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WANG Shih-Ming
LUO Ming-Je
LIN Sheng-Yu
LIAO Hung-Wei
Department of Mechanical Engineering,
R&D Center for Membrane Technology,
Chung Yuan Christian University, Chung-Li 32023, Taiwan, China
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APPLICATION OF WAVELET
TRANSFORM ON DIAGNOSIS AND
PREDICTION OF MILLING CHATTER*
Abstract: In order to avoid the
accuracy deterioration or tool damage caused by milling chatter,
it is necessary to have an efficient and reliable diagnosis
system that can on-line predict/detect the occurrence of
chatter. The diagnosis/predicting system proposed is to on-line
process and analysis the vibration signals of the milling
machine measured by accelerometers. According to the analysis
results, the system will be able to detect/predict the
occurrence of the chatter. The diagnosis algorithm is, first,
collecting both the normal signals and chatter signals from
milling processes, and then, converting the signals through
wavelet transform and fast Fourier transform (FFT). Since the
converted chatter signals exhibit different characteristics
from the normal signals, through defining the characteristic
values, such as root-mean-square value, max value, and ratio of
peak value to root-mean-square value, etc, a diagnosis reference
library that contains the distribution of these characteristic
values is built for diagnosis. When a diagnosis is executing,
the characteristic value of the measured signals is contrasted
with the diagnosis reference. The approach index which shows the
possibility of occurrence of milling chatter will, then, be
calculated through the diagnosis system. Cutting experiments are
con-ducted to verify the proposed diagnosis system. The results
show the success of early chatter detecting for the system.
Key words:
Chatter On-line diagnosis Prediction Wavelet transform |