摘要
煤矿瓦斯监测中,利用D-S证据合成方法实现多传感器信息融合可以提高系统整体决策和预警能力.根据煤矿安全规范设定区域危险等级,使用云模型建立危险等级属性隶属度曲线簇,输入传感器检测量提取各属性隶属度作为D-S融合的基本概率赋值.为了实现高度冲突证据合成,提出D-S与加权平均法混合的分步证据合成算法.仿真结果表明文中提出的算法合成高度冲突证据时,具有令人满意的收敛效果.
D-S evidence combination can improve overall decision and early warning capability in coal mine gas monitoring system. In this study, the danger levels of local region in coal mine are defined according to coal mine safety specification. Cloud model is used for generating the curve clusters of the membership degrees corresponding to the danger levels. The membership degrees extracted from the curve clusters are regarded as basic probability assignment for D-S evidence combination. The study puts forward a step-by-step combination algorithm mixing D-S method and the weighted average method for severe conflicting evidence combination. The simulation results show that the proposed algorithm has satisfactory convergence effect on severe conflicting evidence combination.
出处
《江西理工大学学报》
CAS
2014年第5期62-68,共7页
Journal of Jiangxi University of Science and Technology
基金
江西省教育厅科技资助研究项目(GJJ13398)
江西省研究生创新专项资金资助项目(YC2013-S195)
关键词
瓦斯监测
信息融合
云模型
D-S证据合成
gas monitoring
information fusion
cloud model
D-S evidence combination
作者简介
陈强（1964-），男，教授，主要从事矿井、矿山安全监测、人工免疫理论及应用等方面的研究，E-mail：ls06400@126．com．
