Sparse-TFM Imaging of Lamb Waves for the Near-Distance Defects in Plate-Like Structures

Zhang, Hai Yan; Lin, Min; Fan, Guopeng; Hui, Zhang; Zhu, Wen-Fa; Zhu, Qi

doi:10.3390/met9050503

Cited by 14 publications

(12 citation statements)

References 29 publications

(31 reference statements)

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“…Before the experiment, in order to achieve the biggest aperture and improve the signal strength, the probe was mount on the center of the upper edge of the workpiece. In this way, the in-plane displacement can be produced [20]. The sampling frequency used in the analysis was 50 MHz.…”

Section: Experimental Setup and Pretreatment Resultsmentioning

confidence: 99%

The Auto-Correlation of Ultrasonic Lamb Wave Phased Array Data for Damage Detection

Zhang

Fan

et al. 2019

Metals

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Ultrasonic phased array is widely used for damage detection recently because of its high sensitivity and rapid scanning without sensor movements. However, the measured signal is always influenced by the remnants of the initial excitation and the nonlinear signals from the instrumentation, which limits its application in thin-plate structures. To address this issue, an approach called auto-correlation subtraction is proposed to extract the scattering information of defects in this paper. In order to testify the feasibility of this method for damage detection, the experiments were carried out on three thin aluminum plates combined with the total focusing method (TFM) for imaging. By auto-correlating the full matrix data received by sensors and then subtracting the average auto-correlation of noise recorded by all receivers, the coherent scattered signal containing defect information is recovered. The experimental results indicate that the coherent travel time is in agreement with the theoretical value and the signal-to-noise ratio are improved. Additionally, compared with the cross-correlation technique, the time synchronization between different receivers is not necessary with the auto-correlation method. Results indicate that the presented method can improve the imaging resolution and has a great potential in the field of non-destructive testing.

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Section: Experimental Setup and Pretreatment Resultsmentioning

confidence: 99%

The Auto-Correlation of Ultrasonic Lamb Wave Phased Array Data for Damage Detection

Zhang

Fan

et al. 2019

Metals

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“…The proposed method improves the detection ability of TFM in the near-field range. However, unnecessary noise [16] is generated at the same time, because only a finite number of averaging operations are applied on the diffuse field, which affects the defect identification.…”

Section: Introductionmentioning

confidence: 99%

Instantaneous Phase Coherence Imaging for Near-Field Defects by Ultrasonic Phased Array Inspection

Zhang

Zeng

Fan

et al. 2020

Sensors

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This paper describes an imaging method for near-field defect detection in aluminum plates based on Green’s function recovery and application of instantaneous phase coherence weighting factors. The directly acquired acoustic information of near-field defects is usually obscured by the nonlinear effects due to the physical limitation of the acquisition system. Using the diffuse field to recover the Green’s function can effectively retrieve the early time information. However, averaging operations of finite number in this process produces an imperfect imaging result. In order to improve the image quality, two kinds of instantaneous phased coherence weighting factors are used to weight the Green’s function to reduce the background noise and improve the signal-to-noise ratio: the instantaneous phase coherence factor (IPCF), and the instantaneous phase weighting factor (IPWF). Experiments are conducted on two aluminum plates with two and four near-field defects, respectively. As a result, the background noise of amplitude images weighted by IPCF and IPWF is less than that of the conventional total focusing method (TFM). In addition, the IPCF image achieves a better signal-to-noise ratio (SNR) than that of IPWF, and the phase discontinuity in an IPWF image is suppressed through the IPCF.

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“…Peng et al [12] reduce the computation time by increasing the array aperture on the basis of the uniform sparse array, but the sound field characteristics of the uniform sparse array are quite different from the full array, and the image is greatly affected by the beam sidelobes. In the optimization method of sparse array, Zhang et al [13] used the cross-correlation method to reconstruct the Green's function, restored the ultrasonic signal submerged by noise in the near-field area, and optimized the sparse array using genetic algorithm (GA) to achieve sparse TFM imaging of near-surface defects in the plate structure. Hu et al [14] established a two-layer TFM imaging model, then used GA to optimize the sparse array and used the effective aperture theory to optimize the sparse image.…”

Section: Introductionmentioning

confidence: 99%

Ultrasonic Phased Array Sparse TFM Imaging Based on Virtual Source and Phase Coherent Weighting

2020

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Total focus method (TFM) is an ultrasonic phased array imaging method and has a larger dynamic focusing range and higher spatial resolution than traditional imaging methods. But TFM needs to process a large amount of data, resulting in a long imaging time, which greatly limits its application and development in the industrial field. The sparse method can improve the computing efficiency by reducing the amount of data, but the resolution and intensity of sparse image are very low. This paper proposes a virtual source sparse TFM (VSSTFM) method based on phase coherent weighting (PCW) to improve the spatial resolution and intensity of the sparse TFM imaging. The layout of virtual sources in the virtual source array is designed and optimized by genetic algorithm. According to the phase distribution characteristics of the ultrasonic testing signal, a phase coherence factor is constructed to weight the VSSTFM image to further improve the image quality. Experimental results show that compared with conventional TFM, the proposed method can improve the imaging efficiency by 66.56 % while providing significantly higher image quality than TFM imaging.

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Sparse-TFM Imaging of Lamb Waves for the Near-Distance Defects in Plate-Like Structures

Cited by 14 publications

References 29 publications

The Auto-Correlation of Ultrasonic Lamb Wave Phased Array Data for Damage Detection

The Auto-Correlation of Ultrasonic Lamb Wave Phased Array Data for Damage Detection

Instantaneous Phase Coherence Imaging for Near-Field Defects by Ultrasonic Phased Array Inspection

Ultrasonic Phased Array Sparse TFM Imaging Based on Virtual Source and Phase Coherent Weighting

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