基于光纖光柵傳感的重型機(jī)床立柱熱變形監(jiān)測研究
本文選題:光纖光柵傳感 + 重型機(jī)床立柱; 參考:《武漢理工大學(xué)》2015年碩士論文
【摘要】:重型數(shù)控機(jī)床在加工制造業(yè)中扮演著相當(dāng)重要的角色,提高其加工精度一直是備受關(guān)注的重要研究課題。研究表明,熱誤差占機(jī)床總誤差的45%左右,同時(shí)精度要求越高,其所占比重越大。為了能減少或后期抵消熱誤差,目前對(duì)熱誤差的研究主要集中在機(jī)床溫度場分析、溫度變化與熱變形建模等方面。由于機(jī)床是個(gè)復(fù)雜的物理結(jié)構(gòu),并且存在外界環(huán)境的不可控干擾,溫度場難以重構(gòu),而所建模型的精確性、魯棒性和運(yùn)算效率也影響著熱誤差補(bǔ)償裝置的效果。機(jī)床熱誤差是機(jī)床各部件在熱源影響下產(chǎn)生形變的共同作用效果,而熱變形建模是熱誤差補(bǔ)償技術(shù)的基礎(chǔ),通過所建模型可以根據(jù)實(shí)時(shí)溫度變化預(yù)測并補(bǔ)償形變量而實(shí)現(xiàn)熱誤差的減少。從物理結(jié)構(gòu)上看,立柱的彎曲會(huì)引起橫梁前傾,從而導(dǎo)致加工主軸發(fā)生熱漂移。本文以機(jī)床的大型構(gòu)件—立柱為研究對(duì)象,圍繞其與機(jī)床熱變形之間的關(guān)系開展了如下工作:(1)對(duì)機(jī)床的熱源分布進(jìn)行分析,運(yùn)用光纖光柵溫度傳感器針對(duì)立柱的溫度場進(jìn)行了初步測量,同時(shí)運(yùn)用CCD激光位移傳感器同步采集主軸熱漂移(機(jī)床Y方向熱變形),并對(duì)立柱溫度變化與熱變形數(shù)據(jù)之間的相關(guān)性進(jìn)行分析。(2)并非所有溫度測點(diǎn)與熱變形之間有明顯關(guān)系,因此運(yùn)用模糊聚類方法對(duì)溫度測量點(diǎn)進(jìn)行分組,然后以不同的側(cè)重點(diǎn),分別采用偏相關(guān)分析、最大靈敏度和灰關(guān)聯(lián)分析方法從分組中篩選出關(guān)鍵溫度測量點(diǎn),并基于篩選結(jié)果存在交叉性,提出一種更為平衡的綜合測點(diǎn)優(yōu)化策略。(3)基于所得到的關(guān)鍵溫度測量點(diǎn)分別運(yùn)用多元線性回歸模型、BP神經(jīng)網(wǎng)絡(luò)模型和基于遺傳算法改進(jìn)的BP網(wǎng)絡(luò)模型建立其與機(jī)床熱變形的關(guān)系模型,并對(duì)模型進(jìn)行評(píng)估得到最佳的預(yù)測模型。同時(shí)根據(jù)評(píng)估結(jié)果也驗(yàn)證了不同測點(diǎn)優(yōu)化策略的優(yōu)劣,進(jìn)而提出測點(diǎn)優(yōu)化和建模方法改進(jìn)的建議。(4)為了更方便和深入的研究立柱形變對(duì)機(jī)床熱誤差的影響機(jī)理,基于光纖光柵的應(yīng)變量測量,推導(dǎo)了柱形結(jié)構(gòu)應(yīng)變量與自身形變狀態(tài)之間的關(guān)系。同時(shí)設(shè)計(jì)了柱形結(jié)構(gòu)二維形變實(shí)時(shí)監(jiān)測模型和實(shí)現(xiàn)方案,運(yùn)用該模型能夠在線監(jiān)測機(jī)床柱形結(jié)構(gòu)的彎曲變化特點(diǎn),對(duì)后續(xù)熱誤差補(bǔ)償?shù)难芯可踔潦侵谓Y(jié)構(gòu)的設(shè)計(jì)都有重要參考意義。
[Abstract]:Heavy CNC machine tools play a very important role in the manufacturing industry, and improving their machining accuracy has been an important research topic. The results show that the thermal error accounts for about 45% of the total error of the machine, and the higher the precision is, the greater the proportion of the thermal error is. In order to reduce or offset the thermal error, the research on the thermal error is mainly focused on the analysis of the temperature field of the machine tool, the modeling of the temperature change and the thermal deformation, etc. Because the machine tool is a complex physical structure and there exists uncontrollable disturbance in the external environment, it is difficult to reconstruct the temperature field, and the accuracy, robustness and operational efficiency of the established model also affect the effect of the thermal error compensation device. The thermal error of machine tool is the common effect of deformation produced by the components of machine tool under the influence of heat source, and the thermal deformation modeling is the basis of thermal error compensation technology. The thermal error can be reduced by predicting and compensating the shape variables according to the real time temperature change. From the point of view of physical structure, the bending of the column will cause the beam to lean forward and cause the heat drift of the machining spindle. In this paper, a large component of machine tools-columns as the research object, around the relationship between the thermal deformation of the machine tools carried out the following work: (1) the distribution of heat sources of machine tools are analyzed. The temperature field of the column is preliminarily measured by using the fiber Bragg grating (FBG) temperature sensor. At the same time, CCD laser