Conference item
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
Actions
Access Document
- Files:
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(Preview, Accepted manuscript, pdf, 1.1MB, Terms of use)
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- Publisher copy:
- 10.1109/ICPHYS.2018.8390748
Authors
- 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:
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pubs:833217
- UUID:
-
uuid:1a7cb861-2245-47f0-8179-c6a6588a6a57
- Local pid:
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pubs:833217
- Source identifiers:
-
833217
- Deposit date:
-
2018-04-04
Terms of use
- Copyright holder:
- Institute of Electrical and Electronics Engineers
- Copyright date:
- 2018
- Notes:
- © 2018 IEEE. This is the accepted manuscript version of the article. The final version is available online from Institute of Electrical and Electronics Engineers at: https://doi.org/10.1109/ICPHYS.2018.8390748
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