基于ESN的高速公路黄河特大桥团雾预警系统设计
2022,30(10):181-187
摘要：为解决黄河特大桥团雾出现无法预测、团雾分布状态难以估测、团雾影响范围难以测量对影响黄河特大桥发布交通管控措施的问题，针对黄河特大桥气象条件，设计出一种基于回声状态网络（ESN）预测算法的高速公路黄河特大桥团雾预警系统；预警系统采用分布式结构，由主站和子站构成，利用主站和子站连接的气象传感器、雷视一体等设备，主站和子站都能获取实现团雾预测相关的测量信息；子站通过zigbee网络将获取的数据信息发送给主站，主站中的边缘计算终端利用主站获取的数据和子站传送的数据结合ESN预测算法对是否出现团雾进行预测，并利用雾端路测终端将预警信息发送到云端或指定服务器上；将团雾预警系统部署在黄河特大桥进行实验测试，结果表明：该系统能准确预警黄河特大桥是否出现团雾。
关键词：黄河特大桥；回声状态网络；zigbee网络；团雾预警；边缘计算；
Design of Fog Warning System for Highway Yellow River Special Bridge
Abstract：In order to solve the problem that the fog of the Yellow River Special Bridge cannot be predicted, the distribution state of the fog is difficult to estimate, and the impact range of the fog is difficult to measure the traffic control measures that affect the Yellow River Special Bridge, in view of the meteorological conditions of the Yellow River Special Bridge, a highway yellow river special bridge fog early warning system based on the echo state network (ESN) prediction algorithm is designed; the early warning system adopts a distributed structure, consisting of the main station and the sub-station, using the meteorological sensors, lightning and other equipment connected by the main station and the sub-station. The master station and the sub-station can obtain the measurement information related to the realization of fog prediction; the sub-station sends the obtained data information to the master station through the zigbee network, and the edge computing terminal in the master station uses the data obtained by the master station and the data transmitted by the sub-station to predict whether the fog will occur in combination with the ESN prediction algorithm, and uses the fog end road test terminal to send the early warning information to the cloud or the designated server; the fog early warning system is deployed in the Yellow River Special Bridge for experimental testing. The results show that the system can accurately warn whether there is fog on the Yellow River Special Bridge.
Key words：Yellow River Super Bridge；Echo State Network ; zigbee network；Fog early warning；Edge computers；
收稿日期：2022-03-09
基金项目：山东省交通运输厅科技计划项目(2020B46)
