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  4. A CUSUM-based adaptive bearing fault features tracking method for RUL estimation
 
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A CUSUM-based adaptive bearing fault features tracking method for RUL estimation

Journal
2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023
ISBN
9798350316445
Date Issued
2023-01-01
Author(s)
Yi, Chen Pei
Lin, Yi Jen
Ho, Ping Jui
Chung, Wei Der
Chou, Po Huan
SHIH-CHIN YANG  
DOI
10.1109/ECCE53617.2023.10362599
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/640180
URL
https://api.elsevier.com/content/abstract/scopus_id/85182928712
Abstract
This research is goal to develop a non-intrusive motor bearing fault prognostic method for remaining useful life (RUL) estimation. This technique can determine the incipient system fault in the early stage to prevent fatal failure. Considering the difficulty of requiring enough historical data for traditional prognostic methods, this research proposed a novel method with the concept of cumulative summation (CUSUM). It is utilized to select suitable fault characteristics among the sensor data to fuse a health indicator (HI) for RUL prediction. And to track the degradation trend of the HI under high noise, the recursive least square (RLS) method is introduced. Finally, 3 sets of electrical data from a motor with excessively-loaded bearings are used to verify the proposed method.
Subjects
cumulative summation | health indicator | PMSM | Prognostic | remaining useful life
Type
conference paper

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