scholarly journals A rapid structural damage detection method using integrated ANFIS and interval modeling technique

2014 ◽  
Vol 25 ◽  
pp. 473-484 ◽  
Author(s):  
Futao Zhu ◽  
Yunjie Wu
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Detection Method ◽  
Modeling Technique ◽  
Structural Damage Detection ◽  
Interval Modeling

A structural damage detection method using static noisy data

2005 ◽  
Vol 27 (12) ◽  
pp. 1784-1793 ◽  
Author(s):  
F. Bakhtiari-Nejad ◽  
A. Rahai ◽  
A. Esfandiari
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Detection Method ◽  
Noisy Data ◽  
Structural Damage Detection

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.

Structural damage detection via combining weighted strategy with trace Lasso

2018 ◽  
Vol 22 (3) ◽  
pp. 597-612 ◽  
Author(s):  
Chengbin Chen ◽  
Chudong Pan ◽  
Zepeng Chen ◽  
Ling Yu
Keyword(s):  
Damage Detection ◽  
Swarm Intelligence ◽  
Structural Damage ◽  
Optimization Problem ◽  
Detection Method ◽  
Rapid Development ◽  
Detection Methods ◽  
Detection Accuracy ◽  
Structural Damage Detection ◽  
Selection Operator

With the rapid development of computation technologies, swarm intelligence–based algorithms become an innovative technique used for addressing structural damage detection issues, but traditional swarm intelligence–based structural damage detection methods often face with insufficient detection accuracy and lower robustness to noise. As an exploring attempt, a novel structural damage detection method is proposed to tackle the above deficiency via combining weighted strategy with trace least absolute shrinkage and selection operator (Lasso). First, an objective function is defined for the structural damage detection optimization problem by using structural modal parameters; a weighted strategy and the trace Lasso are also involved into the objection function. A novel antlion optimizer algorithm is then employed as a solution solver to the structural damage detection optimization problem. To assess the capability of the proposed structural damage detection method, two numerical simulations and a series of laboratory experiments are performed, and a comparative study on effects of different parameters, such as weighted coefficients, regularization parameters and damage patterns, on the proposed structural damage detection methods are also carried out. Illustrated results show that the proposed structural damage detection method via combining weighted strategy with trace Lasso is able to accurately locate structural damages and quantify damage severities of structures.

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