Modelling of Fault Detection and Diagnostics for Hybrid Bus Using Chain Graph Models (Articolo in rivista)

Type
Label
  • Modelling of Fault Detection and Diagnostics for Hybrid Bus Using Chain Graph Models (Articolo in rivista) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1002/qre.1691 (literal)
Alternative label
  • Flaccadoro, Diana; Cervellera, Cristiano; Bosia, Giorgio; Riccomagno, Eva (2014)
    Modelling of Fault Detection and Diagnostics for Hybrid Bus Using Chain Graph Models
    in Quality and reliability engineering international (Print)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Flaccadoro, Diana; Cervellera, Cristiano; Bosia, Giorgio; Riccomagno, Eva (literal)
Pagina inizio
  • 975 (literal)
Pagina fine
  • 983 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#altreInformazioni
  • Quartile della rivista: Q1 nel settore Safety, Risk, Reliability and Quality (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 30 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 9 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 7 (literal)
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Department of Mathematics, University of Genova, Genoa, Italy Institute of Intelligent Systems for Automation, National Research Council of Italy, Genoa, Italy Eutecne Srl, Genoa, Italy Department of Mathematics, University of Genova, Genoa, Italy (literal)
Titolo
  • Modelling of Fault Detection and Diagnostics for Hybrid Bus Using Chain Graph Models (literal)
Abstract
  • Graphical models are statistical models supported on a graph structure: nodes represent random variables, and missing edges represent probabilistic relationship of conditional independence. This makes them suited to model the behavior of complex systems that are difficult to model through mathematical equations. In this work, this possibility is exploited in a context of diagnostics and fault detection. Specifically, the fault detection problem is reduced to the evaluation of a conditional probability. The relevant conditional distribution is derived from the analysis of a suitable graphical model taking advantage of the so-called Markov properties. (literal)
  • As a case study, we consider diagnostics of a hybrid bus, characterized by the combined use of a diesel engine and an electrical engine. The aim of the study is to verify the correct operation of the electrical system, in particular the status of the battery. Copyright (C) 2014 John Wiley & Sons, Ltd. (literal)
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