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  • 标题:Research on Safety Monitoring and Warning System Based on Information Fusion for Coking Production
  • 本地全文:下载
  • 作者:Nailu Zhang ; Libo Li ; Xin Liu
  • 期刊名称:International Journal of Hybrid Information Technology
  • 印刷版ISSN:1738-9968
  • 出版年度:2016
  • 卷号:9
  • 期号:8
  • 页码:303-314
  • 出版社:SERSC
  • 摘要:Coking production process is very complex, and full of risk factors, toxic and harmful substance, it’s a typical high risk industry. In view of the prominent safety hazards and strong interference to safety monitoring in coking production, put forward a kind of safety monitoring and warning system based on information fusion for coking production. To achieve the target that safety condition was monitored accurately and hazardous situation warned reliably, safety information of the monitoring and warning areas was collected by sensor network which include combustible gas sensor, dust sensor, temperature sensor, pressure sensor, flowmeter and IP camera ,and the information fusion model of safety monitoring and warning was established, and then, through the BP neural network and the D-S evidence theory algorithm, various safety information was fused. Actual tests show that it has achieved the goal that monitoring accurately and warning reliably. It is of great significance to ensure the security of coking production.
  • 关键词:Coking production; Monitoring and warning system; Information fusion ;model; BP neural network; D-S evidence fusion
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