Quantitative Defect Size Evaluation in Fluid-Carrying Nonmetallic Pipes

Shah, Maharshi B.; Gao, Yuki; Ravan, Maryam; Amineh, Reza K.

doi:10.1109/tmtt.2022.3176904

Cited by 11 publications

(3 citation statements)

References 29 publications

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“…Microwave imaging detection methods enable visual detection of defects. The second method is microwave coefficient detection, which involves processing the amplitude and phase of the echo signal [ 21 , 22 , 23 , 24 ]. By analyzing these characteristics, the location, size, and other parameters of defects can be derived.…”

Section: Introductionmentioning

confidence: 99%

Visual Quantitative Detection of Delamination Defects in GFRP via Microwave

Yang

Wang

et al. 2023

Sensors

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Glass Fiber reinforced polymers (GFRPs) are widely used and play an important role in modern society. The multilayer structure of GFRPs can lead to delamination defects during production and service, which can have a significant impact on the integrity and safety of the equipment. Therefore, it is important to monitor these delamination defects during equipment service in order to evaluate their effects on equipment performance and lifespan. Microwave imaging testing, with its high sensitivity and noncontact nature, shows promise as a potential method for detecting delamination defects in GFRPs. However, there is currently limited research on the quantitative characterization of defect images in this field. In order to achieve visual quantitative nondestructive testing (NDT), we propose a 2D-imaging visualization and quantitative characterization method for delamination defects in GFRP, and realize the combination of visual detection and quantitative detection. We built a microwave testing experimental system to verify the effectiveness of the proposed method. The results of the experiment indicate the effectiveness and innovation of the method, which can effectively detect all delamination defects of 0.5 mm thickness inside GFRP with high accuracy, the signal-to-background ratio (SBR) of 2D imaging can reach 4.41 dB, the quantitative error of position is within 0.5 mm, and the relative error of area is within 11%.

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Section: Introductionmentioning

confidence: 99%

Visual Quantitative Detection of Delamination Defects in GFRP via Microwave

Yang

Wang

et al. 2023

Sensors

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“…They lack more advanced postprocessing that could lead to a higher quality assessment of the material. High-resolution imaging results have been presented in [13][14][15] where near-field holographic imaging has been proposed and applied to the data collected at the near-field of the antennas. The advantages of near-field holographic imaging are: (1) far-field assumptions in conventional holographic imaging are avoided by introducing a new formulation of the solution for the imaging problem, (2) it is capable of processing the evanescent waves leading to higher resolutions beyond the diffraction limit, (3) the assumption for point-wise antennas typically used in conventional holographic imaging is avoided due to the measurement of the so-called point-spread function (PSF), and (4) unlike conventional holographic imaging, it is possible to use the measurement for an array of receiver antennas and achieve super-resolution using narrowband data.…”

Section: Introductionmentioning

confidence: 99%

“…There, narrowband data collected by an array of receiver antennas have been employed for the inspection of double concentric pipes. A similar setup has been also used in [15] for thickness profile estimation of a single nonmetallic pipe.…”

Section: Introductionmentioning

confidence: 99%

Near-Field Imaging of Dielectric Components Using an Array of Microwave Sensors

2023

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Microwave imaging is a high-resolution, noninvasive, and noncontact method for detecting hidden defects, cracks, and objects with applications for testing nonmetallic components such as printed circuit boards, biomedical diagnosis, aerospace components inspection, etc. In this paper, an array of microwave sensors designed based on complementary split ring resonators (CSRR) are used to evaluate the hidden features in dielectric media with applications in nondestructive testing and biomedical diagnosis. In this array, each element resonates at a different frequency in the range of 1 GHz to 10 GHz. Even though the operating frequencies are not that high, the acquisition of evanescent waves in extreme proximity to the imaged object and processing them using near-field holographic imaging allows for obtaining high-resolution images. The performance of the proposed method is demonstrated through simulation and experimental results.

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