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Bayesian network design for fault diagnostics of railway switches

Neumann, Thorsten und Narezo Guzman, Daniela (2019) Bayesian network design for fault diagnostics of railway switches. In: Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019, Seiten 1117-1124. Research Publishing Services. 29th European Safety and Reliability Conference (ESREL 2019), 22.-26. Sept. 2019, Hannover, Deutschland. doi: 10.3850/978-981-11-2724-3_0103-cd. ISBN 978-981112724-3.

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Offizielle URL: http://itekcmsonline.com/rps2prod/esrel2019/e-proceedings/index.html

Kurzfassung

Besides detecting failures and predicting future health conditions of technical systems, fault diagnosis (i.e., fault identification) is a key challenge in the analytic part of prognostics and health management (PHM). In this context, Bayesian networks (BN) has proven to be an effective tool for diagnostic reasoning about faults and effects. Since it is possible to generate such models not only from data but also from expert knowledge or a combination of both (hybrid approach), Bayesian networks are well-suited for many applications and (technical) disciplines. This, in particular, holds for situations where common data-driven approaches (e.g., neural networks, deep learning) suffer from a lack of a reasonable amount of adequate training data. This contribution discusses the detailed design of a comprehensive Bayesian network for railway switches as to be used for fault diagnosis in context of corrective and/or predictive maintenance, for instance. The new model explicitly pursues the modular paradigm of object-oriented Bayesian networks (OOBN), and thus provides a maximum degree of flexibility when adapting it to different types of railway switches. Moreover, it contains Bayesian nodes that act as a kind of "ON/OFF switches" and allow to (de-)activate specific parts of the model without affecting its overall structure. This, in particular, is useful whenever the general Bayesian network comprises modules (e.g., point heater or back drive) that are not available to all switches in the field. Finally, the model benefits from a newly developed, innovative design principle for Bayesian networks which, based on a generalization of the idea of Boolean clusters, reduces (or potentially even completely avoids) the problematic effect of overconfidence in diagnostic reasoning.

elib-URL des Eintrags:https://elib.dlr.de/122317/
Dokumentart:Konferenzbeitrag (Vortrag)
Titel:Bayesian network design for fault diagnostics of railway switches
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Neumann, ThorstenThorsten.Neumann (at) dlr.dehttps://orcid.org/0000-0002-9236-0585NICHT SPEZIFIZIERT
Narezo Guzman, DanielaDaniela.NarezoGuzman (at) dlr.dehttps://orcid.org/0000-0001-9748-1354NICHT SPEZIFIZIERT
Datum:24 September 2019
Erschienen in:Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019
Referierte Publikation:Ja
Open Access:Nein
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Nein
DOI:10.3850/978-981-11-2724-3_0103-cd
Seitenbereich:Seiten 1117-1124
Herausgeber:
HerausgeberInstitution und/oder E-Mail-Adresse der HerausgeberHerausgeber-ORCID-iDORCID Put Code
Beer, MichaelNICHT SPEZIFIZIERTNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Zio, EnricoNICHT SPEZIFIZIERTNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Verlag:Research Publishing Services
ISBN:978-981112724-3
Status:veröffentlicht
Stichwörter:Prognostics and health management, fault diagnosis, railway switches, Bayesian network, object-oriented, overconfidence, hybrid modeling
Veranstaltungstitel:29th European Safety and Reliability Conference (ESREL 2019)
Veranstaltungsort:Hannover, Deutschland
Veranstaltungsart:internationale Konferenz
Veranstaltungsdatum:22.-26. Sept. 2019
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Verkehr
HGF - Programmthema:Verkehrsmanagement (alt)
DLR - Schwerpunkt:Verkehr
DLR - Forschungsgebiet:V VM - Verkehrsmanagement
DLR - Teilgebiet (Projekt, Vorhaben):V - Next Generation Railway Systems III (alt), V - Digitalisierung und Automatisierung des Bahnsystems (alt)
Standort: Berlin-Adlershof
Institute & Einrichtungen:Institut für Verkehrssystemtechnik > Datenerfassung und Informationsgewinnung
Hinterlegt von: Neumann, Dr.-Ing. Thorsten
Hinterlegt am:20 Nov 2019 09:42
Letzte Änderung:20 Jun 2021 15:51

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