Anomaly Detection Based on Data Super-Resolution in Industrial Cyber–Physical Systems With Multirate Sampling-Reference-Cited by-同舟云学术

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Anomaly Detection Based on Data Super-Resolution in Industrial Cyber–Physical Systems With Multirate Sampling

Published:2024-05-15 Issue:10 Volume:24 Page:16478-16490
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Du Xin¹^ORCID,Zhou Chunjie¹^ORCID,Tian Yu-Chu²^ORCID,Wang Kunkun³

Affiliation:

1. Key Laboratory of Ministry of Education for Image Processing and Intelligent Control, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China

2. School of Computer Science, Queensland University of Technology, Brisbane, QLD, Australia

3. Key Laboratory of Ministry of Education for Image Processing and Intelligent Control, School of Cyber Science and Engineering, Huazhong University of Science and Technology, Wuhan, China

Funder

National Natural Science Foundation of China

Australian Research Council (ARC) through the Discovery Project Scheme

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7361/10530892/10494703.pdf?arnumber=10494703

Reference46 articles.

1. A Unified Architectural Approach for Cyberattack-Resilient Industrial Control Systems

2. Multirate Factor Analysis Models for Fault Detection in Multirate Processes

3. Data-driven soft sensor development based on deep learning technique

4. Multiple probability principal component analysis for process monitoring with multi-rate measurements

5. Kernel Generalization of Multi-Rate Probabilistic Principal Component Analysis for Fault Detection in Nonlinear Process

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