https://www.scipedia.com/wd/index.php?action=history&feed=atom&title=Kratochvilova_et_al_2020aKratochvilova et al 2020a - Revision history2026-04-25T21:28:53ZRevision history for this page on the wikiMediaWiki 1.27.0-wmf.10https://www.scipedia.com/wd/index.php?title=Kratochvilova_et_al_2020a&diff=214912&oldid=prevScipediacontent: Scipediacontent moved page Draft Content 717943840 to Kratochvilova et al 2020a2021-02-15T11:33:00Z<p>Scipediacontent moved page <a href="/public/Draft_Content_717943840" class="mw-redirect" title="Draft Content 717943840">Draft Content 717943840</a> to <a href="/public/Kratochvilova_et_al_2020a" title="Kratochvilova et al 2020a">Kratochvilova et al 2020a</a></p>
<table class="diff diff-contentalign-left" data-mw="interface">
<tr style='vertical-align: top;' lang='en'>
<td colspan='1' style="background-color: white; color:black; text-align: center;">← Older revision</td>
<td colspan='1' style="background-color: white; color:black; text-align: center;">Revision as of 11:33, 15 February 2021</td>
</tr><tr><td colspan='2' style='text-align: center;' lang='en'><div class="mw-diff-empty">(No difference)</div>
</td></tr></table>Scipediacontenthttps://www.scipedia.com/wd/index.php?title=Kratochvilova_et_al_2020a&diff=214911&oldid=prevScipediacontent: Created page with " == Abstract == The presented paper concerns the development of condition monitoring system for railroad switches and crossings that utilizes vibration data. Successful utili..."2021-02-15T11:32:57Z<p>Created page with " == Abstract == The presented paper concerns the development of condition monitoring system for railroad switches and crossings that utilizes vibration data. Successful utili..."</p>
<p><b>New page</b></p><div><br />
== Abstract ==<br />
<br />
The presented paper concerns the development of condition monitoring system for railroad switches and crossings that utilizes vibration data. Successful utilization of such system requires a robust and efficient train type identification. Given the complex and unique dynamical response of any vehicle track interaction, the machine learning was chosen as a suitable tool. For design and validation of the system, real on-site acceleration data were used. The resulting theoretical and practical challenges are discussed.<br />
<br />
Document type: Article<br />
<br />
== Full document ==<br />
<pdf>Media:Draft_Content_717943840-beopen994-5874-document.pdf</pdf><br />
<br />
<br />
== Original document ==<br />
<br />
The different versions of the original document can be found in:<br />
<br />
* [http://dx.doi.org/10.1155/2020/8849734 http://dx.doi.org/10.1155/2020/8849734] under the license https://creativecommons.org/licenses/by/4.0/<br />
<br />
* [http://downloads.hindawi.com/journals/jat/2020/8849734.pdf http://downloads.hindawi.com/journals/jat/2020/8849734.pdf],<br />
: [http://downloads.hindawi.com/journals/jat/2020/8849734.xml http://downloads.hindawi.com/journals/jat/2020/8849734.xml],<br />
: [http://dx.doi.org/10.1155/2020/8849734 http://dx.doi.org/10.1155/2020/8849734]<br />
<br />
under the license https://creativecommons.org/licenses/by/4.0/</div>Scipediacontent