• DocumentCode
    616881
  • Title

    Detecting the presence of large biomass particles in pneumatic conveying pipelines using an acoustic sensor

  • Author

    Duo Sun ; Yong Yan ; Carter, Robert M. ; Gang Lu ; Riley, G. ; Wood, Michael

  • Author_Institution
    Sch. of Eng. & Digital Arts, Univ. of Kent, Canterbury, UK
  • fYear
    2013
  • fDate
    6-9 May 2013
  • Firstpage
    1487
  • Lastpage
    1490
  • Abstract
    This paper proposes a novel approach to online automatic detection of the presence of large biomass particles in a pneumatic conveying pipeline using an acoustic emission sensor and time-frequency analysis techniques. The acoustic sensor is used to capture the sound emitted from the collisions between biomass particles and pipe wall. Time-frequency analysis technique is used to eliminate environmental noise from the acoustic signal, extract the revealing information about the collisions, and identify the large particles. The acoustic sensor together with its signal conditioning unit is integrated into a compact enclosure, which can be easily attached to the outer face of a pneumatic pipeline. Experimental results obtained from an industrial pneumatic conveyor demonstrate the method works well and results are promising.
  • Keywords
    acoustic emission; acoustic signal processing; conveyors; pipelines; pneumatic systems; renewable materials; sensors; time-frequency analysis; acoustic emission sensor; acoustic signal; environmental noise; industrial pneumatic conveyor; large biomass particles; online automatic detection; pneumatic conveying pipelines; signal conditioning unit; time-frequency analysis techniques; Acoustic sensors; Acoustics; Biomass; Noise; Pipelines; Time-frequency analysis; acoustic sensor; biomass; fuel handling; large particle detection; time-frequency analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Instrumentation and Measurement Technology Conference (I2MTC), 2013 IEEE International
  • Conference_Location
    Minneapolis, MN
  • ISSN
    1091-5281
  • Print_ISBN
    978-1-4673-4621-4
  • Type

    conf

  • DOI
    10.1109/I2MTC.2013.6555661
  • Filename
    6555661