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Abstract:
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In this thesis, the applications of the recurrence quantification analysis in metal cutting
operation in a lathe, with specific objective to detect tool wear and chatter, are
presented.This study is based on the discovery that process dynamics in a lathe is low dimensional
chaotic. It implies that the machine dynamics is controllable using principles of chaos
theory. This understanding is to revolutionize the feature extraction methodologies
used in condition monitoring systems as conventional linear methods or models are
incapable of capturing the critical and strange behaviors associated with the metal
cutting process.As sensor based approaches provide an automated and cost effective way to monitor
and control, an efficient feature extraction methodology based on nonlinear time series
analysis is much more demanding. The task here is more complex when the information
has to be deduced solely from sensor signals since traditional methods do not address
the issue of how to treat noise present in real-world processes and its non-stationarity.
In an effort to get over these two issues to the maximum possible, this thesis adopts the
recurrence quantification analysis methodology in the study since this feature extraction
technique is found to be robust against noise and stationarity in the signals.The work consists of two different sets of experiments in a lathe; set-I and set-2. The
experiment, set-I, study the influence of tool wear on the RQA variables whereas the set-2 is carried out to identify the sensitive RQA variables to machine tool chatter
followed by its validation in actual cutting. To obtain the bounds of the spectrum of the
significant RQA variable values, in set-i, a fresh tool and a worn tool are used for
cutting. The first part of the set-2 experiments uses a stepped shaft in order to create
chatter at a known location. And the second part uses a conical section having a uniform
taper along the axis for creating chatter to onset at some distance from the smaller end
by gradually increasing the depth of cut while keeping the spindle speed and feed rate
constant.The study concludes by revealing the dependence of certain RQA variables; percent
determinism, percent recurrence and entropy, to tool wear and chatter unambiguously.
The performances of the results establish this methodology to be viable for detection of
tool wear and chatter in metal cutting operation in a lathe. The key reason is that the
dynamics of the system under study have been nonlinear and the recurrence
quantification analysis can characterize them adequately.This work establishes that principles and practice of machining can be considerably
benefited and advanced from using nonlinear dynamics and chaos theory. |