By Nicolas RÉMY and Gabrielle RIVES. Lambda Mu 21 Congress "Risk management and digital transformation: opportunities and threats", October 2018, Reims, France.

It is widely considered that HUMS (Health and Usage Monitoring Systems) shall deeply increase the knowledge of systems usage, directly leading to maintenance and support optimisation, as well as availability improvement.

This article describes LGM’s approach in HUMS design and architecture achieved in the context of an R&D project “Innov’Up Proto 2017” supported by French Paris Région and CAP-DIGITAL organisation.

The purpose of that project was to implement a proof of concept to apply DeepLearning technology for vibrations classification, for instance to estimate the service quality in public transportation, and more generally to analyse usage profile and exploitation for vehicles.

Find the publication here: https://hal.archives-ouvertes.fr/hal-02074493/document