分数阶微分算子在煤矿监测数据融合处理中的应用  

Application of fractional differential operator in coal mine detection data fusion processing

作　　者：左延红[1] 程桦[2] 程堂春[3] ZUO Yanhong;CHENG Hua;CHENG Tangchun(School of Mechanical and Electrical Engineering,Anhui Jianzhu University,Hefei 230601,China;College of Civil Engineering and Architecture,Anhui University of Science and Technology,Huainan 232001,China;Coal Gas Projects Department,SDIC Xinji Energy Co.,Ltd.,Huainan 232001,China)

机构地区：[1]安徽建筑大学机电工程学院,安徽合肥230601 [2]安徽理工大学土木建筑学院,安徽淮南232001 [3]国投新集能源股份有限公司煤制气项目部,安徽淮南232001

出　　处：《煤炭学报》2020年第2期819-826,共8页Journal of China Coal Society

基　　金：国家自然科学基金资助项目(E0204);安徽省高校自然科学重点研究资助项目(KJ2017A523)

摘　　要：在煤矿生产信息的监测与采集中,传感器间的性能及其工作环境难免存在差异性,这些无法避免的差异性致使在同一地点工作的多个传感器对同一生产信息的测量数据间存在较大差异性,从而导致数据监测中心收集到的监测数据很难反映真实的生产信息,直接影响着煤矿生产管理的正常运行秩序和生产系统的生命财产安全。相较传统的消耗重资购置高性能信息监测设备以提高信息数据准确性的硬件性能提升法,提出了基于分数阶微分滤波算法的煤矿生产信息监测数据的多传感器监测数据软件融合处理法。探讨了分数阶微分算子在信号处理中的应用特性,建立了基于分数阶微分算子的煤矿监测数据融合处理模型,并通过0.5阶微分算子在淮南某煤矿井下瓦斯浓度监测数据融合处理实验中的应用验证了分数阶微分滤波算法的优越性。实验证明:分数阶微分算子具备较强的差异性监测数据融合性能,可有效提高煤矿监测数据的准确性和煤矿安全生产管理决策的科学性;与传统的购置高性能信息监测设备以提高信息数据准确性的方法相比,基于分数阶微分滤波算法的煤矿生产信息监测数据的数据融合处理方法具有成本低廉、融合效果显著的突出优点。In the detection and collection of coal mine production information,there are inevitably differences in the performance and working environment between sensors,these unavoidable differences lead to great differences in the measurement data of the same production information from multiple sensors in the same working place.Therefore,the detection data collected by the data detection center can hardly reflect the real production information,which directly affects the normal operation order of the coal mine production management and the safety of life and property of the production system.Comparing with the traditional hardware performance improvement method,which consumes a lot of money for purchasing high-performance information detection equipment to improve the accuracy of information data,this paper proposes a software fusion processing method of multi-sensor detection data based on fractional differential filtering algorithm for coal mine production information monitoring data.After discussed the application characteristics of fractional differential operator in signal processing,then the model of coal mine monitoring data fusion based on fractional differential operator is established,and using 0.5 order differential operator in the data fusion processing experiment of gas concentration detection in a coal mine in Huainan proves the superiority of the fractional differential filter algorithm.The experiment proves that the fractional differential operator has a high performance of differential detection data fusion,it can effectively improve the accuracy of coal mine detection data and scientific decision-making of coal mine safety production management.Compared with the traditional method of purchasing high-performance information detection equipment to improve the accuracy of information data,the data fusion method based on fractional differential filter algorithm has the outstanding advantages of low cost and remarkable fusion effect.

关 键 词：分数阶微分算子 瓦斯监测 煤矿安全生产管理 最小二乘法 数据融合 

分 类 号：TD76[矿业工程—矿井通风与安全] TP391[自动化与计算机技术—计算机应用技术]