%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