Removal of Stationary Sinusoidal Noise from Random Vibration Signals
Author(s) -
Brian Johnson,
Jerome S. Cap
Publication year - 2018
Publication title -
osti oai (u.s. department of energy office of scientific and technical information)
Language(s) - English
Resource type - Reports
DOI - 10.2172/1423933
Subject(s) - sine , sine wave , vibration , acoustics , noise (video) , random noise , chirp , random vibration , harmonic , fourier transform , mathematics , algorithm , computer science , speech recognition , engineering , physics , mathematical analysis , artificial intelligence , optics , laser , geometry , voltage , image (mathematics) , electrical engineering
In random vibration environments, sinusoidal line noise may appear in the vibration signal and can affect analysis of the resulting data. We studied two methods which remove stationary sine tones from random noise: a matrix inversion algorithm and a chirp-z transform algorithm. In addition, we developed new methods to determine the frequency of the tonal noise. The results show that both of the removal methods can eliminate sine tones in prefabricated random vibration data when the sine-to-random ratio is at least 0.25. For smaller ratios down to 0.02 only the matrix inversion technique can remove the tones, but the metrics to evaluate its effectiveness also degrade. We also found that using fast Fourier transforms best identified the tonal noise, and determined that band-pass-filtering the signals prior to the process improved sine removal. When applied to actual vibration test data, the methods were not as effective at removing harmonic tones, which we believe to be a result of mixed-phase sinusoidal noise.
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