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基于BP神经网络的振动筛参数优化分析 被引量:1

Parameter Optimization Analysis of Vibrating Screen Based on BP Neural Network
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摘要 为探究振动筛的筛分参数与筛分效率的非线性映射关系及筛分过程物料复杂运动规律,开展振动筛参数组合优化研究。首先建立振动筛简化后三维模型导入EDEM软件,使用正交试验法设计多组筛分试验,将试验方案中对应参数一一导入EDEM中进行仿真,使用离散元分析法分析振动筛的振幅、振动频率、振动方向角和筛面倾角四个参数对筛分效率的影响,将获得数据导入BP神经网络进行深度学习。采用集成学习的训练集对训练好的模型进行筛机参数影响权重的分析,得出振动频率、振动幅度、振动方向角和筛面倾角对筛分效率有较大影响,故以这四种参数组合表征振动筛运行状态,对不同参数组合对应筛分效率进行分析。振动频率与振动幅度的增加,可以增大筛面的振动强度,不仅加速物料松散及分层效率,增加物料的触筛及透筛概率,又可以改善物料的堵筛情况,但振动强度过大时,物料跃迁时间过长,使得物料与筛面接触时间变短,筛分效率下降;随着振动方向角与倾角的增加可以加速物料的铺展速率,但角度过大时,会降低物料与筛面的碰撞概率,减小物料的透筛概率,从而影响筛分效率。当振幅为3.7 mm、振频为14.3 Hz、振动方向角为44.2°、筛面倾角为12.1°时,振动筛的获得最佳筛分效率,此研究对振动筛优化设计具有一定指导意义。 In order to explore the nonlinear mapping relationship between the screening parameters and the screening efficiency of the vibrating screen and the complex motion law of the materials in the screening process,the optimization of the parameter combination of the vibrating screen was carried out.Firstly,the simplified 3D model of the vibrating screen is established and imported into the EDEM software,the orthogonal test method is used to design multi-group screening tests,the corresponding parameters in the test scheme are imported into EDEM for simulation,and the influence of the four parameters of amplitude,vibration frequency,vibration direction angle and screen surface inclination angle of the vibrating screen is analyzed by discrete element analysis on the screening efficiency,and the obtained data is imported into the BP neural network for deep learning.The training set of ensemble learning was used to analyze the weight of the influence of sieve machine parameters on the trained model,and it was concluded that the vibration frequency,vibration amplitude,vibration direction angle and screen surface inclination angle had a great influence on the screening efficiency,so these four parameter combinations were used to characterize the vibrating screen operating state,and the corresponding screening efficiency of different parameter combinations was analyzed.When the vibration frequency and vibration amplitude increase,the vibration intensity of the screen surface can be increased,which not only accelerates the loosening and layering efficiency of the material,increases the probability of the contact screen and through the sieve of the material,but also improves the blocking situation of the material,but when the vibration intensity is too large,the material transition time is too long,so that the contact time between the material and the sieve surface becomes shorter,and the screening efficiency decreases.With the increase of vibration direction angle and inclination angle,the spreading rate of the material can be accelerated,but when the angle is too large,the probability of collision between the material and the sieve surface will be reduced,and the probability of screening of the material will be reduced,thus affecting the screening efficiency.When the amplitude is 3.7 mm,the vibration frequency is 14.3 Hz,the vibration direction angle is 44.2°,and the screen surface inclination angle is 12.1°,the best screening efficiency of the vibrating screen is obtained,which has certain guiding significance for the optimal design of the vibrating screen.
作者 张晋霞 王研 牛福生 于晓东 李松奕 王延鹏 ZHANG Jinzia;WANG Yan;NIU Fusheng;YU Xiaodong;LI Songyi;WANG Yanpeng(College of Mining Engineering,North China University of Science and Technology,Tangshan 063210,Hebei,China;Hebei Province Mining Industry Develops with Safe Technology Priority Laboratory,Tangshan 063210,Hebei,China;Tangshan Land Sky Tech Co.,Ltd.,Tangshan 063020,Hebei,China)
出处 《有色金属(选矿部分)》 CAS 北大核心 2023年第6期71-79,共9页 Nonferrous Metals(Mineral Processing Section)
基金 中央引导地方科技发展资金项目(226Z4104G) 河北省高等学校科学技术研究项目(ZD2022128) 唐山市科技计划项目(22130226H)。
关键词 振动筛 振动参数 离散元 筛分效率 BP神经网络 vibrating screen vibration parameters discrete elements screening efficiency BP neural network
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