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Statistical Process Control for Modern Switch Failure Detection

Böhm, Thomas und Schenkendorf, René und Lemmer, Karsten (2016) Statistical Process Control for Modern Switch Failure Detection. In: Proceedings of the 11th World Congress on Railway Research, e1-e6. 11th World Congress on Railway Research, 2016-05-29 - 2016-06-02, Mailand, Italien.

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Kurzfassung

A highly available infrastructure is a premise for capable railway operation of high quality. Therefore maintenance is necessary to keep railway infrastructure elements available. Especially switches are critical because they connect different tracks and allow a train to change its moving direction without stopping. Their inspection, maintenance and repair have been identified as a cost driver. Especially switch failures are responsible for a comparable high number of failures and delay minutes. The reduction of failures would not only safe maintenance costs, but let more trains arrive on time and hence increase the attractiveness of the railway transport. Therefore, the Institute of Transportation Systems (TS) in cooperation with the German Railways (DB AG) is exploring ways to apply statistical process control to monitor the condition of switches and their degradation process to reduce failures and thus maintenance costs. Currently, infrastructure managers use commercially available switch diagnostic systems. They are based on measuring the electrical power consumption of the switch engine and comparing it to a manually predefined threshold indicating the failure. But most of these systems do not reach a satisfying accuracy, because they miss too many failures or produce too many false alerts. TS has identified three main aspects to overcome these issues. 1) Instead of interpreting a single feature of the measured signals TS derives multiple statistical features from the signals each defining a different characteristic, so that more useful information is gained for more precise failure detection. 2) The features are used to develop a novel multidimensional correlation model which is robust to non-failure related changes in the original measurements. Therefore false alerts are reduced. 3) The manual adaption of any threshold is eliminated from the process via a new self-adapting algorithm based on clustering techniques. This safes maintenance staffs the effort for recalibrating thresholds when external parameters change, e.g. major temperature shifts with the change of seasons.

elib-URL des Eintrags:https://elib.dlr.de/107578/
Dokumentart:Konferenzbeitrag (Vortrag)
Titel:Statistical Process Control for Modern Switch Failure Detection
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Böhm, Thomasthomas.boehm (at) dlr.dehttps://orcid.org/0000-0003-0027-9470NICHT SPEZIFIZIERT
Schenkendorf, Renérene.schenkendorf (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Lemmer, Karstenkarsten.lemmer (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:Mai 2016
Erschienen in:Proceedings of the 11th World Congress on Railway Research
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Nein
In ISI Web of Science:Nein
Seitenbereich:e1-e6
Status:veröffentlicht
Stichwörter:Condition Based Maintenance; Predictive Maintenance; Railway Switch Diagnostics
Veranstaltungstitel:11th World Congress on Railway Research
Veranstaltungsort:Mailand, Italien
Veranstaltungsart:internationale Konferenz
Veranstaltungsbeginn:29 Mai 2016
Veranstaltungsende:2 Juni 2016
Veranstalter :Ferrovie dello Stato Italiane Group; Trenitalia
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)
Standort: Berlin-Adlershof
Institute & Einrichtungen:Institut für Verkehrssystemtechnik > Bahnsysteme
Hinterlegt von: Böhm, Thomas
Hinterlegt am:16 Nov 2016 09:53
Letzte Änderung:24 Apr 2024 20:12

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