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Abstract
This paper explores a new method for rapid structural damage inspection of steel tube slab (STS) structures along randomly measured paths based on a combination of compressive sampling (CS) and ultrasonic computerized tomography (UCT). In the measurement stage, using fewer randomly selected paths rather than the whole measurement net is proposed to detect the underlying damage of a concrete-filled steel tube. In the imaging stage, the ℓ1-minimization algorithm is employed to recover the information of the microstructures based on the measurement data related to the internal situation of the STS structure. A numerical concrete tube model, with the various level of damage, was studied to demonstrate the performance of the rapid UCT technique. Real-world concrete-filled steel tubes in the Shenyang Metro stations were detected using the proposed UCT technique in a CS framework. Both the numerical and experimental results show the rapid UCT technique has the capability of damage detection in an STS structure with a high level of accuracy and with fewer required measurements, which is more convenient and efficient than the traditional UCT technique.
Highlights
Transit infrastructure condition assessment has become an important subject attracting researchers’ attention
This paper focuses on the rapid ultrasonic computerized tomography (UCT) method based on an algorithm of compressive sampling for the damage detection of steel tube slab (STS) structures in the Shenyang Metro station
This study proposes a novel UCT reconstruction technique in the compressive sampling (CS) platform based on random low-rate measurement paths and the l1-minimization algorithm
Summary
Transit infrastructure condition assessment has become an important subject attracting researchers’ attention. The proposed UCT damage detection method based on CS improves the traditional UCT technique with a high level of accuracy of reconstruction and with fewer required measurements
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