Feature engineering –based machine learning models for operational state recognition of rotating machines

Jukka Junttila*, Ville Lämsä, Leonardo Espinosa-Leal, Anssi Sillanpaa

*Corresponding author for this work

    Research output: Contribution to conferenceConference PosterScientific

    Abstract

    Data-based models for operational state recognition and
    detection of abnormal operation of a gas engine generating
    set (genset) in near real-time were provided. One model can
    classify the current power output level very accurately, and
    the other can detect abnormal operation (novelties), e.g., in
    fault situations, at a specific load level. Thus, a fast and
    accurate two-step state recognition model can be built.
    Original languageEnglish
    Number of pages1
    DOIs
    Publication statusPublished - 21 Mar 2023
    MoE publication typeNot Eligible
    EventFCAI AI Day 2022 - Dipoli, Aalto University, Espoo, Finland
    Duration: 16 Nov 202216 Nov 2022
    https://fcai.fi/ai-day-2022

    Conference

    ConferenceFCAI AI Day 2022
    Country/TerritoryFinland
    CityEspoo
    Period16/11/2216/11/22
    Internet address

    Keywords

    • Operational state recognition
    • Classification
    • Simulation
    • Mechanical vibration
    • Internal combustion engine
    • Feature engineering

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