phm survey : implementation of signal processing methods for monitoring bearings and gearboxes

Abdenour Soualhi (1) , Yasmine Hawwari (2) , Kamal Medjaher (3) , Guy Clerc (4) , Hubert Razik (4) , François Guillet (1)

1 LASPI - Laboratoire d'Analyse des Signaux et des Processus Industriels
2 PRISME - Laboratoire pluridisciplinaire de recherche en ingénierie des systèmes, mécanique et énergétique
3 ENIT - Ecole Nationale d'Ingénieurs de Tarbes
4 MIS - Ampère, Département Méthodes pour l'Ingénierie des Systèmes

The reliability and safety of industrial equipments are one of the main objectives of companies to remain competitive in sectors that are more and more exigent in terms of cost and security. Thus, an unexpected shutdown can lead to physical injury as well as economic consequences. This paper aims to show the emergence of the Prognostics and Health Management (PHM) concept in the industry and to describe how it comes to complement the different maintenance strategies. It describes the benefits to be expected by the implementation of signal processing, diagnostic and prognostic methods in health-monitoring. More specifically, this paper provides a state of the art of existing signal processing techniques that can be used in the PHM strategy. This paper allows showing the diversity of possible techniques and choosing among them the one that will define a framework for industrials to monitor sensitive components like bearings and gearboxes.

Domaines: Energie électrique

Abdenour Soualhi, Yasmine Hawwari, Kamal Medjaher, Guy Clerc, Hubert Razik, et al.. phm survey : implementation of signal processing methods for monitoring bearings and gearboxes. International Journal of Prognostics and Health Management, 2018, 9 (2). ⟨hal-01899884⟩