基于支架推移油缸行程的综采面推进距离算法研究

Research on algorithm of advancing distance of fully mechanized mining face based on the support pushing cylinder stroke

随着智能矿山建设加速推进,各大型煤矿开始采集存储生产数据,建立企业级生产数据仓库,分析挖掘数据价值,实现数据要素驱动企业发展。神东煤炭集团早在2018年就建立了生产数据仓库,首先对所属13矿14井的所有支架电液控数据进行了采集和存储,其中就包括支架推移油缸行程传感器数据,亟需通过业务分析和算法研究,利用已采集的生产数据实现推进进尺数据的自动记录和管理。本文利用综采工作面所有支架的推移油缸行程数据,通过业务深度分析,进行了系列数据处理,结合统计学原理,计算出某综采面整体推进距离,算法精度高、适用性广。该技术研究最终形成了一套计算支架推进距离的完整算法体系。

With the accelerated construction of intelligent mines,large coal mines began to collect and store production data,establish enterprise level production data warehouse,analyze and mine data value,and realize the development of enterprises driven by data elements.Shendong Coal Group established a production data warehouse as early as 2018.Firstly,it collected and stored all the support electro-hydraulic control data of 13 mines and 14 wells,including the support pushing cylinder travel sensor data.It is urgent to use the collected production data to realize the automatic recording and management of advance footage data through business analysis and algorithm research.In this paper,using the pushing cylinder stroke data of all supports of fully mechanized mining face,through business depth analysis,a series of data processing is carried out.Combined with the principle of statistics,the overall advancing distance of a fully mechanized mining face is calculated,this algorithm has high precision and wide applicability.This technical research finally formed a complete algorithm system for calculating the propelling distance of the support.