In this paper, a complete framework is proposed to realize on-line monitoring of surface quality based on
machining mechanism and multi-sensor fusion. Off-line experiments and on-line modeling are integrated
together to obtain the effective features to characterize the relation between the surface quality and sensor
information. Vibration, force and acoustic emission signal are selected and different sensors are mounted
to obtain enough information from the machining process. In addition, parametric and non parametric
methods are used to extract the features which are sensitive to surface quality and insensitive to the
cutting parameters. After the features are selected, methods based on hybrid intelligence are presented to
build the relationship between the surface quality and the corresponding features. The establishment of
the whole framework provides an effective means to realize the online monitoring of surface quality
during the milling process.
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