Abstract:
Algorithms and software and hardware for processing informative signals for filtering acoustic emission data in the recorded range of 2–600 kHz are analyzed and optimized. The method of spectral correlation analysis of signals from a broadband pulse source by determining the absorbing properties of the material at a particular sounding site can be used to identify defective sections of supercharger housings. Spectral correlation analysis of elastic wave signals is performed. The analysis of the noise parameters of the supercharger housings was carried out and the possibility of recording acoustic emission signals against a background of noise was established based on the determination of frequency ranges, as well as the values of acoustic emission signals and noise from operating units and the flow of transported gas.
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