• DocumentCode
    987837
  • Title

    Higher Order Statistics and Independent Component Analysis for Spectral Characterization of Acoustic Emission Signals in Steel Pipes

  • Author

    De la Rosa, Juan José González ; Piotrkowski, Rosa ; Ruzzante, José Evaristo

  • Author_Institution
    Cadiz Univ., Algeciras
  • Volume
    56
  • Issue
    6
  • fYear
    2007
  • Firstpage
    2312
  • Lastpage
    2321
  • Abstract
    Higher order statistics (HOS) are used to characterize acoustic emission events in ring-type samples from steel pipes for the oil industry. Cumulants are used twofold. First, diagonal bispectrum allows the separation of the primary (original) deformation from the reflections produced mainly in the suppressed chord. These longitudinal reflections can hardly be extracted via second-order methods, e.g., wavelet packets and power spectra, because they are partially masked by both Gaussian and non-Gaussian noise. Second, a cumulant-based independent component analysis may be used before the bispectrum, as a preprocessing complement, in the case of multiple-source and multiple-channel recordings. This algorithm suppresses the mutual influence of the sources and sensors. Sample registers were acquired by wide-frequency-range transducers (100-800 kHz) and digitalized by a 2.5-MHz, 12-bit analog-to-digital converter.
  • Keywords
    acoustic emission testing; acoustic signal processing; higher order statistics; independent component analysis; nondestructive testing; petroleum industry; pipes; acoustic emission signals; cumulants; frequency 100 kHz to 800 kHz; higher order statistics; independent component analysis; longitudinal reflections; multiple-channel recordings; oil industry; spectral characterization; steel pipes; wide-frequency-range transducers; word length 12 bit; Acoustic emission; Acoustic reflection; Analog-digital conversion; Gaussian noise; Higher order statistics; Independent component analysis; Petroleum industry; Steel; Transducers; Wavelet packets; Acoustic emission (AE); acoustic signal processing; frequency measurement; frequency-domain analysis; higher order statistics (HOS); nonlinearities; time–frequency analysis;
  • fLanguage
    English
  • Journal_Title
    Instrumentation and Measurement, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9456
  • Type

    jour

  • DOI
    10.1109/TIM.2007.907945
  • Filename
    4389102