基于BP神经网络的沥青洒布精度研究

Research on Accuracy of Asphalt Spraying Based on BP Neural Network

针对传统沥青洒布车洒布精度低的问题,利用多传感器冗余检测信号确保了采集信息的准确性;提出利用非定常效率法来控制沥青洒布精度,设计了基于BP神经网络PID控制法的沥青洒布车控制器,通过建立泵效率数学模型,计算出泵出口压力与喷洒壁压力的关系。利用MATLAB进行仿真,结果表明:采用BP神经网络PID控制法实现了沥青洒布车车速信号、泵速信号、压力信号的快速响应,可以有效地提高沥青洒布精度。

Aimed at the problem of low accuracy of asphalt distributors,multi-sensor redundancy detection signal was applied to ensure the correctness of the acquired information.PID control based on BP neural network was adopted to design the controller of asphalt distributor,and a mathematical model of pump efficiency was built to study the relationship between the pump outlet pressure and spraying wall pressure.Simulation in MATLAB suggests that with the introduction of PID control,signals from vehicle speed,pump speed and pressure receive rapid response,and the accuracy of asphalt spraying is effectively improved.