吴翠平, 李齐轩, 王忠仟, 黄引平, 王陈自力, 杜鹏飞. 利用Python软件绘制原煤可选性曲线的研究[J]. 选煤技术, 2023, 51(1): 79-83. DOI: 10.16447/j.cnki.cpt.2023.01.013
    引用本文: 吴翠平, 李齐轩, 王忠仟, 黄引平, 王陈自力, 杜鹏飞. 利用Python软件绘制原煤可选性曲线的研究[J]. 选煤技术, 2023, 51(1): 79-83. DOI: 10.16447/j.cnki.cpt.2023.01.013
    WU Cuiping, LI Qixuan, WANG Zhongqian, HUANG Yinping, WANG Chenzili, DU Pengfei. Study on plotting of coal washability curve using the software Python[J]. Coal Preparation Technology, 2023, 51(1): 79-83. DOI: 10.16447/j.cnki.cpt.2023.01.013
    Citation: WU Cuiping, LI Qixuan, WANG Zhongqian, HUANG Yinping, WANG Chenzili, DU Pengfei. Study on plotting of coal washability curve using the software Python[J]. Coal Preparation Technology, 2023, 51(1): 79-83. DOI: 10.16447/j.cnki.cpt.2023.01.013

    利用Python软件绘制原煤可选性曲线的研究

    Study on plotting of coal washability curve using the software Python

    • 摘要: 可选性曲线在煤炭分选效果预测、运营管理、结果评价等各阶段都被重用,其准确高效绘制非常必要。为适应当前选煤智能化发展趋势,基于常用的智能算法平台,提出了一种利用Python软件绘制原煤可选性曲线的方法,借用国标煤炭浮沉试验数据,并结合NumPy、Scipy、Matplotlib、Pandas等第三方库,进行选煤生产中常用的HR可选性曲线的绘制。研究结果表明,利用Python软件可实现HR可选性曲线的自动绘制,且绘制结果满足选煤生产需求。利用Python软件绘制煤炭可选性曲线有助于实现煤炭重选效果预测优化决策与选煤智能化系统的无缝衔接。

       

      Abstract: In order to be compatible with the current trends in development of intelligent coal preparation, a new method for plotting raw coal washability curve with the use of the software Python based on the commonly used intelligent algorithm platform is proposed. With the use of the method, the Henry washability curve(HR washability curve), a raw coal washability curve plotting method generally used in coal washing operations, can be plotted by referring to the internationally established raw coal float-and-sink analysis data and by using the third-party libraries like NumPy, Scipy, Matplotlib and Pandas. As evidenced by test results, the HR curve is made possible to be plotted in an automatic manner, and the result obtained can well cater to the needs of coal washing operations; and in an intelligent coal washing system, the use of the Python-based plotting method can help realize seamless integration between prediction of separation effects, optimization and decision-making in operation of a heavy-medium coal washing process.

       

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