针对煤矿生产过程中的采煤机截煤系统故障问题,设计了基于神经网络的专家评价系统,采用神经网络的自主学习和记忆功能解决了传统专家的瓶颈问题,结果表明,此套评价系统具有更高的效率和准确性,能够快速准确地对采煤机截煤系统运行过程进行模拟并生成新的运行参数。 Aiming at the problem of the coal machine cut-off system in the process of coal mine production, an expert evaluation system based on neural network was designed. The bottleneck problem of traditional experts was solved by the self-learning and memory function of neural network. The results show that this system has Higher efficiency and accuracy enable fast and accurate simulation of the operation of a coal winning machine and the generation of new operating parameters.