基于最大熵原理与鉴别信息的机床主轴系统退化分析

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振动与冲击 ›› 2013, Vol. 32 ›› Issue (5) : 62-64.

论文

基于最大熵原理与鉴别信息的机床主轴系统退化分析

董新峰，李郝林，余慧杰

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Degradation analysis of the spindle of machine tool based on maximum entropy and discrimination information

ONG Xin-feng，LI Hao-lin，YU Hui-jie

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摘要

采用最大熵原理与鉴别信息方法对M1432B型磨床工件主轴X2方向退化进行分析：用最大熵原理获得工件主轴在4～10月份振动信号最大熵概率密度分布，再用鉴别信息对该概率密度分布变化进行计算，通过鉴别信息变化判断主轴系统状态的变化，结果表明，M1432B型磨床工件主轴X2方向发生微小退化。

Abstract

spindle system is a common component of the machine tool. The state of the spindle system have serious implication on workpiece to be machined, So the detection of the spindle system is necessary. In this paper, the method of maximum entropy and discrimination information were applied for the degradation analysis of the X2 direction of the M1432 griding machine from April to October. First , we use the maximum entropy prinple to obtain accurate maximum entropy probability density distribution of the vibration, then, use the discrimination information to analyze the changes of maximum entropy probability density distribution that can judge the state of the spindle system of the machine tool. The results show that the X2 direction of the workpiece spindle of the M1432B grinding machine have tiny degradation.

导出引用

董新峰;李郝林;余慧杰 . 基于最大熵原理与鉴别信息的机床主轴系统退化分析[J]. 振动与冲击, 2013, 32(5): 62-64

ONG Xin-feng;LI Hao-lin;YU Hui-jie. Degradation analysis of the spindle of machine tool based on maximum entropy and discrimination information[J]. Journal of Vibration and Shock, 2013, 32(5): 62-64