摘要
提出一种通过Apriori挖掘矿坝失稳特征技术来提高矿井塌方、渗水等危险状况报警的准确性,设计了由超声波回波模块和压力传感器模块组成的矿井信息采集子系统;由DSP中央处理模块组成的矿井风险检测子系统,在此基础上,采用Apriori尾矿坝失稳特征挖掘算法分别对多传感器检测的回波特征和压力信息进行失稳特征挖掘,以提高干扰状态下对风险目标判断的准确度;实验结果表明,以此为基础设计的智能矿井风险决策系统测量相对误差小,能很好地反映矿井下的现场信息,完成对井下回波特征和压力信息进行失稳特征挖掘,挖掘的精度达到了75%以上,高于国际上的70%的要求,满足险情探测和报警需要,具有很强的使用价值。
Proposed by Apriori mining ore dam instability characteristic is a kind of technology to improve the accuracy of the dangerous situation, such as mines, ooze water alarm, designed by ultrasonic echo and pressure sensor module is composed of the mine information ae quisition subsystem; Central processing by the DSP module of mine risk detection subsystem, on this basis, USES the Apriori algorithm for mining tailings dam instability characteristics of multi--sensor detecting echo characteristics and instability characteristics mining pressure in- formation, in order to improve the interference condition of risk target judgment accuracy; Based on the experimental results show that the design of the intelligent mine risk decision system measuring relative error is small, can well reflect the underground scene information, com- plete information of the subsurface echo characteristics and pressure instability characteristics of mining, the mining accuracy reached 75%, higher than 70% in the international requirements, meet the needs of the danger detection and alarm, have very strong use value.
出处
《计算机测量与控制》
北大核心
2013年第6期1682-1684,共3页
Computer Measurement &Control
基金
河南省教育厅科学技术研究重点项目(13A520016)
