Lamb Wave-Based Damage Localization Feature Enhancement and Extraction Method for Stator Insulation of Large Generators Using VMD and Wavelet Transform

Li, Ruihua; Luo, Jing; Hu, Bo

doi:10.3390/s20154205

Cited by 8 publications

(6 citation statements)

References 24 publications

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“…For structural health monitoring in an aluminum alloy plate, the crack damage is generally considered as a notch or an open crack where there is no contact between two cracked surfaces [ 9 , 15 , 32 , 33 ]. In this study, Lamb wave testing is performed on plates with artificial cracks or simulation cracks of different sizes to characterize a through-thickness crack under tensile load.…”

Section: Experimental Validationmentioning

confidence: 99%

A Crack Size Quantification Method Using High-Resolution Lamb Waves

Yang

Zhang

2021

Sensors

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Traditional tone burst excitation cannot attain a high output resolution, due to the time duration. The received signal is much longer than that of excitation during the propagation, which can increase the difficulty of signal processing, and reduce the resolution. Therefore, it is of significant interest to develop a general methodology for crack quantification through the optimal design of the excitation waveform and signal-processing methods. This paper presents a new crack size quantification method based on high-resolution Lamb waves. The linear chirp (L-Chirp) signal and Golay complementary code (GCC) signal are used as Lamb wave excitation signals. After dispersion removal, these excitation waveforms, based on pulse compression, can effectively improve the inspection resolution in plate-like structures. A series of simulations of both healthy plates and plates with different crack sizes are performed by Abaqus CAE, using different excitation waveforms. The first wave package of the S0 mode after pulse compression is chosen to extract the damage features. A multivariate regression model is proposed to correlate the damage features to the crack size. The effectiveness of the proposed crack size quantification method is verified by a comparison with tone burst excitation, and the accuracy of the crack size quantification method is verified by validation experiments.

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Section: Experimental Validationmentioning

confidence: 99%

A Crack Size Quantification Method Using High-Resolution Lamb Waves

Yang

Zhang

2021

Sensors

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“…Over the last decades, some classic methods, such as fast Fourier transform [17,18], wavelet analysis [19,20] and short-time Fourier transform [21,22], are introduced to obtain the signals related with the reflection waves of Lamb waves. Recently, some modern methods including principal component analysis [23,24], empirical mode decomposition [25,26], variational mode decomposition [27,28] and singular spectrum analysis (SSA) [29][30][31], are employed to enhance the reflection waves of damages. Especially, SSA has been proved to be an effective method of signal feature enhancement for Lamb waves by many studies and it is preferred by many researchers for damage detection in thin plates.…”

Section: Introductionmentioning

confidence: 99%

Damage identification of thin plate-like structures combining improved singular spectrum analysis and multiscale cross-sample entropy (ISSA-MCSEn)

Wang¹,

Lu²,

Song³

et al. 2023

Smart Mater. Struct.

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In this paper, a new method integrating the improved singular spectrum analysis and the multiscale cross-sample entropy (ISSA-MCSEn) is developed to identify the size of early damages in thin plate-like structures. In the algorithm, with the help of ISSA, the principal components relevant to the reference and damage-induced signals are successfully extracted, and then the components related to the damage are reconstructed for damage size detection. Lastly, the MCSEn of the reconstructed signal is computed as a new damage index to evaluate the size of the damage. To validate the proposed ISSA-MCSEn algorithm, two different experiments are conducted on aluminum and CFRP plates to detect simulated crack and through-hole, respectively. Comparative performance analysis of ISSA and SSA demonstrates that the total increment of the normalized MCSEn by using ISSA is 30%~81% while the one by using SSA is only 6.5%~9%, which demonstrates that the performance of the proposed ISSA is much better than SSA. The experimental results also show that the average of the normalized MCSEn of the proposed algorithm increases by over 77% and 28% as the size of the two damages in CFRP and aluminium plates changes from 0 to 8mm and 0 to 1.2mm, respectively. Moreover, the relationship between the normalized MCSEn and damages’ size is well linear, and the Pearson’s coefficient of their fitting curves is more than 0.99, which demonstrates that this linear relationship can be employed for damage size detection in both CRFP and aluminium plates. The linear relationship between the damage size and normalized MCSEn is used for damage detection, and the relative error between the actual and detected size is 1.64%~6.92%. In addtion, the performance comparison of ISSA-MCSEn and SSA-FuzzyEn shows that the total increment of the ISSA-MCSEn algorithm due to the damage is 30%~81% while the one of SSA-FuzzyEn is only 4%~15%, which indicates that the proposed ISSA-MCSEn is more sensitive to the damage than SSA-FuzzyEn and it is more suitable for detection of small-size damages.

