A Novel Method for Remaining Useful Life Prediction of Bearing Based on Spectrum Image Similarity Measures

Accurately predicting the remaining useful life (RUL) of bearing by analyzing vibration signals is challenging and meaningful. To address this issue, a novel method based on spectrum image similarity is proposed in this paper. First, spectrum images for the whole lifecycle data of reference bearings...

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Bibliographic Details
Main Authors: Jiang, F. (Author), Li, W. (Author), Wu, B. (Author), Zhang, B. (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
Online Access:View Fulltext in Publisher
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001 10.3390-math10132209
008 220718s2022 CNT 000 0 und d
020 |a 22277390 (ISSN) 
245 1 0 |a A Novel Method for Remaining Useful Life Prediction of Bearing Based on Spectrum Image Similarity Measures 
260 0 |b MDPI  |c 2022 
856 |z View Fulltext in Publisher  |u https://doi.org/10.3390/math10132209 
520 3 |a Accurately predicting the remaining useful life (RUL) of bearing by analyzing vibration signals is challenging and meaningful. To address this issue, a novel method based on spectrum image similarity is proposed in this paper. First, spectrum images for the whole lifecycle data of reference bearings are obtained by performing fast Fourier transformation (FFT). Second, the similarity is calculated between the current monitored data of operating bearing and run-to-failure images of reference bearings. Then, the weights of reference bearings are derived based on the similarity measures. Finally, the RUL of the operating bearing is estimated with the weighted average of the RULs of referenced bearings. The proposed method is demonstrated based on 2012 PHM Data Challenge Competition data, which shows its effectiveness and practicality. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. 
650 0 4 |a RUL prediction 
650 0 4 |a similarity 
650 0 4 |a spectrum image 
650 0 4 |a weight 
700 1 |a Jiang, F.  |e author 
700 1 |a Li, W.  |e author 
700 1 |a Wu, B.  |e author 
700 1 |a Zhang, B.  |e author 
773 |t Mathematics