Hyperdimensional computing in industrial systems: the use-case of distributed fault isolation in a power plant

Denis Kleyko, Evgeny Osipov, Nikolaos Papakonstantinou, Valeriy Vyatkin

Tutkimustuotos: LehtiartikkeliArticleScientificvertaisarvioitu

8 Sitaatiot (Scopus)
116 Lataukset (Pure)

Abstrakti

This article 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 a hardware.

AlkuperäiskieliEnglanti
Sivut30766-30777
JulkaisuIEEE Access
Vuosikerta6
DOI - pysyväislinkit
TilaJulkaistu - 28 toukokuuta 2018
OKM-julkaisutyyppiA1 Julkaistu artikkeli, soviteltu

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