Observatorio de I+D+i UPM

Memorias de investigación
Artículos en revistas:
Deep evolutionary modeling of condition monitoring data in marine propulsion systems
Año:2018
Áreas de investigación
  • Ingeniería eléctrica, electrónica y automática
Datos
Descripción
In many complex industrial scenarios where condition monitoring data are involved, data-driven models can highly support maintenance tasks and improve assets? performance. To infer physical meaningful models that accurately characterize assets? behaviors across a wide range of operating conditions is a difficult issue. Usually, data-driven models are in black-box format, accurate but too complex to intelligibly explain the inherent physics of the process and lacking in conciseness. This study presents a deep evolutionary-based approach to optimally model and predict physical behaviors in industrial assets from operational data. The evolutionary modeling process is combined with long short-term memory networks, which are trained on estimations made by the evolutionary physical model and then used to predict sequences of data over a number of time steps. The likelihood of behaviors of interest is assessed by means of the resulting sequences of residuals, and a resulting score is computed over time. The proposed approach is applied to model and predict a set of temperatures related to a marine propulsion system, anticipating anomalies and changes in operating conditions. It is demonstrated that deep evolutionary modeling results are quite satisfactory for prognostics and obtained physical models are practical and easy to understand.
Internacional
Si
JCR del ISI
Si
Título de la revista
Soft Computing
ISSN
1433-7479
Factor de impacto JCR
Información de impacto
Volumen
DOI
10.1007/s00500-018-3549-3
Número de revista
Desde la página
1
Hasta la página
17
Mes
SIN MES
Ranking
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Ricardo Sanz Bravo (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Laboratorio de Sistemas Autónomos
  • Centro o Instituto I+D+i: Centro de Automática y Robótica (CAR). Centro Mixto UPM-CSIC
  • Departamento: Automática, Ingeniería Eléctrica y Electrónica e Informática Industrial
S2i 2021 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)