Highway tunnel ventilation feedforward control method based on environmental forecasting

Abstract

The invention provides a highway tunnel ventilation feedforward control method based on environmental forecasting. The method comprises steps as follows: sensors in a tunnel collect CO / VI concentration and instant information of traffic flow in the tunnel and transmit the CO / VI concentration and the instant information to a monitoring center computer; the traffic flow of the n time period is substituted into a tunnel traffic flow data predication model, and the traffic flow of the (n+1) time period is predicated; theoretical values of the CO / VI concentration in the n time period and the (n+1) time period are obtained through calculation; a predicated increment of the CO / VI concentration is calculated according to an actually measured CO / VI concentration value as well as the theoretical values of the CO / VI concentration in the n time period and the (n+1) time period; the predicated increment of the CO / VI concentration is input into a fuzzy controller, and the number of changed fans is obtained through processing and calculation of the fuzzy controller and is taken as a controlled variable to be output to a site area controller; the site area controller controls the fans to be started or stopped according to the controlled variable. With the adoption of the method, optimal operation of the tunnel ventilation control system is realized, and traffic safety is guaranteed.

Description

technical field [0001] The invention belongs to the technical field of road tunnels, in particular to a tunnel ventilation feedforward control method based on environment prediction. Background technique [0002] At present, the main methods used in tunnel ventilation automatic control at home and abroad are program control method, direct control method and indirect control method. [0003] The program control method does not consider the change of smoke (VI), CO concentration and traffic flow, but pre-programs the operation of the fan according to the time interval (such as day and night, holidays and normal times). Its essence is timing control, which controls the number of fans to start by counting historical experience data. This method can save the cost of the detection unit to a certain extent, but because it does not consider the changes in CO concentration, VI value and traffic flow, it only pre-programs the operation of the fan according to the time interval, and l...

AI Technical Summary

Problems solved by technology

The limitation of this control method is that it does not consider the instability in the tunnel ventilation process caused by traffic flow and pollutant diffusion in the tunnel ventilation process.

At the same time, the fan runs without tracking, and its running time is longer

The direct control method has no predictive function, and there is often a delay with the real state. For urban highway tunnels, because the tunnel ventilation requirements change rapidly with time, the real-time requirements for urban tunnel ventilation are higher, and the direct control method alone cannot fully meet the needs.

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