Intelligent early warning system of gas and coal spontaneous combustion disaster based on big data: data characteristics, application structure and key technologies

doi:10.16265/j.cnki.issn1003-3033.2021.09.009

Abstract

Abstract: In order to solve problem of multi-source, massive, dynamic and complex information processing in the process of symbiotic disaster early warning, data characteristics, application architecture and key technologies of big data intelligent early warning system of gas and coal spontaneous combustion were analyzed by applying big data driven technology, application architecture of big data driven symbiotic disaster early warning system was built, and key of symbiotic disaster intelligent early warning lies in big data acquisition, integration, analysis application and early warning technology was discussed. The research results show that big data driven technology has strong insight, decision-making power and process optimization ability in the intelligent early warning of mine gas and coal spontaneous combustion symbiosis disaster, which can process massive monitoring data of symbiotic disaster timely and efficiently, extract valuable knowledge, and realize the construction of application architecture of symbiotic disaster big data intelligent early warning system.

Key words: big data, gas, coal spontaneous combustion, symbiotic disaster, intelligent early warning

CLC Number:

X924.3

ZHANG Jufeng, SHI Shiliang, LU Yi, YOU Bo, WU Fanghua, WU Kuan. Intelligent early warning system of gas and coal spontaneous combustion disaster based on big data: data characteristics, application structure and key technologies[J]. China Safety Science Journal, 2021, 31(9): 60-66.

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