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Sensitizing The Multiple Damage Identification In Beam Structure Using Hoelder Exponent And Wavelets

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TLDR
In this paper, a damage identification algorithm based on continuous wavelet transform is presented and next the algorithm is verified using a numerical beam model with different simulated damage cases, and the effect of using only damaged data (mode shape from damaged beam) is investigated and compared.
Abstract
In case of damage identification using continuous wavelet transform, the damage is identified by sensing the local perturbations in the spatial signal. First, a damage identification algorithm based on continuous wavelet transform is presented in this paper and next the algorithm is verified using a numerical beam model with different simulated damage cases. Multiple location damage cases are studied for damage identification. The effect of using only damaged data (mode shape from damaged beam) is investigated and compared. Another method of simultaneously detecting, locating and quantifying damage in a single graph is to plot the Hoelder exponent along the beam length. At each discrete point (node number) of beam, the Hoelder exponent is estimated and the resulting values are plotted along the length of beam. Any sudden variation of the exponent at a particular region, provide information on possibility of damage and the minimum value of exponent at that region gives the damage severity.

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References
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Journal ArticleDOI

Singularity detection and processing with wavelets

TL;DR: It is proven that the local maxima of the wavelet transform modulus detect the locations of irregular structures and provide numerical procedures to compute their Lipschitz exponents.
ReportDOI

Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: A literature review

TL;DR: A review of the technical literature concerning the detection, location, and characterization of structural damage via techniques that examine changes in measured structural vibration response is presented in this article, where the authors categorize the methods according to required measured data and analysis technique.
Journal ArticleDOI

Damage detection from changes in curvature mode shapes

TL;DR: In this article, a new parameter called curvature mode shape is investigated as a possible candidate for identifying and locating damage in a structure, and it is shown that the absolute changes in the curvature shape are localized in the region of damage and hence can be used to detect damage.
Journal ArticleDOI

Vibration–based structural damage identification

TL;DR: Current research regarding feature selection and statistical model development will be emphasized with the application of vibration–based damage detection to a large–scale laboratory structure.
Journal ArticleDOI

Damage detection using the frequency-response-function curvature method

TL;DR: In this article, the frequency response function (FRF) curvature method is proposed for structural damage detection, which is based on only the measured data without the need for any modal identification.
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