摘要
为解决螺旋输送机在混凝土小预制件生产过程中的能耗高,效率低等问题,提出了一种面向高效率、低能耗的混凝土螺旋输送机设计参数优化方法。首先,建立混凝土螺旋输送机工作过程的速度和力学模型,揭示影响螺旋输送过程能耗和效率的重要因素。在此基础上,以螺距、转速和输送长度为优化变量,以螺旋输送过程总能耗最小、输送效率最大化为目标,建立混凝土螺旋输送机设计参数多目标优化模型,并提出一种基于改进的非支配排序遗传算法(NSGA-Ⅱ)进行优化求解。最后,通过将多目标优化结果与单目标优化结果进行对比分析,验证了所提出优化方法在提高混凝土螺旋输送效率的同时可有效降低生产能耗。
To solve the problems of high energy consumption and low efficiency of the screw conveyor in the production process of small concrete precast parts,a high-efficiency and low-energy concrete screw conveyor design parameter optimization method was proposed.The speed and mechanical model of the concrete screw conveyor during the working process was established,which revealed many factors that affect the energy consumption and efficiency of the conveying process.Basically,to minimize the total energy consumption and maximize the conveying efficiency in the screw conveying process,a concrete screw conveyor multi-objective optimization model for design parameters was established.The screw pitch,speed and conveying length were used as optimization variables in the optimization model.Then,an optimization solution method based on fast elitist Non-dominated Sorting Genetic Algorithm(NSGA-Ⅱ)algorithm was proposed.By comparing the results of multi-objective optimization with that of single-objective optimization,the result showed that the proposed optimization method could effectively reduce energy consumption while improving transportation efficiency.
作者
李丽
甘镇瑜
李聪波
李玲玲
刘继伟
王慧娟
LI Li;GAN Zhenyu;LI Congbo;LI Lingling;LIU Jiwei;WANG Huijuan(College of Engineering and Technology,Southwest University,Chongqing 400715,China;State Key Laboratory of Mechanical Transmission,Chongqing University,Chongqing 400000,China;Chongqing Changzheng Heavy Industry Co.,Ltd.,Chongqing 400083,China)
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2023年第8期2585-2594,共10页
Computer Integrated Manufacturing Systems
基金
国家自然科学基金资助项目(51875480)
重庆市技术创新与应用发展项目(cstc2019jscx-mbdx0118)
重庆市杰出青年科学基金资助项目(CSTB2022NSCQ-JQX0030)。
关键词
高效节能
混凝土螺旋输送机
多目标优化
NSGA-Ⅱ
high efficiency and energy saving
concrete screw conveyor
multi-objective optimization
fast elitist non-dominated sorting genetic algorithm
