Fault Diagnosis of Rolling Bearing Based on Knowledge Graph With Data Accumulation Strategy-Reference-Cited by-同舟云学术

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Fault Diagnosis of Rolling Bearing Based on Knowledge Graph With Data Accumulation Strategy

Published:2022-10-01 Issue:19 Volume:22 Page:18831-18840
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Xiao Xiangqu¹,Li Chaoshun¹^ORCID,Huang Jie¹,Yu Tian¹

Affiliation:

1. School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan, China

Funder

National Natural Science Foundation of China

Applied Fundamental Frontier Project of Wuhan Science and Technology Bureau

Hubei Provincial Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/9906561/09872316.pdf?arnumber=9872316

Reference37 articles.

1. A New Interpretable Learning Method for Fault Diagnosis of Rolling Bearings

2. Fault diagnosis of rotating machinery based on multiple ANFIS combination with GAs

3. Improved weighted random forest for classification problems;shahhosseini;Proc Int Online Conf Intell Decis Sci,2020

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4. Multi-domain fusion for cargo UAV fault diagnosis knowledge graph construction;Autonomous Intelligent Systems;2024-06-21

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