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Basic tools for vibration analysis with applications to predictive maintenance of rotating machines: an overview

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Abstract

The paper presents some basic tools for vibration signals with application in predictive maintenance of rotating machines. After an overview of the maintenance approach, the condition monitoring in predictive maintenance is discussed. Also, signal processing in vibration monitoring, making use of some basic tools as change detection, independent component analysis, time-frequency analysis, and energy distribution in time-frequency plane are presented. These techniques can be combined in a general approach, offering new possibilities for more robust detection of changes in vibration signals and assuring proactive actions in predictive maintenance.

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Acknowledgements

The authors thank the Executive Agency for Higher Education, Research, Development and Innovation Funding (UEFISCDI) and Ministry of Research and Innovation, for the support under Contract PN-II-PT-PCCA-2013-4-0044 and 2019-2022 Core Program, Project PN 301, RO-SmartAgeing.

Also, the authors are highly thankful to the reviewers for providing suggestions and comments that helped in improving the manuscript.

Funding

The research funding provided by Executive Agency for Higher Education, Research, Development and Innovation Funding (UEFISCDI) and Ministry of Research and Innovation, Contract PN-II-PT-PCCA-2013-4-0044 and 2019-2022 Core Program, Project PN 301, RO-SmartAgeing.

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  1. National Institute for R&D in Informatics, 8-10 Averescu Avenue, 011455, Bucharest, Romania

    Theodor D. Popescu

  2. “Dunǎrea de Jos” University of Galati, 47, Domneasca Street, 800008, Galati, Romania

    Dorel Aiordachioaie & Anisia Culea-Florescu

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  1. Theodor D. Popescu
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Correspondence to Theodor D. Popescu.

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Writing (original draft preparation): Theodor D. Popescu; writing (review and editing): Dorel Aiordachioaie, Anisia Culea-Florescu).

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Popescu, T.D., Aiordachioaie, D. & Culea-Florescu, A. Basic tools for vibration analysis with applications to predictive maintenance of rotating machines: an overview. Int J Adv Manuf Technol 118, 2883–2899 (2022). https://doi.org/10.1007/s00170-021-07703-1

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