Chatter is one of the critical factors that hinder machining quality in machining processes. To identify and evaluate chatter online, the acceleration is used to obtain the vibration signal of spindle. And by using the energy entropy of wavelet packet decomposition, the vibration signal is decomposed to judge the stability of milling and distinguish the vibration states. The stability of milling can be determined by the multi-sensor. Understanding the difference of signal in different conditions and analyzing the vibration forms the spectrum analysis is the second step. Then decomposition of the vibration signal with wavelet packet presents a significant law in the energy distribution of signal in different vibration forms. Several milling tests are conducted and shows that the milling state changing from stability to instability is same to the changing energy intensity between forced vibration and chatter. The energy entropy can describe the different distribution of energy well, which is a good way to identify the milling state and the vibration states.
ZHANG Zhi
,
LIU Chengying
,
LIU Xinjun
,
ZHANG Jie
. Analysis of Milling Vibration State Based on the Energy Entropy of WPD[J]. Journal of Mechanical Engineering, 2018
, 54(21)
: 57
-62
.
DOI: 10.3901/JME.2018.21.057
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