【摘要】：機床主軸是現代機械加工中的核心部件,主軸精度決定了工件的加工精度,因此,對主軸的研究就顯得尤為重要。主軸空間振動最直接表現是圓度誤差與回轉誤差,通過對以上兩種誤差的研究便能清晰把握一個機床主軸的運動狀態(tài)。論文選擇了三點法誤差分離技術為理論基礎進行研究,圍繞提高圓度誤差與回轉誤差分離精度展開論述。首先,本文對比分析了目前比較常見的誤差分離方法,并最終選擇了具有一定研究價值的三點法誤差分離技術展開討論。闡述了該分離方法的基本原理,分析發(fā)現權函數在三點法誤差分離技術中具有重要意義,當權函數選擇不合理時,可能導致諧波抑制現象的發(fā)生,從而產生錯誤的誤差分離結果。其次,從數學分析的角度對權函數的特性進行了研究。圍繞權函數,提出了改善誤差分離精度的兩個標準—全局性、局部性。依據以上兩個標準,運用極大熵函數方將不可微優(yōu)化目標函數轉化為連續(xù)可微的優(yōu)化函數。結合粒子群優(yōu)化算法,優(yōu)化得到了可預防諧波抑制現象發(fā)生的全局傳感器安裝角度。仿真效果表明:全局最優(yōu)值很大程度上提高了誤差分離精度。最后,針對現實情況下傳感器噪聲信號對誤差分離效果影響這一問題,本文進一步提出了一套抑制傳感器噪聲信號的優(yōu)化方法。該方法不再圍繞權函數展開研究,而是將三點法誤差分離技術中的權系數與權函數當作統(tǒng)一整體進行分析,確立了新的優(yōu)化目標函數。再次結合粒子群優(yōu)化算法,優(yōu)化得到了噪聲抑制下的傳感器安裝角度。理論分析與仿真結果表明,該角度下的誤差分離精度仍能保持較高水平,并且該角度組合對傳感器噪聲信號具有良好的抑制效果�？紤]到由于傳感器安裝角度偏差可能帶來的誤差分離精度下降和諧波抑制現象發(fā)生等問題,本文提出了克服此類缺點的方法,即區(qū)間優(yōu)化。通過該方法的運用,有效解決了傳感器安裝過程中由于安裝偏差所帶來的誤差分離精度下降問題。綜上所述,本文圍繞提高三點法誤差分離精度展開深入研究。針對不同問題,優(yōu)化得到了傳感器安裝角度全局最優(yōu)值、噪聲抑制最優(yōu)值、區(qū)間最優(yōu)值。最終,通過仿真分析和實驗測試充分證明了理論研究的可靠性和優(yōu)化結果的正確性。
[Abstract]:The spindle of machine tool is the core part in modern machining. The precision of spindle determines the machining accuracy of workpiece. Therefore, the research of spindle is particularly important. The most direct manifestation of spatial vibration of spindle is roundness error and rotation error. The motion state of a machine tool spindle can be clearly grasped by studying the above two kinds of errors. In this paper, the three-point error separation technique is chosen as the theoretical basis, and the improvement of the accuracy of roundness error and rotation error separation is discussed. Firstly, the common error separation methods are compared and discussed in this paper. Finally, the three-point error separation method with certain research value is chosen to discuss. The basic principle of the separation method is expounded. It is found that the weight function is of great significance in the three-point error separation technique. When the weight function is not reasonable, it may lead to the occurrence of harmonic suppression. This results in erroneous error separation results. Secondly, the characteristics of weight function are studied from the angle of mathematical analysis. Around the weight function, two criteria to improve the accuracy of error separation are proposed, namely, global and local. According to the above two criteria, the objective function of nondifferentiable optimization is transformed into a continuous differentiable optimization function by using the maximum entropy function. Combined with particle swarm optimization algorithm, the global sensor installation angle which can prevent harmonic suppression is obtained. Simulation results show that the global optimal value greatly improves the accuracy of error separation. Finally, in order to solve the problem that the sensor noise signal affects the error separation effect, a set of optimization methods to suppress the sensor noise signal is proposed in this paper. Instead of focusing on the weight function, the method analyzes the weight coefficient and the weight function in the three-point error separation technique as a unified whole, and establishes a new optimization objective function. Finally, the sensor installation angle under noise suppression is obtained by combining particle swarm optimization algorithm. Theoretical analysis and simulation results show that the accuracy of error separation at this angle is still high, and the combination of the angle has a good suppression effect on the sensor noise signal. Considering the problem that the error separation accuracy and harmonic suppression may be decreased due to the angle deviation of sensor installation, this paper proposes a method to overcome this kind of shortcoming, namely interval optimization. Through the application of this method, the problem of the error separation accuracy decline caused by the installation deviation during the installation of the sensor is effectively solved. To sum up, this paper focuses on improving the accuracy of three-point error separation. According to different problems, the global optimal value of sensor installation angle, the optimal value of noise suppression and the optimal value of interval are obtained. Finally, the reliability of the theoretical research and the correctness of the optimization results are fully proved by simulation analysis and experimental tests.
【學位授予單位】：西安電子科技大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TG502.3

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本文編號：2331861