A New Enhanced Feature Extraction Strategy for Bearing Remaining Useful Life Estimation
| Affiliation auteurs | !!!! Error affiliation !!!! |
| Titre | A New Enhanced Feature Extraction Strategy for Bearing Remaining Useful Life Estimation |
| Type de publication | Conference Paper |
| Year of Publication | 2014 |
| Auteurs | Ben Ali J, Saidi L, Chebel-Morello B, Fnaiech F |
| Conference Name | 201415TH INTERNATIONAL CONFERENCE ON SCIENCES & TECHNIQUES OF AUTOMATIC CONTROL & COMPUTER ENGINEERING (STA'2014) |
| Publisher | IEEE; IEEE Tunisia Sect; Assoc Tunisienne Tech Numeriques & Automatique; Univ Sfax, Nat Engn Sch Sfax, Lab Sci & Tech Automat Control & Comp Engn |
| Conference Location | 345 E 47TH ST, NEW YORK, NY 10017 USA |
| ISBN Number | 978-1-4799-5907-5 |
| Mots-clés | Bearing, feature extraction, Prognostics and Health Management (PHM), Remaining Useful Life (RUL) |
| Résumé | Accurate Remaining Useful Life (RUL) prediction of critical assets is an important challenge in condition based maintenance to improve reliability and to decrease machine's breakdown and maintenance's cost. Bearing is one of the most important components in industries that need to be monitored and the user should predict its RUL. The challenge of this study is to propose a new strategy for RUL feature extraction. The proposed methodology provides better features in term of monotonicity. This specification ensures a better RUL prediction by comparing the test degradation features to the library of instance. Experimental results show that the proposed methodology is very promising for RUL estimation by industry. |