Damage detection in plate-like structures using High-Order mode shape derivatives

Abstract

This paper investigates the application and reliability of using high-order mode shape derivatives especially, the fourth derivative in damage detection of plate-like structures. Numerical analyses have been carried out for low-and high-order mode shapes of simply supported and cantilever steel plate models. Six scenarios of damages are studied for plate models to represent different damage characteristics. The influence of artificial noise on the damage identification using changes in fourth derivative of mode shapes has been investigated. Based on the numerical studies, it is shown that the fourth derivative of mode shape is promising in detecting and locating structural damage in plate-like structures since it is localized at the damage locations even for a small amount of damage using only one of the mode shapes. Both low-and high-order mode shapes give successful results. Also, damage indices of the fourth derivatives give smoother localization and consequently better damage identification than those of curvature of mode shapes. Furthermore, using high-order modes (which can be measured by advanced sensors) does not improve the results of damage identification using the fourth derivative. Unfortunately, damage detection using changes in fourth derivative of mode shapes is sensitive to measurement noise.

Full‐field out‐of‐plane vibration displacement acquisition based on speckle‐projection digital image correlation and its application in damage localization

“…For the damage localization problem, in comparison with mode shapes, the curvature mode shapes are more sensitive to damage and are used more widely 18 . However, due to the noise susceptibility of curvature mode shape estimation, even a small noise level can be significantly amplified by the numerical finite difference method, leading to degradation of the damage localization accuracy 19,20 . To circumvent this problem, statistical methods, smoothing techniques, and wavelet transform methods are commonly adopted to reduce the effects of measurement noise on curvature mode shape estimation 21,22 .…”

“…18 However, due to the noise susceptibility of curvature mode shape estimation, even a small noise level can be significantly amplified by the numerical finite difference method, leading to degradation of the damage localization accuracy. 19,20 To circumvent this problem, statistical methods, smoothing techniques, and wavelet transform methods are commonly adopted to reduce the effects of measurement noise on curvature mode shape estimation. 21,22 In this paper, a Gaussian-Laplacian filter is proposed to enhance the noise robustness and accuracy of curvature mode shape estimation.…”

An identification method of the weak link of stiffness for cantilever beam structure

“…Fourth-order derivatives of the mode shapes were employed to detect and locate the damage in simply supported and cantilever steel-plate model structures but with the drawback of a heightened sensitivity to measurement noise. 20 In the absolute difference mode shape curvature (ADMSC) method, this method is based on the difference between the intact curvature mode shape and the damaged curvature mode shape to detect and locate the damaged location of the beam structure. The limitation of this method is that depends on undamaged modal response of the structure.…”