Automatic top coal caving is the key technology for automatic longwall top-coal caving(LTCC), and coal-gangue mixedness recognition is the bottleneck. The author analyzes the progress of coal -gangue mixedness recognition technology of LTCC based on naturalγ-ray, acoustic signal and image. It points out that the image-based coal-gangue mixedness recognition technology is the future development direction; introduces the progress of coal - rock interface recognition in fully-mechanized coal mining and coal-gangue recognition in separation. The author also proposes idea to introduce deep learning theory into the study of coal-gangue mixedness recognition, which provides new thought for the application of artificial intelligence technology in coal mining, and improves the top-coal recovery rate and coal quality.%自动化放煤是实现自动化综放开采的关键技术,放煤过程中对于煤矸混合度的自动识别是研究的难点.文章依次论述了基于自然射线、 声波信号、 图像的放顶煤工作面煤矸混合度识别技术的研究进展,提出了基于图像的煤矸混合度识别技术是未来的发展方向,以及综采工作面的煤岩界面的识别技术及分选中的煤矸识别技术的研究进展,总结了为放顶煤工作面煤矸混合度识别提供的宝贵经验.提出了将深度学习理论引入到煤矸混合度识别研究中,为人工智能技术在采矿行业中的应用提供了新思路,对提高综放开采顶煤回收率、 提高煤质、 实现工作面自动化有重要意义.
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