[1]鄢红章,张艮水,兰志超,等.基于粒子群算法的烟草卷接机控制系统设计与优化[J].机械与电子,2023,41(03):27-29.
 YAN Hongzhang,ZHANG Genshui,LAN Zhichao,et al.Design and Optimization of Tobacco Coiler Control System Based on Particle Swarm Optimization[J].Machinery & Electronics,2023,41(03):27-29.
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基于粒子群算法的烟草卷接机控制系统设计与优化()
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《机械与电子》[ISSN:1001-2257/CN:52-1052/TH]

卷:
41
期数:
2023年03期
页码:
27-29
栏目:
自动控制与检测
出版日期:
2023-03-31

文章信息/Info

Title:
Design and Optimization of Tobacco Coiler Control System Based on Particle Swarm Optimization
文章编号:
1001-2257 ( 2023 ) 03-0027-03
作者:
鄢红章张艮水兰志超郭子国胡祥胜李 诚梁 静
湖北中烟工业有限责任公司,湖北 武汉 430040
Author(s):
YAN Hongzhang ZHANG Genshui LAN Zhichao GUO Ziguo HU Xiangsheng LI Cheng LIANG Jing
( China Tobacco Hubei Industrial Co. , Ltd. , Wuhan 430040 , China )
关键词:
卷接机粒子群算法烟草设备控制系统
Keywords:
coiler particle swarm optimization tobacco equipment control system
分类号:
TS43
文献标志码:
A
摘要:
针对烟草卷接机,基于微波检测质量技术,引入粒子群算法,提出了一种重量控制方法实现对平准电机的稳定控制。所设计的基于粒子群算法的烟草卷接机控制系统,以烟草卷接机为主体配合扫描装置、重量控制装置等组件实现烟支生产功能,具有良好的控制精度。最后通过针对性的案例分析,对比卷接机烟支重量自动控制系统优化前后的控制效果,进一步验证所设计系统的可靠性及可行性。
Abstract:
Aiming at the tobacco coiler , based on the microwave quality detection technology , this paper introduces the particle swarm optimization algorithm , and proposes a weight control method to realize the stable control of the leveling motor.The tobacco coiler control system based on particle swarm optimization algorithm designed in this paper takes the tobacco coiler as the main body and cooperates with the scanning device , weight control device and other components to realize the cigarette production function , which has good control accuracy.Finally , through the targeted case analysis , the control effect of cigarette weight automatic control system before and after optimization? s compared to further verify the reliability and feasibility of the designed system.

参考文献/References:

[ 1 ] 李二超,高振磊 . 改进粒子速度和位置更新公式的粒子群优化算法[ J ] . 南京师大学报(自然科学版), 2022 , 45( 1 ): 118-126.

[ 2 ] 袁秀秀,刘亚丽,贾楠 . 基于烟草行业的科技查新项目数据统计分析[ J ] . 湖南文理学院学报, 2022 , 34 ( 1 ): 80-84.
[ 3 ] 吕柏行,郭志光,赵韦皓,等 . 标准粒子群算法的优化方式综述[ J ] . 科学技术创新, 2021 ( 28 ): 33-37.
[ 4 ] 杨博雯 . 粒子群优化算法的惯性权重研究[ D ] . 锦州:渤海大学,2021.
[ 5 ] 冯茜,李擎,全威,等 . 多目标粒子群优化算法研究综述[ J ] . 工程科学学报, 2021 , 43 ( 6 ): 745-753.
[ 6 ] 杜昱忻 . 智能控制技术在烟草设备中的应用研究[ J ] .河北农机,2020 ( 7 ): 124.
[ 7 ] 蒋健 . 烟草设备电气控制的常见问题及对策分析[ J ] .自动化应用,2018( 1 ): 47-48.
[ 8 ] 李明 . 标准粒子群算法的收敛性分析及改进研究[ D ] .锦州:渤海大学,2017.
[ 9 ] 方英武,王轶,赵海燕,等 . 基于粒子群优化的 PID 自适应温度控制算法 [ J ] . 计算机与数字工程,2015 , 43( 12 ): 2117-2119 , 2134.
[ 10 ] 赵乃刚,邓景顺 . 粒子群优化算法综述[ J ] . 科技创新导报,2015 , 12 ( 6 ): 216-219.
[ 11 ] 买地那依·库尔班 . 简述烟草设备电气控制常见问题与对策[ J ] . 电子制作, 2015 ( 9 ): 239.
[ 12 ] 杨旭,韩忠华 . 一种用于细支烟卷烟机的重量控制系统[ J ] . 电脑知识与技术, 2018 , 14 ( 36 ): 235-237.

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备注/Memo

备注/Memo:
收稿日期: 2022-06-13
作者简介:鄢红章 ( 1975- ),男,湖北襄阳人,学士,工程师,研究方向为卷烟工艺与机械装备;张艮水 ( 1968- ),男,湖北襄阳人,学士,工程师,研究方向为卷烟工艺与机械装备。
更新日期/Last Update: 2023-04-06