CN114838809A - Audio signal measuring method for self-adaptively improving frequency measurement precision - Google Patents
Audio signal measuring method for self-adaptively improving frequency measurement precision Download PDFInfo
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Abstract
The invention provides an audio signal measuring method for improving frequency measuring precision in a self-adaptive mode, and aims to provide an audio signal measuring method for improving the calculation resolution of FFT processing in a self-adaptive mode under the condition that the sampling rate and the actual FFT processing calculation data quantity are not changed, so that the signal frequency detecting precision is improved. The invention comprises the following procedures: firstly, setting the sampling rate of an analog-digital converter, setting a deviation proportion k and setting the data extraction number m to be 1, performing windowing processing on n acquired data during initial acquisition, performing FFT (fast Fourier transform) operation processing to acquire corresponding data in a complex form, performing a calibration algorithm according to the acquired parameters and the data to calculate the main frequency f1 of an input signal, further calculating the multiple relation x between the main frequency f1 of the input signal and the current frequency resolution fp, performing self-adaptive adjustment on the data extraction number m according to the comparison result of the multiple relation x and the set deviation proportion k, re-sampling after adjustment to acquire a frequency value f2 with higher precision, and outputting a measurement result after comparison. The invention is applied to the technical field of audio signal measurement.
Description
Technical Field
The invention is applied to the technical field of audio signal measurement, and particularly relates to an audio signal measurement method for adaptively improving frequency measurement precision.
Background
In life, various electronic devices with audio input, such as mobile phones, computers and the like, and various electrical appliances have the function of audio acquisition. The audio acquisition modules need to be verified in terms of their functions and performance before being shipped out of the factory. Common parameters for evaluating the audio acquisition function are: the frequency of the input signal, the amplitude of the input signal, noise floor, harmonic components, etc. The range of sound frequency which can be distinguished by human ears is 20-20000 Hz, so that the frequency of signals needing to be tested by the audio module is also in the range. According to the nyquist sampling theorem, as long as the sampling frequency is greater than or equal to twice the highest frequency of the effective signal, the sampling value can contain all the information of the original signal, and the sampled signal can be restored to the original signal without distortion. During the test, the sampling frequencies of the analog-to-digital converters are 48KHz, 96KHz and 192 KHz. In order to verify whether the frequency of the signal acquired by the audio module is accurate, the input signal needs to be converted from the time domain to the frequency domain, so that various indexes of the signal can be calculated more conveniently. The FFT (fast fourier transform) converts the time domain signal into the frequency domain signal, and the input parameters include: signal under test, sampling frequency.
The resolution calculation formula of the FFT process is: fp = Fs/N, fp is frequency resolution, Fs is sampling rate, and N is the data number of the acquired signals. If the accuracy of measuring the signal frequency is to be improved, the signal sampling rate needs to be reduced, or the number of data of the acquired signal needs to be increased.
For the uncertainty of the frequency of the front-end input signal, it cannot be determined how much the sampling rate is set to be more appropriate, and when the hardware determines, the chip of the analog-to-digital converter also determines, so that the sampling rate that the analog-to-digital converter can select to use is fixed. If the data volume of the acquired signals is simply increased, more resources and cost are consumed.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides the audio signal measuring method which can adaptively improve the calculation resolution of the FFT processing under the condition that the sampling rate and the actual FFT processing calculation data volume are not changed, thereby improving the signal frequency detection precision.
