An automated health indicator construction methodology for prognostics based on multi-criteria optimization.
ISA Trans
; 113: 81-96, 2021 Jul.
Article
em En
| MEDLINE
| ID: mdl-32209250
ABSTRACT
In recent years, the development of autonomous health management systems received increasing attention from worldwide companies to improve their performances and avoid downtime losses. This can be done, in the first step, by constructing powerful health indicators (HI) from intelligent sensors for system monitoring and for making maintenance decisions. In this context, this paper aims to develop a new methodology that allows automatically choosing the pertinent measurements among various sources and also handling raw data from high-frequency sensors to extract the useful low-level features. Then, it combines these features to create the most appropriate HI following the previously defined multiple evaluation criteria. Thanks to the flexibility of the genetic programming, the proposed methodology does not require any expertise knowledge about system degradation trends but allows easily integrating this information if available. Its performance is then verified on two real application case studies. In addition, an insightful overview on HI evaluation criteria is also discussed in this paper.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Contexto em Saúde:
1_ASSA2030
Base de dados:
MEDLINE
Assunto principal:
Prognóstico
/
Indicadores Básicos de Saúde
Tipo de estudo:
Etiology_studies
/
Prognostic_studies
/
Risk_factors_studies
Aspecto:
Determinantes_sociais_saude
/
Patient_preference
Limite:
Humans
Idioma:
En
Revista:
ISA Trans
Ano de publicação:
2021
Tipo de documento:
Article