scholarly journals Damage identification of structures using experimental modal analysis and continuous wavelet transform

2017 ◽  
Vol 2 (1) ◽  
pp. 61-71
Author(s):  
A. Gholizad ◽  
H. Safari ◽  
◽  
Keyword(s):  
Wavelet Transform ◽  
Modal Analysis ◽  
Continuous Wavelet Transform ◽  
Damage Identification ◽  
Experimental Modal Analysis ◽  
Continuous Wavelet

Damage Identification Research for Steel Plate Based on Lamb Wave

2013 ◽  
Vol 330 ◽  
pp. 225-230 ◽  
Author(s):  
Xin Gang Li ◽  
Qiang Chen ◽  
Shu Hua Chen ◽  
Yue Min Wang ◽  
Guo Zhi Song
Keyword(s):  
Wave Propagation ◽  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Lamb Wave ◽  
Damage Identification ◽  
Steel Plate ◽  
Wave Structure ◽  
Continuous Wavelet ◽  
The Law ◽  
Identification Research

According to the characteristics of wave propagation in steel plate, choosing the suitable excite mode and frequency. Based on the wave structure of A0S0, obtaining its displacement discipline, then arriving at the sensitivity effect for different depth of defect in different frequency. Making different depth circular damage in the steel plate, calculating the law of lamb wave in different damage by using continuous wavelet transform.

scholarly journals A Novel Method to Estimate the Damage Severity Using Spatial Wavelets and Local Regularity Algorithm

2020 ◽  
Vol 14 (54) ◽  
pp. 36-55
Author(s):  
Mallikarjuna Reddy ◽  
Arun Kumar K
Keyword(s):  
Wavelet Transform ◽  
Mode Shape ◽  
Continuous Wavelet Transform ◽  
Structural Damage ◽  
Damage Identification ◽  
Local Regularity ◽  
Beam Model ◽  
Continuous Wavelet ◽  
Novel Method ◽  
Shape Data

 In the process of structural damage detection using continuous wavelet transform (CWT), the perturbation or damage is located by identifying the defects locally in the input signal data.  In this work the damage identification procedure using continuous wavelet transform is developed. This method is studied numerically using a simple beam model. The influence of reduced spatial sampling using fundamental mode shape is investigated in detail. The method is also investigated to ascertain the smallest level of damage identified using strain energy mode shape data.

scholarly journals Continuous Wavelet Transform of Schwartz Distributions in DL2′(Rn), n ≥ 1

Symmetry ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1106
Author(s):  
Jagdish N. Pandey
Keyword(s):  
Wavelet Transform ◽  
Function Space ◽  
Continuous Wavelet Transform ◽  
Inversion Formula ◽  
Continuous Wavelet ◽  
The Real ◽  
Schwartz Distributions ◽  
Distributional Sense ◽  
Wavelet Inversion

We define a testing function space DL2(Rn) consisting of a class of C∞ functions defined on Rn, n≥1 whose every derivtive is L2(Rn) integrable and equip it with a topology generated by a separating collection of seminorms {γk}|k|=0∞ on DL2(Rn), where |k|=0,1,2,… and γk(ϕ)=∥ϕ(k)∥2,ϕ∈DL2(Rn). We then extend the continuous wavelet transform to distributions in DL2′(Rn), n≥1 and derive the corresponding wavelet inversion formula interpreting convergence in the weak distributional sense. The kernel of our wavelet transform is defined by an element ψ(x) of DL2(Rn)∩DL1(Rn), n≥1 which, when integrated along each of the real axes X1,X2,…Xn vanishes, but none of its moments ∫Rnxmψ(x)dx is zero; here xm=x1m1x2m2⋯xnmn, dx=dx1dx2⋯dxn and m=(m1,m2,…mn) and each of m1,m2,…mn is ≥1. The set of such wavelets will be denoted by DM(Rn).

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