Proceedings of the 4th International Conference on Public Management and Intelligent Society, PMIS 2024, 15–17 March 2024, Changsha, China

Research Article

An Intelligent Early Warning Method Based on Cloud Platform Dynamic Monitoring to Prevent Coal Spontaneous Combustion

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  • @INPROCEEDINGS{10.4108/eai.15-3-2024.2346559,
        author={Zihang  Ma},
        title={An Intelligent Early Warning Method Based on Cloud Platform Dynamic Monitoring to Prevent Coal Spontaneous Combustion},
        proceedings={Proceedings of the 4th International Conference on Public Management and Intelligent Society, PMIS 2024, 15--17 March 2024, Changsha, China},
        publisher={EAI},
        proceedings_a={PMIS},
        year={2024},
        month={6},
        keywords={cloud platform; dynamic monitoring; spontaneous coal combustion; intelligent early warning},
        doi={10.4108/eai.15-3-2024.2346559}
    }
    
  • Zihang Ma
    Year: 2024
    An Intelligent Early Warning Method Based on Cloud Platform Dynamic Monitoring to Prevent Coal Spontaneous Combustion
    PMIS
    EAI
    DOI: 10.4108/eai.15-3-2024.2346559
Zihang Ma1,*
  • 1: Xi 'an University of Science and Technology
*Contact email: 1157084460@qq.com

Abstract

Spontaneous coal combustion is one of the major disasters in coal mine safety production, transportation and storage. Rapid monitoring of coal spontaneous combustion characteristic parameters and timely early warning of danger levels are important guarantees for achieving the safe production of large quantities of coal. In order to deal with the sudden occurrence of coal spontaneous combustion disasters and the problem of processing large amounts of dynamically changing data, the key to rationally applying cloud platform data collection and processing technology is to dynamically monitor the occurrence of coal spontaneous combustion, establish a data collection database, and construct characteristic temperatures and indicators. The linear relationship between gases forms a coal spontaneous combustion monitoring technology that integrates multi-parameter data, effectively improving monitoring and early warning capabilities. The research results show that the intelligent system composed of cloud platform dynamic monitoring technology and intelligent early warning system has great effect in preventing the occurrence of spontaneous coal combustion. It can accurately and real-time handle and respond to the occurrence of spontaneous coal combustion, and can record various relevant data for later processing.