Structural Damage Detection of Continuous Beam by NExT Based Wavelet Packet Energy

2012 ◽  
Vol 490-495 ◽  
pp. 2588-2593
Author(s):  
Peng Yan ◽  
Qiao Li
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Decomposition Method ◽  
Wavelet Packet ◽  
Damage Index ◽  
Detection Algorithm ◽  
Reference Points ◽  
Favorable Effect ◽  
Continuous Beam ◽  
Structural Damage Detection

For the purpose of effective damage localization, combined with natural excitation technique (NExT) and wavelet packet (WP) decomposition method, a new algorithm named NExT based wavelet packet energy (WPE) damage detection algorithm was proposed for continuous beam. Finite measuring points of bridge structure response are set firstly, and then classified as reference points and response points. Calculated with each corresponding two-point, the virtual impulse response signals are taken as input data of WP decomposition method. Finally, structural damage detection is carried out by using WPE as damage index. Through a three-span continuous beam finite element model, this algorithm was discussed with respect to the applicability and effectiveness of damage detection. The analysis results reveal that, with certain robustness to noise, the proposed algorithm has favorable effect on damage interval localization. Therefore, the algorithm put forward is practical to detect damage of continuous beam.

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 from wavelet packet sensitivity

2005 ◽  
Vol 27 (9) ◽  
pp. 1339-1348 ◽  
Author(s):  
S.S. Law ◽  
X.Y. Li ◽  
X.Q. Zhu ◽  
S.L. Chan
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Wavelet Packet ◽  
Structural Damage Detection

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.

Structural Damage Detection of the Simple Beam Based on Responses Phase Space

2012 ◽  
Vol 605-607 ◽  
pp. 989-995 ◽  
Author(s):  
Cheng Cheng ◽  
Zhen Hua Nie ◽  
Hong Wei Ma
Keyword(s):  
Phase Space ◽  
Dynamic Response ◽  
Damage Detection ◽  
Structural Damage ◽  
Phase Plane ◽  
Damage Index ◽  
Phase Space Reconstruction ◽  
Dynamic Responses ◽  
Reconstruction Method ◽  
Structural Damage Detection

In this paper, the technology of attractor phase space in chaotic theory is introduced and applied in the structural damage detection. Firstly the phase plane is constructed with the displacement and acceleration responses. Using the changes of phase plane topology of intact and damaged responses, a new damage index is extracted, and the structural damage existence and severity are identified successfully. Since some of the state variables can not be measured, a method of phase space reconstruction is proposed using single dynamic response. The dynamic responses are directly displayed into phase space, realizing transforming the signals from time domain to space domain. Then using the reconstructed phase space, the damage is diagnosed. The results indicate that the phase space reconstruction method has good robustness to noise, and higher sensitivity compared with traditional modal-based methods. The phase space reconstruction method can calculate the value of the damage index using single dynamic response, so that a single sensor can monitor structural damage existence and severity.

Application of Wavelet Packet Transform and Neural Network to Detect Damage of Elastic Thin Plate

2012 ◽  
Vol 594-597 ◽  
pp. 1105-1108 ◽  
Author(s):  
Dong Hai Xie ◽  
Hong Wei Tang
Keyword(s):  
Damage Detection ◽  
Thin Plate ◽  
Structural Damage ◽  
Civil Engineering ◽  
Wavelet Packet ◽  
Engineering Application ◽  
Physical Models ◽  
Structural Damage Detection ◽  
Engineering Structures ◽  
Elastic Thin Plate

In recent years,most existing engineering structures which have approached their normal life span, such as concrete plate, concrete beam etc., Almost all of these architecture structures are subjected to damage due to external loads, initial design defect etc. Structural damage detection and assessment has been becoming a focus of increasing interest in civil engineering field. However,At present, the study on structural damage detection is still at initial stage and the adopted main approaches are theoretical analysis and numerical simulation, but physical models are scarce. This leads to the yielded theories and methods are not sufficiently applicable for practical engineering application. Aiming at this, this paper focuses on developing effective methods of using wavelet and neural networks to detect the damage of elastic thin plate due to their extensive applications in civil engineering.

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