基于Bp神经网络的矿井热环境评价体系研究

为了科学评价矿井热环境,系统地考虑了内部热源、环境、矿井结构三个方面因素,构建了评价指标,以人对矿井热环境的适应性确立分级指标,建立一个新的矿井热害评价指标体系。运用MATLAB软件对评价指标体系进行神经网络建模,对矿井热环境问题定量化评价、分析。通过对张双楼煤矿热害改造前后的实际生产情况进行评价该矿井热环境体系能准确地反映矿井实际生产情况。该系统简单、可操作性强,可以用来进行矿井热环境的评价工作,也可以预测矿井热害改造后的情况。

Research on mine thermal environment evaluation system based on Bp neural network

In order to evaluate the mine thermal environment scientifically, evaluation indexes were established by systematically considering the internal heat source, the surrounding environment and the structural factors of the mine, a new evaluation index system of mine thermal damage was established.Matlab was used to model the evaluation index system.After the evaluation of the actual production situation before and after the transformation of thermal damage in zhangshuanglou coal mine, it is verified that the thermal environment system can reflect the actual production situation in the mine accurately.It can be used to evaluate the mine thermal environment and predict the situation after the mine thermal damage reconstruction. The system is simple, operable and can be used.