Railway Point-Operating Machine Fault Detection Using Unlabeled Signaling Sensor Data

Railway Point-Operating Machine Fault Detection Using Unlabeled Signaling Sensor Data

In this study, we propose a methodology for the identification of potential fault occurrences of railway point-operating machines, using unlabeled signal sensor data. Data supplied by Network Rail, UK, is processed using a fast Fourier transform signal processing approach, coupled with the mean and...

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Bibliographic Details
Main Authors: Pritesh Mistry, Phil Lane, Paul Allen
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Sensors
Subjects:
condition monitoring
signal processing
fast Fourier transform
railway point-operating machines
turnout
fault detection
Online Access:https://www.mdpi.com/1424-8220/20/9/2692

Internet

https://www.mdpi.com/1424-8220/20/9/2692

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