Separation of acoustic emission signals by computerized analyses

Features extracted from acoustic emission signals by means of different analysis methods can be evaluated by the application of pattern recognition computer programs. By these methods it can be established whether the employed features - maximum amplitude, signal rise time, pulse sum, pulse area, pulse energy and mean amplitude, as well as simple characteristics of frequency spectra - are capable of distinguishing acoustic emission signals or whether combinations of features lead to better results when single features fail. The efficiencies of different analyses and the pattern recognition programs are examined by four simulated types of signals. According to the employed analysis method there are distinct differences regarding the separation of acoustic emission. However, by applying feature combinations, signal groups not separable by single analysis methods can be distinguished.