摘要
磨削加工是木质材料加工中非常重要的环节,直接影响产品加工精度和表面质量。目前关于木材磨削加工的理论研究不足,磨削工艺参数和动力配置不合理,导致磨削加工能耗较高。采用5因素5水平正交试验,考察了磨削深度(T_s)、砂带磨料粒度(G)、砂带速度(V)和进给速度(U) 4个磨削参数,以及磨削方向与木材纹理的夹角(λ)对砂带磨削杨木和红松时的空转功率(P_i)、有功功率(P_a)、磨削功率(P_s)、磨削力做功功率(P_(sf))及功率利用率(μ)的影响。采用BP(back propagation)神经网络系统建立木质材料砂带磨削P_(sf)和μ的仿真模型,最后用功率利用率的直观分析法对磨削工艺参数进行优化。结果表明:磨削参数对Psf的影响顺序为U>T_s>V>G,且都为高度显著影响因素;对μ的影响顺序为T_s>G>V>U,T_s为高度显著影响因素,G和V为显著影响因素。最佳功率利用率(高磨削效率)的磨削方案为:磨削深度0.1 mm,砂带速度10.74 m/s,进给速度5.16 m/min,磨料粒度60目,杨木横纹磨削,红松斜纹磨削。平均功率利用率45%,最大功率利用率78%,最小功率利用率21%。
Sanding is one of the very important steps during wood material processing,which directly affects the machining accuracy and surface quality of products. At present,no adequate and elaborate theory of wood sanding has been established. Moreover,the sanding parameters and dynamic power configuration were unreasonable,which led to high energy consumption. In this study,orthogonal experiments were performed to investigate the influence of sanding parameters,such as sanding depth( Ts),grit size( G),sanding speed( V),feed speed( U),and also the angle between sanding direction and wood grain direction( λ) on idle power( Pi),active power( Pa),sanding power( Ps),working power( Psf) and power utilization rate( μ) when poplar( Populus L.) and Korean Pine( Pinus koraiensis Sieb. et Zucc.) were sanded. BP( back propagation) neural network system was used to develop a simulation model of Psf and μ for the abrasive belt sanding of wood materials,and the orthogonal experimental design analysis of power utilization rate was used to optimize sanding parameters. The influence order of sanding parameters on Psf was U>Ts >V>G,and all of which were highly significant. The influence order of sanding parameters on μ was Ts >G >V>U,Ts was the highly significant factor,while G and V were significant factors. The optimum power utilization rate led to high sanding efficiency,and the specific parameters were as follows: the sanding thickness of 0.1 mm,sanding speed of 10.74 m/s,feed speed of 5.16 m/min and grit size of 60 mesh. The sanding direction of poplar under the circumstance was cross the wood grain and that of Korean Pine was incline the wood grain. The results showed that the average power utilization rate was 45%,the maximum power utilization rate was 78%,and the minimum power utilization rate was 21%. In terms of the simulation model using BP neural network when sanding poplar,the confidence of fitting results was about 92%. The average predicted deviation of Psf was 6.4%,and the average predicted deviation of μ was 8.3%. It
作者
应俊华
成锋
张健
吴丹妮
罗斌
李黎
YING Junhua;CHENG Feng;ZHANG Jian;WU Danni;LUO Bin;LI Li(MOE Key Laboratory ofWood Materials Science and Application,Beijing 100083,China)
出处
《林业工程学报》
CSCD
北大核心
2019年第3期38-45,共8页
Journal of Forestry Engineering
基金
"十三五"国家重点研发计划(2018YFD0600304)
中央高校基本科研业务费专项资金(2017JC11)
关键词
砂带磨削
木材
磨削能耗
磨削参数
abrasive belt sanding
wood
sanding energy consumption
sanding parameters
