Wavelet-Based Structural Damage Detection

2007 ◽  
Author(s):  
Shuncong Zhong ◽  
S. Olutunde Oyadiji
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Crack Detection ◽  
Damage Index ◽  
Multiple Cracks ◽  
Structural Damage Detection ◽  
Simply Supported ◽  
Modal Data ◽  
The Difference ◽  
Detail Coefficient

In this paper, a new wavelet-based approach for crack identification in beam-like structures is presented and applied to simply-supported beams with single or multiple cracks. A novel damage index, based on finding the difference between two sets of detail coefficients obtained by the use of the Stationary Wavelet Transform (SWT) of two reconstructed sets of modal displacement data of the cracked beam-like structure, is proposed for single crack detection or multiple crack detection. These two sets of mode shape data represent the left half and the modified right half of the modal data of the structure. Currently, SWT is widely used in the field of image processing for image noise reduction and image quality improvement. However, because it can provide an accurate estimate of the variances at each scale and facilitate the identification of salient features in a signal, SWT has great potential in the field of structural damage detection. In this paper, the modal responses of the damaged simply supported beams used are computed using the finite element method (FEM). The modal data generate is decomposed by SWT into a smooth curve, called approximation coefficient, and detail coefficient. It is shown that the detail coefficient includes crack information that is useful for structural damage detection. Therefore, a novel damage index, the difference of the SWT detail coefficients of two reconstructed sets of modal displacement data, is proposed and employed. The numerical simulation results show that the proposed wavelet-based method has a good anti-noise ability and it does not require the modal parameters of an intact structure as a baseline for crack detection. Therefore, it can be recommended for real applications in structural health monitoring and damage detection.

Structural Damage Detection Depending on Curvature Matrix of Change in Flexibility

2011 ◽  
Vol 255-260 ◽  
pp. 389-393
Author(s):  
Yong Mei Li ◽  
Bin Zhou ◽  
Xi Yuan Zhou ◽  
Guo Fu Sun ◽  
Bo Yan Yang
Keyword(s):  
Numerical Simulation ◽  
Damage Detection ◽  
Cantilever Beam ◽  
Lower Order ◽  
Structural Damage ◽  
Structural Damage Detection ◽  
Principal Diagonal ◽  
Simply Supported ◽  
Damage Location ◽  
Difference Calculation

Flexibility is more sensitive to structural damage than frequency or mode. Curvature matrix of change in flexibility is presented as a new index of nondestructive damage detection, which is derived from change in structural flexibilities calculated from before damaging and after damaging by means of difference calculation twice, firstly to columns, and then to rows. Therefore a new indicator called as δ Flexibility Curvature Matrix Diagonal (δFCMD) is constructed from the principal diagonal elements based on curvature matrix of change in flexibility. The numerical simulation examples indicate that the damage location and severity in structures, with single damage, multiple ones, slight ones and ones at the supports, can be detected efficiently for a cantilever beam, a fixed supported beam, a simply supported beams and so on by the indicator of δFCMD depending on only a few of lower order modes.

Structural Damage Detection Using Parameters Combined with Changes in Flexibility Based on BP Neural Networks

2011 ◽  
Vol 243-249 ◽  
pp. 5475-5480
Author(s):  
Zhang Jun
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Damage Detection ◽  
Bp Neural Network ◽  
Structural Damage ◽  
The State ◽  
Structural Damage Detection ◽  
Bp Neural Networks ◽  
Simply Supported ◽  
Modal Flexibility

Modals of BP neural networks with different inputs and outputs are presented for different damage detecting schemes. To identify locations of structural damages, the regular vectors of changes in modal flexibility are looked on as inputs of the networks, and the state of localized damage are as outputs. To identify extents of structural damage, parameters combined with changes in flexibility and the square changes in frequency are as inputs of the networks, and the state of damage extents are as outputs. Examples of a simply supported beam and a plate show that the BP neural network modal can detect damage of structures in quantitative terms.

Study on Damage Location of Spatial Structures Based on Wavelet Analysis of Model Strain Energy

2013 ◽  
Vol 639-640 ◽  
pp. 1033-1037
Author(s):  
Yong Mei Li ◽  
Bing Zhou ◽  
Guo Fu Sun ◽  
Bo Yan Yang
Keyword(s):  
Wavelet Analysis ◽  
Damage Detection ◽  
Structural Damage ◽  
Strain Energy ◽  
Damage Identification ◽  
Damage Index ◽  
Structural Damage Detection ◽  
Modal Strain Energy ◽  
Wavelet Method ◽  
Long Span

