摘要
采用关联维数定量刻画铣削过程中的不同工作状态的振动特征,估计出已加工表面的粗糙度。在计算关联维数中,对选择嵌入维数和延迟时间提出了一种改进的G-P算法,求解出在不同主轴转速、不同进给速度、不同切削深度的切削用量下铣削振动信号的关联维数。研究表明:在不同切削状态下,工件的振动信号的关联维数不同;且随着工件振动信号关联维数的增加,加工表面粗糙度也随之增加。因此,关联维数可以作为识别已加工表面粗糙度的特征量。
The correlation dimension is applied to describe the vibration characteristics of the milling in the different machining condition and predict roughness of the milled surface. An improved G-P algorithm is introduced for the correlation dimension estimation,which can detemine the embedding dimensionand delay time. The vibration signals of NC milling machine under different working conditions are analyzed by using the improved G-P method.The results demonstrate that the correlation dimension of vibration signal of the milling is different for the different state of working, such as spindle speed,feeding rate ,milling depth and the machined surface roughness increases as correlation dimension rises. So it can be used as the characteristics for recognizing the finished surface＇s roughness.
出处
《机械设计与制造》
北大核心
2009年第10期181-183,共3页
Machinery Design & Manufacture
基金
福建省重点高新技术项目(2005H035)
自然科学基金计划资助项目(A0610020)
关键词
关联维数
表面粗糙度
铣削
振动信号
Correlation dimension
SUrface roughness
Milling
Vibration signals
