A study on health diagnosis and prognosis of an industrial diesel motor: hidden Markov models and particle filter approach

Walid Mechri (1) , Hai Canh Vu (1) , Phuc Do Van (1) , Klingelschmid Timothee (1) , Flavien Peysson (2) , Didier Theilliol (1)

1 CRAN - Centre de Recherche en Automatique de Nancy
2 PREDICT [Vandœuvre-lès-Nancy]

The paper presents a study on health diagnosis and prognosis of an industrial diesel motor. Two well-known approaches, Hidden Markov Model (HMM) and particle filter (PF), are applied from real recorded data with different measurements. The recorded data is firstly pre-processed and health indicator is then chosen before implementing each used approach. The obtained results are analyzed and discussed. The use and advantages of each approach are finally highlighted.

Mots clés: Prognostic; Faults diagnosis; Particle filter; Hidden Markov Models; Diesel motor

Domaines: Automatique / Robotique

Walid Mechri, Hai Canh Vu, Phuc Do Van, Klingelschmid Timothee, Flavien Peysson, et al.. A study on health diagnosis and prognosis of an industrial diesel motor: hidden Markov models and particle filter approach. 13th International Science Conference Diagnostics of Processes and Systems, DPS 2017, Sep 2017, Sandomierz, Poland. ⟨hal-01531036⟩