基于GA-BP神经网络的带式输送机故障监测系统研究

Research on Fault Monitoring System of Belt Conveyor Based on GABP Neural Network

带式输送机设备复杂,故障类型多,采用BP神经网络进行故障诊断时收敛速度慢,因此采用GA-BP神经网络建立带式输送机故障监测系统。对带式输送机故障监测系统整体结构进行设计,并对主控制器以及编码器电路进行详细设计。系统软件在主程序中调用子程序,并详细分析故障诊断子程序的工作原理。为验证GA-BP神经网络的有效性,采用MATLAB仿真,仿真结果显示GA-BP神经网络故障诊断准确率高,收敛速度快。

The belt conveyor device is complex and the type of fault is diverse.The convergence speed is slow when the BP neural network is used to do fault diagnosis,so the GA-BP neural network is used to establish a belt conveyor fault monitoring system.The overall structure of the belt conveyor fault monitoring system is designed,and the main controller and the encoder circuit are detailed.System software calls subroutines in the main program,the working principle of fault diagnostic subroutines is analyzed.In order to verify the effectiveness of the GA-BP neural network,MATLAB simulation is done.The simulation results show that the accuracy of the GA-BP neural network fault diagnosis is high,and the convergence speed is fast.