面向绿色高效制造的铣削加工工艺参数多目标优化

发布时间：2018-04-04 00:14

本文选题：能耗　切入点：绿色制造　出处：《湖南科技大学》2017年硕士论文

【摘要】：随着全球的能源储备量逐渐减少以及环境污染问题日益突出,全球制造业正面临着由能源缺乏和气候变化等问题所带来的巨大挑战。机械制造业肩负着为发展国民经济的各部门提供现代化技术装备的任务,其发展规模和水平,则是反映国家的经济实力和科研水平的重要标志。机床工业是机械制造业的基础和重要组成部分,机床作为机械制造业的基本生产设备,直接影响着其他机械产品的生产技术水平和经济效益。全球机床保有量庞大,且使用范围广泛,然而,相关参考文献数据显示机床能量利用率和加工效率相对较低、环境污染物排放严重。实现机床绿色高效制造已成工业界和学术界需要解决的重点问题,同时也是机床研究迫切需要解决的关键技术。本文以国家高技术研究发展计划课题(课题编号:2014AA041504):“典型机床绿色生产工艺技术评估及应用支持系统研究”为依托,针对典型机床能量利用率、碳排放和加工效率问题,提出了面向绿色高效制造的数控铣削工艺参数多目标优化这一课题。首先,分析了机床整个加工过程的能耗特性和机床的组成结构,基于数控机床的能耗特性与组成结构,将数控机床能量消耗分解成模块能量消耗,建立数控机床各模块能耗模型与工艺参数之间的函数关系式,根据现有的理论,从而得到面向绿色制造的能量效率和碳排放工艺参数优化模型。其次,以典型四坐标立式加工中心为例搭建数控机床加工能耗测试平台,并在典型四坐标立式加工中心上进行机床切削生产加工能耗数据采集。通过对实验数据分析与数值回归拟合,得到了各模块功率函数表达式和能耗模型,从而得到能量效率与碳排放函数表达式。通过设计实验获取数据对能量效率与碳排放函数模型进行验证,同时研究工艺参数对能量效率和碳排放的影响规律,得出立式加工中心铣削加工碳排放随着主轴转速的提高而增大,随进给速度、铣削深度和铣削宽度的增大而降低;能量效率随主轴转速、进给速度、铣削深度和铣削宽度的增大而增大;在相同主轴转速的情况下,选取较大的进给速度、切削深度和切削宽度在一定程度上可以有效地降低切削加工中的碳排放,显著提高机床的能量效率和加工效率。最后,采用量子遗传算法对面向绿色高效制造的工艺参数多目标优化模型求解优化工艺参数。通过对企业现有参数、优选参数和两组优化参数的铣削实验结果进行对比,得出优选工艺参数和两组优化工艺参数的结果优于现有工艺参数的结果,从而验证了优化方法的可行性,同时分析了优选方法与两种优化方法的不同之处。
[Abstract]:With the decrease of global energy reserves and the increasing environmental pollution, global manufacturing industry is facing great challenges caused by energy shortage and climate change.The machinery manufacturing industry shoulders the task of providing modern technical equipment for the development of various departments of the national economy. The scale and level of its development is an important symbol reflecting the economic strength and scientific research level of the country.Machine tool industry is the foundation and important part of mechanical manufacturing industry. As the basic production equipment of mechanical manufacturing industry, machine tool has a direct impact on the production technology level and economic benefits of other mechanical products.The global machine tool has a large quantity and a wide range of applications. However, the related reference data show that the machine tool energy efficiency and processing efficiency are relatively low, and the environmental pollutant emissions are serious.The realization of green and efficient manufacturing of machine tools has become a key problem to be solved by industry and academic circles, and it is also the key technology of machine tool research that needs to be solved urgently.This paper is based on the National High Technology Research and Development Program (Project No.: 2014AA041504: "study on the Technology Evaluation and Application support system of Green production of typical Machine tools"), aiming at the problems of energy utilization, carbon emission and processing efficiency of typical machine tools.The multi-objective optimization of NC milling parameters for green efficient manufacturing is proposed.Firstly, the energy consumption characteristics of the whole machining process and the structure of the machine tool are analyzed. Based on the energy consumption characteristics and composition structure of the NC machine tool, the energy consumption of the NC machine tool is decomposed into module energy consumption.The functional relationship between the energy consumption model and process parameters of each module of NC machine tool is established. According to the existing theory, the optimization model of energy efficiency and carbon emission process parameters for green manufacturing is obtained.Secondly, taking the typical four-coordinate vertical machining center as an example, the test platform of NC machine tool processing energy consumption is built, and the data collection of machine tool cutting production energy consumption is carried out on the typical four-coordinate vertical machining center.By analyzing the experimental data and fitting with numerical regression, the power function expression and energy consumption model of each module are obtained, and the energy efficiency and carbon emission function expressions are obtained.The function model of energy efficiency and carbon emission is verified by designing experimental data, and the influence of process parameters on energy efficiency and carbon emission is studied.The results show that carbon emission increases with the increase of spindle speed, decreases with the increase of feed speed, milling depth and milling width, and energy efficiency increases with spindle speed and feed speed.With the increase of milling depth and milling width, the carbon emission in cutting can be reduced to a certain extent by selecting larger feed speed, cutting depth and cutting width at the same spindle speed.The energy efficiency and machining efficiency of machine tools are improved significantly.Finally, Quantum genetic algorithm (QGA) is used to solve the multi-objective optimization model of process parameters for green and efficient manufacturing.By comparing the milling experiment results of the existing parameters, the optimal selection parameters and the two groups of optimized parameters, it is concluded that the optimized process parameters and the two groups of optimized process parameters are superior to the existing ones.The feasibility of the optimization method is verified and the difference between the optimal selection method and the two optimization methods is analyzed.
【学位授予单位】：湖南科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TG547

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