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論文作者 武云霞
論文導(dǎo)師 王成勇,論文學(xué)位 碩士,論文專(zhuān)業(yè) 機(jī)械制造及其自動(dòng)化
論文單位 廣東工業(yè)大學(xué),點(diǎn)擊次數(shù) 39,論文頁(yè)數(shù) 77頁(yè)File Size4863k
論文網(wǎng) http://www.lw23.com/lunwen_126703557/ 石墨電極;電火花加工;BP神經(jīng)網(wǎng)絡(luò)
Graphite electrode;EDM;BP neural network
    石墨電極具有電極損耗小、加工速度快、耐高溫、加工精度高等優(yōu)點(diǎn)，是模具電火花加工理想的電極材料。開(kāi)展石墨電極電火花加工工藝研究，對(duì)于推動(dòng)石墨電極的應(yīng)用，提高模具的加工精度具有理論指導(dǎo)意義。 本論文通過(guò)對(duì)石墨電極電火花加工特性及電加工工藝與電加工機(jī)床的適應(yīng)性研究，建立石墨電極電火花加工參數(shù)優(yōu)化模型，為石墨電極電火花加工提供依據(jù)。 1、通過(guò)大量的電加工實(shí)驗(yàn)和多種測(cè)試手段，研究了電極極性、脈沖寬度、脈沖間隔、開(kāi)路電壓、峰值電流、石墨顆粒尺寸和工件材料對(duì)石墨電極電火花加工的影響規(guī)律。 2、分別在4種不同的電火花加工機(jī)床上對(duì)石墨電極電加工特性進(jìn)行了研究，分析了石墨電極電火花加工工藝與電火花機(jī)床的適應(yīng)性。 3、初步利用BP神經(jīng)網(wǎng)絡(luò)技術(shù)建立了石墨電極電火花加工參數(shù)優(yōu)化模型。 通過(guò)系列實(shí)驗(yàn)研究和理論分析，獲得以下結(jié)論： 1、脈沖寬度和峰值電流對(duì)石墨電極電火花加工特性(電極損耗、加工速度和表面粗糙度)影響比較顯著，脈沖寬度越大，電極損耗越小，存在負(fù)損耗。開(kāi)路電壓和脈沖間隔存在最優(yōu)值，石墨顆粒尺寸和工件材料對(duì)石墨電極電火花加工特性影響也比較顯著。 2、Charmilles ROBOFORM 35機(jī)床的加工速度較快，加工精度高，但電極損耗較大，適合精密加工；Sodick A35R機(jī)床加工精度良好，電極損耗較小，但加工速度慢，效率低；GOLD SAN機(jī)床和AGIE機(jī)床放電狀態(tài)不穩(wěn)定，容易發(fā)生電弧放電和燒蝕現(xiàn)象，加工精度低，不太適合石墨電極電火花加工。 3、石墨電極電火花加工工藝模型可以有效地預(yù)測(cè)加工效果，該模型對(duì)加工速度、表面粗糙度和電極損耗比的平均預(yù)測(cè)誤差分別為3.62％、2％、15.7％，真實(shí)反映了機(jī)床的加工工藝規(guī)律。

    Because of the advantages such as lower wear ratio, rapid machining speed, high heat-resistant and machining precision, graphite electrode is a kind of perfect electrode material in the EDM process of die and mould. In order to improve its use in the industry, it is valuable and important to research machining technology of graphite electrode for EDM.In this thesis, parameters optimized selection model of graphite electrode for EDM is established based on the research of EDM characteristics of graphite electrode and adaptability of machining technology to different EDM machine tools.Effects of electrode polarity, pulse duration, pulse interval, open-circuit voltage, peak current, grain size of graphite electrode and workpiece material on EDM characteristics of graphite electrode were studied through a lot of experiments and analysis. EDM characteristics of graphite electrode were measured on four EDM machine tools in order to analyze adaptability of machining technology to EDM machine tools. EDM machining technology model with graphite electrode established by BP neural network were carried out.The results indicate that effects of pulse duration and peak current on EDM characteristics, including the electrode wear, material removal rate and surface roughness, are significant. There are an optimum pulse-off time and open-circuit voltage in this experiment. Grain size of graphite, workpiece material and it was also found in this thesis that EDM machine tools affect the results of EDM characteristics. It was proved that that EDM machining technology model with graphite electrode established by BP neural network can effectively predict machining effect, and really reflect machining technology rule of machine tools. The mean predicted errors were 3.62%, 2%, 15.7% for material removal rate, surface roughness and electrode wear, respectively,