Double-Stage DMAS With Fresnel Zone Filtering in Guided Waves Damage Imaging

Malatesta, Michelangelo Maria; Neubeck, Robert; Moll, Jochen; Tschöke, Kilian; Marchi, Luca De

doi:10.1109/tuffc.2022.3162323

Cited by 6 publications

(5 citation statements)

References 49 publications

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“…Nevertheless, if another perspective is taken to observe Equation (19), it can be found that the essence of MUSIC algorithm is phase matching. In the classical MUSIC, the steering vector Aðx, yÞ is designed according to every potential scattering source, while the actual location information of the scattering source is included in the phase difference of the original response signals, which can be represented by signal subspace U s .…”

Section: Focusing Music Algorithm With Forward Propagationmentioning

confidence: 99%

“…Therefore, from the view of phase matching, since the phase is in alignment with each other after back propagation in signal subspace U s , as long as the steering vector is revised in the form without ToF information, Equation (19) still works. Because the phase difference is zero, that is, ½u 1 , u 2 , :::u M , = 0, the steering vector A is reformed as:…”

Section: Focusing Music Algorithm With Forward Propagationmentioning

confidence: 99%

“…Among amplitude imaging, the representative method is delay-and-sum (DAS) developed by Wang et al 17 and then improved by other scholars. 18,19 In DAS, the signals are superimposed according to time of flight (ToF) and total amplitude is extracted as imaging index. Furthermore, the total focusing method (TFM) [20][21][22] is presented to sum up all the signals from the dataset established by full matrix capture, which is actually a DAS-based method but with larger data.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Forward-propagation-free focusing MUSIC algorithm for Lamb waves

Lang

Yang

Kong

et al. 2023

Structural Health Monitoring

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The multiple signal classification (MUSIC) algorithm is originally used for direction of arrival estimation and frequency identification. MUSIC-like algorithms have gained their popularity in structural health monitoring (SHM) owing to their super-resolution characteristic and the virtue of baseline independence. MUSIC essentially is a searching algorithm to find the best phase difference matching between the eigenvector from signal subspace and the presupposed steering vector. However, in the guided-wave-based SHM (in plate-like structure, the guided wave is Lamb wave), the dispersion effect will definitely lead to phase distortion. Therefore, Xu et al. presented a focusing MUSIC algorithm where the time reversal technique is adopted to eliminate the dispersion in the way of back propagation. Seeing that the phase difference information, which is necessary for MUSIC, disappears after back propagation, the damage scattered wave packet, obtained by window truncation, is forward propagated again at the constant group velocity to recover the time of flight information. Nevertheless, the forward propagation process is superfluous from the view of phase matching. In the presented forward-propagation-free focusing MUSIC (FPF-F MUSIC) algorithm (the simplified version of Xu’s work), by revising the steering vector in the form of phase coincidence, the matching relation for MUSIC is modified from phase difference matching to phase alignment matching, so that the forward propagation and the steering vector traversal setting for every inspection point are all omitted. The damage localization performance of FPF-F MUSIC is verified on the aluminum plate with double through-hole and surface defects under uniform linear and circular arrays.

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Section: Focusing Music Algorithm With Forward Propagationmentioning

confidence: 99%

Section: Focusing Music Algorithm With Forward Propagationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Forward-propagation-free focusing MUSIC algorithm for Lamb waves

Lang

Yang

Kong

et al. 2023

Structural Health Monitoring

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“…DMAS has been further improved as lagbased DMAS (L-DMAS) [29], subarray average DMAS (SA-DMAS) [30], double-stage DMAS (DS-DMAS) [31], baseband DMAS (BB-DMAS) [32], etc. It has been applied to CFRP defect imaging detection [33], demonstrating its ability to suppress noise and artefacts. However, the DMAS-based approaches do not consider the autocorrelation component of the echo data, resulting in output energy loss and high computational complexity with multiplication operations.…”

Section: Introductionmentioning

confidence: 99%

High-resolution defect imaging of composites using delay-sum-and-square beamforming algorithm

Zhao,

Zhang,

Zhang

et al. 2024

Meas. Sci. Technol.

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High-resolution ultrasonic imaging for defects in anisotropic multilayer carbon fiber reinforced polymers (CFRPs) is challenging because of the severe ultrasonic attenuation and the low signal-to-noise ratio (SNR) of echoes. The existing delay-multiply-and-sum (DMAS) beamforming outperforms delay-and-sum (DAS) beamforming in resolution, but with high computational complexity and energy loss. This paper presents a novel delay-sum-and-square (DSAS) beamforming algorithm. It takes full advantage of spatial coherence of captured data in the receiving and transmitting apertures. The non-coherent components caused by background noise are suppressed during the imaging. The back-wall reflection method (BRM) is used to correct the direction-dependent velocity. Full-matrix data is experimentally captured and processed on three different CFRP samples. Compared with DAS and DMAS, DSAS has a significant improvement in resolution, SNR and contrast. It demonstrates excellent defect characterization and noise suppression capability with only 17.4% computation time of DMAS.

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“…The guided wave-based SHM techniques is a major category of SHM methodologies that are widely studied due to the relatively cheap operational cost, the capability to scan large areas and the ability to detect small imperfections/damage [6], [7]. Many algorithms such as the delay-and-sum (DAS) [8], [9] and the time reversal [10], [11] and multiple signal classification (MUSIC) [12], [13] algorithms have also been extensively analyzed for damage imaging using guided waves.…”

Section: Introductionmentioning

confidence: 99%

Guided Wave Based Damage Identification in Composite Strips Using Inverse Multiresolution Wavelet Methods

Dimitriou,

Saravanos

2023

10th ECCOMAS Thematic Conference on Smart Structures and Materials

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An inverse procedure for damage identification based on guided waves using the multiresolution finite wavelet domain method is presented. The forenamed method utilizes Daubechies wavelet and scaling functions for the approximation of state variables and as such, it involves two types of solutions, the coarse and the fine solutions. In that way, the multiresolution nature of the method can be utilized for efficient damage estimation in experimental applications since the fine solutions of the method have manifested remarkable localization capabilities and high sensitivity to damage. In order to fully take advantage of the additional functionalities of the multiresolution method, full-field displacement measurements of the guided wave propagation phenomenon are employed. Wavelet decomposition using Daubechies wavelets is now applied on the measurements in each different time step. The decomposition will lead to an approximation and a detail component that are directly comparable to the coarse and fine solution of the multiresolution simulation, respectively. Therefore, several multiresolution models can be created using the same Daubechies wavelets as the decomposition of the experimental data, so as to compare the simulation results with the measured ones. Numerical results evince that comparing the detail component of the experiments with the fine solution of the simulations, and their respective wavenumber spectra, using appropriate metrics can lead to efficient damage identification. In such manner, an optimization process can be conducted, utilizing the cross-correlation of both the structural responses and their wavenumber content for the definition of the objective function, in order to characterize the investigated damaged composite strip cases. This procedure can lead to more sensitive and accurate damage estimation due to the advantages of the multiresolution analysis.

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Double-Stage DMAS With Fresnel Zone Filtering in Guided Waves Damage Imaging

Cited by 6 publications

References 49 publications

Forward-propagation-free focusing MUSIC algorithm for Lamb waves

Forward-propagation-free focusing MUSIC algorithm for Lamb waves

High-resolution defect imaging of composites using delay-sum-and-square beamforming algorithm

Guided Wave Based Damage Identification in Composite Strips Using Inverse Multiresolution Wavelet Methods

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