Dr. Renyuan Qin Profile

Dr. Renyuan Qin

at City Univ of Hong Kong

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Publications (2)

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Proceedings Article | 22 March 2021 Presentation + Paper

Effect of sampling rates on the accuracy of acoustic-laser technique in defect detection and upsampling using machine learning

Renyuan Qin, Denvid Lau

Proceedings Volume 11592, 115920G (2021) https://doi.org/10.1117/12.2582919

KEYWORDS: Defect detection, Machine learning, Nondestructive evaluation, Fiber reinforced polymers, Data acquisition, Target detection, Signal detection, Composites, Acoustics

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As a non-destructive testing (NDT) method, the acoustic-laser technique has demonstrated its effectiveness in defect detection of composite systems. The technique is particularly useful for the detection of near-surface defects in fiber reinforced polymer bonded concrete by vibrating the material with an acoustic excitation and measuring the vibration signals with a laser beam. However, same as the other vibration-based measurement methods, the accuracy of acoustic-laser technique is sensitive towards sampling rate during the measurements. The sampling rate of acoustic-laser measurement adopted in previous studies is as high as 50000 Hz to assure the accuracy of measurement. However, such high sampling rate cannot always be guaranteed due to the limitation of data acquisition system, or any missing data generated during the measurement. In this study, the effect of sampling rates on the accuracy of acoustic-laser technique is investigated through the experimental study. Six sampling rates, i.e. 10 Hz, 100 Hz, 1000 Hz, 10000 Hz, 25000 Hz, and 50000 Hz, are adopted to measure the FRP bonded system with an interfacial defect, in order to study the relationship between the sampling rate and measurement accuracy. Moreover, an upsampling method using machine learning is proposed in this study, in order to reconstruct the missing data to the target sampling rate, so that the accuracy of the detection can be improved from low sampling rate measurement with missing data.

Proceedings Article | 22 April 2020 Presentation + Paper

Use of high-speed camera for defect detection in FRP bonded system under different excitation methods

Renyuan Qin, Qiwen Qiu, Denvid Lau

Proceedings Volume 11380, 1138017 (2020) https://doi.org/10.1117/12.2558066

KEYWORDS: Fiber reinforced polymers, High speed cameras, Imaging systems, Defect detection

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Fiber reinforced polymers (FRP) strengthening has been demonstrated as an effective method to reinforce or repair the structural elements in the application of civil engineering. One issue that affects the effectiveness of FRP bonded system is the interfacial integrity between FRP and bonded substrate. The interfacial defect can cause the deterioration of the performance of strengthened/repaired structures, which should be identified as early as possible. Compared with conventional non-destructive techniques (NDTs), image acquisition method, such as high-speed camera, has received increasing attention due to the advantages of its non-sensor/wiring requirements. Coupled with proper video processing techniques, the high-speed camera has been reported as an effective tool in the interfacial defect detection for FRP bonded system. Moreover, the accuracy of results from high-speed camera is sensitive to the excitation resources applied on the FRP bonded system, since the vibration response of FRP varies under different excitation methods. In this research, three typical excitation methods for FRP bonded system, i.e. mechanical impact excitation, air pressure excitation and acoustic excitation, were tested to evaluate their effects on the detection accuracy using high-speed camera in FRP bonded system. The findings provide practical recommendations on the selection of proper excitation methods for the applications of high-speed cameras in the defect detection of FRP bonded system.

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