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我国大部分煤矿都装有监控系统用来检测矿井内部环境参数的变化,但由于检测技术的突破范围较小,因此能检测到环境变化的系统大概只占总数的60%,有将近一半的系统仍处于等待维修当中,在这将近一半的监测系统中还有一部分是达不到设计要求的,像这部分的系统不仅发挥不到应有的作用,还造成了资金浪费,急待维修的系统一直处于闲置当中,面对占据数量如此之大的系统闲置,可用系统的情况不容乐观。基于这种情况的发生,经研究在煤矿瓦斯挖掘中嵌入DBSCAN聚类算法,以提高煤矿的安全性能。
Most of China’s coal mines are equipped with monitoring systems to detect changes in the internal environmental parameters of the mine. However, due to the small breakthrough range of detection technologies, systems that can detect environmental changes account for only about 60% of the total. Nearly half of the systems Are still waiting for maintenance. In this half of the monitoring systems, some of them fail to meet the design requirements. Systems like this one not only failed to play their due role, but also resulted in the system of wasted funds and urgent maintenance Has been in the midst of idle, in the face of the system occupy a large number of idle, the available system is not optimistic. Based on this situation, DBSCAN clustering algorithm is embedded in coal mine gas excavation to improve the safety performance of coal mines.