displacement sensor is used to synchronously collect the thermal drift of spindle (thermal deformation in the Y direction of machine tool), and the correlation between the temperature change of the column and the thermal deformation data is analyzed. (2) not all the temperature measuring points have obvious relationship with the thermal deformation. Therefore, the temperature measurement points are grouped by fuzzy clustering method, and then the key temperature measurement points are selected from the grouping by using the partial correlation analysis, the maximum sensitivity and the grey correlation analysis, respectively, with different emphases, and the method of maximum sensitivity and grey correlation analysis is used to select the key temperature measurement points from the groups. And based on the results of the screening, A more balanced optimization strategy for integrated measurement points is proposed. (3) based on the obtained critical temperature measurement points, the multiple linear regression model / BP neural network model and the improved BP neural network model based on genetic algorithm are used to establish the computer respectively. The relation model of bed thermal deformation, The best prediction model is obtained by evaluating the model. At the same time, according to the evaluation results, the merits and demerits of different measuring points optimization strategies are verified, and the suggestions for improving the measurement point optimization and modeling methods are put forward. (4) in order to study the influence mechanism of column deformation on the thermal error of machine tools more conveniently and deeply, Based on the strain measurement of fiber grating, the relationship between the strain of cylindrical structure and its deformation state is derived. At the same time, the real time monitoring model and realization scheme of two-dimensional deformation of cylindrical structure are designed. The model can be used to monitor the bending characteristics of cylindrical structure of machine tools on line. It is of great significance to study the subsequent thermal error compensation and even the design of cylindrical structure.
【學(xué)位授予單位】:武漢理工大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2015
【分類號(hào)】:TG659
【參考文獻(xiàn)】
相關(guān)期刊論文 前10條
1 代貴松;楊建國;朱小龍;;基于因子分析和貝葉斯估計(jì)的機(jī)床熱誤差建模[J];組合機(jī)床與自動(dòng)化加工技術(shù);2013年09期
2 姜杉;趙志剛;孫明陸;郭建慧;于紅;;數(shù)控機(jī)床主軸熱特性分析[J];天津大學(xué)學(xué)報(bào)(自然科學(xué)與工程技術(shù)版);2013年09期
3 楊漪;姚曉棟;楊建國;張余升;袁峰;;基于主成分分析與BP神經(jīng)網(wǎng)絡(luò)相結(jié)合的機(jī)床主軸熱漂移誤差建模[J];上海交通大學(xué)學(xué)報(bào);2013年05期
4 陳群強(qiáng);梁睿君;葉文華;劉寶俊;劉世豪;;數(shù)控機(jī)床滾珠絲杠的溫度場研究[J];系統(tǒng)仿真技術(shù);2013年02期
5 趙瑞月;梁睿君;葉文華;;基于模糊聚類與偏相關(guān)分析的機(jī)床溫度測點(diǎn)優(yōu)化[J];機(jī)械科學(xué)與技術(shù);2012年11期
6 沈岳熙;楊建國;;基于嶺回歸的數(shù)控機(jī)床溫度布點(diǎn)優(yōu)化及其熱誤差建模[J];機(jī)床與液壓;2012年05期
7 章婷;葉文華;梁睿君;單以才;劉世豪;;數(shù)控機(jī)床熱誤差變參數(shù)GM(1,1)的建模[J];中南大學(xué)學(xué)報(bào)(自然科學(xué)版);2012年01期
8 蘇鐵明;葉三排;孫偉;;基于FCM聚類和RBF神經(jīng)網(wǎng)絡(luò)的機(jī)床熱誤差補(bǔ)償建模[J];組合機(jī)床與自動(dòng)化加工技術(shù);2011年10期
9 章婷;劉世豪;;數(shù)控機(jī)床熱誤差補(bǔ)償建模綜述[J];機(jī)床與液壓;2011年01期
10 閆嘉鈺;楊建國;;數(shù)控機(jī)床熱誤差的最優(yōu)線性組合建模[J];上海交通大學(xué)學(xué)報(bào);2009年04期
相關(guān)碩士學(xué)位論文 前3條
1 盧艷峰;數(shù)控機(jī)床滑枕懸伸變形誤差補(bǔ)償技術(shù)研究[D];大連理工大學(xué);2010年
2 陽江源;數(shù)控機(jī)床熱誤差檢測與建模研究[D];大連理工大學(xué);2010年
3 張冰冰;數(shù)控成形磨床移動(dòng)式立柱溫度特性分析及擬合方法研究[D];浙江大學(xué);2010年
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