[1]沈国浪,童昕,李占福.应用GA-BP神经网络优化平摆复合振动筛的振动参数[J].华侨大学学报(自然科学版),2018,39(4):509-513.[doi:10.11830/ISSN.1000-5013.201803010]
 SHEN Guolang,TONG Xin,LI Zhanfu.Application of GA-BP to Optimize Vibration Parameters of Vibrating Screen of Translation-Swing Composite Motion[J].Journal of Huaqiao University(Natural Science),2018,39(4):509-513.[doi:10.11830/ISSN.1000-5013.201803010]
点击复制

应用GA-BP神经网络优化平摆复合振动筛的振动参数()
分享到:

《华侨大学学报(自然科学版)》[ISSN:1000-5013/CN:35-1079/N]

卷:
第39卷
期数:
2018年第4期
页码:
509-513
栏目:
出版日期:
2018-07-18

文章信息/Info

Title:
Application of GA-BP to Optimize Vibration Parameters of Vibrating Screen of Translation-Swing Composite Motion
文章编号:
1000-5013(2018)04-0509-05
作者:
沈国浪1 童昕12 李占福2
1. 华侨大学 机电及自动化学院, 福建 厦门 361021;2. 福建工程学院 福建省数字化装备重点实验室, 福建 福州 350108
Author(s):
SHEN Guolang1 TONG Xin12 LI Zhanfu2
1. College of Mechanical Engineering and Automation, Huaqiao University, Xiamen 361021, China; 2. Fujian Key Laboratory of Digital Equipment, Fujian University of Technology, Fuzhou 350108, China
关键词:
振动筛 振动参数 离散单元法 筛分效率 遗传算法-BP神经网络
Keywords:
vibrating screen vibration parameter discrete element method screening efficiency genetic algorithm-BP neural network
分类号:
TD452
DOI:
10.11830/ISSN.1000-5013.201803010
文献标志码:
A
摘要:
针对目前筛分理论的研究仅局限于单因素考虑的问题,提出应用遗传算法(GA)优化的BP神经网络对数据空间进行全局寻优,且考虑所有因素对筛分结果的综合影响.首先,通过离散单元法的筛分仿真试验,获取实际筛分过程中难以获取的数据.然后,利用GA优化的BP神经网络对平摆复合振动筛的振动参数进行优化,选择5-9-1的BP神经网络结构类型,得到优化后的振动参数组合,即振幅为2 mm,振动频率为26 Hz,振动方向角为46°,摆动频率为21 Hz,摆角为1°.对优化后的结果进行一次模拟仿真验证,结果表明:验证结果与测试结果相吻合.
Abstract:
Aiming at the problem that the current screening theory was limited to one factor, a BP neural network optimized by genetic algorithm(GA)was proposed for global optimization of data space when the effects of multiple factors on screening results were considered. Firstly, the data difficult to obtain in the actual sieving process was obtained by using the simulation experiment based on discrete element method. Then, the BP neural network with structure of type 5-9-1 optimized by GA was adopted to optimize the vibration parameters of vibrating screen of translation-swing composite motion. The vibration parameters after optimization were as follows: vibration amplitude 2 mm, vibration frequency 26 Hz, vibrating direction angle 46°, swing frequency 21 Hz, and swing angle 1°. Finally, the optimized results were verified by simulation experiment. The results show that the simulation experiment results are in good agreement with test results.

参考文献/References:

