Mimosa Strong Medicine for Maintenance

Riku Salokangas (Corresponding author), Erkki Jantunen, Martin Larrañaga, Petri Kaarmila

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    1 Citation (Scopus)

    Abstract

    The paper describes how the use of Mimosa open source data model supports the development of a low-cost condition monitoring system that is capable to carry out automatic diagnosis and prognosis. Mimosa follows the ISO 13374 definitions (condition monitoring) and links well with the ISO 17359 (diagnosis) and ISO 13381 (prognosis). The Mimosa data model defines all the necessary ontology for the automatic system. As a use case the paper describes the installation of the Mimosa data model in a Raspberry where MariaDB is used as the database engine. A low-cost accelerometer has been installed to a Raspberry thus enabling the collection of vibration data from rolling element bearings of a conveyor. In addition, a low-cost system that uses Arduino is presented for data collection in future use cases. The necessary signal analysis functions are programmed with Python which offers a wide collection of useful functions. The paper summarises the key role of Mimosa in building and using this kind of automatic monitoring systems.
    Original languageEnglish
    Title of host publicationAdvances in Asset Management and Condition Monitoring
    Subtitle of host publicationCOMADEM 2019
    EditorsAndrew Ball, Len Gelman, B.K.N. Rao
    PublisherSpringer Science+Business Media
    Pages35-47
    ISBN (Electronic)978-3-030-57745-2
    ISBN (Print)978-3-030-57744-5
    DOIs
    Publication statusPublished - 2020
    MoE publication typeA4 Article in a conference publication
    Event32nd International Congress and Exhibition on Condition Monitoring and Diagnostic Engineering Management, COMADEM 2019 - University of Huddersfield, Huddersfield, United Kingdom
    Duration: 3 Sept 20195 Sept 2019

    Publication series

    SeriesSmart Innovation, Systems and Technologies
    Volume166
    ISSN2190-3018

    Conference

    Conference32nd International Congress and Exhibition on Condition Monitoring and Diagnostic Engineering Management, COMADEM 2019
    Abbreviated titleCOMADEM 2019
    Country/TerritoryUnited Kingdom
    CityHuddersfield
    Period3/09/195/09/19

    Keywords

    • CBM
    • Diagnostics
    • Low-cost hardware
    • Mimosa
    • Prognostics

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