Abstract Fiber-reinforced polymer (FRP)-bonded civil structures have been increasingly used in various construction fields, such as building, bridge, and tunnel. To maintain their designed mechanical performance, the integrity of interfacial bonding should be detected on a regular basis. From many recent laboratory studies, acoustic-laser technique is promising to be applied for identifying the presence of delamination or debonding in FRP-bonded civil structures. However, the defect detection performance of this technique towards real infrastructure encounters a challenging problem related to airborne vehicle noise as the number of cars circulating in urban area increases rapidly. In this study, we deal with the effect of vehicle noise on acoustic-laser technique when applying it in defect detection of FRP-bonded structures. Vehicle sound is found to not only raise the noise floor in measured frequency spectrum but also induce noise-related peaks (below 2000 Hz). Noise from a single passing vehicle causes greater reduction in signal-to-noise (SNR) ratio than that from a platoon of vehicle stream. Additionally, detecting large defect is more vulnerable to acoustic interference of vehicle noise than the small one. A quantitative function between the SNR and the noise level is set up to estimate the performance for defect detection in a construction area near the traffic flow. To handle the vehicle noise issue, a de-noising scheme is proposed and demonstrated for practical defect detection in the field.

中文翻译：

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车辆诱导空气噪声下玻璃钢土木结构的缺陷检测

摘要 纤维增强聚合物（FRP）粘结土木结构在建筑、桥梁、隧道等各种建筑领域得到越来越多的应用。为了保持其设计的机械性能，应定期检测界面结合的完整性。从最近的许多实验室研究来看，声学激光技术有望用于识别 FRP 粘合土木结构中是否存在分层或脱粘。然而，随着在市区流通的汽车数量迅速增加，该技术对实际基础设施的缺陷检测性能遇到了与空中车辆噪声相关的具有挑战性的问题。在这项研究中，我们在将声学激光技术应用于 FRP 粘合结构的缺陷检测时，处理了车辆噪声对声学激光技术的影响。发现车辆声音不仅会提高测量频谱中的本底噪声，还会引起与噪声相关的峰值（低于 2000 Hz）。与来自一排车流的噪声相比，来自单个经过车辆的噪声导致信噪比 (SNR) 比的降低更大。此外，检测大缺陷比小缺陷更容易受到车辆噪声的声学干扰。建立了 SNR 和噪声水平之间的定量函数，以估计交通流附近建筑区域中缺陷检测的性能。为了处理车辆噪声问题，提出并演示了一种去噪方案，用于现场实际缺陷检测。与来自一排车流的噪声相比，来自单个经过车辆的噪声导致信噪比 (SNR) 比的降低更大。此外，检测大缺陷比小缺陷更容易受到车辆噪声的声学干扰。建立了 SNR 和噪声水平之间的定量函数，以估计交通流附近建筑区域中缺陷检测的性能。为了处理车辆噪声问题，提出并演示了一种去噪方案，用于现场实际缺陷检测。与来自一排车流的噪声相比，来自单个经过车辆的噪声导致信噪比 (SNR) 比的降低更大。此外，检测大缺陷比小缺陷更容易受到车辆噪声的声学干扰。建立了 SNR 和噪声水平之间的定量函数，以估计交通流附近建筑区域中缺陷检测的性能。为了处理车辆噪声问题，提出并演示了一种去噪方案，用于现场实际缺陷检测。建立了 SNR 和噪声水平之间的定量函数，以估计交通流附近建筑区域中缺陷检测的性能。为了处理车辆噪声问题，提出并演示了一种去噪方案，用于现场实际缺陷检测。建立了 SNR 和噪声水平之间的定量函数，以估计交通流附近建筑区域中缺陷检测的性能。为了处理车辆噪声问题，提出并演示了一种去噪方案，用于现场实际缺陷检测。