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基于X射线散射的煤炭灰分快速检测模型的构建

Development of a rapid coal ash detection model based on X-Ray scattering

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【作者】 毛思维张翔宇刘海增李圣洁江雨尧

【Author】 MAO Si-wei;ZHANG Xiang-yu;LIU Hai-zeng;LI Sheng-jie;JIANG Yu-yao;School of Materials Science and Engineering, Anhui University of Science and Technology;Beijing Aerospace Petrochemical Technology and Equipment Engineering Co.,Ltd.;

【通讯作者】 刘海增;

【机构】 安徽理工大学材料科学与工程学院北京航天石化技术装备工程有限公司

【摘要】 煤炭灰分的快速、准确检测对于优化燃烧过程与实现清洁排放至关重要。针对现有检测方法存在的流程复杂、时效性差等问题,设计了一种基于X射线散射技术的煤炭灰分在线检测方案。通过设计多角度、多距离的散射实验,系统分析了散射信号与灰分的响应关系,并构建检测模型进行验证与误差分析。结果表明:以65°、60°的角度组合与20 cm的检测距离为最佳参数,在此条件下模型决定系数R~2达0.990 5,并发现煤样粒度在25 mm及以下范围内波动时对检测结果无显著影响。同时测得灰分值与真实值的绝对误差与相对误差均低于行业允许范围,证明了该技术方案具有良好的准确性与可靠性,为实现煤炭灰分的在线快速检测提供了有效的技术途径。

【Abstract】 The rapid and accurate detection of coal ash content is crucial for optimizing the combustion process and achieving clean emissions. To address issues such as complex procedures and poor timeliness in existing detection methods, an online detection scheme for coal ash content based on X-ray scattering technology was designed. Through systematically designed scattering experiments at multiple angles and distances, the response relationship between the scattering signal and ash content was analyzed, and a detection model was constructed for verification and error analysis. The results indicate that the optimal parameters are an angle combination of 65° and 60° with a detection distance of 20 cm. Under these conditions, the model’s coefficient of determination(R~2) reaches 0.9905. Furthermore, it was found that the fluctuation of coal particle size within the range of 25 mm and below has no significant effect on the detection results. Meanwhile, the absolute error and relative error between the measured ash content values and the actual values were both lower than the industry-permissible range, demonstrating that this technical scheme possesses good accuracy and reliability, thereby providing an effective technical approach for the online rapid detection of coal ash content.

【基金】 国家重点研发计划子课题:难选焦煤精深分选关键工艺环节精准控制技术(2023YFC2907705)
  • 【文献出处】 煤炭加工与综合利用 ,Coal Processing & Comprehensive Utilization , 编辑部邮箱 ,2026年02期
  • 【分类号】TD94;TQ533
  • 【下载频次】20
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