针对该工作面回采期间采煤机自动截割煤体、液压支架自动拉移架过程中,协同能力较差、人工干预次数较多的现象,以华宁焦煤公司22104智能化综采工作面为研究对象,构建了一种基于液压系统的采煤机与支架协同控制系统,将采煤机各参量引入到GA-BP的联合建模中,并采用遗传算法(GA)和BP神经网络相结合的方法对采煤机与支架协同控制进行优化,以实现改善移架间距及延伸式护帮作用的效果。实践表明,该技术改进能够有效地提高对支架的控制作用,减少移架间距的偏差,其预测准确度可增加10%左右,大大地提升了综采工作面生产工作效率,为矿井综采工作面智能化、自动化建设奠定良好的基础。

In response to the phenomenon of poor collaborative ability and frequent manual intervention during the automatic cutting of coal body by the shearer and the automatic pulling and moving brackets of the hydraulic support during the stoping period of the working face, taking the 22104 intelligent fully mechanized mining face of Huaning Coking Coal Company as the research object, a hydraulic system based shearer and bracket collaborative control system is constructed. The various parameters of the shearer are introduced into the joint modeling of GA-BP, and the method of combining genetic algorithm (GA) with BP neural network are adopted to optimize the collaborative control of the shearer and bracket, in order to achieve the effect of improving the spacing of the moving brackets and the extended type side protective role. The practice shows that this technological improvement can effectively enhance the control action on the bracket, reduce the deviation of the moving brackets spacing, increase the prediction accuracy by about 10%, greatly improve the production work efficiency of the fully mechanized mining face, and lay a good foundation for the intelligent and automated construction of the mine fully mechanized mining face.