Mechanical Fault Diagnosis With Noisy Multisource Signals via Unified Pinball Loss Intuitionistic Fuzzy Support Tensor Machine-Reference-Cited by-同舟云学术

Mechanical Fault Diagnosis With Noisy Multisource Signals via Unified Pinball Loss Intuitionistic Fuzzy Support Tensor Machine

Published:2024-01 Issue:1 Volume:20 Page:62-72
ISSN:1551-3203
Container-title:IEEE Transactions on Industrial Informatics
language:
Short-container-title:IEEE Trans. Ind. Inf.

Author:

Zhang Yifang¹,Han Bing²,Han Min³^ORCID

Affiliation:

1. Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China

2. National Engineering Research Center of Ship and Shipping Control System, Shanghai Ship and Shipping Research Institute Co., Ltd., Shanghai, China

3. Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education, Dalian University of Technology, Dalian, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Fujian Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/9424/10355676/10070126.pdf?arnumber=10070126

Reference29 articles.

1. Network-Based Fault Detection Filter and Controller Coordinated Design for Unmanned Surface Vehicles in Network Environments

2. Data-Driven Fault Diagnosis for Traction Systems in High-Speed Trains: A Survey, Challenges, and Perspectives

3. Fault-Tolerant Master–Slave Synchronization for Lur'e Systems Using Time-Delay Feedback Control

4. Parity Space-Based Fault Estimation for Linear Discrete Time-Varying Systems

5. Intelligent Fault Detection for Rotating Machinery Using Cyclic Morphological Modulation Spectrum and Hierarchical Teager Permutation Entropy

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