[1] 郭年琴,匡永江.振动筛国内外研究现状及发展[J].世界有色金属,2009(5):26-27.
[2] 赵跃民,刘初升,张成勇.煤炭干法筛分理论与设备的进展[J].煤,2008,17(2):15-18.DOI:10.3969/j.issn.1005-2798.2008.02.003.
[3] 王桂锋.振动筛筛分研究及优化设计[D].厦门:华侨大学,2011.
[4] 肖建章,童昕.基于DEM的进料速率对颗粒筛分影响的研究[J].煤炭工程,2012,1(10):85-88.
[5] CLEARY P W,SAWLEY M L.DEM modelling of industrial granular flows: 3D case studies and the effect of particle shape on hopper discharge[J].Applied Mathematical Modelling,2002,26(2):89-111.DOI:10.1016/S0307-904X(01)00050-6.
[6] LI Jing,WEBB C,PANDIELLA S S,et al.Discrete particle motion on sieves: A numerical study using the DEM simulation[J].Powder Technology,2003,133(1):190-202.DOI:10.1016/S0032-5910(03)00092-5.
[7] 林钰珍.基于并联机构的高效多维振动筛设计与研究[D].镇江:江苏大学,2009.
[8] 仇云飞.摆动与平动复合的新型振动筛数值模拟及松散机理的研究[D].厦门:华侨大学,2015.
[9] 张卡德,黄致建,郝艳华.振动筛机架结构的优化设计[J].华侨大学学报(自然科学版),2010,31(4):363-366.DOI:10.11830/ISSN.1000-5013.2010.04.0363.
[10] 周碧,童昕,李占福,等.新型振动筛松散机理[J].机械设计与研究,2016(3):149-153.DOI:10.13952/j.cnki.jofmdr.2016.0121.
[11] LI Zhanfu,TONG Xin,ZHOU Bi,et al.Modeling and parameter optimization for the design of vibrating screens[J].Minerals Engineering,2015,83:149-155.DOI:10.1016/j.mineng.2015.07.009.
[12] 沈国浪,李占福,童昕,等.基于DEM的振动筛振动参数对分层质量的影响[J].煤炭科学技术,2017,45(5):217-222.DOI:10.13199/j.cnki.cst.2017.05.036.
[13] 姚立娟,曾杨,郑庆华,等.汽车起重机力矩限制器算法模型的实现[J].机械设计与研究,2011,27(1):106-108.DOI:10.13952/j.cnki.jofmdr.2011.01.025.
[14] 李烁,徐元铭,张俊.基于神经网络响应面的复合材料结构优化设计[J].复合材料学报,2005,22(5):134-140.DOI:10.3321/j.issn:1000-3851.2005.05.022.
[15] 代向歌,彭高明.BP-GA算法对斗轮堆取料机回转平台的结构优化[J].机械设计与研究,2012,28(1):105-108.DOI:10.3969/j.issn.1006-2343.2012.01.029.
[16] TAN Gangping,WANG Dengfeng,LI Qian.Vehicle interior sound quality prediction based on back propagation neural network[J].Procedia Environmental Sciences,2011,11(B):471-477.DOI:10.1016/j.proenv.2011.12.075.

相似文献/References:

[1]朱来发,金花雪,范伟,等.加速度传感器的振动筛螺栓松动故障诊断系统[J].华侨大学学报(自然科学版),2024,45(1):10.[doi:10.11830/ISSN.1000-5013.202307003]
 ZHU Laifa,JIN Huaxue,FAN Wei,et al.Fault Diagnosis System for Bolt Loosening in Vibrating Screen Based on Acceleration Sensor[J].Journal of Huaqiao University(Natural Science),2024,45(4):10.[doi:10.11830/ISSN.1000-5013.202307003]
[2]李威宏,童昕,李占福,等.集成学习在直线振动筛的应用及参数优化[J].华侨大学学报(自然科学版),2020,41(6):695.[doi:10.11830/ISSN.1000-5013.201912026]
 LI Weihong,TONG Xin,LI Zhanfu,et al.Application and Parameter Optimization of Ensemble Learning in Linear Vibrating Screen[J].Journal of Huaqiao University(Natural Science),2020,41(4):695.[doi:10.11830/ISSN.1000-5013.201912026]

备注/Memo

备注/Memo:
收稿日期: 2018-03-07
通信作者: 童昕(1964-),男,教授,博士,主要从事机电系统动态分析与控制的研究.E-mail:xtong@fjut.edu.cn.
基金项目: 国家自然科学基金资助项目(51175190); 福建省科技创新平台资助项目(2014H202); 福建省高校自然科学青年基金重点资助项目(JZ160460); 华侨大学研究生科研创新基金项目(1601103005)
更新日期/Last Update: 2018-07-20