Non-baseline identification of delamination in plates using wavelet-aided fractal analysis of two-dimensional mode shapes

Bai, Runbo; Radzieński, Maciej; Cao, Maosen; Ostachowicz, Wiesław; Su, Zhongqing

doi:10.1177/1045389x14554136

Cited by 11 publications

(8 citation statements)

References 48 publications

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“…Figure 7 presents the f = 50 Hz pure unit sinusoidal time series and their Fourier transforms (FT), which are employed to simulate the signal measured from accelerometers in modal test with a shaker via harmonic excitation. First, WGN is added to the time series directly as presented in Equation (11). Figure 7 presents the slight, middle, and heavy polluted sinusoidal time series and the corresponding FT. We can see that even when signals are submerged by noises, little influence is found on the corresponding frequency spectrums, especially on the peak value at 50 Hz, the true component of the simulated vibration.…”

Section: Noise Immunity Comparisonsmentioning

confidence: 99%

“…This is similar to the frequency‐based method, whose application and accuracy is restricted by the dependence of the baseline data, too. Motivated by this issue, many improvements are implemented in modal testing or signal processing . As damages will cause local singularity in mode shape, the no‐baseline methods can be started by revealing singularities and hence damage locations.…”

Section: Introductionmentioning

confidence: 99%

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The hybrid multivariate analysis method for damage detection

Yang

Chen

Xie

et al. 2015

Struct. Control Health Monit.

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SUMMARYAs the defects and superiorities of indices are mutualisms frequently, such as noise immunity and damage sensitivity, damage identification based on single damage index may hardly present the effective result all the time, so multiple indices fusion method is introduced in this paper to achieve some complementary improvements. In this paper, two kinds of no-baseline mode shape-based damage indices, namely, the generalized local entropy and the curvature waveform capacity fractural, are utilized to construct the basic index set for combination, and the fuzzy cluster method is introduced in order to establish fusion process. These two parts generate the hybrid multivariate analysis method finally. The multivariate analysis' superiority mainly displays on two aspects: (1) the use of no-baseline mode shape-based method ensures the damage detection efficiency with the absence of healthy mode shape serving as baseline and (2) the fusion conducted by cluster method provides the mutual support and complementation among indices, which can enhance the robustness of algorithm. The performances of the present method are verified via sufficient numerical examples, and then experiments are demonstrated on three typical engineering structures, namely, cantilever beam, blower wheel, and rotor, for further validations.

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Section: Noise Immunity Comparisonsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The hybrid multivariate analysis method for damage detection

Yang

Chen

Xie

et al. 2015

Struct. Control Health Monit.

View full text Add to dashboard Cite

show abstract

“…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%

“…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. Many algorithms for estimating the FD have been proposed, such as algorithms by Pickover and Khorasani [2], Katz [3,4], Higuchi [5], Maragos and Sun [6], Petrosian [7]. In time series analysis, Katz's fractal dimension (KFD) calculation is derived directly from a 1D waveform signal, eliminating the preprocessing step of creating a binary sequence and is widely used to quantify the singularity or complexity of a waveform.…”

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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“…The fractal dimension method proposed by Hadjileontiadis et al [21,22] can be a feasible solution, but the original fractal dimension method cannot give the accurate damage location in higher mode shapes. With the aid of the affine transformation, the application of fractal dimension method was extended to higher mode shapes [23][24][25][26][27][28]. Besides the fractal dimension, entropy is also an applicable evaluation for complexity and singularity.…”

mentioning

confidence: 99%

Hybrid two-step method of damage detection for plate-like structures

Yang

Chen

Xie

et al. 2015

Struct. Control Health Monit.

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Summary This paper develops a two‐step approach for structural damage detection. In the first step, the two‐dimensional generalized local entropy (2D‐GLE) is proposed to identify the damage location and number for plates. Based on the 2D‐GLE, singularities in plates are revealed with the aid of mode shapes; hence, damages are localized, and the number of which is estimated. Besides, the statistical analysis is applied in the analysis of 2D‐GLE damage maps to overcome the difficulty in damage detection methods without baseline data. In the second step, the damage severities at the identified locations are evaluated via the optimization using artificial bee colony (ABC) with the designed frequency object function. The advantages of the present method are as follows: (1) No‐baseline in the measurement of mode shapes. Damage localization via the 2D‐GLE avoids using healthy mode shapes serving as baselines in damage detection, and then only damaged mode shapes are required. (2) No down‐sampling. Compared with the wavelet‐based methods, no down‐sampling enhances the algorithmic robustness and accuracy. (3) Efficiency. This hybrid two‐step method shrinks the solving parameter domain sharply in optimization via the first step. Hence, only the severity parameters need to be investigated in ABC. (4) Robustness. ABC ensures the robustness of the proposed method. Different damage cases are investigated in simulations, single‐damage/multiple‐damage cases, and noise immunity tests demonstrate that the proposed method is effective and accurate in damage detection. At last, a simple experiment is given to verify the present algorithm. Copyright © 2015 John Wiley & Sons, Ltd.

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Non-baseline identification of delamination in plates using wavelet-aided fractal analysis of two-dimensional mode shapes

Cited by 11 publications

References 48 publications

The hybrid multivariate analysis method for damage detection

The hybrid multivariate analysis method for damage detection

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

Hybrid two-step method of damage detection for plate-like structures

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