Tolkku: A toolbox for decision support from condition monitoring data

Olli Saarela, Mikko Lehtonen, Jari Halme, Antti Aikala, K. Raivio

    Research output: Contribution to journalArticle in a proceedings journalScientificpeer-review

    Abstract

    This paper describes a software toolbox (a software library) designed for condition monitoring and diagnosis of machines. This toolbox implements both new methods and prior art and is aimed for practical down-to-earth data analysis work. The target is to improve knowledge of the operation and behaviour of machines and processes throughout their entire life-cycles. The toolbox supports different phases of condition based maintenance with tools that extract essential information and automate data processing. The paper discusses principles that have guided toolbox design and the implemented toolbox structure. Case examples are used to illustrate how condition monitoring applications can be built using the toolbox. In the first case study the toolbox is applied to fault detection of industrial centrifuges based on measured electrical current. The second case study outlines an application for centralized monitoring of a fleet of machines that supports organizational learning
    Original languageEnglish
    Article number012044
    JournalJournal of Physics: Conference Series
    Volume364
    Issue numberConference 1
    DOIs
    Publication statusPublished - 2012
    MoE publication typeA4 Article in a conference publication
    Event25th International Congress on Condition Monitoring and Diagnostic Engineering, COMADEM 2012 - Huddersfield, United Kingdom
    Duration: 18 Jun 201220 Jun 2012
    Conference number: 25

    Fingerprint

    computer programs
    centrifuges
    fault detection
    arts
    learning
    maintenance
    cycles

    Keywords

    • Condition monitoring
    • diagnosis
    • condition-based maintenance
    • software

    Cite this

    Saarela, Olli ; Lehtonen, Mikko ; Halme, Jari ; Aikala, Antti ; Raivio, K. / Tolkku : A toolbox for decision support from condition monitoring data. In: Journal of Physics: Conference Series. 2012 ; Vol. 364, No. Conference 1.
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    abstract = "This paper describes a software toolbox (a software library) designed for condition monitoring and diagnosis of machines. This toolbox implements both new methods and prior art and is aimed for practical down-to-earth data analysis work. The target is to improve knowledge of the operation and behaviour of machines and processes throughout their entire life-cycles. The toolbox supports different phases of condition based maintenance with tools that extract essential information and automate data processing. The paper discusses principles that have guided toolbox design and the implemented toolbox structure. Case examples are used to illustrate how condition monitoring applications can be built using the toolbox. In the first case study the toolbox is applied to fault detection of industrial centrifuges based on measured electrical current. The second case study outlines an application for centralized monitoring of a fleet of machines that supports organizational learning",
    keywords = "Condition monitoring, diagnosis, condition-based maintenance, software",
    author = "Olli Saarela and Mikko Lehtonen and Jari Halme and Antti Aikala and K. Raivio",
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    Tolkku : A toolbox for decision support from condition monitoring data. / Saarela, Olli; Lehtonen, Mikko; Halme, Jari; Aikala, Antti; Raivio, K.

    In: Journal of Physics: Conference Series, Vol. 364, No. Conference 1, 012044, 2012.

    Research output: Contribution to journalArticle in a proceedings journalScientificpeer-review

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    T2 - A toolbox for decision support from condition monitoring data

    AU - Saarela, Olli

    AU - Lehtonen, Mikko

    AU - Halme, Jari

    AU - Aikala, Antti

    AU - Raivio, K.

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    AB - This paper describes a software toolbox (a software library) designed for condition monitoring and diagnosis of machines. This toolbox implements both new methods and prior art and is aimed for practical down-to-earth data analysis work. The target is to improve knowledge of the operation and behaviour of machines and processes throughout their entire life-cycles. The toolbox supports different phases of condition based maintenance with tools that extract essential information and automate data processing. The paper discusses principles that have guided toolbox design and the implemented toolbox structure. Case examples are used to illustrate how condition monitoring applications can be built using the toolbox. In the first case study the toolbox is applied to fault detection of industrial centrifuges based on measured electrical current. The second case study outlines an application for centralized monitoring of a fleet of machines that supports organizational learning

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    KW - diagnosis

    KW - condition-based maintenance

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    JF - Journal of Physics: Conference Series

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