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This paper developed a new ultrasonic computerized tomography (CT) method for damage inspections of a steel tube slab (STS) structure based on compressive sampling (CS). CS is a mathematic theory providing an approximate recovery for a sparse signal with minimal reconstruction error from under-sampled measurements. Considering the natural sparsity of the damage, CS algorithm is employed to image the defect in the concrete-filled steel tube of Shenyang Metro line 9 for reducing the work time. Thus, in the measurement stage, far fewer ultrasonic measurement paths were selected from the dense net of conventional ultrasonic CT techniques to capture the underlying damage information. Then, in the imaging stage, l1-norm minimization algorithm of CS theory is selected to recover the internal damage via fusing measurement data and solving optimization problem. The functionality of the proposed method is validated by three numerical concrete tube models with various conditions. Additionally, both the conventional ultrasonic CT technique and the proposed one are employed for ultrasonic inspection of the STS structure in Shenyang Metro line 9. Both the numerical and experimental results indicate that the proposed ultrasonic CT improved by CS has a great potential for damage detection, which provides an alternative accurate and effective way for non-destructive testing/evaluation (NDT/E).

Improved Ultrasonic Computerized Tomography Method for STS (Steel Tube Slab) Structure Based on Compressive Sampling Algorithm