DOI: 10.11799/ce201710007
Research progress of automatic recognition of coal - gangue mixedness in longwall top-coal caving face
LI Liang-hui
Abstract：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.
Keywords：LTCCcoal-gangue mixednessautomatic recognitionartificial intelligence
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 30-34 )