Khalifa, Othman Omran and Densibali , Amirasyid and Faris, Waleed Fekry
(2006)
Image processing for chatter identification in machining processes.
International Journal of Advanced Manufacturing Technology, 31.
pp. 443-449.
ISSN 1433-3015 (O); 0268-3768 (P)
Abstract
Identifying chatter or intensive self-excited relative
tool–workpiece vibration is one of the main challenges
in the realization of automatic machining processes. Chatter
is undesirable because it causes poor surface finish and
machining accuracy, as well as reducing tool life. The
identification of chatter is performed by evaluating the
surface roughness of a turned workpiece undergoing chatter
and chatter-free processes. In this paper, an image-processing
approach for the identification of chatter vibration in
a turning process was investigated. Chatter is identified by
first establishing the correlation between the surface
roughness and the level of vibration or chatter in the
turning process. Images from chatter-free and chatter-rich
turning processes are analyzed. Several quantification
parameters are utilized to differentiate between chatter
and chatter-free processes. The arithmetic average of gray
level Ga is computed. Intensity histograms are constructed
and then the variance, mean, and optical roughness
parameter of the intensity distributions are calculated.
The surface texture analysis is carried out on the images
using a second-order histogram or co-occurrence matrix of
the images. Analysis is performed to investigate the ability
of each technique to differentiate between a chatter-rich
and a chatter-free process. Finally, a machine vision system
is proposed to identify the presence of chatter vibration in a
turning process.
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