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作 者:刘进 马立峰[1] 王志霞[1] 韩威[1] 吴凤彪 LIU Jin;MA Lifeng;WANG Zhixia;HAN Wei;WU Fengbiao(College of Mechanical Engineering,Taiyuan University of Science and Technology,Taiyuan 030024,China;Department of Mechanical and Electrical Engineering,Shanxi Institute of Energy,Taiyuan 030006,China)
机构地区:[1]太原科技大学机械工程学院,山西太原030024 [2]山西能源学院机电工程系,山西太原030006
出 处:《煤炭工程》2023年第2期152-157,共6页Coal Engineering
基 金:中信重工技术开发项目(20C12-4)。
摘 要:为解决国内相关企业在设计制造过程中缺乏指导降低能耗的破碎能耗理论模型的问题,依托芬兰美卓60-110E型旋回破碎机的基本参数,应用Solidworks搭建三维模型,基于EDEM离散元仿真软件,分析进动角、动锥底角、动锥转速、排矿口大小等关键参数对破碎机能耗的影响,建立破碎机能耗理论预测模型,并得到旋回破碎机性能最优时的关键参数值。根据响应面分析与模型方差分析结果表明:进动角与动锥转速对能耗模型的影响最为显著;当获得同等大小破碎力的情况下,进动角为0.48°、动锥底角为79.99°、动锥转速为130.00r/min、排矿口大小为166.24mm时,旋回破碎机的性能最优,与原工作参数下的旋回破碎机单位能耗相比,能耗降低约1.9%;最后通过与现场数据对比分析,模型基本可靠。该模型的建立可以为高性能旋回破碎机的设计及能耗预测方面的研究提供参考。Aiming at the lack the theoretical model of crushing energy consumption to guide the reduction of energy consumption in the design and manufacturing for gyratory crusher enterprises in China, based on the basic parameters of Metso 60-110E gyratory crusher in Finland, a three-dimensional model is built with Solidworks. The influence of key parameters such as precession angle, bottom angle of moving cone, speed of moving cone, and size of ore outlet on energy consumption of the crusher are analyzed using EDEM, and a theoretical prediction model of the crusher’s energy consumption is established. The key parameters of the gyratory crusher are obtained. The results of response surface analysis and model variance analysis show that the precession angle and cone speed have the most significant influence on the energy consumption model. When the same crushing force is obtained, the precession angle is 0.48°, the bottom angle of the moving cone is 79.99°, the rotating speed of the moving cone is 130.00r/min, and the size of the ore outlet is 166.24mm, the performance of the gyratory crusher is optimal. Compared with the unit energy consumption of the gyratory crusher under the original working parameters, the energy consumption is reduced by about 1.9%. Finally, by comparing with the field data, the model is basically reliable. The model can provide reference for the design and energy consumption prediction of high performance gyratory crusher.
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