基于BP神经网络的煤矿水泵系统控制方法研究

Research of Control Method of Coal Mine Pump System Based on BP Neural Network

在煤矿井下排水系统中,目前常用的方法是根据几项关键因素或凭经验直接决定水泵的启停。该方法缺乏理论依据,经常要根据现场情况修改水泵的启停安排。针对该问题,提出一种基于BP神经网络的煤矿水泵系统控制方法。该方法选取水位、涌水量、时段、累计运行时间这4个关键参数来建立BP神经网络,通过对网络不断调整和优化,得到一个稳定的网络模型;用该模型对水泵的启停时间进行判断,实现对多台水泵的合理安排。Matlab仿真结果表明,使用BP神经网络对水泵系统进行控制是合理、有效的,对实现煤矿安全生产和节能减排有积极的意义。

In coal mine drainage system,the most common method to determine pump start or stop is according to several key factors or experience to directly determine.The method lacks theoretical basis and often needs to modify the arrangement according to site conditions.For the problem,the paper presented a pump control method based on BP neural network,which selects four key parameters including water level,water inflow,time period and cumulative running time to establish a network,and gets a stable network model through continuously adjusting and optimizing the network.The model is then used to determine start and stop time of pump,so as to achieve reasonable arrangement of multiple pumps.Matlab simulation results showed that it is reasonable and effective to control pump system by BP neural network,and the method has a positive significance to achieve safe production and energy saving of coal mine.