https://www.scipedia.com/wd/index.php?action=history&feed=atom&title=Guzman_et_al_2018bGuzman et al 2018b - Revision history2026-06-10T20:55:48ZRevision history for this page on the wikiMediaWiki 1.27.0-wmf.10https://www.scipedia.com/wd/index.php?title=Guzman_et_al_2018b&diff=207017&oldid=prevScipediacontent: Scipediacontent moved page Draft Content 216733245 to Guzman et al 2018b2021-02-03T18:17:07Z<p>Scipediacontent moved page <a href="/public/Draft_Content_216733245" class="mw-redirect" title="Draft Content 216733245">Draft Content 216733245</a> to <a href="/public/Guzman_et_al_2018b" title="Guzman et al 2018b">Guzman et al 2018b</a></p>
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</td></tr></table>Scipediacontenthttps://www.scipedia.com/wd/index.php?title=Guzman_et_al_2018b&diff=207016&oldid=prevScipediacontent: Created page with " == Abstract == Railway switches are crucial for normal operation and during disruptions of the railroad system since they allow trains to use alternative routes. Switches mo..."2021-02-03T18:17:04Z<p>Created page with " == Abstract == Railway switches are crucial for normal operation and during disruptions of the railroad system since they allow trains to use alternative routes. Switches mo..."</p>
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== Abstract ==<br />
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Railway switches are crucial for normal operation and during disruptions of the railroad system since they allow trains to use alternative routes. Switches moving parts are subject to high deterioration and prone to malfunctioning, representing a potential safety hazard. Thus frequent inspection, maintenance and renewal are required. Models to optimize the railroad system operation and reduce costs are possible on the basis of inspections vehicles, online condition monitoring, inspection standardization and data-based models. This paper presents a switch condition now- and forecasting model based on continuous monitored data (switch engine current during blades movement). The model is capable of identifying unusual behavior due to emerging failures without the need of manually set switch-specific thresholds. In this approach no labelled training data set of historic switch failures is required for training the model. Its output combined with maintenance information and the switch functional model sheds light on switch degradation modes, helping to optimize maintenance actions.<br />
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== Original document ==<br />
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The different versions of the original document can be found in:<br />
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* [https://elib.dlr.de/114441 https://elib.dlr.de/114441]<br />
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* [https://zenodo.org/record/1491428 https://zenodo.org/record/1491428] under the license http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode<br />
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* [http://dx.doi.org/10.5281/zenodo.1491428 http://dx.doi.org/10.5281/zenodo.1491428],<br />
: [https://zenodo.org/record/1491428 https://zenodo.org/record/1491428] under the license http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode<br />
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* [https://zenodo.org/record/1491428 https://zenodo.org/record/1491428],<br />
: [http://dx.doi.org/10.5281/zenodo.1491427 http://dx.doi.org/10.5281/zenodo.1491427] under the license http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode<br />
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DOIS: 10.5281/zenodo.1491428 10.5281/zenodo.1491427</div>Scipediacontent