• DocumentCode
    1374584
  • Title

    Knock acoustic signal estimation using parametric inversion

  • Author

    Boubal, Olivier ; Oksman, Jacques

  • Author_Institution
    Ecole Superieure d´´Electr., Gif-sur-Yvette, France
  • Volume
    49
  • Issue
    4
  • fYear
    2000
  • fDate
    8/1/2000 12:00:00 AM
  • Firstpage
    890
  • Lastpage
    895
  • Abstract
    Knock in spark ignition engines goes against car manufacturers´ efforts to reduce fuel consumption as well as exhaust gas emissions. This paper develops a signal-processing method to quantify knock. After discussing some classical techniques of knock energy estimation, an acoustical measurement technique is presented. An original signal-processing method based on a parametric compartmental model for both knock and apparatus is used. A special inversion technique is also proposed to obtain actual knock parameters. The knock-related parameters are computed through a two-step process. First, a deconvolution algorithm is used to obtain a sparse spike train signal. Then, an efficient inversion method follows. The whole process is applied to real data from a one-cylinder engine. Results are compared to those obtained from an existing technique. They demonstrate the usefulness of such a procedure in a common industrial application
  • Keywords
    acoustic signal processing; deconvolution; filtering theory; internal combustion engines; inverse problems; parameter estimation; time-frequency analysis; transient response; acoustical measurement technique; adapted inversion process; deconvolution algorithm; impulse response; knock acoustic signal estimation; nonlinear optimization; one-cylinder engine; parametric compartmental model; parametric inversion; signal-processing method; spark ignition engines; sparse spike train signal; time model; two-step process; Acoustic emission; Combustion; Electric shock; Engines; Estimation; Ignition; Resonance; Resonant frequency; Signal processing; Sparks;
  • fLanguage
    English
  • Journal_Title
    Instrumentation and Measurement, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9456
  • Type

    jour

  • DOI
    10.1109/19.863944
  • Filename
    863944