Remaining Useful Life Prediction of Bearing with Vibration Signals Based on a Novel Indicator
Joint Authors
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-29
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Aiming at reducing the production downtime and maintenance cost, prognostics and health management (PHM) of rotating machinery often includes the remaining useful life (RUL) prediction of bearings.
In this paper, a method combining the generalized Weibull failure rate function (WFRF) and radial basis function (RBF) neural network is developed to deal with the RUL prediction of bearings.
A novel indicator, namely, the power value on the sensitive frequency band (SFB), is proposed to track bearing degradation process.
Generalized WFRF is used to fit the degradation indicator series to reduce the effect of noise and avoid areas of fluctuation in the time domain.
RBF neural network is employed to predict the RUL of bearings with times and fitted power values at present and previous inspections as input.
Meanwhile, the life percentage is selected as output.
The performance of the proposed method is validated by an accelerated bearing run-to-failure experiment, and the results demonstrate the advantage of this method in achieving more accurate RUL prediction.
American Psychological Association (APA)
Wu, Bo& Wei, Li& Qiu, Ming-quan. 2017. Remaining Useful Life Prediction of Bearing with Vibration Signals Based on a Novel Indicator. Shock and Vibration،Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1205138
Modern Language Association (MLA)
Wu, Bo…[et al.]. Remaining Useful Life Prediction of Bearing with Vibration Signals Based on a Novel Indicator. Shock and Vibration No. 2017 (2017), pp.1-10.
https://search.emarefa.net/detail/BIM-1205138
American Medical Association (AMA)
Wu, Bo& Wei, Li& Qiu, Ming-quan. Remaining Useful Life Prediction of Bearing with Vibration Signals Based on a Novel Indicator. Shock and Vibration. 2017. Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1205138
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1205138