ELABORATE STRUCTURAL DAMAGE DETECTION USING AN IMPROVED GENETIC ALGORITHM AND MODAL DATA

2013 ◽  
Vol 13 (06) ◽  
pp. 1350024 ◽  
Author(s):  
S. S. NASERALAVI ◽  
S. GERIST ◽  
E. SALAJEGHEH ◽  
J. SALAJEGHEH
Keyword(s):  
Genetic Algorithm ◽  
Finite Element ◽  
Structural Damage ◽  
Structural Damage Detection ◽  
Improved Genetic Algorithm ◽  
Eigenvalues And Eigenvectors ◽  
Damage Functions ◽  
Element Mesh ◽  
Modal Data ◽  
Design Variables

This paper addresses a proficient strategy for detection of structural damages in details using the variations of eigenvalues and eigenvectors. There are two concerns in this study. First, the severity of damage can vary within the damaged elements; second, it is possible that the damage extents do not exactly match the pre-generated finite element mesh. The first concern forms the motivation for employing the proper damage functions to model the elemental damages, and the second for considering the nodal positions as design variables. To obtain the design variables, an improved genetic algorithm is introduced in which two new operators are embedded. This strategy is applied to a beam and a plate structure as the cases of study. The results demonstrate the applicability and efficiency of the proposed algorithm in elaborate damage detections.

Structural Damage Detection Using a Minimum Rank Update Theory

1994 ◽  
Vol 116 (2) ◽  
pp. 222-231 ◽  
Author(s):  
D. C. Zimmerman ◽  
M. Kaouk
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Structural Damage ◽  
Element Model ◽  
Structural Damage Detection ◽  
Eigenvalues And Eigenvectors ◽  
Minimum Rank ◽  
Rigid Body Modes ◽  
Actual Damage ◽  
The Finite Element Model

A computationally attractive algorithm is developed to provide an insight to the location and extent of structural damage. The algorithm makes use of an original finite element model and a subset of measured eigenvalues and eigenvectors. The developed theory approaches the damage location and extent problem in a decoupled fashion. First, a theory is developed to determine the location of structural damage. With location determined, an extent algorithm is then developed. The extent algorithm is a minimum rank update, which is consistent with the effects of many classes of structural damage on a finite element model. If the actual damage results in a rank p change to the finite element model, then the extent algorithm produces exact results if p eigenvalues and eigenvectors are measured exactly. In addition, the extent algorithm preserves any rigid body modes of the structure. The algorithms are demonstrated using both numerical and actual experimental data. The effects of eigenvector measurement and expansion errors are demonstrated and techniques to overcome the effects of noise are discussed.

Photogrammetry-based structural damage detection by tracking a visible laser line

2019 ◽  
Vol 19 (1) ◽  
pp. 322-336 ◽  
Author(s):  
Yongfeng Xu
Keyword(s):  
Finite Element ◽  
Damage Detection ◽  
Structural Damage ◽  
Detection Method ◽  
Element Model ◽  
Target Line ◽  
Laser Line ◽  
Modal Parameters ◽  
Structural Damage Detection ◽  
Visible Laser

Research works on photogrammetry have received tremendous attention in the past few decades. One advantage of photogrammetry is that it can measure displacement and deformation of a structure in a fully non-contact, full-field manner. As a non-destructive evaluation method, photogrammetry can be used to detect structural damage by identifying local anomalies in measured deformation of a structure. Numerous methods have been proposed to measure deformations by tracking exterior features of structures, assuming that the features can be consistently identified and tracked on sequences of digital images captured by cameras. Such feature-tracking methods can fail if the features do not exist on captured images. One feasible solution to the potential failure is to artificially add exterior features to structures. However, painting and mounting such features can introduce unwanted permanent surficial modifications, mass loads, and stiffness changes to structures. In this article, a photogrammetry-based structural damage detection method is developed, where a visible laser line is projected to a surface of a structure, serving as an exterior feature to be tracked; the projected laser line is massless and its existence is temporary. A laser-line-tracking technique is proposed to track the projected laser line on captured digital images. Modal parameters of a target line corresponding to the projected laser line can be estimated by conducting experimental modal analysis. By identifying anomalies in curvature mode shapes of the target line and mapping the anomalies to the projected laser line, structural damage can be detected with identified positions and sizes. An experimental investigation of the damage detection method was conducted on a damaged beam. Modal parameters of a target line corresponding to a projected laser line were estimated, which compared well with those from a finite element model of the damaged beam. Experimental damage detection results were validated by numerical ones from the finite element model.

Optimization Methodology for Composite Stiffened Panel Based on Genetic Algorithm

2014 ◽  
Vol 952 ◽  
pp. 34-37
Author(s):  
Da Feng Jin ◽  
Zhe Liu ◽  
Zhi Rui Fan
Keyword(s):  
Genetic Algorithm ◽  
Finite Element Method ◽  
Finite Element ◽  
Design Space ◽  
Design Guidelines ◽  
Stiffened Panel ◽  
Stacking Sequence ◽  
Design Variables ◽  
Composite Stiffened Panel ◽  
Optimization Methodology

A novel optimization methodology for stiffened panel is proposed in this paper. The purpose of the optimization methodology is to improve the first buckling load of the panel which is obtained by finite element method. The stacking sequence of the stiffeners is taken as design variables. In order to ensure the manufacturability of design, the design guidelines of stacking sequence are taken into account. A DOE based on Halton Sequence makes the initial points of genetic algorithm spread more evenly in the design space of laminate parameters and consequently accelerates the search to convergence. The numerical example verifies the efficiency of this method.

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