Compressive sampling–based ultrasonic computerized tomography technique for damage detection in concrete-filled steel tube in a bridge

Binbin Li, Bo Liu, Fan Xu, Yang Liu, Wentao Wang and Tao Yang

International Journal of Distributed Sensor Networks, 2021, vol. 17, issue 2, 1550147720986113

Abstract: Ultrasonic computerized tomography is a promising technique for damage detection by enabling ultrasonic waves via multiple measurement paths leading to accurate localization of structural damage. Unlike traditional ultrasonic computerized tomography that requires numerous measurements and costly computation, a compressive sampling advancing both the measuring phase and the imaging phase is proposed in this study to achieve accurate identification with no low-speed traditional ultrasonic computerized tomography technique measurements or costly computation in real-world applications. The proposed rapid ultrasonic computerized tomography approach advances both the measuring phase and the imaging phase. In the measuring phase, far few ultrasonic measurement paths are randomly selected to capture the characteristics of the ultrasonic waves carrying the underlying damaged information. And in the imaging phase, â„“ 1 -norm minimization optimization algorithm is used to reconstruct the internal damage, rendering the sparest solution related to the physical damages. The functionality of the proposed approach is validated by both numerical simulation and experimental testing. The results indicate that the improved ultrasonic computerized tomography technique in compressive sampling framework has a great potential for rapid damage detection, which is a game-changing technique for accurate and cost-efficient damage detection in real-world applications.

Keywords: Compressive sampling; structural health monitoring; nondestructive testing/evaluation; ultrasonic computerized tomography (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:17:y:2021:i:2:p:1550147720986113

DOI: 10.1177/1550147720986113

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