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September 18, 2025MathematicsOpen Access

Off-Site Geological Surveying of Longwall Face Based on the Fusion of Multi-Source Monitoring Data

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The method improves geological surveying accuracy, achieving sub-decimeter precision for unmanned mining.
Local dip angles of longwall faces are estimated from the spatial attitudes of hydraulic supports, enhancing coal seam models.
Image segmentation using U-net enables automatic extraction of coal and rock columns, which contributes to the geological profile.
Field tests confirmed the method's effectiveness, addressing previous limitations in geological adaptability for intelligent mining.

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This new method improves geological adaptability in unmanned mining, integrating multi-source monitoring data for accurate coal seam modeling.

Zhu et al. (2025) studied this question.

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This new method improves geological adaptability in unmanned mining, integrating multi-source monitoring data for accurate coal seam modeling.