基于分布式长标距FBG光纤传感的混凝土梁桥荷载识别技术

Load Identification Technology of Concrete Beam Bridge based on Distributed Long Gauge FBG Optical Fiber Sensor

以G2京沪高速公路新沂河大桥运营期出现大量梁体裂缝为工程背景,建立分布式长标距FBG健康监测系统,提出广义动态应变时程积分反演车重和车速的方法,并通过有限元理论验证了该方法的可靠性。对系统采集大量样本进行分析,发现新沂河大桥2号梁跨中传感器反演车速数据与WIM值吻合良好,大多数的相对误差在±10%内。2号梁跨中传感器应变数据反演车重数据最为理想,车重识别数据误差集中在±20%内。通过工程应用验证证明,基于FBG应变影响线积分反演车重方法可以有效降低单点取值时信噪比低而引起的误差,获得稳定结果,是WIM直接识别方法的一种有效验证技术手段。

In this paper, a distributed long gauge FBG health monitoring system is established for the Xinyi River Bridge on the Beijing to Shanghai Expressway(G2) that a large number of cracks occur in the beams during its operation period. The methods are proposed for the identification and inversion of vehicle weight and vehicle speed based on generalized dynamic strain signal integral, which are verified by finite element theory as well. Through the analysis of a large number of samples collected by the system, it is found that the vehicle speed data retrieved with the sensor in the middle span of No. 2 beam of Xinyi River Bridge are in good agreement with WIM values, and most of the relative errors are within ± 10%. The results show that the strain data obtained with the sensor in the middle span of No.2 beam is the most ideal to retrieve the vehicle weight, and the error of vehicle weight identification data is within ± 20%. The project application case shows that the vehicle weight inversion method based on FBG strain influence line integral can effectively reduce the error caused by low signal-to-noise ratio and obtain stable results, which is an effective verification technology for WIM direct identification method.