[ Quelques techniques de séparation des composantes déterministes et aléatoires ]
Volume 41, Issue 1, November 2023, Pages 57–70
Donald Romarick Rotimbo Mbourou1, Gaston N’Tchayi Mbourou2, Paul Makanga Koumba3, and Marius Béka Be Nguéma4
1 Ecole Polytechnique de Masuku, Université des Sciences et Techniques de Masuku, Franceville, Haut-Ogooué, Gabon
2 Ecole Polytechnique de Masuku, Université des Sciences et Techniques de Masuku, Franceville, Haut-Ogooué, Gabon
3 Ecole Normale Supérieure de l’Enseignement Technique, Libreville, Estuaire, Gabon
4 Ecole Polytechnique de Masuku, Université des Sciences et Techniques de Masuku, Franceville, Haut-Ogooué, Gabon
Original language: French
Copyright © 2023 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
In many fields, different elements (mechanical, electronic, electromechanical, etc.) come into play independently to ensure the overall operation of devices/machines: electrical cables, gears, bearings, pulleys, etc. In maintenance operations, the signals from these different elements in operation are often a mixture of multiple contributions, the level of complexity of which may vary, for example, depending on the measurement point, during the data acquisition stage. There may be a number of reasons for wanting to access only the signal from a particular component (e.g., to monitor service life, diagnose the faulty part and/or predict the time remaining before a serious breakdown), rather than all the contributions measured. It is therefore essential to have a range of tools to enable us to remove harmful signals (sometimes called noise). This article presents some techniques for separating discrete and random components.
Author Keywords: Monitoring, diagnosis, prognosis, discrete and random components, noise, speed fluctuation, resampling.
Volume 41, Issue 1, November 2023, Pages 57–70
Donald Romarick Rotimbo Mbourou1, Gaston N’Tchayi Mbourou2, Paul Makanga Koumba3, and Marius Béka Be Nguéma4
1 Ecole Polytechnique de Masuku, Université des Sciences et Techniques de Masuku, Franceville, Haut-Ogooué, Gabon
2 Ecole Polytechnique de Masuku, Université des Sciences et Techniques de Masuku, Franceville, Haut-Ogooué, Gabon
3 Ecole Normale Supérieure de l’Enseignement Technique, Libreville, Estuaire, Gabon
4 Ecole Polytechnique de Masuku, Université des Sciences et Techniques de Masuku, Franceville, Haut-Ogooué, Gabon
Original language: French
Copyright © 2023 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
In many fields, different elements (mechanical, electronic, electromechanical, etc.) come into play independently to ensure the overall operation of devices/machines: electrical cables, gears, bearings, pulleys, etc. In maintenance operations, the signals from these different elements in operation are often a mixture of multiple contributions, the level of complexity of which may vary, for example, depending on the measurement point, during the data acquisition stage. There may be a number of reasons for wanting to access only the signal from a particular component (e.g., to monitor service life, diagnose the faulty part and/or predict the time remaining before a serious breakdown), rather than all the contributions measured. It is therefore essential to have a range of tools to enable us to remove harmful signals (sometimes called noise). This article presents some techniques for separating discrete and random components.
Author Keywords: Monitoring, diagnosis, prognosis, discrete and random components, noise, speed fluctuation, resampling.
Abstract: (french)
Dans de nombreux domaines, différents éléments (mécaniques, électroniques, électromécaniques,...) entrent en action de façon indépendante pour assurer le fonctionnement global des appareils/machines: câbles électriques, engrenages, roulements, poulies... Dans le cadre des opérations de maintenance, les signaux provenant de ces différents éléments en fonctionnement sont souvent un mélange de multiples contributions dont le taux de complexité peut par exemple varier suivant le point de mesure, lors de l’étape d’acquisition de données. Plusieurs raisons peuvent nous pousser à vouloir accéder uniquement au signal d’un élément précis (surveillance de la durée de vie, diagnostic de la partie défaillante et/ou pronostic du temps résiduel avant une grave panne) plutôt qu’à l’ensemble des contributions mesurées. Il est donc indispensable de posséder une panoplie d’outils qui vont nous permettre de supprimer les signaux nuisibles (parfois appelé bruit). Cet article présente quelques techniques de séparation des composantes discrètes et aléatoires.
Author Keywords: Surveillance, diagnostic, pronostic, composantes discrètes et aléatoires, bruit, fluctuation de vitesse, re-échantillonnage.
How to Cite this Article
Donald Romarick Rotimbo Mbourou, Gaston N’Tchayi Mbourou, Paul Makanga Koumba, and Marius Béka Be Nguéma, “Some techniques for separating discrete and random components,” International Journal of Innovation and Applied Studies, vol. 41, no. 1, pp. 57–70, November 2023.
