Audio signal measuring method capable of adaptively improving frequency measurement precisionTechnical Field
The invention is applied to the technical field of audio signal measurement, and particularly relates to an audio signal measurement method capable of adaptively improving frequency measurement accuracy.
Background
Various electronic devices with audio input such as mobile phones and computers and various electrical appliances which are common in life have the function of audio acquisition. These audio acquisition modules require verification of their function and performance prior to shipment. Common parameters for evaluating the audio acquisition function are: the frequency of the input signal, the amplitude of the input signal, the noise floor, harmonic components, etc. The range of sound frequencies that can be distinguished for the human ear is 20-20000 Hz, so the frequency of the signal that our audio module needs to test is also in this 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 sampled value may contain all information of the original signal, and the sampled signal may be restored to the original signal without distortion. During the test, the sampling frequency of the common analog-to-digital converter is 48KHz,96KHz and 192KHz. In order to verify whether the frequency of the signal collected 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) is to convert a time domain signal into a frequency domain signal, and the input parameters are: signal under test, sampling frequency.
The resolution calculation formula of the FFT processing is: fp=fs/N, where fp is the frequency resolution, fs is the sampling rate, and N is the number of data of the acquired signal. If the accuracy of measuring the signal frequency is to be improved, it is necessary to reduce the signal sampling rate or increase the number of data of the acquired signal.
For uncertainty of the front-end input signal frequency, it cannot be determined how much more proper the sampling rate is set, and when the hardware determines that the chip of the analog-to-digital converter also determines, then the sampling rate that the analog-to-digital converter can select to use is fixed. If the data volume of the acquisition signal is simply increased, more resources and cost are required.
Disclosure of Invention
The invention aims to solve the technical problem of overcoming the defects of the prior art and providing the audio signal measurement method which adaptively improves the calculation resolution of FFT processing under the condition that the sampling rate and the calculated data quantity of actual FFT processing are unchanged, thereby improving the signal frequency detection precision.
The technical scheme adopted by the invention is as follows: the audio signal measuring method comprises the following steps:
Step S1, setting a fixed sampling rate Fs for an analog-digital converter for sampling and setting a deviation ratio as k;
step 2, setting data extraction number m=1 during primary sampling, wherein the data amount sampled by the analog-to-digital converter is not processed;
s3, performing primary signal acquisition, reading N data sampled by the analog-to-digital converter and storing the N data in a memory;
Step S4, after finishing the storage, performing windowing processing on the N data, performing FFT operation processing to generate N complex-form data, and calculating the main frequency f1 of the input signal according to the sampling rate Fs of the analog-to-digital converter, the N complex-form data, the data extraction number m and a window function calibration algorithm;
Step S5, setting the multiple relation between the main frequency f1 of the input signal and the current frequency resolution fp as x, wherein 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, the main frequency f1 of the input signal is obtained according to primary sampling, the number N of primary sampling data, the set deviation proportion k and the current frequency resolution fp are subjected to adjustment of the data extraction number m, the value of the data extraction number m is subjected to value taking according to an intermediate variable N, n= (fp x k)/(N x f 1), secondary signal acquisition is performed according to the adjusted data extraction number m, new N data are obtained, and after windowing processing is performed on the new N data, FFT operation processing is performed on the new N data, so that new N complex forms of data are generated;
Step S7, calculating the main frequency f2 of the input signal according to the sampling rate Fs of the analog-to-digital converter, the new N complex data, the data extraction number m and a calibration algorithm of a window function;
And S8, calculating the numerical value of the current multiple relation x according to the main frequency f2 of the adjusted input signal, comparing the value of the multiple relation x with the value of the set deviation proportion k, and when the value of x > =k, indicating that the frequency resolution reaches the set range and outputting a 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 the extracted data value is evaluated, the multiple relation x of the main frequency f1 of the input signal and the current frequency resolution fp is adopted to be compared 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 the user can be automatically evaluated, and finally the accuracy of frequency calculation can be improved. And the user is not required to adjust the sampling rate of the analog-to-digital converter and the number of acquired data according to the frequency of the input signal. Wherein, the selection of the window function in step S4 and step S7 is set according to the user' S requirement.
In a preferred embodiment, the window functions in step S4 and step S7 are nuttall th-order window functions.
According to the scheme, the window function is selected according to the requirement of a user, and through selecting nuttall four third-order window functions, the purpose is to enable the side lobe attenuation of thd+n to be < -80dB, so that the measurement accuracy is ensured.
Further preferably, the calculating frequency of the calibration algorithm of the nuttall four third-order window functions includes the following steps:
Step C1, the data are processed by FFT operation and are N complex form data x+yj, the modulus p of the N complex form data is obtained by calculation,；
Step C2, finding the data with the maximum modulus valueAnd the second largest data of the modulusAnd the data corresponds to a sequential position in the N dataAnd；
Step C3, calculating the calibration coefficient according to the parameters，；
Step C4, calculating a calibration coefficient according to the parameters，Wherein、、All are Nuttall four-term third-order calculationsA constant of the coefficient;
Step C5, calculating the frequency f,。
The above scheme shows that the frequency calibration algorithm of the FFT processing different window functions is different, and the frequency f can be calculated by selecting the calibration algorithm suitable for the FFT processing according to the window functions.