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“…In the last decades, with the help of the rapid development and successful applications of time series analysis methods, many signal processing technologies, including filtering [21], correlation analysis [22], fast Fourier transform [23,24], shorttime Fourier transform [25,26], empirical mode decomposition (EMD) [27,28], ensemble EMD [29], variational mode decomposition (VMD) [30] and other methods [31][32][33][34][35][36], are implemented to enhance or extract the feature of the damage from the complex signals in Lamb wave-based SHMs. Moreover, some researches recently indicate that the singularities of the signal are related to some features of the structural damage, and these singularities are usually obtained by singular spectrum analysis (SSA).…”

Section: Introductionmentioning

confidence: 99%

Singular spectrum analysis and fuzzy entropy-based damage detection on a thin aluminium plate by using PZTs

Song

Ming

et al. 2022

Smart Mater. Struct.

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In this research, a new method based on singular spectrum analysis (SSA) and fuzzy entropy is developed for damage detection on thin wall-like structures, and the normalized fuzzy entropy is employed as an indicator to identify the severity of the damage. The Lead Zirconate Titanate (PZT) transducers are used in this research to generate and detect the Lamb waves. During the detection, the collected signals from the PZT sensors are firstly decomposed and reconstructed by SSA to extract the feature of the damage, and then the reconstructed signals with the feature of the damage are processed to obtain the normalized fuzzy entropy. An experimental setup of an aluminium plate with added magnets is fabricated to validate the proposed method. The experimental results show that when magnets are attached on the aluminium plate, the normalized fuzzy entropy is smaller than that when there are no magnets. That is because when magnets are placed on the plate, the movement and some vibration modes of Lamb waves are disturbed by the added magnets and this disturbing effect can be enhanced by increasing the number and locations of the added magnets, and eventually the complexity and nonlinearity of the waves are weakened. The experimental results of a single damage with different number of magnets indicate that the normalized fuzzy entropy decreases linearly as the number of the added magnets increases, which demonstrates that the proposed method can be used to detect the severity of the damage. Moreover, the experimental results of multi-damage on different locations indicate that the normalized fuzzy entropy is relevant with both the total number and locations of the added magnets. The normalized fuzzy entropy decreases linearly as the total number of the magnets increases, and the entropy of a single damage is smaller than that of the multi-damage with the same total number of magnets, which demonstrates that the proposed method also can be used for multi-damage detection on a thin plate. This study provides us a new approach to identifying a single or multiple damages on thin wall-like structures.

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Lamb Wave-Based Damage Localization Feature Enhancement and Extraction Method for Stator Insulation of Large Generators Using VMD and Wavelet Transform

Cited by 8 publications

References 24 publications

A Crack Size Quantification Method Using High-Resolution Lamb Waves

A Crack Size Quantification Method Using High-Resolution Lamb Waves

Damage identification of thin plate-like structures combining improved singular spectrum analysis and multiscale cross-sample entropy (ISSA-MCSEn)

Singular spectrum analysis and fuzzy entropy-based damage detection on a thin aluminium plate by using PZTs

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