煤与矸石图像识别技术在选煤中的应用进展
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刘抗，宋聪聪，赵鹏艳
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1.河南省科学院应用物理研究所有限公司，河南郑州，450000；2.河南省科学院，河南郑州，450000
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摘要：选煤作为煤炭清洁利用的关键核心环节，煤和矸石能否实现精准分离，直接影响着煤炭品质以及利用效率。传统的传统分离技术，主要依靠人工操作或者物理手段完成，传统方法存在分离效率低下、分离精度较差以及成本居高不下等问题。图像识别技术因其具备非接触式检测、实时性良好、智能化程度较高等一系列突出优势，逐渐成为解决这一难题的重要技术途径。本文对煤与矸石图像识别技术发展进程进行系统梳理，从图像采集与预处理、特征提取、识别模型构建三个不同维度，深入剖析传统机器视觉技术和深度学习技术在实际应用过程中特点。依托选煤厂的实际应用事例，对技术落地进程中的难题展开探究，参考工业数据处理经验提出优化的方向，从而为促进选煤行业智能化提升给予理论参考以及实践思路。
关健词：煤与矸石；图像识别；选煤技术；智能化分离
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Application progress of coal and gangue image recognition technology in coal selection
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Kang Liu,Congcong Song, Pengyan Zhao
1.Institute of Applied Physics Co., Ltd., Henan Academy of Sciences, Zhengzhou, Henan, 450000, China；2.Henan Academy of Sciences, Zhengzhou, Henan, 450000, China
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Abstract: Coal selection, as a key core link in the clean and efficient use of coal, whether coal and gangue can be accurately separated affects the quality and utilization efficiency of coal. The traditional separation technology mainly relies on manual operation or physical means to complete, and the traditional method has problems such as low separation efficiency, separation accuracy, and high cost. Image recognition technology has gradually become an important technical approach to solve this problem because of its outstanding advantages such as non-contact detection, good realtime performance, and high degree of intelligence. This paper systematically sorts out the development process of coal and gangue image recognition technology, analyzes the characteristics of traditional machine vision technology and learning technology in the actual application process from three different dimensions of image acquisition and preprocessing, feature extraction, and recognition model construction. Based on the actual application examples of coal preparation plants this paper explores the difficulties in the process of technology implementation, and proposes the direction of optimization with reference to the experience of industrial data processing, so as to provide theoretical reference and ideas for promoting the intelligent improvement of the coal selection industry.
Keywords : Coal and gangue; Image recognition; Coal selection technology; Intelligent
参考文献
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[2] 陈彪.基于深度学习的煤矸图像识别研究[D].中国矿业大学,2023.
[3] 陈佳鑫,赵国贞,程伟,等.基于动态称量和图像识别技术的井下煤矸石智能分选装置研发[J].矿业研究与开发,2023,43(02):178-183.
[4] 郜亚松.基于集成学习的煤和矸石图像识别技术研究与实现[J].电脑知识与技术,2021,17(10):197-199.
[5] 梁澈.粗糙集理论在煤矸石图像识别技术中的应用[D].西安科技大学,2010.
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