Time-frequency Analysis for Validating Prognostics Algorithms of Rolling Element Bearings-Reference-Cited by-同舟云学术

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Time-frequency Analysis for Validating Prognostics Algorithms of Rolling Element Bearings

Published:2024-02-04 Issue: Volume: Page:327-331
ISSN:
Container-title:2024 26th International Conference on Advanced Communications Technology (ICACT)
language:
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Author:

Zhu Guanhua¹,Xu Xiaoling²,Zhong Qing²,Lu Bing-Yuh²,Lu Yushen²,Xu Guangming²,Zhou Yumeng²,Jiang Ziyi²,Sun Kai²,Wang Minhao²

Affiliation:

1. Guangdong University of Petrochemical Technology,Guangdong Provincial Key Lab. of Petrochemical Equipment and Fault Diagnosis,Maoming City,Guangdong,China

2. Guangdong University of Petrochemical Technology,Faculty of Automation,Maoming City,Guangdong,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10471761/10471762/10471976.pdf?arnumber=10471976

Reference17 articles.

1. Machinery health prognostics: A systematic review from data acquisition to RUL prediction

2. A hybrid deep-learning model for fault diagnosis of rolling bearings

3. Remaining useful life prediction of roller bearings based on improved 1D-CNN and simple recurrent unit

4. Signal-to-Signal Translation for Fault Diagnosis of Bearings and Gears With Few Fault Samples

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