Detection of patterns in pressure signal of compressed air system using wavelet transform

Mohamad Thabet, David Sanders, Nils Bausch

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

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    Abstract

    This paper investigates detecting patterns in the pressure signal of a compressed air system (CAS) with a load/unload control using a wavelet transform. The pressure signal of a CAS carries useful information about operational events. These events form patterns that can be used as ‘signatures’ for event detection. Such patterns are not always apparent in the time domain and hence the signal was transformed to the time-frequency domain. Three different CAS operating modes were considered: idle, tool activation and faulty. The wavelet transforms of the CAS pressure signal reveal unique features to identify events within each mode. Future work will investigate creating machine learning tools for that utilize these features for fault detection in CAS.
    Original languageEnglish
    Title of host publicationEnergy and Sustainable Futures
    Subtitle of host publicationProceedings of 2nd ICESF 2020
    EditorsIosif Mporas, Pandelis Kourtessis, Amin Al-Habaibeh, Abhishek Asthana, Vladimir Vukovic, John Senior
    PublisherSpringer
    Pages61-67
    ISBN (Electronic)9783030639167
    ISBN (Print)9783030639150, 9783030639181
    DOIs
    Publication statusPublished - 30 Apr 2021
    Event2nd International Conference on Energy and Sustainable Futures: ICESF - University of Hertfordshire
    Duration: 10 Sept 202011 Sept 2020

    Publication series

    NameSpringer Proceedings in Energy
    PublisherSpringer
    Volume34
    ISSN (Print)2352-2534
    ISSN (Electronic)2352-2542

    Conference

    Conference2nd International Conference on Energy and Sustainable Futures
    Period10/09/2011/09/20

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