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Prism signal processing for machine condition monitoring II: Experimental data and fault detection

Abstract:
The Internet of Things (IoT) concept, alongside wireless technologies, supports the mounting of sensors in inaccessible positions and thus provides new opportunities for machine condition monitoring. This paper outlines experimental results using Prism signal processing to track rotor angular acceleration via a Wireless Acceleration Sensor (WAS) mounted on a rotating shaft. The instantaneous frequency and amplitude of each component of the angular acceleration is tracked, with a view to providing diagnostic information. The experimental results illustrate how amplitude data can provide indications of gear faults, via further Prism signal processing.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/ICPHYS.2018.8390748

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author


Publisher:
Institute of Electrical and Electronics Engineers
Host title:
1st IEEE International Conference on Industrial Cyber-Physical Systems (ICPS 2018)
Journal:
1st IEEE International Conference on Industrial Cyber-Physical Systems (ICPS 2018). More from this journal
Publication date:
2018-06-21
Acceptance date:
2018-03-11
DOI:


Keywords:
Pubs id:
pubs:833217
UUID:
uuid:1a7cb861-2245-47f0-8179-c6a6588a6a57
Local pid:
pubs:833217
Source identifiers:
833217
Deposit date:
2018-04-04

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