计算机集成制造系统 ›› 2019, Vol. 25 ›› Issue (第2): 391-402.DOI: 10.13196/j.cims.2019.02.012

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薄煤层煤岩刨削比能耗优化模型

郭辰光1,岳海涛1,赵丽娟1,张建卓1,谢华龙2   

  1. 1.辽宁工程技术大学机械工程学院
    2.东北大学机械工程及自动化学院
  • 出版日期:2019-02-28 发布日期:2019-02-28
  • 基金资助:
    国家自然科学基金资助项目(51674134,51574140,51304105)。

Specific energy consumption optimization model of thin coal seam plowing

  • Online:2019-02-28 Published:2019-02-28
  • Supported by:
    Project supported by the National Natural Science Foundation,China(No.51674134,51574140,51304105).

摘要: 合理选择刨削工艺参数可有效节省薄煤层综采过程中的能量损耗,是实现煤岩绿色、可持续开采的关键。鉴于此,对刨煤机刨削工艺参数优化进行了研究,综合考虑刨头刨削煤岩、刨刀刨削煤岩温升、机组沿煤岩采面移动、刨落煤岩推移与运输、辅助系统损耗等过程,构建了刨煤机能量损耗模型;建立了以煤岩刨削比能耗最小为目标的煤岩刨削工艺参数优化模型;基于自适应自然选择粒子群算法完成了优化模型寻优求解;结合薄煤层井下开采实例验证了所建立比能耗优化模型有效性;比较分析了刨削速度、截深、刀间距3个优化变量对刨削比能耗的影响规律。结果表明,自适应自然选择粒子群算法具有较好的收敛速度与求解精度,所建模型可为煤岩刨削工艺参数设计提供理论依据;该方法能够有效降低薄煤层综采过程能量损耗,对工程应用具有很好的指导意义。

关键词: 薄煤层, 刨削工艺参数, 比能耗, 自适应自然选择粒子群优化, 刨煤机

Abstract: Correct selection of plowing parameters is an effective method to reduce energy consumption for thin coal seam mining process,and it is the key to achieve green and sustainable coal mining.For this reason,the plowing process parameters optimization of plough was researched.An energy consumption model of plough was proposed by considering the plowing processes for plow body force of coal cutting,plough bit temperature rising of coal cutting,plough unit moving along with coal seam mining face,plowed coal particles moving and transport and the auxiliary systems consumption.The process parameters optimization model with minimum specific energy consumption objective of thin coal seam plowing was established,and the adaptive natural selection particle swarm optimization method was applied to solve the optimal solution.A thin coal seam mining experiment case was performed to verify the effectiveness of the specific energy consumption optimization model,and the influence rules of three optimize variables which were cutting speed,cutting depth,bits interval on energy consumption were compared and analyzed.The results showed that the adaptive natural selection particle swarm optimization algorithm had good convergence speed and solving accuracy.The proposed optimization model not only could provide some theoretical basis for plowing process parameters design,but also reduce energy consumption for the thin coal seam mining process effectively,which provided a good guiding significance for engineering application.

Key words: thin coal seam, plowing process parameters, specific energy consumption, adaptive natural selection particle swarm optimization, plough

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