Mimosa Strong Medicine for Maintenance

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

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

    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 on-tology 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 publication32nd International Congress and Exhibition on Condition Monitoring and Diagnostic Engineering Management
    Number of pages11
    Publication statusAccepted/In press - Sep 2019
    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 Sep 20195 Sep 2019

    Conference

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

    Fingerprint

    Medicine
    Data structures
    Condition monitoring
    Bearings (structural)
    Costs
    Signal analysis
    Accelerometers
    Engines
    Monitoring

    Keywords

    • CBM
    • Mimosa
    • Diagnostics
    • Prognostics
    • Low-Cost Hardware

    Cite this

    Salokangas, R., Jantunen, E., Larranaga, M., & Kaarmila, P. (Accepted/In press). Mimosa Strong Medicine for Maintenance. In 32nd International Congress and Exhibition on Condition Monitoring and Diagnostic Engineering Management
    Salokangas, Riku ; Jantunen, Erkki ; Larranaga, Martin ; Kaarmila, Petri. / Mimosa Strong Medicine for Maintenance. 32nd International Congress and Exhibition on Condition Monitoring and Diagnostic Engineering Management. 2019.
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    title = "Mimosa Strong Medicine for Maintenance",
    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 on-tology 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.",
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    Salokangas, R, Jantunen, E, Larranaga, M & Kaarmila, P 2019, Mimosa Strong Medicine for Maintenance. in 32nd International Congress and Exhibition on Condition Monitoring and Diagnostic Engineering Management. 32nd International Congress and Exhibition on Condition Monitoring and Diagnostic Engineering Management, COMADEM 2019, Huddersfield, United Kingdom, 3/09/19.

    Mimosa Strong Medicine for Maintenance. / Salokangas, Riku (Corresponding author); Jantunen, Erkki; Larranaga, Martin; Kaarmila, Petri.

    32nd International Congress and Exhibition on Condition Monitoring and Diagnostic Engineering Management. 2019.

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

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    AU - Jantunen, Erkki

    AU - Larranaga, Martin

    AU - Kaarmila, Petri

    PY - 2019/9

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    AB - 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 on-tology 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.

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    KW - Mimosa

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    KW - Prognostics

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    Salokangas R, Jantunen E, Larranaga M, Kaarmila P. Mimosa Strong Medicine for Maintenance. In 32nd International Congress and Exhibition on Condition Monitoring and Diagnostic Engineering Management. 2019