The technical scheme adopted by the invention is as follows: the audio signal measuring method of the present invention comprises the steps of:
step S1, setting a fixed sampling rate Fs and a deviation ratio k for the analog-to-digital converter for sampling;
step S2, setting a data extraction number m =1 during initial sampling, and not processing the data volume sampled by the analog-to-digital converter;
step S3, performing primary signal acquisition, reading N data sampled by the analog-to-digital converter and storing the data in a memory;
step S4, after finishing the storage, executing windowing processing on the N data, then performing FFT operation processing to generate N data in complex form, and calculating the main frequency f1 of the input signal according to the sampling rate Fs of the analog-to-digital converter, the N data in complex form, the data extraction number m and the calibration algorithm of the window function;
step S5, setting the multiple relation between the main frequency f1 of the input signal and the current frequency resolution fp as x, and x = f1/fp, fp = Fs/N, calculating the numerical value of the current multiple relation x according to the main frequency f1 of the input signal, and comparing the value of the multiple relation x with the value of the set deviation proportion k;
step S6, when x is less than k, adjusting a data extraction number m according to a primary frequency f1 of an input signal obtained by primary sampling, the number N of primary sampling data, a set deviation proportion k and a current frequency resolution fp, taking a value of the data extraction number m according to an intermediate variable N, wherein N = (fp ×/(N × f 1), simultaneously executing secondary signal acquisition according to the adjusted data extraction number m, obtaining new N data, executing windowing processing on the new N data, and then performing FFT operation processing to generate new N complex form data;
step S7, calculating the main frequency f2 of the input signal according to the sampling rate Fs of the analog-digital converter, the new N complex form data, the data extraction number m and the calibration algorithm of the window function;
and step S8, calculating the numerical value of the current multiple relation x according to the adjusted main frequency f2 of the input signal, comparing the value of the multiple relation x with the set value of the deviation proportion k, indicating that the frequency resolution reaches the set range when x > = k, and outputting the measurement result, otherwise, returning to the step S6.
According to the scheme, the audio signal acquired for the first time is analyzed, and whether the second processing analysis is needed or not is judged according to the analysis result. When evaluating the extracted data value, comparing the multiple relation x of the main frequency f1 of the input signal and the current frequency resolution fp with a set deviation proportion k, wherein k is a user set value, and when the k value is larger, the frequency resolution fp is higher. Whether the current detection frequency meets the resolution required by a user can be automatically evaluated, and finally, the frequency calculation precision can be improved. And the user is not required to adjust the sampling rate of the analog-to-digital converter and the number of collected data according to the frequency of the input signal. Wherein, the selection of the window function in the steps S4 and S7 is set according to the user' S requirement.
Preferably, the window function in step S4 and step S7 is a nuttall fourth-order third-order window function.
According to the scheme, the window function is selected according to the requirement of a user, the sidelobe attenuation of thd + n can be < -80dB by selecting nuttall four-term third-order window functions, and the measurement accuracy is further ensured.
Further preferably, the calculating frequency of the calibration algorithm of the nuttall quadrinomial third-order window function includes the following steps:
step C1, the data is processed by FFT operation to be N complex form data x + yj, the modulo p of the N complex data is obtained by calculation,
；
step C2, finding the data with the maximum module value
Data second largest in sum
And the data corresponds to the sequential position in the N data
And
；
step C3, calculating calibration coefficient according to the parameters
，
；
Step C4, calculating calibration coefficient according to the parameters
，
In which
、
、
All four-term third-order calculation of Nuttall
A constant of the coefficient;
step C5, calculating the frequency f,
。
according to the scheme, the frequency calibration algorithms of the window functions with different FFT processing are different, the calibration algorithm suitable for the frequency f can be selected according to the window functions to calculate the frequency f, and the calibration algorithm used in the scheme is a bimodal spectral line calibration method.
Preferably, in step S6, the value of the data extraction number m should satisfy m > = n and be a divisor of the current frequency resolution fp.
According to the scheme, when the data extraction number m is set, the sampling rate after data extraction is guaranteed to be an integer by limiting that the extraction number must be a common divisor of the sampling rate.
Preferably, the method for performing secondary signal acquisition according to the adjusted data extraction number m in step S6 specifically includes: reading m data when reading signals each time, storing the last read data in the m data read each time into a memory, and obtaining new N signal data after finishing storing the N data.
According to the scheme, the data volume actually read is N x m through the adjusted data extraction number m, the data finally obtained in each signal reading process is obtained, and more accurate sampling data are obtained through stable numerical values obtained after multiple times of reading.
Drawings
FIG. 1 is a flow chart of the present invention.
