Abstract:
Signal processing using orthogonal cutting force
components for tool condition monitoring has established
itself in literature. In the application of single axis strain sensors
however a linear combination of cutting force components
has to be processed in order to monitor tool wear. This
situation may arise when a single axis piezoelectric actuator
is simultaneously used as an actuator and a sensor, e.g. its
vibration control feedback signal exploited for monitoring
purposes. The current paper therefore compares processing
of a linear combination of cutting force components to the
reference case of processing orthogonal components. Reconstruction
of the dynamic force acting at the tool tip from
signals obtained during measurements using a strain gauge
instrumented tool holder in a turning process is described. An
application of this dynamic force signal was simulated on a
filter-model of that tool holder thatwould carry a self-sensing
actuator. For comparison of the orthogonal and unidirectional
force component tool wear monitoring strategies the same
time-delay neural network structure has been applied.Wearsensitive
features are determined by wavelet packet analysis
to provide information for tool wear estimation. The probability
of a difference less than 5 percentage points between the
flank wear estimation errors of above mentioned two processing
strategies is at least 95 %. This suggests the viability of
simultaneous monitoring and control by using a self-sensing
actuator.
