摘要
随着科技的发展与进步,煤矿智能化已经成为目前矿业生产中的重点研究方向。但是在薄煤层工作面中由于顶板条件的复杂性以及作业环境的多变性,导致目前的井下自动化控制技术中存在液压支架自动跟机不能完美适应井下顶底板环境且采煤机难以精准定位的问题。以薄煤层工作面自动化控制系统为基础,结合图像识别以及多传感器融合的方法研究采煤机的定位技术,并对液压支架定姿的关键技术进行了分析,期望提高薄煤层自动化系统在煤矿井下的适应性,减少工作面的操作人员,提高煤矿生产的效率。
With the development and progress of science and technology,coal mine intelligence has become the key research direction in mining production.However,due to the complexity of the roof conditions and the variability of the working environment in the thin coal seam working face,the current underground automatic control technology has the problem that the hydraulic support can not adapt to the underground roof and floor environment perfectly,and the shearer is difficult to accurately locate.Based on the automatic control system of thin coal seam working face,studied the positioning technology of shearer combined with image recognition and multi-sensor fusion,and analyzed the key technology of hydraulic support attitude determination.It is expected to improve the adaptability of thin coal seam automation system in coal mine,reduce the operators of working face and improve the efficiency of coal mine production.
作者
刘超
Liu Chao(Equipment Branch,China Coal Research Institute,Beijing 102606,China)
出处
《煤矿机械》
2024年第4期34-37,共4页
Coal Mine Machinery
基金
煤炭科学技术研究院有限公司科技发展基金项目(基础基金)(2022CX-II-07)。
关键词
煤矿生产
自动控制
液压支架定姿
采煤机定位
coal mine production
automatic control
hydraulic support attitude determination
shearer positioning
