Proceedings of the 8th Scientific Conference on Information Technologies for Intelligent Decision Making Support (ITIDS 2020)

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Cyber-Physical Systems and Reliability Issues

Authors
Nafisa Yusupova, Dmitry Rizvanov, Dmitry Andrushko
Corresponding Author
Dmitry Rizvanov
Available Online 10 November 2020.
DOI
10.2991/aisr.k.201029.026How to use a DOI?
Keywords
cyber-physical systems, internet of things, classification, time-series, machine learning
Abstract

Anomaly detection is a well researched concept used in many areas, including engineering systems design, where it helps detect errors and prevent failures. Traditional anomaly detection methods, based either on comparing the behavior of the real system with its model or on different signal processing methods, have been successfully applied for Fault Detection and Isolation (FDI) in mechatronic systems. Cyber-Physical Systems (CPS) are complex in both structural and behavioral terms. They consist of numerous heterogeneous components that generate large volumes of data, exchange information and form extremely complex patterns of behaviour. This makes it almost impossible to effectively set up and apply classical reliability assessment methods. The article discusses the basic models of machine learning and the possibility of their application to solve the problem of CPS reliability. It is proposed to use neural networks with long short-term memory (LSTM) to detect anomalies in the CPS. The neural network architecture with 3 hidden, input and output layers was designed. The experiment with testing data (Tennessee Eastman Process dataset) was conducted and analysis of the results was carried out.

Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 8th Scientific Conference on Information Technologies for Intelligent Decision Making Support (ITIDS 2020)
Series
Advances in Intelligent Systems Research
Publication Date
10 November 2020
ISBN
10.2991/aisr.k.201029.026
ISSN
1951-6851
DOI
10.2991/aisr.k.201029.026How to use a DOI?
Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - CONF
AU  - Nafisa Yusupova
AU  - Dmitry Rizvanov
AU  - Dmitry Andrushko
PY  - 2020
DA  - 2020/11/10
TI  - Cyber-Physical Systems and Reliability Issues
BT  - Proceedings of the 8th Scientific Conference on Information Technologies for Intelligent Decision Making Support (ITIDS 2020)
PB  - Atlantis Press
SP  - 133
EP  - 137
SN  - 1951-6851
UR  - https://doi.org/10.2991/aisr.k.201029.026
DO  - 10.2991/aisr.k.201029.026
ID  - Yusupova2020
ER  -