Investigation of the effect of a bend on pipe inspection using microwave NDT

Chen, Guanren; Katagiri, Takuya; Song, Haicheng; Yusa, Noritaka; Hashizume, Hidetoshi

doi:10.1016/j.ndteint.2019.102208

Cited by 19 publications

(11 citation statements)

References 23 publications

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“…As the frequency increased, each curve showed an overall upward trend. This occurred because signals of shorter wavelengths change more in phase as they propagate in dielectric materials [33]. In order to characterize the randomness of the target crack, the crack was simplified to the model shown in tennas.…”

Section: Simulation Validationmentioning

confidence: 99%

“…As the frequency increased, each curve showed an overall upward trend. This occurred because signals of shorter wavelengths change more in phase as they propagate in dielectric materials [33]. Figures 6a, 7a and 8a show the relationship between ∆η t−s and frequency in 30-40 GHz bands with different crack widths, depths, and angles, respectively.…”

Section: Simulation Validationmentioning

confidence: 99%

Section: Simulation Validationmentioning

confidence: 99%

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Simplistic, Efficient, and Low-Cost Crack Detection of Dielectric Materials Based on Millimeter-Wave Interference

Chen

Yin

et al. 2022

Electronics

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This paper proposes a simplistic, efficient, and low-cost method of millimeter-wave nondestructive testing (NDT) of dielectric material cracks based on millimeter-wave interference. A relationship between combining efficiency, phase difference, and amplitude difference was analyzed. We found that phase difference was the main factor that affects combining efficiency. A change in combining efficiency of more than 1% was caused by a phase-difference altering of greater than 1.2° in a specific range. A relevant model was simulated with CST, and the operating frequency and antenna spacing were optimized to enhance sensitivity of the measuring system. Then, a Ka-band NDT system was built to test the combining efficiencies of different cracks. The experimental results showed that for polytetrafluoroethylene (PTFE) plates with a thickness of 5 mm, cracks with a width of about 0.4 mm, which is about 0.07 λg, could be detected at 35 GHz. Experimental results, simulation results, and theoretical derivation are basically consistent. Large-scale online applications of this NDT method in various industries appear feasible due to the above characteristics.

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Section: Simulation Validationmentioning

confidence: 99%

“…As the frequency increased, each curve showed an overall upward trend. This occurred because signals of shorter wavelengths change more in phase as they propagate in dielectric materials [33]. Figures 6a, 7a and 8a show the relationship between ∆η t−s and frequency in 30-40 GHz bands with different crack widths, depths, and angles, respectively.…”

Section: Simulation Validationmentioning

confidence: 99%

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Simplistic, Efficient, and Low-Cost Crack Detection of Dielectric Materials Based on Millimeter-Wave Interference

Chen

Yin

et al. 2022

Electronics

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“…Many academic research activities are being carried out on piping. Intensity-based optical system [9,10], microwave nondestructive testing [11], pipe NDT inspection using an automated robot [12][13][14], eddy-current-based crack recognition [15], etc., are among the investigated techniques. However, most damage detection techniques depend on the empirical and subjective judgment of experienced experts.…”

Section: Introductionmentioning

confidence: 99%

Improving the Ability of a Laser Ultrasonic Wave-Based Detection of Damage on the Curved Surface of a Pipe Using a Deep Learning Technique

Tola

Lee

et al. 2021

Sensors

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With the advent of the Fourth Industrial Revolution, the economic, social, and technological demands for pipe maintenance are increasing due to the aging of the infrastructure caused by the increase in industrial development and the expansion of cities. Owing to this, an automatic pipe damage detection system was built using a laser-scanned pipe’s ultrasonic wave propagation imaging (UWPI) data and conventional neural network (CNN)-based object detection algorithms. The algorithm used in this study was EfficientDet-d0, a CNN-based object detection algorithm which uses the transfer learning method. As a result, the mean average precision (mAP) was measured to be 0.39. The result found was higher than COCO EfficientDet-d0 mAP, which is expected to enable the efficient maintenance of piping used in construction and many industries.

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“…To date, a wide variety of techniques have been developed for structural health monitoring. These techniques include ultrasonic/acoustic-based techniques [ 3 , 4 , 5 , 6 , 7 , 8 , 9 ], eddy-current-based techniques [ 10 , 11 , 12 ], and microwave-based techniques [ 13 , 14 , 15 ]. These technologies are promising for specific structural health monitoring applications, however, they are not readily suited to being scaled up for applications such as monitoring the structural health of an entire city.…”

Section: Introductionmentioning

confidence: 99%

Sparse and Random Sampling Techniques for High-Resolution, Full-Field, BSS-Based Structural Dynamics Identification from Video

Martinez

Green

Silva

et al. 2020

Sensors

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Video-based techniques for identification of structural dynamics have the advantage that they are very inexpensive to deploy compared to conventional accelerometer or strain gauge techniques. When structural dynamics from video is accomplished using full-field, high-resolution analysis techniques utilizing algorithms on the pixel time series such as principal components analysis and solutions to blind source separation the added benefit of high-resolution, full-field modal identification is achieved. An important property of video of vibrating structures is that it is particularly sparse. Typically video of vibrating structures has a dimensionality consisting of many thousands or even millions of pixels and hundreds to thousands of frames. However the motion of the vibrating structure can be described using only a few mode shapes and their associated time series. As a result, emerging techniques for sparse and random sampling such as compressive sensing should be applicable to performing modal identification on video. This work presents how full-field, high-resolution, structural dynamics identification frameworks can be coupled with compressive sampling. The techniques described in this work are demonstrated to be able to recover mode shapes from experimental video of vibrating structures when 70% to 90% of the frames from a video captured in the conventional manner are removed.

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Investigation of the effect of a bend on pipe inspection using microwave NDT

Cited by 19 publications

References 23 publications

Simplistic, Efficient, and Low-Cost Crack Detection of Dielectric Materials Based on Millimeter-Wave Interference

Simplistic, Efficient, and Low-Cost Crack Detection of Dielectric Materials Based on Millimeter-Wave Interference

Improving the Ability of a Laser Ultrasonic Wave-Based Detection of Damage on the Curved Surface of a Pipe Using a Deep Learning Technique

Sparse and Random Sampling Techniques for High-Resolution, Full-Field, BSS-Based Structural Dynamics Identification from Video

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