Paper
16 August 2001 Structural health monitoring using wavelet transforms
Venkata Kasi Amaravadi, Vittal S. Rao, Leslie R. Koval, Mark M. Derriso
Author Affiliations +
Abstract
A new method of damage detection using wavelet transforms and curvature mode shapes is proposed in this paper. A damage in the structure results in changing its dynamic characteristics such as natural frequencies, damping, and mode shapes. A number of researchers have investigated structural health monitoring techniques for identifying, locating, and quantifying the damage using the changes in the dynamic response of a damaged structure. Curvature mode shape and wavelet maps are two such methods that have already been used to locate damages. These methods have some limitations in determining the exact location of the damages. We have developed a technique by combining these two methods for enhancing the sensitivity and accuracy in damage location. The mode shapes are double differentiated using the central difference approximation to obtain the curvature mode shape. Then a wavelet map is constructed for the curvature mode shape. It is shown that this method can be used to determine the location of the damages. The proposed method is applied to detect damage in an experimental lattice structure and a cantilever beam with multiple damages. The mode shapes are obtained analytically using finite element analysis and also experimentally using laser vibrometer. The experimental results obtained are satisfactory.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Venkata Kasi Amaravadi, Vittal S. Rao, Leslie R. Koval, and Mark M. Derriso "Structural health monitoring using wavelet transforms", Proc. SPIE 4327, Smart Structures and Materials 2001: Smart Structures and Integrated Systems, (16 August 2001); https://doi.org/10.1117/12.436537
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Cited by 28 scholarly publications.
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KEYWORDS
Wavelets

Wavelet transforms

Damage detection

Signal detection

Structural health monitoring

Discrete wavelet transforms

Aluminum

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