Single domain generalizable and physically interpretable bearing fault diagnosis for unseen working conditions-Reference-Cited by-同舟云学术

Single domain generalizable and physically interpretable bearing fault diagnosis for unseen working conditions

Author:

Kim Iljeok^ORCID,Wook Kim Sung,Kim Jeongsan,Huh Hyunsuk,Jeong Iljoo,Choi Taegyu,Kim Jeongchan,Lee Seungchul^ORCID

Funder

Institute of Civil Military Technology Cooperation

Ministry of Trade, Industry and Energy

Defense Acquisition Program Administration

Korea Institute of Energy Technology Evaluation and Planning

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference35 articles.

1. A New Interpretable Learning Method for Fault Diagnosis of Rolling Bearings;Zhang;IEEE Transactions on Instrumentation and Measurement,2020

2. Electric Locomotive Bearing Fault Diagnosis;Shao;IEEE Transactions on Industrial Electronics,2018

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