JIANG Fuxing, QU Xiaocheng, WANG Yanliang, WEI Quande, LIU Jun, ZHAO Qingmin, LIU Weixin. Study on monitoring & control and early warning technology ofmine pressure bump based on cloud computing[J]. COAL SCIENCE AND TECHNOLOGY, 2018, (1).
Citation:
JIANG Fuxing, QU Xiaocheng, WANG Yanliang, WEI Quande, LIU Jun, ZHAO Qingmin, LIU Weixin. Study on monitoring & control and early warning technology ofmine pressure bump based on cloud computing[J]. COAL SCIENCE AND TECHNOLOGY, 2018, (1).
JIANG Fuxing, QU Xiaocheng, WANG Yanliang, WEI Quande, LIU Jun, ZHAO Qingmin, LIU Weixin. Study on monitoring & control and early warning technology ofmine pressure bump based on cloud computing[J]. COAL SCIENCE AND TECHNOLOGY, 2018, (1).
Citation:
JIANG Fuxing, QU Xiaocheng, WANG Yanliang, WEI Quande, LIU Jun, ZHAO Qingmin, LIU Weixin. Study on monitoring & control and early warning technology ofmine pressure bump based on cloud computing[J]. COAL SCIENCE AND TECHNOLOGY, 2018, (1).
1.University of Science and Technology Beijing, Beijing , China;2.Beijing Anke Xingye Science and Technology Company Limited,Beijing , China;3.Beijing Anke Xingye Research Institute Company Limited of Mine Safety Technology, Beijing , China;4.Yima CoalIndustry Group Corporation Limited, Yima , China;5.Shandong Energy Zibo Mining Group Corporation Limited, Zibo , China;6.Shandong Dongshan Wanglou Coal Mining Corporation Limited, Jining , China
In order to study an interrelation between the each monitored and measured parameter of mine pressure bump and to improve the accuracy of mine pressure bump monitoring, measuring and early warning, with the analysis conducted on the mine pressure bump occurred mechanism and the monitoring and measuring principle of each monitoring and measuring means, the big data analysis method and the cloud platform technology were applied and a mine pressure bump monitoring, measuring and early warning platform with the multi-parameters combined monitoring and measure was developed. The study results showed that the platform could improve the compatibility and synchronism of each monitoring and measured parameter and could realize the deep digging and remote analysis on the monitoring and measured data. The platform could make the block and grading early warning of the mine. The different monitoring and measuring method and the early warning index were applied to the coal mining face, mine roadway heading face and no obvious mining disturbance area in order to improve the pertinence and accuracy of the early warning. Each index and the specific gravity taken by each parameter in the early warning algorithm could be adjusted according to the mine pressure bump type, influence factor, monitoring and measuring index activity degree and others. The early warning algorithm could be improved to the adaptability of the mining and geological complicated environment. The site applications in over 10 mines showed that the system could effectively improve the effect of the monitoring and measured data to the mine safety production.
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