基于灰分和硫含量的屯兰矿选煤厂褐煤最佳洗选条件研究

    Research on the optimal washing conditions of lignite in Tunlan Mine Coal Processing Plant based on ash and sulfur content

    • 摘要: 基于屯兰矿选煤厂褐煤的浮沉数据,采用等增量产品质量方法,研究了同时受多个产品约束的综合产率最大化问题。采用溶剂法和Mathcad软件法分别测定了重介质水浴(DMB)和重介质旋流器(DMC)对粗粒级(130~18 mm)和细粒级(18 ±0.5 mm)的最佳分离密度,对增量产品质量法进行了4种不同情况的分析。对硫含量为0.98%的18.26%的目标复合灰,当增加的灰量被Solver均衡时,复合产率达到最大,为87.45%;通过对增量硫进行溶剂平衡,目标硫含量为0.83%,灰分含量为14.65%,产率达到最大值76.55%;多个产品质量(灰分和硫分)被Solver同时使用,当灰分和硫分分别为11.12%和0.74%时,产率达到最大值,仅为66.87%;利用Mathcad软件同时实现产量最大化的多个约束条件,当灰分和硫含量分别为11.00%和0.74%时,产率达到最大值66.33%。基于同时满足多个产品质量(灰分和硫分)约束和单个产品质量约束,使用Solver和Mathcad软件成功实现了产量最大化。

       

      Abstract: Based on the floatation and sinking data of lignite from the Tunlan Mine coal processing plant, the integrated yield maximization problem subject to multiple product constraints at the same time was investigated using the equal incremental product quality method. The optimum separation densities of heavy media water bath (DMB) and heavy media cyclone (DMC) for coarse (130~18 mm) and fine (18 ±0.5 mm) grains were determined by solvent method and Mathcad software method, respectively, and the incremental product quality method was analyzed for four different cases. For a target composite ash of 18.26% with a sulfur content of 0.98%, the composite yield reached a maximum of 87.45% when the incremental ash was equalized by Solver; by solvent equilibrating the incremental sulfur, the yield reached a maximum of 76.55% with a target sulfur content of 0.83% and an ash content of 14.65%; and multiple product qualities (ash and sulfur) were solved by Solver Simultaneous use of multiple product qualities (ash and sulphur) was used and the yield reached a maximum value of 66.87% when the ash and sulphur contents were 11.12% and 0.74%, respectively; Multiple constraints for yield maximization were achieved simultaneously using Mathcad software and the yield reached a maximum value of 66.33% when the ash and sulphur contents were 11.00% and 0.74%, respectively. Based on simultaneous satisfaction of multiple product quality (ash and sulfur) constraints and single product quality constraints, yield maximization was successfully achieved using Solver and Mathcad software.

       

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