【摘要】：隨著“中國制造2025”計劃的提出,我國開始實施制造強國三步走戰(zhàn)略。而數(shù)控機床作為工業(yè)母機,在制造業(yè)中占有重要的地位,因此提高數(shù)控機床精度是非常有意義的。提高數(shù)控機床精度方法之一就是對數(shù)控機床誤差進行建模分析和補償,這篇論文主要圍繞著數(shù)控機床的誤差測量和建模分析來寫。在數(shù)控機床各種誤差源中,熱誤差是數(shù)控機床等精密加工機械的最大誤差源之一。根據(jù)國內(nèi)外研究者的研究內(nèi)容,本文搭建了數(shù)控機床主軸熱誤差研究平臺,主要從熱誤差測量、溫度敏感點選擇、建模和模型對比驗證分析四個方面展開敘述,具體如下:(1)首先搭建數(shù)控機床熱誤差測量平臺,然后通過模糊聚類分析和灰色關聯(lián)分析對數(shù)控機床熱誤差測溫點進行優(yōu)化選擇,確保數(shù)據(jù)的有效性和準確性,為接下來的建模收集和分析數(shù)據(jù)。(2)基于卡爾曼濾波-灰色模型理論(Kalman Filter-GM)建模,能夠有效地減少噪聲對觀測值的影響,這樣就可以得到觀測值比較好的估計,從而確�；贙alman Filter-GM的數(shù)控機床熱誤差的有效建模;在建立模型過程中,相比傳統(tǒng)的最小二乘法估計參數(shù),這種方法更加穩(wěn)健,因此這種模型相對于傳統(tǒng)的建模來說較好;(3)文中的殘差修正模型是通過模擬值與建模數(shù)據(jù)建立的,這種方法可以讓預測效果更好;基于卡爾曼濾波方法通過迭代變形數(shù)據(jù)分別構建了幾個灰色模型,然后通過數(shù)據(jù)融合的方法把這幾個灰色模型的數(shù)據(jù)進行融合,最終得到了預測數(shù)據(jù)的最佳估計值。(4)基于Kalman Filter-GM所建立的數(shù)控機床熱誤差模型,與傳統(tǒng)的建模方法最小二乘法和最小二乘法支持向量機的數(shù)控機床熱誤差建模方法進行數(shù)據(jù)對比分析,最終得出結論,此種建模方法更好。
[Abstract]:With the proposal of "made in China 2025", China began to implement the three-step strategy of manufacturing power. As an industrial master machine, numerical control machine occupies an important position in the manufacturing industry, so it is very meaningful to improve the precision of numerical control machine tool. One of the methods to improve the accuracy of NC machine tool is to analyze and compensate the error of NC machine tool. This paper is mainly written around the error measurement and modeling analysis of NC machine tool. Among all kinds of error sources, thermal error is one of the biggest error sources of CNC machine tools and other precision machining machines. According to the research content of researchers at home and abroad, this paper builds the research platform of the spindle thermal error of NC machine tool, mainly from four aspects: the measurement of thermal error, the selection of temperature sensitive points, the modeling and the analysis of model comparison and verification. The details are as follows: (1) first, the thermal error measurement platform of NC machine tools is built, and then the temperature measurement points of thermal error are optimized by fuzzy clustering analysis and grey correlation analysis to ensure the validity and accuracy of the data. Collecting and analyzing data for the following modeling. (2) based on Kalman filter-grey model theory (Kalman Filter-GM) modeling, it can effectively reduce the effect of noise on the observed value, so we can get a better estimate of the observed value. In order to ensure the effective modeling of numerical control machine tool thermal error based on Kalman Filter-GM, this method is more robust than the traditional least square method in the process of modeling. Therefore, this model is better than the traditional modeling. (3) the residual correction model in this paper is based on the simulation value and the modeling data, this method can make the prediction effect better; Based on Kalman filtering method, several grey models are constructed by iterative deformation data, and then the data of these grey models are fused by data fusion method. Finally, the best estimate of the predicted data is obtained. (4) the thermal error model of NC machine tool based on Kalman Filter-GM. Compared with the traditional modeling methods, the least square method and the least square support vector machine, the numerical control machine tool thermal error modeling method is compared and analyzed. Finally, it is concluded that this modeling method is better.
【學位授予單位】：蘭州理工大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TG659

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