Detailed Description
As shown in fig. 1, in the present embodiment, the present invention includes the following steps:
step S1, setting a fixed sampling rate Fs and a deviation ratio k for the analog-to-digital converter for sampling;
step S2, setting a data extraction number m =1 during initial sampling, and not processing the data volume sampled by the analog-to-digital converter;
step S3, performing primary signal acquisition, reading N data sampled by the analog-to-digital converter and storing the data in a memory;
step S4, after finishing the storage, executing windowing processing on the N data, then performing FFT operation processing to generate N data in complex form, and calculating the main frequency f1 of the input signal according to the sampling rate Fs of the analog-to-digital converter, the N data in complex form, the data extraction number m and the calibration algorithm of the window function;
step S5, setting the multiple relation between the main frequency f1 of the input signal and the current frequency resolution fp as x, and x = f1/fp, fp = Fs/N, calculating the numerical value of the current multiple relation x according to the main frequency f1 of the input signal, and comparing the value of the multiple relation x with the value of the set deviation proportion k;
and step S6, when x is less than k, adjusting the data extraction number m according to the primary frequency f1 of the input signal obtained by primary sampling, the number N of the primary sampling data, the set deviation proportion k and the current frequency resolution fp, taking the value of the data extraction number m according to the intermediate variable N, wherein N = (fp ×/(N × f 1), simultaneously executing secondary signal acquisition according to the adjusted data extraction number m, obtaining new N data, executing windowing processing on the new N data, and then performing FFT operation processing to generate new N complex form data. The method for performing secondary signal acquisition according to the adjusted data extraction number m specifically comprises the following steps: reading m data when reading signals each time, storing the last read data in the m data read each time into a memory, and obtaining new N signal data after finishing storing the N data;
step S7, calculating the main frequency f2 of the input signal according to the sampling rate Fs of the analog-digital converter, the new N complex form data, the data extraction number m and the calibration algorithm of the window function;
and step S8, calculating the numerical value of the current multiple relation x according to the adjusted main frequency f2 of the input signal, comparing the value of the multiple relation x with the set value of the deviation proportion k, indicating that the frequency resolution reaches the set range when x > = k, and outputting the measurement result, otherwise, returning to the step S6.
In this embodiment, the window function in step S4 and step S7 selects nuttall quadrinomial third-order window function, and then the sidelobe attenuation of thd + n can be < -80 dB.
In addition, the window functions with corresponding performance can be freely selected according to the audio signal parameters to be measured in the steps S4 and S7, and an exemplary window function is shown in table 1:
in this embodiment, the calculating frequency of the calibration algorithm of the nuttall fourth-order window function includes the following steps:
step C1, the data is processed by FFT operation to be N complex form data x + yj, and the data is obtained by calculationThe modulo p of the N complex data,
(ii) a Wherein x in the complex form data x + yj represents a real part of the complex form data, and y represents an imaginary part of the complex form data;
step C2, finding the data with the maximum module value
Data second largest in sum
And the data corresponds to the sequential position in the N data
And
；
step C3, calculating calibration coefficient according to the parameters
，
；
Step C4, calculating calibration coefficient according to the parameters
，
Wherein
、
、
All four-term third-order calculation of Nuttall
The constant of the coefficient(s) is (are),
，
，
；
step C5, calculating the frequency f,
。
in this embodiment, the value of the data extraction number m in step S6 needs to satisfy m > = n and is a divisor of the current frequency resolution fp.
