基于ZigBee技术与信息融合的煤矿安全监测系统设计
发布时间：2019-01-05 02:50
【摘要】：针对煤矿生产作业环境和开采过程中的灾害危险因素,设计了基于Zig Bee技术与信息融合的煤矿安全监测系统。通过构建基于Zig Bee协议的无线传感器网络,实现对井下环境数据的采集、传输。论文根据系统的数据分析的具体需求,提出基于模糊贴近度和灰色关联度的两级数据融合模型,其中采用模糊贴近度算法作为一级数据融合,提取环境参数特征向量。二级数据融合利用灰色关联度算法对特征向量再次进行融合,通过对现场数据分析,结果表明该算法可以准确地判定矿井的安全状况,给出煤矿安全等级决策。
[Abstract]:A coal mine safety monitoring system based on Zig Bee technology and information fusion is designed in view of the disaster risk factors in coal mine production environment and mining process. By constructing the wireless sensor network based on Zig Bee protocol, the acquisition and transmission of underground environmental data are realized. According to the demand of data analysis of the system, a two-level data fusion model based on fuzzy closeness degree and grey correlation degree is proposed, in which the fuzzy closeness algorithm is used as the first level data fusion, and the feature vectors of environmental parameters are extracted. The second level data fusion uses grey correlation degree algorithm to fuse the feature vector again. By analyzing the field data, the result shows that the algorithm can accurately judge the mine safety condition and give the coal mine safety grade decision.
【作者单位】： 神东煤炭集团布尔台煤矿;西安华光信息技术有限责任公司;
【分类号】：TD76
本文编号：2401162
[Abstract]:A coal mine safety monitoring system based on Zig Bee technology and information fusion is designed in view of the disaster risk factors in coal mine production environment and mining process. By constructing the wireless sensor network based on Zig Bee protocol, the acquisition and transmission of underground environmental data are realized. According to the demand of data analysis of the system, a two-level data fusion model based on fuzzy closeness degree and grey correlation degree is proposed, in which the fuzzy closeness algorithm is used as the first level data fusion, and the feature vectors of environmental parameters are extracted. The second level data fusion uses grey correlation degree algorithm to fuse the feature vector again. By analyzing the field data, the result shows that the algorithm can accurately judge the mine safety condition and give the coal mine safety grade decision.
【作者单位】： 神东煤炭集团布尔台煤矿;西安华光信息技术有限责任公司;
【分类号】：TD76
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