Deep Learning Based Classification of Rail Defects Using On-board Monitoring in the Stockholm Underground
The purpose of this work is to find out if an artificial neural network can be useful purpose of this work is to find out if an artificial neural network can be useful in order to detect rail squats with the existing Quiet Track Measurement System (QTMS). Squats are surface-initiated rail defects which...
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| Format: | Others |
| Language: | English |
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KTH, Spårfordon
2020
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273576 |