Vibration-Based Damage Detection in Plates Using Damage Location Vectors

2011 ◽  
Author(s):  
Mohammed O. Kayed ◽  
Mustafa H. Arafa ◽  
Said M. Megahed
Keyword(s):  
Finite Element ◽  
Damage Detection ◽  
Structural Damage ◽  
Damage Identification ◽  
Element Model ◽  
Response Functions ◽  
Promising Technique ◽  
Experimental Frequency ◽  
Damage Location ◽  
Non Destructive

Vibration-based techniques are increasingly being recognized as effective non-destructive structural damage identification tools. One promising technique relies on combining a finite element model (FEM) of the structure under investigation with a set of experimental frequency response functions (FRFs) to construct a so-called Damage Location Vector (DLV). This paper aims to assess damage detection using DLVs both theoretically and experimentally. To this end, the method is first studied theoretically on a thin plate using simulated damage. The method is then tested experimentally on a free-free plate provided with several damage cases using impact hammer testing. The main contribution of the present work lies in attempting to improve the DLV techniques through the use of the experimental FRF data of the intact structure in addition to the theoretical FRF from a finite element. The results obtained indicate that the improved algorithm can be used to successfully detect structural damage.

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 New Damage Detection Method: Big Bang-Big Crunch (BB-BC) Algorithm

2013 ◽  
Vol 20 (4) ◽  
pp. 633-648 ◽  
Author(s):  
Zahra Tabrizian ◽  
Ehsan Afshari ◽  
Gholamreza Ghodrati Amiri ◽  
Morteza Hossein Ali Beigy ◽  
Seyed Mohammad Pourhoseini Nejad
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Element Model ◽  
Optimization Method ◽  
Big Bang ◽  
Continuous Variable ◽  
Particle Swarm Optimizer ◽  
Damage Scenarios ◽  
Damage Location ◽  
Big Crunch

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.

Wavelet-based multi-scale finite element modeling and modal identification for structural damage detection

2017 ◽  
Vol 20 (8) ◽  
pp. 1185-1195 ◽  
Author(s):  
Wen-Yu He ◽  
Songye Zhu ◽  
Zhi-Wei Chen
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Damage Detection ◽  
Structural Damage ◽  
Degrees Of Freedom ◽  
Element Model ◽  
Modal Identification ◽  
Multi Scale ◽  
Multi Resolution Analysis ◽  
Resolution Analysis

Wavelet techniques enable multi-resolution analysis that can represent a function (either field or signal function) in a multi-scale manner. This article presents a damage detection method with dynamically changed scales in both temporal and spatial domains, by taking advantage of the wavelet-based multi-resolution analysis. This method combines a wavelet-based finite element model (WFEM) that employs B-spline wavelet as shape functions and wavelet-based modal identification method to detect structural damage progressively. High-fidelity modal information can be computed or identified with minimized computation cost by lifting the wavelet scales in the wavelet-based finite element model and in signal processing individually according to the actual requirements. Numerical examples demonstrate that the accuracy of damage detection is improved considerably by this lifting strategy during the damage detection process. Besides, fewer degrees of freedom are involved in the wavelet-based finite element model than those of traditional finite element method. The computational efficiency can be improved to large extent and computation resources can be utilized more rationally using the proposed multi-scale approach.

STRUCTURAL DAMAGE IDENTIFICATION USING A GLOBAL OPTIMIZATION TECHNIQUE

2009 ◽  
Vol 09 (04) ◽  
pp. 745-763 ◽  
Author(s):  
W. L. BAYISSA ◽  
N. HARITOS
Keyword(s):  
Global Optimization ◽  
Damage Detection ◽  
Structural Damage ◽  
Damage Identification ◽  
Optimization Technique ◽  
Simulated Data ◽  
Element Model ◽  
Physical Relationship ◽  
Response Parameter ◽  
Global Optimization Technique

This paper presents a two-stage, vibration-based structural damage detection, localization, and severity estimation using an adaptive simulated annealing (ASA) global optimization technique. First, a "damage-sensitive" response parameter that has a strong physical relationship with structural physical properties is presented for detection and localization of structural damage using a nonmodel-based damage identification approach. Secondly, an ASA optimization algorithm is employed to estimate structural damage severity via minimization of a cost-function expressed in terms of the scalar distance between the "damage-sensitive" response parameter determined from a potentially damaged structure and that computed from a finite element model of the undamaged structure. The significance of this study is that the method can be used for damage detection, localization, and estimation of damage severity in two stages and can be applied to input-output as well as output-only damage identification problems. Finally, the proposed technique is demonstrated on simulated data obtained from a simply supported reinforced concrete beam and experimental modal data obtained from the I-40 Bridge.

Vibration-Based Structural Damage Identification Under Interval Uncertainty

2016 ◽  
Author(s):  
David Yoo ◽  
Jiong Tang
Keyword(s):  
Structural Damage ◽  
Prior Information ◽  
Random Distribution ◽  
Damage Identification ◽  
Interval Uncertainty ◽  
Damage Location ◽  
Physical Access ◽  
Non Destructive ◽  
Destructive Methods ◽  
Fuzzy Interval

Identifying damages in mechanical structures in advance is essential part of preventing catastrophic losses. Among several non-destructive methods, the vibration-based method, which utilizes global characteristics of the structures, has several advantages such as not requiring prior information on possible damage location and physical access to it. In the meantime, the mechanical structures are inevitably subject to uncertainties, whose distribution is often unknown in practical situations due to such as limited amount of available data. Uncertainties are treated as interval uncertainty in such cases. In this regard, this study presents vibration-based damage identification under interval uncertainty. To obtain reliable result, this research does not assume any random distribution, e.g., uniform distribution, inside interval. Since detected damage is not assumed to be monotonic function with respect to interval uncertainty either, traditional fuzzy interval arithmetic is not applicable. Instead, we first carry out exhaustive search to see the effect of the interval uncertainty on the identified damage; i.e., discretizing interval uncertainty into sub-intervals and executing damage identification under all possible combinations to see the effect of the interval uncertainty on the identified damage. We then develop the unique algorithm based on M-H algorithm to facility computational efficiency.

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