Time domain digit weighting method for non-stable noise signals

Abstract

The invention relates to a time domain digit weighting method for non-stable noise signals. The method includes the following steps that (1) data acquisition is conducted on the non-stable noise signals to acquire noise digital signals p(Tau); (2) a weighting amplitude curve A(f) is established according to the octave sound level modification value of a noise weighting network; (3) mirror transformation processing is conducted on the weighting amplitude curve A(f), and a non-periodic real even function A'(f) of a frequency domain weighting network is acquired; (4) inverse Fourier transform is carried out to acquire an impulse response function A'(t) of the weighting network; (5) a window function Wbeta(t) is selected to conduct windowing truncation processing on the A'(t); (6) a windowing weighting wavelet function A'wbeta(t) is acquired; (7) interpolation resampling is conducted on the windowing weighting wavelet function, and the time interval of the windowing weighting wavelet function is made to be consistent with the time interval of collected original noise digital signals; (8) the acquired non-stable noise digital signals p(Tau) and the windowing weighting wavelet function are subjected to related comparison transform, so that time domain weighting fluctuation signals pw(t) are acquired; (9) a weighting overall sound pressure level curve Lw(t) of the non-stable signals is obtained through sound level transform calculation.

Description

technical field [0001] The invention relates to a noise signal analysis and processing method, in particular to a time-domain digital weighting method for a non-stationary noise signal whose frequency component changes rapidly with time. Background technique [0002] The human ear has a large dynamic range of sound perception, and the loudness perceived by the auditory sense is proportional to the logarithm of the sound pressure ratio. Therefore, the concept of sound pressure level is used in acoustics to reflect the human ear's self-perceived perception of loudness. . In addition, due to the particularity of the structure of the human ear, the human ear has different sensitivities to noises of different frequencies. In order to obtain an evaluation standard consistent with human subjective perception, there is a certain relationship between the measured decibel value and the subjectively felt loudness. Relevance, the International Organization for Standardization applies d...

AI Technical Summary

Problems solved by technology

This calculation method is cumbersome and complicated, and requires multiple filtering calculations (the number of subbands), which requires a large amount of calculation. At the same time, there is also the problem of aliasing of subband spectrum energy and causing calculation errors.

In addition, this method cannot obtain the weighted time-domain fluctuation signal of the sound

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