Study On Highway Tunnel Ventilation Supervision And Control System Based On Intelligent Cybernetics And OPC

Ventilation supervision and control system is an important part of highway tunnel supervision and control system. And the study on the long highway tunnel ventilation supervision and control system is a significant task. This dissertation was dedicated to the improvement of the real-time and openness peculiarity of the ventilation supervision and control system.There was a lack of prediction function in the finished tunnel ventilation fuzzy control system, which resulted in the delay of control. In present dissertation, the input real-time traffic flow was substituted by the predicted traffic flow, which made the system control to be much more real-time. Traffic flow is of 'black box' and non-linearity peculiarity. For this reason, artificial neural network theory was used and a neural network model was created to predict the highway tunnel traffic volume in the dissertation, which was achieved by MATLAB. And this model was of great prediction precision.An OPC DA server and an OPC DA client with friendly human machine interface and excellent management function were developed using WinCC in present dissertation, namely the sever of the tunnel supervision and control system and the ventilation control computer. And it was carried out that the client communicated with the server through standard OPC interface. In this way, the openness and expansibility peculiarity of the system was improved greatly.