An intelligent air-noise recognition system is described that uses pattern recognition techniques to distinguish noise signatures of five different types of acoustic sources, including jet planes, propeller planes, a helicopter, train, and wind turbine. Information for classification is calculated using the power spectral density and autocorrelation taken from the output of a single microphone. Using this system, as many as 90 percent of test recordings were correctly identified, indicating that the linear discriminant functions developed can be used for aerospace source identification.


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    Title :

    A smart pattern recognition system for the automatic identification of aerospace acoustic sources


    Contributors:

    Publication date :

    1989-04-01


    Type of media :

    Conference paper


    Type of material :

    No indication


    Language :

    English


    Keywords :