摘要
刀具磨损状态与刀具的振动信号密切相关。本文介绍了数据采集平台和实验过程,利用db5离散小波方法分析铣削振动信号。结果表明:第三、四层细节信号的标准差随切削过程变化不明显,而第一、二层细节信号的标准差随着刀具磨损的加剧而增大,因此,可以将其作为特征参数用于铣削过程监控。
Cutting tool wear has close relation with the vibration signals.This paper introduces the data acquisition platform and experimental process,using the db5 discrete wavelets to analyse the milling vibration signal.It is proved that the standard deviations of the third and forth detail level signals have no various change.On the other hand,the standard deviation of the first and second detail level signals increases with the wear increase.So they can be used as characteristic parameters in the milling process monitoring.
出处
《南昌航空大学学报(自然科学版)》
CAS
2011年第3期42-47,共6页
Journal of Nanchang Hangkong University(Natural Sciences)
基金
江西省科技支撑计划项目(CB200903362)
关键词
小波变换
振动信号
刀具磨损
铣削
wavelet transform
vibration signals
tool wear
milling