In a preferred embodiment, the value of the data extraction number m in step S6 needs to 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 is guaranteed to be an integer by limiting that the extraction number is necessarily a common divisor of the sampling rate.
In a preferred embodiment, in step S6, the method for performing secondary signal acquisition according to the adjusted data extraction number m specifically includes: and reading m data when the signal is read every time, and storing the data which is read out last in the m data read at the time in a memory, so as to obtain new N signal data after finishing N times of data storage.
According to the scheme, the data quantity actually read is N x m through the adjusted data extraction number m, the data finally obtained when the signal is read each time is taken, and more accurate sampling data is obtained through taking stable values after multiple times of reading.
Drawings
Fig. 1 is a flow chart of the present invention.
Detailed Description
As shown in fig. 1, in this embodiment, the present invention includes the steps of:
Step S1, setting a fixed sampling rate Fs for an analog-digital converter for sampling and setting a deviation ratio as k;
step 2, setting data extraction number m=1 during primary sampling, wherein the data amount sampled by the analog-to-digital converter is not processed;
s3, performing primary signal acquisition, reading N data sampled by the analog-to-digital converter and storing the N data in a memory;
Step S4, after finishing the storage, performing windowing processing on the N data, performing FFT operation processing to generate N complex-form data, and calculating the main frequency f1 of the input signal according to the sampling rate Fs of the analog-to-digital converter, the N complex-form data, the data extraction number m and a window function calibration algorithm;
Step S5, setting the multiple relation between the main frequency f1 of the input signal and the current frequency resolution fp as x, wherein 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 S6, when x is less than k, the main frequency f1 of the input signal is obtained according to primary sampling, the number N of primary sampling data, the set deviation proportion k and the current frequency resolution fp are subjected to adjustment of the data extraction number m, the value of the data extraction number m is subjected to value taking according to an intermediate variable N, n= (fp x k)/(N x f 1), meanwhile, secondary signal acquisition is performed according to the adjusted data extraction number m, new N data are obtained, and after windowing processing is performed on the new N data, FFT operation processing is performed on the new N data, so that new N complex data are generated. The method for executing secondary signal acquisition according to the adjusted data extraction number m specifically comprises the following steps: reading m data when reading signals every time, and storing the data read out last in the m data read at the time in a memory to obtain new N signal data after finishing N times of data storage;
Step S7, calculating the main frequency f2 of the input signal according to the sampling rate Fs of the analog-to-digital converter, the new N complex data, the data extraction number m and a calibration algorithm of a window function;
And S8, calculating the numerical value of the current multiple relation x according to the main frequency f2 of the adjusted input signal, comparing the value of the multiple relation x with the value of the set deviation proportion k, and when the value of x > =k, indicating that the frequency resolution reaches the set range and outputting a measurement result, otherwise, returning to the step S6.
In this embodiment, the window functions in step S4 and step S7 select nuttall four third-order window functions, so as to achieve that the side lobe attenuation of thd+n can be < -80dB.
In addition, step S4 and step S7 may freely select a window function of a corresponding performance according to the audio signal parameter to be measured, and the example window functions are shown in table 1:
；
in this embodiment, the calculating frequency of the calibration algorithm of the nuttall four third-order window functions includes the following steps:
Step C1, the data are processed by FFT operation and are N complex form data x+yj, the modulus p of the N complex form data is obtained by calculation,; Wherein x in the complex form data x+yj represents the real part of the complex form data and y represents the imaginary part of the complex form data;
Step C2, finding the data with the maximum modulus valueAnd the second largest data of the modulusAnd the data corresponds to a sequential position in the N dataAnd；
Step C3, calculating the calibration coefficient according to the parameters，；
Step C4, calculating a calibration coefficient according to the parameters，Wherein、、All are Nuttall four-term third-order calculationsThe constant of the coefficient is set to be,，，；
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 be a divisor of the current frequency resolution fp.
Embodiment one:
the frequency of the input audio signal is 20Hz, and the sampling number N of the data is 8192;
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Comparison of conventional measurement methods:
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embodiment two:
The frequency of the input audio signal is 30Hz, and the sampling number N of the data is 8192;
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Comparison of conventional measurement methods:
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Embodiment III:
The frequency of the input audio signal is 40Hz, and the sampling number N of the data is 8192;
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Comparison of conventional measurement methods:
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Conclusion: setting the sampling rate of the analog-to-digital converter, setting a deviation ratio k and setting the data extraction number m as 1, performing windowing processing on the acquired n data during primary acquisition, performing FFT operation processing to acquire corresponding complex data, performing calibration algorithm calculation to calculate the main frequency f1 of an input signal according to the acquired parameters and the data, further calculating the multiple relation x of 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 multiple relation x and the set deviation ratio k, performing secondary sampling and screening of the sampled data through the adjusted data extraction number, and performing calculation to acquire a measured value according to a function after automatic parameter adjustment to realize self-adaptive improvement of the measurement resolution. The method and the device achieve the purpose of adaptively improving the calculation resolution of FFT processing under the condition that the sampling rate and the calculated data quantity of actual FFT processing are unchanged, and improve the signal frequency detection precision under the condition that the consumed resources and the cost are the same.