Abstract

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.

Document type: Article

Full document

The PDF file did not load properly or your web browser does not support viewing PDF files. Download directly to your device: Download PDF document

Original document

The different versions of the original document can be found in:

http://downloads.hindawi.com/journals/jat/2020/8849734.xml,
http://dx.doi.org/10.1155/2020/8849734
under the license https://creativecommons.org/licenses/by/4.0/
Back to Top

Document information

Published on 01/01/2020

Volume 2020, 2020
DOI: 10.1155/2020/8849734
Licence: Other

Document Score

0

Views 0
Recommendations 0

Share this document

claim authorship

Are you one of the authors of this document?