發(fā)布時(shí)間：2018-04-04 00:14

  本文選題：能耗　切入點(diǎn)：綠色制造　出處：《湖南科技大學(xué)》2017年碩士論文

【摘要】：隨著全球的能源儲(chǔ)備量逐漸減少以及環(huán)境污染問(wèn)題日益突出,全球制造業(yè)正面臨著由能源缺乏和氣候變化等問(wèn)題所帶來(lái)的巨大挑戰(zhàn)。機(jī)械制造業(yè)肩負(fù)著為發(fā)展國(guó)民經(jīng)濟(jì)的各部門提供現(xiàn)代化技術(shù)裝備的任務(wù),其發(fā)展規(guī)模和水平,則是反映國(guó)家的經(jīng)濟(jì)實(shí)力和科研水平的重要標(biāo)志。機(jī)床工業(yè)是機(jī)械制造業(yè)的基礎(chǔ)和重要組成部分,機(jī)床作為機(jī)械制造業(yè)的基本生產(chǎn)設(shè)備,直接影響著其他機(jī)械產(chǎn)品的生產(chǎn)技術(shù)水平和經(jīng)濟(jì)效益。全球機(jī)床保有量龐大,且使用范圍廣泛,然而,相關(guān)參考文獻(xiàn)數(shù)據(jù)顯示機(jī)床能量利用率和加工效率相對(duì)較低、環(huán)境污染物排放嚴(yán)重。實(shí)現(xiàn)機(jī)床綠色高效制造已成工業(yè)界和學(xué)術(shù)界需要解決的重點(diǎn)問(wèn)題,同時(shí)也是機(jī)床研究迫切需要解決的關(guān)鍵技術(shù)。本文以國(guó)家高技術(shù)研究發(fā)展計(jì)劃課題(課題編號(hào):2014AA041504):“典型機(jī)床綠色生產(chǎn)工藝技術(shù)評(píng)估及應(yīng)用支持系統(tǒng)研究”為依托,針對(duì)典型機(jī)床能量利用率、碳排放和加工效率問(wèn)題,提出了面向綠色高效制造的數(shù)控銑削工藝參數(shù)多目標(biāo)優(yōu)化這一課題。首先,分析了機(jī)床整個(gè)加工過(guò)程的能耗特性和機(jī)床的組成結(jié)構(gòu),基于數(shù)控機(jī)床的能耗特性與組成結(jié)構(gòu),將數(shù)控機(jī)床能量消耗分解成模塊能量消耗,建立數(shù)控機(jī)床各模塊能耗模型與工藝參數(shù)之間的函數(shù)關(guān)系式,根據(jù)現(xiàn)有的理論,從而得到面向綠色制造的能量效率和碳排放工藝參數(shù)優(yōu)化模型。其次,以典型四坐標(biāo)立式加工中心為例搭建數(shù)控機(jī)床加工能耗測(cè)試平臺(tái),并在典型四坐標(biāo)立式加工中心上進(jìn)行機(jī)床切削生產(chǎn)加工能耗數(shù)據(jù)采集。通過(guò)對(duì)實(shí)驗(yàn)數(shù)據(jù)分析與數(shù)值回歸擬合,得到了各模塊功率函數(shù)表達(dá)式和能耗模型,從而得到能量效率與碳排放函數(shù)表達(dá)式。通過(guò)設(shè)計(jì)實(shí)驗(yàn)獲取數(shù)據(jù)對(duì)能量效率與碳排放函數(shù)模型進(jìn)行驗(yàn)證,同時(shí)研究工藝參數(shù)對(duì)能量效率和碳排放的影響規(guī)律,得出立式加工中心銑削加工碳排放隨著主軸轉(zhuǎn)速的提高而增大,隨進(jìn)給速度、銑削深度和銑削寬度的增大而降低;能量效率隨主軸轉(zhuǎn)速、進(jìn)給速度、銑削深度和銑削寬度的增大而增大;在相同主軸轉(zhuǎn)速的情況下,選取較大的進(jìn)給速度、切削深度和切削寬度在一定程度上可以有效地降低切削加工中的碳排放,顯著提高機(jī)床的能量效率和加工效率。最后,采用量子遺傳算法對(duì)面向綠色高效制造的工藝參數(shù)多目標(biāo)優(yōu)化模型求解優(yōu)化工藝參數(shù)。通過(guò)對(duì)企業(yè)現(xiàn)有參數(shù)、優(yōu)選參數(shù)和兩組優(yōu)化參數(shù)的銑削實(shí)驗(yàn)結(jié)果進(jìn)行對(duì)比,得出優(yōu)選工藝參數(shù)和兩組優(yōu)化工藝參數(shù)的結(jié)果優(yōu)于現(xiàn)有工藝參數(shù)的結(jié)果,從而驗(yàn)證了優(yōu)化方法的可行性,同時(shí)分析了優(yōu)選方法與兩種優(yōu)化方法的不同之處。
[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.
【學(xué)位授予單位】：湖南科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TG547

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