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Defect detection of FRP-bonded civil structures under vehicle-induced airborne noise

机译：车辆诱导空气噪声下FRP键合的民用结构的缺陷检测

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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.
机译：纤维增强聚合物（FRP） - 粘性的民用结构越来越多地用于各种建筑领域，如建筑，桥梁和隧道。为了保持其设计的机械性能，应定期检测界面键合的完整性。从最近的许多实验室研究中，声学激光技术有望应用于识别FRP键合的民间结构中分层或剥离的存在。然而，这种技术对真实基础设施的缺陷检测性能遇到与空中车辆噪声有关的具有挑战性的问题，因为在城市地区循环的汽车数量迅速增加时。在这项研究中，我们在施加FRP粘结结构的缺陷检测时处理车辆噪声对声学激光技术的影响。车辆声音不仅在测量的频谱中升高了噪声地板，还要诱导与噪声相关的峰（低于2000Hz）。来自单个通过车辆的噪声导致比车辆流的排噪声（SNR）比例更大。另外，检测大的缺陷更容易受到车辆噪声的声学干扰而不是小的缺陷。 SNR和噪声水平之间的定量功能设置为估计在交通流附近的施工区域中的缺陷检测性能。为了处理车辆噪声问题，提出了一种去噪并证明了该领域的实际缺陷检测。

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