改进BP网络在煤矿通风系统故障检测中的应用

Application of improved BP neural network in fault detection of mine ventilation system

针对BP神经网络传统学习算法步长难以确定的问题,提出了采用基于RLS算法的BP神经网络检测煤矿通风系统故障的方法;简要介绍了BP神经网络的结构,详细介绍了RLS学习算法和仿真过程。仿真结果表明,采用RLS算法的BP神经网络能够满足煤矿通风系统故障检测的要求。

For problem that step of traditional learning algorithm of BP neural network is difficult to determine, the paper proposed a method of using BP neural network based on RLS algorithm to detect fault of mine ventilation system. It introduced structure of the BP neural network briefly, and introduced RLS learning algorithm and simulation process in details. The simulation results show that the BP neural network with RLS algorithm can meet the requirements of fault detection of mine ventilation system.