The first embodiment is as follows:
the frequency of an input audio signal is 20Hz, and the sampling number N of data is 8192;
comparison of conventional measurement methods:
example two:
the frequency of an input audio signal is 30Hz, and the sampling number N of data is 8192;
comparison of conventional measurement methods:
example three:
the frequency of an input audio signal is 40Hz, and the sampling number N of data is 8192;
comparison of conventional measurement methods:
and (4) conclusion: the sampling rate of an analog-digital converter is set through application, a deviation proportion k is set, the number m of data extraction is set to be 1, windowing processing is carried out on n acquired data during initial acquisition, then FFT operation processing is carried out to acquire corresponding data in a complex form, a calibration algorithm is executed according to the acquired parameters and the acquired data to calculate the main frequency f1 of an input signal, the multiple relation x of the main frequency f1 of the input signal and the current frequency resolution fp is further calculated, the number m of data extraction is adaptively adjusted according to the comparison result of the multiple relation x and the set deviation proportion k, secondary sampling and sampling data screening are carried out through the adjusted number of data extraction, a measured value is calculated according to a function after parameters are automatically adjusted to acquire a measured value, and the adaptive improvement of the measurement resolution is achieved. The method achieves the self-adaptive improvement of the calculation resolution of the FFT processing under the condition that the sampling rate and the actual FFT processing calculation data volume are not changed, and improves the signal frequency detection precision under the condition that the consumed resources and the cost are the same.
Claims (5)
1. An audio signal measuring method for adaptively improving frequency measurement accuracy is characterized by comprising the following steps:
step S1, setting a fixed sampling rate Fs and a deviation ratio k for the analog-to-digital converter for sampling;
step S2, setting a data extraction number m =1 during initial sampling, and not processing the data volume sampled by the analog-to-digital converter;
step S3, performing primary signal acquisition, reading N data sampled by the analog-to-digital converter and storing the data in a memory;
step S4, after finishing the storage, executing windowing processing on the N data, then performing FFT operation processing to generate N data in complex form, and calculating the main frequency f1 of the input signal according to the sampling rate Fs of the analog-to-digital converter, the N data in complex form, the data extraction number m and the calibration algorithm of the window function;
step S5, setting the multiple relation between the main frequency f1 of the input signal and the current frequency resolution fp as x, and x = f1/fp, fp = Fs/N, calculating the numerical value of the current multiple relation x according to the main frequency f1 of the input signal, and comparing the value of the multiple relation x with the value of the set deviation proportion k;
step S6, when x is less than k, adjusting a data extraction number m according to a primary frequency f1 of an input signal obtained by primary sampling, the number N of primary sampling data, a set deviation proportion k and a current frequency resolution fp, taking a value of the data extraction number m according to an intermediate variable N, wherein N = (fp ×/(N × f 1), simultaneously executing secondary signal acquisition according to the adjusted data extraction number m, obtaining new N data, executing windowing processing on the new N data, and then performing FFT operation processing to generate new N complex form data;
step S7, calculating the main frequency f2 of the input signal according to the sampling rate Fs of the analog-digital converter, the new N complex form data, the data extraction number m and the calibration algorithm of the window function;
and step S8, calculating the numerical value of the current multiple relation x according to the adjusted main frequency f2 of the input signal, comparing the value of the multiple relation x with the set value of the deviation proportion k, indicating that the frequency resolution reaches the set range when x > = k, and outputting the measurement result, otherwise, returning to the step S6.
2. The method as claimed in claim 1, wherein the window function in steps S4 and S7 is nuttall quaternary window function.
3. The audio signal measuring method for adaptively improving the frequency measurement accuracy according to claim 2, wherein the calculating the frequency by the calibration algorithm of the nuttally quadrinomial third-order window function comprises the following steps:
step C1, the data is processed by FFT operation to be N complex form data x + yj, the modulo p of the N complex data is obtained by calculation,
；
step C2, finding the data with the maximum module value
Data second largest in sum
And the data corresponds to the sequential position in the N data
And
；
step C3, calculating calibration coefficient according to the parameters
，
；
Step C4, calculating calibration coefficient according to the parameters
，
Wherein
、
、
All four-term third-order calculation of Nuttall
A constant of the coefficient;
step C5, calculating the frequency f,
。
4. the audio signal measuring method for adaptively improving the frequency measurement accuracy according to claim 1, wherein: in step S6, the value of the data extraction number m needs to satisfy m > = n and is a divisor of the current frequency resolution fp.
5. The audio signal measuring method according to claim 1, wherein the method for performing secondary signal acquisition according to the adjusted data extraction number m in step S6 specifically comprises: reading m data when reading signals each time, storing the last read data in the m data read each time into a memory, and obtaining new N signal data after finishing storing the N data.
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