Structural Damage Detection Accounting for Loss of Data in Wireless Network Sensors

2009 ◽  
Vol 413-414 ◽  
pp. 125-132 ◽  
Author(s):  
Ser Tong Quek ◽  
Viet Anh Tran ◽  
Xiao Yan Hou
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Wireless Sensors ◽  
Detection Method ◽  
Truss Structures ◽  
Monitoring Systems ◽  
Structural Damage Detection ◽  
Cumulative Energy ◽  
Health Monitoring Systems ◽  
Identification Parameter

For detection of damage in frame and truss structures, the normalized cumulative energy is proposed as the identification parameter within the framework of the damage locating vector (DLV) method. Due to the limited number of sensors used, it is necessary to filter out the actual damaged elements from the identified set of potential damaged elements. An intersection scheme using only the measured signals is proposed for the filtering and verified using a warehouse frame comprising truss, beam and column elements. As wireless sensors are introduced into structural health monitoring systems, loss of data during transmission is one significant issue which needs to be addressed. An algorithm to patch the loss data is proposed and when integrated with the proposed damage detection method is experimentally shown to be feasible using a cantilever truss.

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.

Temperature Effects on Guided Wave Structural Damage Detection

2008 ◽  
Vol 47-50 ◽  
pp. 129-132 ◽  
Author(s):  
Chan Yik Park ◽  
Seung Moon Jun
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Guided Waves ◽  
Guided Wave ◽  
Low Velocity Impact ◽  
Structural Damage Detection ◽  
Low Velocity ◽  
Simple Method ◽  
Temperature Changes ◽  
Health Monitoring Systems

Guided wave structural damage detection is one of promising candidates for the future aircraft structural health monitoring systems. There are several advantages of guided wave based damage detection: well established theoretical studies, simple sensor devices, large sensing areas, good sensitivity, etc. However, guided wave approaches are still vulnerable to false warnings of detecting damage due to temperature changes of the structures. Therefore, one of main challenges is to find an effective way of compensating temperature changes and to imply it to existing damage detect algorithms. In this paper, a simple method for applying guided waves to the problem of detecting damage in the presence of temperature changes is presented. In order to examine the effectiveness of the presented method, delaminations due to low-velocity impact on composite plate specimens are detected. The results show that the presented approach is simple but useful for detecting structural damage under the temperature variations.

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 Disassembling-Based Structural Damage Detection Using Static Measurement Data

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Eun-Taik Lee ◽  
Hee-Chang Eun
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Degrees Of Freedom ◽  
Measurement Data ◽  
Truss Structures ◽  
Detection Methods ◽  
Internal Stresses ◽  
Structural Damage Detection ◽  
Constraint Forces ◽  
Entire Structure

Damage detection methods can be classified into global and local approaches depending on the division of measurement locations in a structure. The former utilizes measurement data at all degrees of freedom (DOFs) for structural damage detection, while the latter utilizes data of members and substructures at a few DOFs. This paper presents a local method to detect damages by disassembling an entire structure into members. The constraint forces acting at the measured DOFs of the disassembled elements at the damaged state, and their internal stresses, are predicted. The proposed method detects locally damaged members of the entire structure by comparing the stress variations before and after damage. The static local damage can be explicitly detected when it is positioned along the constraint load paths. The validity of the proposed method is illustrated through the damage detection of two truss structures, and the disassembling (i.e., local) and global approaches are compared using numerical examples. The numerical applications consider the noise effect and single and multiple damage cases, including vertical, diagonal, and chord members of truss structures.

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