The research to identify and locate the damage to the engineering structure mainly aimed at some simple structure forms before, such as beam and framework. Damage shows changes of local characteristics of the signal, while wavelet analysis can reflect local damage traits of the signal in time domain and frequency domain. For confirming the validity and applicability of structural damage identification methods, wavelet analysis is used to spatial structural damage detection. The wavelet analysis technique provides new ideas and methods of spatial steel structural damage detection. Based on the theory of wavelet singularity detection，with the injury signal of modal strain energy as structural damage index，the mixing of the modal strain energy and wavelet method to identify and locate the damage to the spatial structure is considered. The multiplicity of the bars and nodes can be taken into account, and take the destructive and nondestructive modal strain energy of Kiewitt-type reticulated shell with 40m span as an example of numerical simulation，the original damage signal and the damage signal after wavelet transformation is compared. The location of the declining stiffness identified by the maximum of wavelet coefficients，analyzed as signal by db1 wavelet，and calculate the graph relation between coefficients of the wavelets and the damage to the structure by discrete or continuous wavelet transform, and also check the accuracy degree of this method with every damage case. Finally，the conclusion is drawn that the modal strain energy and wavelet method to identify and locate the damage to the long span reticulated shell is practical, effective and accurate, that the present method as a reliable and practical way can be adopted to detect the single and several locations of damage in structures.

Structural Damage Detection by Using Modal Data and Wave Propagation

2005 ◽  
Author(s):  
Toshiyuki Ikeshita ◽  
Toshihiro Nakane ◽  
Yoshikazu Kitagawa
Keyword(s):  
Wave Propagation ◽  
Damage Detection ◽  
Structural Damage ◽  
Structural Integrity ◽  
Monitoring Systems ◽  
Structural Damage Detection ◽  
Seismic Safety ◽  
Modal Data ◽  
Extent Of Damage ◽  
Criterion Method

Demand for monitoring systems applied to structures for quality assurance and for evaluating seismic risk is stronger than ever. Here, a monitoring systems to assess structural integrity was developed in which the damage-detection strategy uses two newly developed methods to first identify the damage sites globally (i.e., detect whether the damage occurred or not, and detect the story level) and to then evaluate the damage sites locally. One method identifies the sites and extent of damage globally by using an improved MDLAC (Multiple Damage Location Assurance Criterion) method by using modal data (i.e., frequency and mode shape), and the other identifies the damage sites locally by using wave propagation. Results showed that these two methods are practical and effective in assessing structural integrity of a structure for seismic safety.

Structural damage detection based on variational Bayesian inference and delayed rejection adaptive Metropolis algorithm

2020 ◽  
pp. 147592172092125
Author(s):  
Xiaoyou Wang ◽  
Rongrong Hou ◽  
Yong Xia ◽  
Xiaoqing Zhou
Keyword(s):  
Bayesian Inference ◽  
Damage Detection ◽  
Probability Density ◽  
Structural Damage ◽  
Posterior Probability ◽  
Damage Index ◽  
Structural Damage Detection ◽  
Variational Bayesian ◽  
Variational Bayesian Inference ◽  
Posterior Probability Density

Existing studies on sparse Bayesian learning for structural damage detection usually assume that the posterior probability density functions follow standard distributions which facilitate to circumvent the intractable integration problem of the evidence by means of numerical sampling or analytical derivation. Moreover, the uncertainties of each mode are usually quantified as a common parameter to simplify the calculation. These assumptions may not be realistic in practice. This study proposes a sparse Bayesian method for structural damage detection suitable for standard and nonstandard probability distributions. The uncertainty corresponding to each mode is assumed as different. Variational Bayesian inference is developed and the posterior probability density functions of each unknown are individually derived. The parameters are found to follow the gamma distribution, whereas the distribution of the damage index cannot be directly obtained because of the nonlinear relationship in its posterior probability density function. The delayed rejection adaptive Metropolis algorithm is then adopted to generate numerical samples of the damage index. The coupled damage index and parameters in the variational Bayesian inference are successively calculated via an iterative process. A laboratory-tested frame is utilised to verify the effectiveness of the proposed method. The results indicate that the sparse damage can be accurately detected. The proposed method has the advantage of high accuracy and broad applicability.

Detection of Small Damage of Beam Structures Based on the Slope of Proper Orthogonal Mode

2010 ◽  
Vol 97-101 ◽  
pp. 4457-4460
Author(s):  
Dan Sheng Wang ◽  
Ying Bo Zhang ◽  
Hai Ping Yang ◽  
Hong Ping Zhu
Keyword(s):  
Damage Detection ◽  
Health Monitoring ◽  
Structural Damage ◽  
Detection Method ◽  
Numerical Study ◽  
Structural Damage Detection ◽  
Beam Structures ◽  
Study Results ◽  
The Difference ◽  
Proper Orthogonal

In recent two decades, the issues on structural damage detection and health monitoring have been paid considerable attention in mechanical and civil engineering communities. A lot of researchers have developed many methods to try to resolve the problems. To this day, detection of the small damage of structures, however, has still been a difficulty. The correlation theories of proper orthogonal decomposition (POD) and the basic principle of a new structural damage detection method based on the slope of POD are introduced in this paper. Numerical study on beam structures for small damage detection based on the proposed method is implemented. From the study results one can find that the method based on the slope of the difference of proper orthogonal modes (POMs) has the abilities to localize the small damage of beam structures.

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