Sparse Bayesian Learning Approach for Broken Rotor Bar Fault Diagnosis-Reference-Cited by-同舟云学术

Sparse Bayesian Learning Approach for Broken Rotor Bar Fault Diagnosis

Published:2023 Issue: Volume:72 Page:1-10
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Ma Ming¹^ORCID,Cao Zheng¹^ORCID,Fu Haijun¹^ORCID,Xu Weichao²^ORCID,Dai Jisheng¹^ORCID

Affiliation:

1. Department of Electronic Information Engineering, Jiangsu University, Zhenjiang, China

2. Department of Automatic Control, Guangdong University of Technology, Guangzhou, 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/ielx7/19/10012124/10214057.pdf?arnumber=10214057

Reference39 articles.

1. Fault detection and classification in kinematic chains by means of PCA extraction-reduction of features from thermographic images;osornio-rios;Measurement,2022

2. The variational approximation for Bayesian inference

3. Extraction of Frequency Information for the Reliable Screening of Rotor Electrical Faults Via Torque Monitoring in Induction Motors

4. FDD Massive MIMO Channel Estimation With Arbitrary 2D-Array Geometry

5. Fault detection of broken rotor bar in LS-PMSM using random forests

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