Damage characterization in plates using singularity of scale mode shapes

Cao, Maosen; Xu, Hao; Bai, Runbo; Ostachowicz, Wiesław; Radzieński, Maciej; Chen, L.

doi:10.1063/1.4916678

Cited by 10 publications

(2 citation statements)

References 26 publications

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“…Singularity, usually caring the most important information of signal, can be used to determine the abnormal phenomenon of the signal. Hitherto, many kinds of singularity detection techniques have been developed [1], among which the fractal dimension (FD) analysis based methods have been the most widely used ones [2][3][4][5][6][7][8]. The FD is a ratio that provides a statistical index of complexity, which compares how the detail in a pattern changes with the scale at which it is measured.…”

Section: Introductionmentioning

confidence: 99%

Singularity detection of 2D signals using fractal dimension analysis of scale information

Bai¹,

Xu²,

Feng³

2016

J. vibroeng.

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Fractal dimension (FD) analysis has been widely used in signal processing. The key issue in signal processing is the singularity detection. One of the main problems for FD analysis of signals is its susceptibility to measurement noise, likely obscuring the identification of singularities. To address this deficiency, a new physical quantity, named ‘the scale-window fractal dimension (SWFD)’, is proposed and a SWFD analysis method is formed to identify the singularities in the noisy 2D signal. With this method, the noisy 2D signal first is decomposed into sets of scale signals with the aid of 2D Gabor wavelet transforms; then SWFD estimates are calculated along every scale signals to form the FD surface. The singularities can be localized by the sudden changes in the spatial variation of the FD surface. As an application of the method, the identification of damage singularity for an experimental composite plate is performed with the mode shapes measured by a scanning laser vibrometer as the analyzed 2D signals. The results show that the SWFD analysis method has the prominent features of high accuracy of singularity localization and strong robustness to noise.

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Section: Introductionmentioning

confidence: 99%

Singularity detection of 2D signals using fractal dimension analysis of scale information

Bai¹,

Xu²,

Feng³

2016

J. vibroeng.

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“…The interest to monitor a structure for purpose of damage detection at an early stage is prevailing in the fields of civil, mechanical and aerospace engineering (Li et al 2013). Lots of vibration-based damage detection methods (Ni et al 2001;Lei et al 2013;Min et al 2015;Blachowski et al 2015;Cao et al 2015;An et al 2015) have been developed in the past decades. Among these methods, the flexibility-based technique (Pandey and Biswas 1994;An and Ou 2013a) has attracted considerable attention.…”

Section: Introductionmentioning

confidence: 99%

Numerical study on LDLT decomposition-based damage locating vector method for truss structures

An¹,

Błachowski²,

Ou³

2015

Proceedings of the Second International Conference on Performance-Based and Life-Cycle Structural Engineering (PLSE 2015)

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Real-time structural health monitoring is very important for truss structures especially those having large-spans. In recent years, many methods have been proposed for damage monitoring of truss structures. However, damage sensitivity of these methods is still required to be improved. In this work an efficient damage localization technique for truss structures is proposed, which is based on the LDL T decomposition of the flexibility difference matrix and the Damage Locating Vectors (DLV) method. Compared with the present Stochastic DLV (SDLV) method, the proposed method is modified in two ways. First of all, the way of calculating the damage locating vectors is modified by using LDL T decomposition instead of Singular Value Decomposition. Secondly, in order to compute the flexibility, the mass matrix which is obtained from the finite element model is used to mass-normalize mode shapes identified from ambient excitations. As a result, the proposed LDL T -DLV method has a higher sensitivity to damage for different types of truss members. The effectiveness of the proposed LDL T -DLV method is validated with the numerical example of a laboratory-scale Bailey truss bridge.

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