Remaining Useful Life Prediction Method Based on Multisensor Fusion Under Time-Varying Operating Conditions-Reference-Cited by-同舟云学术

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Remaining Useful Life Prediction Method Based on Multisensor Fusion Under Time-Varying Operating Conditions

Published:2024 Issue: Volume:73 Page:1-13
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Huang Xin¹^ORCID,Chen Wenwu¹^ORCID,Qu Dingrong¹^ORCID,Qu Shidong²^ORCID,Wen Guangrui³^ORCID

Affiliation:

1. SINOPEC Research Institute of Safety Engineering Co., Ltd., Qingdao, China

2. SINOPEC Tianjin Company, Tianjin, China

3. School of Mechanical Engineering, Xi’an Jiao-tong University, Xi’an, China

Funder

SINOPEC Ministry of Science and Technology Research Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/19/10367905/10474062.pdf?arnumber=10474062

Reference31 articles.

1. Memory Residual Regression Autoencoder for Bearing Fault Detection

2. Multisensor Feature Fusion for Bearing Fault Diagnosis Using Sparse Autoencoder and Deep Belief Network

3. Remaining useful life prediction based on a multi-sensor data fusion model

4. Data fusion techniques for fault diagnosis of industrial machines: A survey;Chaleshtori;Comput. Sci. Eng.,2022

5. A data-level fusion approach for degradation modeling and prognostic analysis under multiple failure modes

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