Mimosa Strong Medicine for Maintenance

Riku Salokangas; Erkki Jantunen; Martin Larrañaga; Petri Kaarmila

doi:10.1007/978-3-030-57745-2_4

Mimosa Strong Medicine for Maintenance

Riku Salokangas^*
, Erkki Jantunen
, Martin Larrañaga
, Petri Kaarmila

^*Corresponding author for this work

Mondragon University

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-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 language	English
Title of host publication	Advances in Asset Management and Condition Monitoring
Subtitle of host publication	COMADEM 2019
Editors	Andrew Ball, Len Gelman, B.K.N. Rao
Publisher	Springer
Pages	35-47
ISBN (Electronic)	978-3-030-57745-2
ISBN (Print)	978-3-030-57744-5
DOIs	https://doi.org/10.1007/978-3-030-57745-2_4
Publication status	Published - 2020
MoE publication type	A4 Article in a conference publication
Event	32nd International Congress and Exhibition on Condition Monitoring and Diagnostic Engineering Management, COMADEM 2019 - University of Huddersfield, Huddersfield, United Kingdom Duration: 3 Sept 2019 → 5 Sept 2019

Publication series

Series	Smart Innovation, Systems and Technologies
Volume	166
ISSN	2190-3018

Conference

Conference	32nd International Congress and Exhibition on Condition Monitoring and Diagnostic Engineering Management, COMADEM 2019
Abbreviated title	COMADEM 2019
Country/Territory	United Kingdom
City	Huddersfield
Period	3/09/19 → 5/09/19

Funding

Research leading to these results has received funding from the EU Horizon 2020 program under the project Serena (Number 767561).

Keywords

CBM
Diagnostics
Low-cost hardware
Mimosa
Prognostics

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-030-57745-2_4

Cite this

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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 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.",

keywords = "CBM, Diagnostics, Low-cost hardware, Mimosa, Prognostics",

author = "Riku Salokangas and Erkki Jantunen and Martin Larra{\~n}aga and Petri Kaarmila",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 32nd International Congress and Exhibition on Condition Monitoring and Diagnostic Engineering Management, COMADEM 2019, COMADEM 2019 ; Conference date: 03-09-2019 Through 05-09-2019",

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doi = "10.1007/978-3-030-57745-2\_4",

language = "English",

isbn = "978-3-030-57744-5",

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booktitle = "Advances in Asset Management and Condition Monitoring",

address = "Germany",

}

Salokangas, R, Jantunen, E, Larrañaga, M & Kaarmila, P 2020, Mimosa Strong Medicine for Maintenance. in A Ball, L Gelman & BKN Rao (eds), Advances in Asset Management and Condition Monitoring: COMADEM 2019. Springer, Smart Innovation, Systems and Technologies, vol. 166, pp. 35-47, 32nd International Congress and Exhibition on Condition Monitoring and Diagnostic Engineering Management, COMADEM 2019, Huddersfield, United Kingdom, 3/09/19. https://doi.org/10.1007/978-3-030-57745-2_4

Mimosa Strong Medicine for Maintenance. / Salokangas, Riku; Jantunen, Erkki; Larrañaga, Martin et al.
Advances in Asset Management and Condition Monitoring: COMADEM 2019. ed. / Andrew Ball; Len Gelman; B.K.N. Rao. Springer, 2020. p. 35-47 (Smart Innovation, Systems and Technologies, Vol. 166).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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T1 - Mimosa Strong Medicine for Maintenance

AU - Salokangas, Riku

AU - Jantunen, Erkki

AU - Larrañaga, Martin

AU - Kaarmila, Petri

PY - 2020

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N2 - 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.

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 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.

KW - CBM

KW - Diagnostics

KW - Low-cost hardware

KW - Mimosa

KW - Prognostics

UR - https://www.scopus.com/pages/publications/85091314266

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DO - 10.1007/978-3-030-57745-2_4

M3 - Conference article in proceedings

AN - SCOPUS:85091314266

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BT - Advances in Asset Management and Condition Monitoring

A2 - Ball, Andrew

A2 - Gelman, Len

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Y2 - 3 September 2019 through 5 September 2019

ER -

Mimosa Strong Medicine for Maintenance

Abstract

Publication series

Conference

Funding

Keywords

UN SDGs

Access to Document

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