基于遗传算法的颗粒态辣椒螺旋输送机优化设计
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摘要
根据正交试验法进行螺旋轴有限元仿真试验,获得各组螺旋叶片最大主应力δ,通过数值拟合,建立最大主应力与设计变量的数值模型,并将模型计算值与试验值进行了比较,验证了模型的准确性,结果表明模型具有较高的精度。以最大主应力最小和输送量最大为优化目标,基于遗传算法对目标进行优化,获得最优设计变量。与传统设计方法相比,遗传算法优化后的螺旋轴根部集中的最大主应力明显下降,有效延长了螺旋轴使用寿命。
According to the orthogonal experimental method,the screw shaft finite element simulation test was carried out to obtain the maximum principal stress δ of the spiral blades of each group. The numerical model of maximum principal stress and design variable were established by the numerical fitting. To verify the accuracy of the model,the predicted value of the model was compared with the experimental value,which shows that the model has high accuracy. With the optimization of the minimum surface stress and the maximum conveying capacity,the objective was optimized based on genetic algorithm to obtain the optimal design variables. Compared with the traditional design method,the maximum principal stress concentration of the root of helical shaft optimized by genetic algorithm obviously decreases,effectively extending its service life.
According to the orthogonal experimental method,the screw shaft finite element simulation test was carried out to obtain the maximum principal stress δ of the spiral blades of each group. The numerical model of maximum principal stress and design variable were established by the numerical fitting. To verify the accuracy of the model,the predicted value of the model was compared with the experimental value,which shows that the model has high accuracy. With the optimization of the minimum surface stress and the maximum conveying capacity,the objective was optimized based on genetic algorithm to obtain the optimal design variables. Compared with the traditional design method,the maximum principal stress concentration of the root of helical shaft optimized by genetic algorithm obviously decreases,effectively extending its service life.
引文
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[3]贾朝斌,程珩.螺旋输送机参数化设计方法研究[J].机械设计与制造,2015(4):206-208,213.
[4]王东霞.螺旋输送机的数值分析及优化设计研究[D].郑州:河南工业大学,2012.
[5]薛风,潘江如,石宁.螺旋输送机变螺旋面升角的问题探讨[J].矿山机械,2015(8):69-72.
[6] LU Jiandong,ZHAO Tianshu,ZHANG Lizheng,et al. Simulation Research About the Influence of Particle Characteristics on Transition of Particles in the Horizontal Screw Conveyor. China Academic Conference on Printing&Packaging&Media Technology[C]. Singapore:Springer,2016.
[7] WANG Duanyi. Multi-Objective Optimization Design of Screw Conveyor Using Genetic Algorithm[J]. Advanced Materials Research,2013,(732/733):402-406.
[8]向冬枝,徐余伟.螺旋输送机设计参数的选择和确定[J].水泥技术,2010(1):29-33.
[9] ZHAO Xiaosong,HSU Chia-Yu,CHANG Pei-Chann,et al. A genetic algorithm for the multi-objective optimization of mixed-model assembly line based on the mental workload[J]. Engineering Applications of Artificial Intelligence,2016(47):140-160.
[10] CHEN X,MA L,LI C,et al. Experimental study and genetic algorithm-based optimization of cutting parameters in cutting engineering ceramics[J]. The International Journal of Advanced Manufacturing Technology,2014,74(5/6/7/8):807-817.
[11] QU S,ZHAO J,WANG T. Experimental study and machining parameter optimization in milling thin-walled plates based on NSGA-II[J]. The International Journal of Advanced Manufacturing Technology,2017,89(5/6/7/8):2399-2409.
[12] NABAVI S,ZHANG L. Design and Optimization of Piezoelectric MEMS Vibration Energy Harvesters Based on Genetic Algorithm[J]. IEEE Sensors Journal,2017,17(22):7372-7382.
[13] TAO F U,LIU W J,ZHAO J B. Parameters Optimization in Cutting of High-strength Mould Steel Based on NSGA-II[J].Materials for Mechanical Engineering,2013,37(12):85-91.
[14]胡宗斌,徐履冰,石来德.非标准机械设备设计手册[M].北京:机械工业出版社,2002.
[15]孔令德,季新培,王鹰,等.螺旋输送机螺旋体挠度有限元分析[J].江苏理工大学学报,1996(5):1-9.
[16]舒服华,桂中华.基于遗传算法的纸浆螺旋输送机优化设计[J].中华纸业,2008,29(24):36-39.