Comprehensive Remaining Useful Life Prediction for Rolling Element Bearings Based on Time-Varying Particle Filtering-Reference-Cited by-同舟云学术

Comprehensive Remaining Useful Life Prediction for Rolling Element Bearings Based on Time-Varying Particle Filtering

Published:2022 Issue: Volume:71 Page:1-10
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Cui Lingli¹^ORCID,Li Wenjie¹^ORCID,Wang Xin¹^ORCID,Zhao Dezun¹^ORCID,Wang Huaqing²^ORCID

Affiliation:

1. Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing, China

2. College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/9717300/09744115.pdf?arnumber=9744115

Reference36 articles.

1. PRONOSTIA: An experimental platform for bearings accelerated degradation tests;nectoux;Proc IEEE Int Conf Prognostics Health Manage,2012

2. Anomaly Detection and Fault Prognosis for Bearings

3. The Sequential Importance Sampling Particle Filter with a Systematic Resampling in the State Estimation of Power Systems

4. comparison of resampling schemes for particle filtering;douc;ISPA 2005 the 4th International Symposium on Image and Signal Processing and Analysis 2005 ISPA-05,2005

5. Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics;qiu;J Sound Vibrat,2006

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