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Statistical Process Control for Modern Switch Failure Detection

Böhm, Thomas and Schenkendorf, René and 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, 29. Mai - 02. Jun. 2016, Mailand, Italien.

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Abstract

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.

Item URL in elib:https://elib.dlr.de/107578/
Document Type:Conference or Workshop Item (Speech)
Title:Statistical Process Control for Modern Switch Failure Detection
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Böhm, Thomasthomas.boehm (at) dlr.dehttps://orcid.org/0000-0003-0027-9470
Schenkendorf, Renérene.schenkendorf (at) dlr.deUNSPECIFIED
Lemmer, Karstenkarsten.lemmer (at) dlr.deUNSPECIFIED
Date:May 2016
Journal or Publication Title:Proceedings of the 11th World Congress on Railway Research
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Page Range:e1-e6
Status:Published
Keywords:Condition Based Maintenance; Predictive Maintenance; Railway Switch Diagnostics
Event Title:11th World Congress on Railway Research
Event Location:Mailand, Italien
Event Type:international Conference
Event Dates:29. Mai - 02. Jun. 2016
Organizer:Ferrovie dello Stato Italiane Group; Trenitalia
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Traffic Management (old)
DLR - Research area:Transport
DLR - Program:V VM - Verkehrsmanagement
DLR - Research theme (Project):V - Next Generation Railway Systems III (old)
Location: Berlin-Adlershof
Institutes and Institutions:Institute of Transportation Systems > Railway System
Deposited By: Böhm, Thomas
Deposited On:16 Nov 2016 09:53
Last Modified:31 Jul 2019 20:04

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