A Vibration-Based Structural Damage Detection Method and its Applications to Engineering Structures

2011 ◽  
Author(s):  
K. He ◽  
W. D. Zhu
Keyword(s):  
Damage Detection ◽  
Iterative Algorithm ◽  
Structural Damage ◽  
Detection Method ◽  
New Physics ◽  
Logistic Function ◽  
Frame Structure ◽  
Engineering Structures ◽  
System Equations ◽  
Extent Of Damage

Two major challenges associated with a vibration-based damage detection method using changes in natural frequencies are addressed: accurate modeling of structures and the development of a robust inverse algorithm to detect damage, which are defined as the forward and inverse problems, respectively. To resolve the forward problem, new physics-based finite element modeling techniques are developed for fillets in thin-walled beams and for bolted joints, so that complex structures can be accurately modeled with a reasonable model size. To resolve the inverse problem, a logistic function transformation is introduced to convert the constrained optimization problem to an unconstrained one, and a robust iterative algorithm using the Levenberg-Marquardt method is developed to accurately detect the locations and extent of damage. The new methodology can ensure global convergence of the iterative algorithm in solving under-determined system equations and deal with damage detection problems with relatively large modeling error and measurement noise. It is applied to various engineering structures including lightning masts, a space frame structure and one of its components, and a pipeline. The exact locations and extent of damage can be detected in the numerical simulation, and the locations and extent of damage can be successfully detected in experimental damage detection.

Damage Detection of Space Frame Structures With L-Shaped Beams and Bolted Joints Using Changes in Natural Frequencies

2011 ◽  
Author(s):  
K. He ◽  
W. D. Zhu
Keyword(s):  
Damage Detection ◽  
Natural Frequencies ◽  
Detection Method ◽  
Detection Algorithm ◽  
Bolted Joints ◽  
Frame Structure ◽  
Modeling Error ◽  
Space Frame ◽  
Extent Of Damage ◽  
Space Frame Structure

It is difficult to use conventional non-destructive testing methods to detect damage, such as loosening of bolted connections, in a space frame structure due to the complexity of the structure and the nature of the possible damage. A vibration-based method that uses changes in the natural frequencies of a structure to detect the locations and extent of damage in it has the advantage of being able to detect various types of damage in the structure, including loosening of bolted connections. Since the vibration-based method is model-based, applying it to a space frame structure with L-shaped beams and bolted joints will face challenges ranging from the development of an accurate dynamic model of the structure to that of a robust damage detection algorithm for a severely under-determined, nonlinear least-square problem under the effects of relatively large modeling error and measurement noise. With the development of the modeling techniques for fillets in thin-walled beams (He and Zhu, 2009, “Modeling of Fillets in Thin-Walled Beams Using Shell/Plate and Beam Finite Elements,” ASME J. Vibr. Acoust., 131(5), p. 051002) and bolted joints (He and Zhu, “Finite Element Modeling of Structures with L-shaped Beams and Bolted Joints,” ASME J. Vibr. Acoust., p. 011010) by the authors, accurate physics-based models of space frame structures can be developed with a reasonable model size. A new damage detection algorithm that uses a trust-region search strategy combined with a logistic function transformation is developed to improve the robustness of the vibration-based damage detection method. The new algorithm can ensure global convergence of the iterations and minimize the effects of modeling error and measurement noise. The damage detection method developed is experimentally validated on an aluminum three-bay space frame structure with L-shaped beams and bolted joints. Three types of introduced damage, including joint damage, member damage, and boundary damage, were successfully detected. In the numerical simulation where there are no modeling error and measurrement noise, the almost exact locations and extent of damage can be detected.

Research for Structural Damage Identification Method Based on Stable Time Series and Principal Component Analysis

2014 ◽  
Vol 578-579 ◽  
pp. 1020-1023
Author(s):  
Jing Zhou Lu ◽  
Jia Chen Wang ◽  
Xu Zhu
Keyword(s):  
Principal Component Analysis ◽  
Time Series ◽  
Damage Detection ◽  
Structural Damage ◽  
Computing Time ◽  
Principal Component ◽  
Component Analysis ◽  
Identification Accuracy ◽  
Frame Structure ◽  
Ar Model

In this paper, we introduce a set of techniques for time series analysis based on principal component analysis (PCA). Firstly, the autoregressive (AR) model is established using acceleration response data, and the root mean squared error (RMSE) of AR model is calculated based on PCA. Then a new damage sensitive feature (DSF) based on the AR coefficients is presented. To test the efficacy of the damage detection and localization methodologies, the algorithm has been tested on the analytical and experimental results of a three-story frame structure model of the Los Alamos National Laboratory. The result of the damage detection indicates that the algorithm is able to identify and localize minor to severe damage as defined for the structure. It shows that the suggested method can lead to less amount of computing time, high suitability and identification accuracy.

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 Nonlinear Damage Detection Method Using AR/ARCH Model

2017 ◽  
Vol 17 (08) ◽  
pp. 1750083 ◽  
Author(s):  
J. J. Cheng ◽  
H. Y. Guo ◽  
Y. S. Wang
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Fatigue Cracks ◽  
Arch Model ◽  
Structure Model ◽  
Relevant Research ◽  
Engineering Structures ◽  
The Past ◽  
Damage Indicator ◽  
Shear Building

Structural health monitoring (SHM) has received increasing attention in the research community over the past two decades. Most of the relevant research focuses on linear structural damage detection. However, the majority of the damage in civil engineering structures is nonlinear, such as fatigue cracks that open and close under dynamic loading. In this study, a new hybrid AR/ARCH model in the field of economics and a proposed damage indicator (DI) which is the second-order variance indicator (SOVI) based on the model have been used for detecting structural nonlinear damage. The data from an experimental three-storey structure and a simulated eight-storey shear building structure model have been used to verify the effectiveness of the algorithm and SOVI. In addition, a traditional linear DI: cepstral metric indicator (CMI) has also been used to diagnose the nonlinear damage. The results of the CMI and SOVI were compared and it is found that there are advantages in using the SOVI in the field of nonlinear structural damage.

scholarly journals Structural Damage Identification Based on the Minimum System Realization and Sensitivity Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-12
Author(s):  
W. R. Li ◽  
Y. F. Du ◽  
S. Y. Tang ◽  
L. J. Zhao
Keyword(s):  
Sensitivity Analysis ◽  
Damage Detection ◽  
Structural Damage ◽  
Damage Identification ◽  
Structural Information ◽  
Structural Response ◽  
Frame Structure ◽  
Structural Damage Detection ◽  
System Realization ◽  
Minimum System

On the basis of the thought that the minimum system realization plays the role as a coagulator of structural information and contains abundant information on the structure, this paper proposes a new method, which combines minimum system realization and sensitivity analysis, for structural damage detection. The structural damage detection procedure consists of three steps: (1) identifying the minimum system realization matrixes A, B, and R using the structural response data; (2) defining the mode vector, which is based on minimum system realization matrix, by introducing the concept of the measurement; (3) identifying the location and severity of the damage step by step by continuously rotating the mode vector. The proposed method was verified through a five-floor frame model. As demonstrated by numerical simulation, the proposed method based on the combination of the minimum realization system and sensitivity analysis is effective for the damage detection of frame structure. This method not only can detect the damage and quantify the damage severity, but also is not sensitive to the noise.

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