The invention discloses a road network level vehicle overload identification and emergency early warning method, and the method comprises the specific implementation steps: installing a corner sensor, a camera and a tachymeter near a bridge support, and measuring the main beam corner and vehicle information in structural deformation at the same time; establishing a typical vehicle database with known vehicle weight by using an RBF (Radial Basis Function) artificial neuron network, and establishing a vehicle weight prediction model; when a vehicle passes through a bridge, transmitting the vehicle information to an input layer of the artificial neuron network, and outputting the vehicle weight data through conversion of a hidden layer; enabling the vehicle weight prediction models of other bridges in the road network to receive the vehicle weight data and input the vehicle weight data into the vehicle weight prediction models of other bridges, and calculating and transmitting the turning angle and the deflection to the grading early warning system. According to the method, the vehicle prediction model is established by adopting the artificial neural network, and before the vehicle gets on the bridge, damage of the vehicle to the bridge is predicted, so that bridge accidents are prevented.
本发明公开了一种路网层次的车辆超载识别及应急预警方法,具体实施方式为:在桥梁支座附近安装转角传感器、摄像头和测速仪,同时测量结构变形中的主梁转角和车辆信息,利用RBF(径向基)人工神经元网络建立已知车辆重量的典型车辆数据库,建立车重预测模型,当车辆经过桥梁时,车辆信息传输到人工神经元网络的输入层,经过隐含层的转换,输出车重数据,同时该路网内其他桥梁的车重预测模型也会接收到该车重数据,输入到其他桥梁自身的车重预测模型中,计算出转角和挠度,传输到分级预警系统。本发明采用人工神经网络进行车辆预测模型的建立,在车辆上桥前,对车辆对桥梁的损坏有所预知,预防桥梁事故的发生。
Road network level vehicle overload identification and emergency early warning method
一种路网层次的车辆超载识别及应急预警方法
2021-12-10
Patent
Electronic Resource
Chinese
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