Jiang Baofeng, Jia Pengjiao, Zhao Wen, Wang Wentao
College of Resource and Civil Engineering, Northeastern University, Shenyang, Liaoning Province, China.
Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI, 48109-2125, United States of America.
PLoS One. 2018 Jan 2;13(1):e0190281. doi: 10.1371/journal.pone.0190281. eCollection 2018.
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.
本文探索了一种基于压缩采样（CS）和超声计算机断层扫描（UCT）相结合的沿随机测量路径对钢管混凝土板（STS）结构进行快速结构损伤检测的新方法。在测量阶段，建议使用较少的随机选择路径而非整个测量网络来检测钢管混凝土的潜在损伤。在成像阶段，采用ℓ1最小化算法，根据与STS结构内部情况相关的测量数据来恢复微观结构信息。研究了具有不同损伤程度的数值混凝土管模型，以证明快速UCT技术的性能。在CS框架下，使用所提出的UCT技术对沈阳地铁站的实际钢管混凝土进行了检测。数值和实验结果均表明，快速UCT技术能够在STS结构中以高精度进行损伤检测，且所需测量次数较少，比传统UCT技术更方便、高效。
