【摘要】：作為衡量國(guó)家制造業(yè)和綜合國(guó)力水平的標(biāo)志,高檔數(shù)控機(jī)床在現(xiàn)代工業(yè)中的地位日益加重。在機(jī)床多種誤差源中,熱誤差在機(jī)床總誤差重的比重可達(dá)到40%~70%,因此,控制并削弱熱誤差對(duì)提高精密機(jī)床的精度非常重要。國(guó)內(nèi)外研究表明,熱誤差補(bǔ)償技術(shù)重點(diǎn)圍繞著溫度敏感點(diǎn)選擇、熱誤差建模和補(bǔ)償?shù)热齻�(gè)方面給予研究。雖然目前已有比較完善的理論體系和補(bǔ)償實(shí)施技術(shù),但仍然存在一些影響其廣泛應(yīng)用、且亟需解決的關(guān)鍵性問題,如溫度測(cè)點(diǎn)優(yōu)化過程中溫度變量之間的共線性影響以及模型預(yù)測(cè)穩(wěn)健性不足等。針對(duì)上述熱誤差補(bǔ)償技術(shù)的缺陷,本文從溫度敏感點(diǎn)選擇、熱誤差建模和補(bǔ)償?shù)确矫嫣岢隽讼嚓P(guān)理論和方法,并進(jìn)行了大量實(shí)驗(yàn)數(shù)據(jù)分析,最后以實(shí)際機(jī)床為例進(jìn)行了熱誤差補(bǔ)償實(shí)驗(yàn)驗(yàn)證。論文主要的研究?jī)?nèi)容如下:1)提出了一種數(shù)控機(jī)床穩(wěn)健性熱誤差建模方法,將以灰色關(guān)聯(lián)度為核心的溫度敏感點(diǎn)優(yōu)化方法和以主成分回歸分析為核心的建模算法配合使用,共同對(duì)溫度敏感點(diǎn)優(yōu)化所需遵循的大權(quán)重、低耦合和少布點(diǎn)策略進(jìn)行處理,既簡(jiǎn)化了測(cè)點(diǎn)優(yōu)化的復(fù)雜度,又有效地提升了模型的預(yù)測(cè)精度和穩(wěn)健性。2)采用傳統(tǒng)的模糊聚類結(jié)合灰色關(guān)聯(lián)度的溫度敏感點(diǎn)優(yōu)化算法,對(duì)全年分季度的機(jī)床熱誤差數(shù)據(jù)給予了研究,闡述了該方法選擇出的溫度敏感點(diǎn)存在變動(dòng)性特征及其對(duì)模型精度影響。3)研究了多元線性回歸算法、時(shí)間序列分布滯后和主成分回歸算法的模型精度和穩(wěn)健性特征,并總結(jié)得到三種模型在熱誤差建模補(bǔ)償中的適用范圍。另外,提出了基于主成分回歸分析的分布滯后模型精度提升方法。4)介紹了熱誤差補(bǔ)償技術(shù)的軟件實(shí)施方法,包括數(shù)控平臺(tái)、熱誤差測(cè)量集成系統(tǒng)、最佳溫度敏感點(diǎn)的優(yōu)化選擇、熱誤差數(shù)學(xué)模型建立、熱誤差補(bǔ)償與精度評(píng)定。評(píng)定結(jié)果表明補(bǔ)償效果顯著。
[Abstract]:As a symbol of national manufacturing industry and comprehensive national strength, the status of high-grade CNC machine tools in modern industry is getting more and more serious. Among the various error sources of machine tool, the proportion of thermal error in the total error weight of machine tool can reach 400.Therefore, it is very important to control and weaken the thermal error to improve the precision of precision machine tool. Studies at home and abroad show that the thermal error compensation technology focuses on three aspects: temperature sensitive point selection, thermal error modeling and compensation. Although there is a relatively sound theoretical system and compensation implementation techniques, there are still some key problems that affect their wide application and are in urgent need of solution, For example, the collinearity effect between temperature variables and the lack of robustness of the model in the optimization of temperature measurement points. In view of the defects of the above thermal error compensation technology, this paper puts forward some related theories and methods from the aspects of temperature sensitive point selection, thermal error modeling and compensation, and carries out a lot of experimental data analysis. Finally, the experimental verification of thermal error compensation is carried out with the actual machine tool as an example. The main contents of this paper are as follows: 1) A robust thermal error modeling method for NC machine tools is proposed. The temperature sensitive point optimization method with grey correlation degree as the core and the modeling algorithm with principal component regression analysis as the core are used together. In order to simplify the complexity of the optimization of temperature sensitive points, the strategy of large weight, low coupling and less point placement is used in the optimization of temperature sensitive points. Moreover, the prediction accuracy and robustness of the model are improved effectively. 2) the thermal error data of machine tools are studied by using the traditional temperature sensitive point optimization algorithm based on fuzzy clustering and grey correlation degree. The variability of temperature sensitive points selected by this method and its influence on model accuracy are described. 3) the model accuracy and robustness of multivariate linear regression algorithm, time series distribution lag and principal component regression algorithm are studied. The application range of three models in thermal error modeling compensation is summarized. In addition, a method of improving the accuracy of distributed lag model based on principal component regression analysis is proposed. 4) the software implementation method of thermal error compensation technology is introduced, including numerical control platform, integrated thermal error measurement system, Optimal selection of optimal temperature sensitive points, mathematical model of thermal error, thermal error compensation and accuracy evaluation. The evaluation results show that the compensation effect is remarkable.
【學(xué)位授予單位】：合肥工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TG659

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