本文選題：光纖光柵傳感 + 重型機床立柱�。� 參考：《武漢理工大學》2015年碩士論文

【摘要】：重型數(shù)控機床在加工制造業(yè)中扮演著相當重要的角色,提高其加工精度一直是備受關注的重要研究課題。研究表明,熱誤差占機床總誤差的45%左右,同時精度要求越高,其所占比重越大。為了能減少或后期抵消熱誤差,目前對熱誤差的研究主要集中在機床溫度場分析、溫度變化與熱變形建模等方面。由于機床是個復雜的物理結構,并且存在外界環(huán)境的不可控干擾,溫度場難以重構,而所建模型的精確性、魯棒性和運算效率也影響著熱誤差補償裝置的效果。機床熱誤差是機床各部件在熱源影響下產生形變的共同作用效果,而熱變形建模是熱誤差補償技術的基礎,通過所建模型可以根據(jù)實時溫度變化預測并補償形變量而實現(xiàn)熱誤差的減少。從物理結構上看,立柱的彎曲會引起橫梁前傾,從而導致加工主軸發(fā)生熱漂移。本文以機床的大型構件—立柱為研究對象,圍繞其與機床熱變形之間的關系開展了如下工作:(1)對機床的熱源分布進行分析,運用光纖光柵溫度傳感器針對立柱的溫度場進行了初步測量,同時運用CCD激光位移傳感器同步采集主軸熱漂移(機床Y方向熱變形),并對立柱溫度變化與熱變形數(shù)據(jù)之間的相關性進行分析。(2)并非所有溫度測點與熱變形之間有明顯關系,因此運用模糊聚類方法對溫度測量點進行分組,然后以不同的側重點,分別采用偏相關分析、最大靈敏度和灰關聯(lián)分析方法從分組中篩選出關鍵溫度測量點,并基于篩選結果存在交叉性,提出一種更為平衡的綜合測點優(yōu)化策略。(3)基于所得到的關鍵溫度測量點分別運用多元線性回歸模型、BP神經網絡模型和基于遺傳算法改進的BP網絡模型建立其與機床熱變形的關系模型,并對模型進行評估得到最佳的預測模型。同時根據(jù)評估結果也驗證了不同測點優(yōu)化策略的優(yōu)劣,進而提出測點優(yōu)化和建模方法改進的建議。(4)為了更方便和深入的研究立柱形變對機床熱誤差的影響機理,基于光纖光柵的應變量測量,推導了柱形結構應變量與自身形變狀態(tài)之間的關系。同時設計了柱形結構二維形變實時監(jiān)測模型和實現(xiàn)方案,運用該模型能夠在線監(jiān)測機床柱形結構的彎曲變化特點,對后續(xù)熱誤差補償?shù)难芯可踔潦侵谓Y構的設計都有重要參考意義。
[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.
【學位授予單位】：武漢理工大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TG659

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