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

Manus Henry; Vladimir V. Sinitsin

doi:10.1109/ICPHYS.2018.8390748

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

Manus Henry, Vladimir V. Sinitsin

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

9 Citations (Scopus)

9 Downloads (Pure)

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.

Original language	English
Title of host publication	Proceedings - 2018 IEEE Industrial Cyber-Physical Systems, ICPS 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	458-463
Number of pages	6
ISBN (Electronic)	9781538665312
DOIs	https://doi.org/10.1109/ICPHYS.2018.8390748
Publication status	Published - 15 Jun 2018
Externally published	Yes
Event	IEEE International Conference on Industrial Cyber-Physical Systems, - Saint Petersburg, Russian Federation Duration: 15 May 2018 → 18 May 2018 Conference number: 1 https://www.ieee-tems.org/events/1st-ieee-international-conference-industrial-cyber-physical-systems-icps-2018/#:~:text=ICPS%202018,May%2015%2D18%2C%202018.

Publication series

Name	Proceedings - 2018 IEEE Industrial Cyber-Physical Systems, ICPS 2018

Conference

Conference	IEEE International Conference on Industrial Cyber-Physical Systems,
Abbreviated title	ICPS 2018
Country/Territory	Russian Federation
City	Saint Petersburg
Period	15/05/18 → 18/05/18
Internet address	https://www.ieee-tems.org/events/1st-ieee-international-conference-industrial-cyber-physical-systems-icps-2018/#:~:text=ICPS%202018,May%2015%2D18%2C%202018.

Keywords

Accelerometer
Diagnostics
Prism signal processing
Rotating machinery
Wireless acceleration sensor

ASJC Scopus subject areas

Artificial Intelligence
Hardware and Architecture
Control and Optimization
Industrial and Manufacturing Engineering

Access to Document

10.1109/ICPHYS.2018.8390748

Post-PrintAccepted author manuscript, 1.2 MBLicence: Unspecified

Cite this

Henry, M., & Sinitsin, V. V. (2018). Prism signal processing for machine condition monitoring II: Experimental data and fault detection. In Proceedings - 2018 IEEE Industrial Cyber-Physical Systems, ICPS 2018 (pp. 458-463). (Proceedings - 2018 IEEE Industrial Cyber-Physical Systems, ICPS 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICPHYS.2018.8390748

Prism signal processing for machine condition monitoring II : Experimental data and fault detection. / Henry, Manus; Sinitsin, Vladimir V.

Proceedings - 2018 IEEE Industrial Cyber-Physical Systems, ICPS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 458-463 (Proceedings - 2018 IEEE Industrial Cyber-Physical Systems, ICPS 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

Henry, M & Sinitsin, VV 2018, Prism signal processing for machine condition monitoring II: Experimental data and fault detection. in Proceedings - 2018 IEEE Industrial Cyber-Physical Systems, ICPS 2018. Proceedings - 2018 IEEE Industrial Cyber-Physical Systems, ICPS 2018, Institute of Electrical and Electronics Engineers Inc., pp. 458-463, IEEE International Conference on Industrial Cyber-Physical Systems, Saint Petersburg, Russian Federation, 15/05/18. https://doi.org/10.1109/ICPHYS.2018.8390748

Henry M, Sinitsin VV. Prism signal processing for machine condition monitoring II: Experimental data and fault detection. In Proceedings - 2018 IEEE Industrial Cyber-Physical Systems, ICPS 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 458-463. (Proceedings - 2018 IEEE Industrial Cyber-Physical Systems, ICPS 2018). https://doi.org/10.1109/ICPHYS.2018.8390748

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

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Keywords

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