%0 Journal Article
	%A V. G. Rajesh and  M. V. Rajesh
	%D 2008
	%J International Journal of Mechanical and Mechatronics Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 21, 2008
	%T Bearing Fault Feature Extraction by Recurrence Quantification Analysis
	%U https://publications.waset.org/pdf/14406
	%V 21
	%X In rotating machinery one of the critical components
that is prone to premature failure is the rolling bearing.
Consequently, early warning of an imminent bearing failure is much
critical to the safety and reliability of any high speed rotating
machines. This study is concerned with the application of Recurrence
Quantification Analysis (RQA) in fault detection of rolling element
bearings in rotating machinery. Based on the results from this study it
is reported that the RQA variable, percent determinism, is sensitive
to the type of fault investigated and therefore can provide useful
information on bearing damage in rolling element bearings.
	%P 1037 - 1041