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Hyperdimensional computing in industrial systems: the use-case of distributed fault isolation in a power plant
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0002-6032-6155
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-0069-640X
VTT Technical Research Center of Finland.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, Aalto University, Finland.ORCID iD: 0000-0002-9315-9920
2018 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 6, p. 30766-30777Article in journal (Refereed) Published
Abstract [en]

This paper presents an approach for distributed fault isolation in a generic system of systems. The proposed approach is based on the principles of hyperdimensional computing. In particular, the recently proposed method called Holographic Graph Neuron is used. We present a distributed version of Holographic Graph Neuron and evaluate its performance on the problem of fault isolation in a complex power plant model. Compared to conventional machine learning methods applied in the context of the same scenario the proposed approach shows comparable performance while being distributed and requiring simple binary operations, which allow for a fast and efficient implementation in hardware.

Place, publisher, year, edition, pages
IEEE, 2018. Vol. 6, p. 30766-30777
National Category
Computer Systems Computer Sciences
Research subject
Dependable Communication and Computation Systems
Identifiers
URN: urn:nbn:se:ltu:diva-69034DOI: 10.1109/ACCESS.2018.2840128ISI: 000437220700001Scopus ID: 2-s2.0-85047613488OAI: oai:DiVA.org:ltu-69034DiVA, id: diva2:1212026
Note

Validerad;2018;Nivå 2;2018-08-06 (rokbeg)

Available from: 2018-06-01 Created: 2018-06-01 Last updated: 2018-08-06Bibliographically approved

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Kleyko, DenisOsipov, EvgenyVyatkin, Valeriy

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