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Presentation + Paper
27 March 2018 Finite element simulation of photoacoustic fiber optic sensors for surface corrosion detection on a steel rod
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Abstract
Structural steel members have become integral components in the construction of civil engineering infrastructures such as bridges, stadiums, and shopping centers due to versatility of steel. Owing to the uniqueness in the design and construction of steel structures, rigorous non-destructive evaluation techniques are needed during construction and operation processes to prevent the loss of human lives and properties. This research aims at investigating the application of photoacoustic fiber optic transducers (FOT) for detecting surface rust of a steel rod. Surface ultrasonic waves propagation in intact and corroded steel rods was simulated using finite element method (FEM). Radial displacements were collected and short-time Fourier transform (STFT) was applied to obtain the spectrogram. It was found that the presence of surface rust between the FOT and the receiver can be detected in both time and frequency domain. In addition, spectrogram can be used to locate and quantify surface rust. Furthermore, a surface rust detection algorithm utilizing the FOT has been proposed for detection, location and quantification of the surface rust.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Qixiang Tang, Jones Owusu Twumasi, Jie Hu, Xingwei Wang, and Tzuyang Yu "Finite element simulation of photoacoustic fiber optic sensors for surface corrosion detection on a steel rod", Proc. SPIE 10599, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XII, 105991N (27 March 2018); https://doi.org/10.1117/12.2295032
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Ultrasonics

Wave propagation

Algorithm development

Detection and tracking algorithms

Finite element methods

Error analysis

Receivers

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