Model-based fault diagnosis methods for systems with stochastic process

Model-based fault diagnosis methods for systems with stochastic process – A survey

Published:2022-11 Issue: Volume:513 Page:137-152
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Zhao Zhen,Liu Peter Xiaoping,Gao Jinfeng

Funder

National Natural Science Foundation of China

Zhejiang Sci-Tech University

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference158 articles.

1. Robust fault detection for networked systems with communication delay and data missing;He;Automatica,2009

2. Robust detection of intermittent sensor faults in stochastic LTV systems;Zhang;Neurocomputing,2020

3. Event-triggered fault detection observer design for affine fuzzy systems;Liu;Neurocomputing,2017

4. Remarks on terminology in the field of supervision, fault detection and diagnosis;Schrick;Proceeding of the IFAC Fault Detection, Supervision and Safety for Technical Processes, Kingston Upon Hull, UK,1997

5. A survey and classification of incipient fault diagnosis approaches;Safaeipour;J. Process Control,2021

Cited by 28 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An exhaustive review of battery faults and diagnostic techniques for real-world electric vehicle safety;Journal of Energy Storage;2024-10

2. Adaptive Fast Desensitized Kalman Filter;Circuits, Systems, and Signal Processing;2024-08-01

3. Advancing Wine Fermentation: Extended Kalman Filter for Early Fault Detection;2024-05-24

4. A fault diagnosis method for flexible converter valve equipment based on DSC-BIGRU-MA;Frontiers in Energy Research;2024-04-12

5. Attention on the key modes: Machinery fault diagnosis transformers through variational mode decomposition;Knowledge-Based Systems;2024-04