detection is compared with particle swarm optimizer with passive congregation (PSOPC) algorithm. This work shows that BB-BC optimization method is a feasible methodology to detect damage location and severity while introducing numerous advantages compared to referred method.


2018 ◽  
Vol 2018 ◽  
pp. 1-20 ◽  
Author(s):  
Manolis Georgioudakis ◽  
Vagelis Plevris

Structural damage identification is a scientific field that has attracted a lot of interest in the scientific community during the recent years. There have been many studies intending to find a reliable method to identify damage in structural elements both in location and extent. Most damage identification methods are based on the changes of dynamic characteristics and static responses, but the incompleteness of the test data is a great obstacle for both. In this paper, a structural damage identification method based on the finite element model updating is proposed, in order to provide the location and the extent of structural damage using incomplete modal data of a damaged structure. The structural damage identification problem is treated as an unconstrained optimization problem which is solved using the differential evolution search algorithm. The objective function used in the optimization process is based on a combination of two modal correlation criteria, providing a measure of consistency and correlation between estimations of mode shape vectors. The performance and robustness of the proposed approach are evaluated with two numerical examples: a simply supported concrete beam and a concrete frame under several damage scenarios. The obtained results exhibit high efficiency of the proposed approach for accurately identifying the location and extent of structural damage.


2018 ◽  
Vol 2 (3) ◽  
pp. 164 ◽  
Author(s):  
Du Dinh-Cong ◽  
Sang Pham-Duy ◽  
Trung Nguyen-Thoi

The article presents an effective method for damage assessment of 2D frame structures using incomplete modal data by optimization procedure and model reduction technique. In this proposed method, the structural damage detection problem is defined as an optimization problem, in which a hybrid objective function and the damage severity of all elements are considered as the objective function and the continuous design variables, respectively. The teaching-learning-based optimization (TLBO) algorithm is applied as a powerful optimization tool to solve the problem. In addition, owing to the use of incomplete measurements, an improved reduction system (IRS) technique is adopted to reduce the mass and stiffness matrices of structural finite element model. The efficiency and robustness of the proposed method are validated with a 4-storey (3 bay) steel plane frame involving several damage scenarios without and with measurement noise. The obtained results clearly demonstrate that even the incompleteness and noisy environment of measured modal data, the present method can work properly in locating and estimating damage of the frame structure by utilizing only the first five incomplete modes' data.  This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Author(s):  
Wen-Yu He ◽  
Wei-Xin Ren ◽  
Lei Cao ◽  
Quan Wang

The deflection of the beam estimated from modal flexibility matrix (MFM) indirectly is used in structural damage detection due to the fact that deflection is less sensitive to experimental noise than the element in MFM. However, the requirement for mass-normalized mode shapes (MMSs) with a high spatial resolution and the difficulty in damage quantification restricts the practicability of MFM-based deflection damage detection. A damage detection method using the deflections estimated from MFM is proposed for beam structures. The MMSs of beams are identified by using a parked vehicle. The MFM is then formulated to estimate the positive-bending-inspection-load (PBIL) caused deflection. The change of deflection curvature (CDC) is defined as a damage index to localize damage. The relationship between the damage severity and the deflection curvatures is further investigated and a damage quantification approach is proposed accordingly. Numerical and experimental examples indicated that the presented approach can detect damages with adequate accuracy at the cost of limited number of sensors. No finite element model (FEM) is required during the whole detection process.


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