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.

scholarly journals A Real-Time Structural Damage Detection method for High-Pile Wharf Foundations

2021 ◽  
Vol 283 ◽  
pp. 01022
Author(s):  
Yongcheng Liu ◽  
Yonglai Zheng ◽  
Yujue Zhou
Keyword(s):  
Damage Detection ◽  
Real Time ◽  
Finite Element Modelling ◽  
Structural Damage ◽  
Detection Method ◽  
Lateral Displacement ◽  
Detection Methods ◽  
Economic Damage ◽  
Structural Damage Detection ◽  
Port Engineering

As one of the most common structural forms in port engineering, the operation environment of high-pile wharf is quite harsh and complex, and its pile foundation often produces structural damage of different degrees. Until now, there is a lack of efficient, safe and economic damage detection methods. A novel and precise real-time structural damage detection (SDD) method using both finite element modelling (FEM) and 1D convolutional neural networks (CNNs) is established in this study. The results indicate that the proposed method could accurately identify the presence and location of damage in real time. The results also demonstrated that the proposed 1D CNNs based model are more sensitive to the longitudinal and lateral displacement responses of the high-pile wharf structure.

Structural damage detection based on iteratively reweighted l1 regularization algorithm

2018 ◽  
Vol 22 (6) ◽  
pp. 1479-1487 ◽  
Author(s):  
Xiaoqing Zhou ◽  
Rongrong Hou ◽  
Yuhan Wu
Keyword(s):  
Damage Detection ◽  
Nonconvex Optimization ◽  
Structural Damage ◽  
Optimization Problem ◽  
Detection Method ◽  
Sparse Recovery ◽  
Detection Methods ◽  
Regularization Technique ◽  
Regularization Algorithm ◽  
Entire Structure

Structural damage usually appears in a few sections or members only, which is sparse compared with the total elements of the entire structure. According to the sparse recovery theory, the recently developed damage detection methods employ the l1 regularization technique to exploit the sparsity condition of structural damage. However, in practice, the solution obtained by the l1 regularization is typically suboptimal. The l0 regularization technique outperforms the l1 regularization in various aspects for sparse recovery, whereas the associated nonconvex optimization problem is NP-hard and computationally infeasible. In this study, a damage detection method based on the iteratively reweighted l1 regularization algorithm is proposed. An iterative procedure is employed such that the nonconvex optimization problem of the l0 regularization can be efficiently solved through transforming it into a series of weighted l1 regularization problems. Experimental example demonstrates that the proposed damage detection method can accurately locate the sparse damage over a large number of elements. The advantage of the iteratively reweighted l1 regularization algorithm over the l1 regularization in damage detection is also demonstrated.

Application of Phased Array Antenna Technique in Structural Damage Detection

2011 ◽  
Vol 368-373 ◽  
pp. 1667-1671
Author(s):  
Yu Zhang ◽  
Long Yu ◽  
Yun Ju Yan ◽  
Yu Guo
Keyword(s):  
Wave Propagation ◽  
Damage Detection ◽  
Structural Damage ◽  
Phased Array ◽  
Tone Burst ◽  
Array Antenna ◽  
Detection Accuracy ◽  
Structural Damage Detection ◽  
Phased Array Antenna ◽  
Energy Leakage

Over decades phased array antenna technique attracts much more attention in Lamb wave based structural damage detection. Lamb wave generated by the piezoelectric wafers omnidirectionally could be steered at a specific direction during its propagation. Thus, the wave beam steering and focusing has been established, the location of structural damage is done with pulse-echo method by wave propagation. However, the detection accuracy will decrease as side bands energy leakage during wave propagation, so, signals to be generated have to be modified by window tone burst in order to concentrate energy in main bands and minimize the effect of dispersion side bands. In this paper, signals modified by Hanning-windowed tone burst was used to decrease the effect of side bands energy leakage, the results improved the detection accuracy better than signals without window tone burst and show good agreement with theoretical results. Meanwhile, A numerical simulation of aluminium plate demonstrates that phased array antenna technique is feasible in structural damage detection.

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.

scholarly journals A Universal Fast Algorithm for Sensitivity-Based Structural Damage Detection

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Q. W. Yang ◽  
J. K. Liu ◽  
C.H. Li ◽  
C.F. Liang
Keyword(s):  
Damage Detection ◽  
Fast Algorithm ◽  
Structural Damage ◽  
Research Area ◽  
Detection Methods ◽  
Structural Damage Detection ◽  
Response Data ◽  
Flexibility Matrix ◽  
New Research ◽  
Measured Response

Structural damage detection using measured response data has emerged as a new research area in civil, mechanical, and aerospace engineering communities in recent years. In this paper, a universal fast algorithm is presented for sensitivity-based structural damage detection, which can quickly improve the calculation accuracy of the existing sensitivity-based technique without any high-order sensitivity analysis or multi-iterations. The key formula of the universal fast algorithm is derived from the stiffness and flexibility matrix spectral decomposition theory. With the introduction of the key formula, the proposed method is able to quickly achieve more accurate results than that obtained by the original sensitivity-based methods, regardless of whether the damage is small or large. Three examples are used to demonstrate the feasibility and superiority of the proposed method. It has been shown that the universal fast algorithm is simple to implement and quickly gains higher accuracy over the existing sensitivity-based damage detection methods.

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