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作 者:洪武 张文亮 杨琛 和继高 高泽宇 HONG Wu;ZHANG Wenliang;YANG Chen;HE Jigao;GAO Zeyu(Yunnan Jinding Zinc Industry Co.,Ltd.,Lanping 671401,China;BGRIMM Machinery and Automation Technology Co.,Ltd.,Beijing 100160,China)
机构地区:[1]云南金鼎锌业有限公司,云南兰坪671401 [2]北矿机电科技有限责任公司,北京100160
出 处:《有色设备》2024年第3期30-36,共7页Nonferrous Metallurgical Equipment
基 金:工信部智能制造新模式应用项目(Z135060009002)。
摘 要:智能剥离单元是智能剥锌系统中的核心装备,用于对阴极铝板上的电沉积金属锌片进行剥离。本文以某公司研发的全新一代BKAS-32型智能剥锌机的智能剥离单元为研究对象,针对其非对称液压缸控制系统的特点,建立了电液比例阀控液压系统的数学模型,设计了基于单神经元控制算法的剥离过程液压控制系统模型并进行了仿真分析,通过与传统PID控制系统的仿真结果进行对比,论证了基于单神经元控制算法的剥离过程液压控制系统性能的优越性。经过现场应用表明,应用单神经元控制算法的智能剥离单元的剥离刀具组件双向运行速度曲线平滑,对称性高,两侧剥离刀具组件的速度差小于1%,极大地增加了智能剥离单元剥离作业的稳定性。In the field of zinc hydrometallurgy,the intelligent stripping unit is the core equipment of the intelligent stripping system.It used to strip the electrodeposited metal zinc sheets on the cathode aluminum plate.This article takes the intelligent stripping unit of the new generation BKAS-32 intelligent zinc stripping system developed by BGRIMM as the research object.Based on the characteristics of asymmetric hydraulic cylinder control system,a mathematical model of the electro-hydraulic proportional valve control hydraulic system is established.A hydraulic control system model for the stripping process based on the single neuron control algorithm is designed and simulated.By comparing the simulation results with the traditional PID control system,the superiority of the single neuron control system performance for the stripping process is demonstrated.After on-site application,it has been shown that the bidirectional running speed curve of the stripping tool of the intelligent stripping unit which using the single neuron control algorithm is more smooth.This intelligent stripping unit also has the higher symmetry.The speed difference between the stripping tool on both sides is less than 1%.The single neuron control algorithm greatly increasing the stability of the stripping operation of the intelligent stripping unit.
关 键 词:智能剥离单元 非对称液压缸 单神经元控制 PID 仿真
分 类 号:TF35[冶金工程—冶金机械及自动化] TF813
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