Coal bunker spontaneous combustion prediction and visual monitoring system and method
By simulating the spontaneous combustion process of coal in an experimental coal bunker, a mapping relationship between internal and external parameters was established, and a neural network model was used for prediction. This solved the problems of lag and accuracy in monitoring spontaneous combustion in coal bunkers, and enabled real-time, accurate visual monitoring and early warning.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- XIAN UNIV OF SCI & TECH
- Filing Date
- 2026-05-21
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies for monitoring spontaneous combustion in coal bunkers suffer from significant lag and low prediction accuracy, making it difficult to achieve comprehensive monitoring and accurate prediction of the internal temperature field of the coal bunker.
By establishing a scaled-down experimental coal bunker, setting up heating devices, sensing components, data acquisition modules, and processing equipment, the spontaneous combustion process of coal is simulated, changes in internal and external parameters are obtained, a mapping relationship is established, machine learning and neural network models are used for prediction, and real-time visualization monitoring is performed in conjunction with multi-source data.
It enables real-time, accurate, and visual monitoring of the coal bunker interior, improves the level of coal mine safety production, provides an effective early warning mechanism for spontaneous combustion, overcomes the problem of insufficient data, and improves prediction accuracy.
Smart Images
Figure CN122409744A_ABST