School of Civil Engineering, Tongji University, Shanghai 200092, China.
Zhejiang Zhoushan Sea Crossing Bridge Co., Ltd., Zhoushan 316031, China.
Sensors (Basel). 2022 Sep 27;22(19):7342. doi: 10.3390/s22197342.
Establishing an online perception mechanism for a driver's front blind area on a full bridge under vertical vortex-induced vibration (VVIV) is essential for ensuring road safety and traffic control on bridge decks under specific conditions. Based on accelerations of vibration monitoring of the main girders, this paper uses a real-time acceleration integration algorithm to obtain real-time displacements of measurement points; realizes the real-time estimation of the dynamic configurations of a main girder through parametric function fitting; and then can perceive the front blind area for vehicles driving on bridges experiencing VVIV in real time. On this basis, taking a long-span suspension bridge suffering from VVIV as an engineering example, the influence of different driving conditions on the front blind area is examined. Then, the applicability of the intelligent perception technology framework of the front blind area is verified. The results indicate that, during VVIV, the driver's front blind area changes periodically and the vehicle model has the most significant impact on the front blind area; in contrast, the vehicle's speed and the times of the vehicle entering the bridge have minimal impact on it. Meanwhile, it is shown that the framework can accurately perceive front blind areas of vehicles driving on the bridge, and identify different vehicle models, speeds and times of vehicle bridge entries in real time.
建立全桥在垂直涡激振动（VVIV）下驾驶员前方盲区的在线感知机制，对于确保特定条件下桥面的道路安全和交通控制至关重要。本文基于主梁振动监测的加速度，采用实时加速度积分算法获取测点的实时位移；通过参数函数拟合实现主梁动力形态的实时估计，从而可以实时感知经历 VVIV 的桥上行驶车辆的前方盲区。在此基础上，以一座遭受 VVIV 的大跨度悬索桥为例，考察了不同行驶条件对前方盲区的影响，进而验证了前方盲区智能感知技术框架的适用性。结果表明，在 VVIV 过程中，驾驶员的前方盲区呈周期性变化，车辆模型对前方盲区的影响最大；相比之下，车辆速度和车辆过桥次数对其影响最小。同时，该框架可以准确感知桥上行驶车辆的前方盲区，并实时识别不同的车辆模型、速度和车辆过桥时间。
