Long-distance tubular column liquid level depth efficient detection method based on short-time linear frequency modulation excitation

Abstract

The invention belongs to the field of liquid level detection, and relates to a long-distance tubular column liquid level depth efficient detection method based on short-time linear frequency modulation excitation, which comprises the following steps: inputting linear frequency modulation sound waves into a long-distance tubular column, and carrying out continuous resonance on an air column in the long-distance tubular column; collecting an acoustic signal of an air column in the pipe; filtering the acoustic signal by using a filter; performing windowing processing on the time domain signal by adopting a window function; calculating a frequency amplitude at a non-integer serial number in the excitation frequency band by using discrete Fourier transform to obtain a refined frequency spectrum; carrying out normalization processing on the refined frequency spectrum and taking a logarithm to obtain a logarithm frequency spectrum; smooth filtering processing is carried out on the logarithmic spectrum, and the logarithmic spectrum and the filtering result spectrum are correspondingly subtracted to obtain the resonance characteristic of the signal; carrying out fast Fourier transform on the resonance characteristics, calculating a correction value by adopting a three-spectral-line interpolation method, and estimating the number of formants of the resonance characteristics; the liquid level depth of the long-distance pipe column is calculated according to the formant number; the method has the advantages that the anti-noise capability is high, the measurement result is not influenced by the arrangement mode of the tubular columns, and the time required for measurement is short.

Description

Technical Field

[0001] The present invention belongs to the field of long-distance pipe string liquid level depth detection, and particularly relates to an efficient detection method for long-distance pipe string liquid level depth based on short-time linear frequency modulation excitation. Background Technique

[0002] In fields such as petroleum engineering, chemical engineering, and aerospace, liquid level is an important control parameter. Real-time, rapid, and accurate liquid level detection is an important link for judging the working state of the system and conducting monitoring and maintenance, and has become a necessary task to ensure safe production. In the practical applications of industrial scenarios such as oil well flowing liquid level measurement, cross-regional long pipeline transportation, and large-scale water conservancy projects, the length of the pipe string usually exceeds 500m, and even reaches several kilometers. The demand for liquid level detection over long distances is becoming increasingly prominent.

[0003] At present, the liquid level measurement method based on the pipe string sound field model excites the air column in the pipe by sending white noise and high-frequency linear sound waves, and after collecting the resonance signal, signal processing is carried out, and the liquid level depth is measured according to the mathematical relationship between the resonance characteristics and the pipe string length. However, during the long-distance propagation process, the high-frequency components of the sound wave attenuate rapidly and are often completely attenuated before reaching the liquid level, seriously affecting the excitation effect; secondly, the sound signal collected by the sound sensor not only contains the resonance signal of the air column, but also contains interference such as the excitation source itself and complex background noise. The weak resonance signal is easily submerged, seriously interfering with the extraction and recognition of resonance characteristics, and thus affecting the stability and accuracy of liquid level measurement, and even resulting in large measurement errors. Summary of the Invention

[0004] To solve the above problems existing in the prior art, the present invention proposes an efficient detection method for long-distance pipe string liquid level depth based on short-time linear frequency modulation excitation. The method includes:

[0005] S101. Set the measuring device at the port of the long-distance pipe string;

[0006] S102. Set the parameters of the measuring device, and the measuring device inputs the generated linear frequency modulation sound wave into the long-distance pipe string to continuously resonate the air column in the pipe;

[0007] S103. Collect the acoustic signal of the air column in the pipe, filter the acoustic signal, and perform normalization processing on the filtered signal to obtain the normalized time-domain signal;

[0008] S104. Perform windowing processing on the normalized time-domain signal by using the plancktaper window function;

[0009] S105. Calculate the frequency amplitudes at non-integer sequence numbers within the excitation frequency band using the discrete Fourier transform based on the windowed time-domain signal. Add additional refined frequency points between every two adjacent spectral lines to obtain a more densely distributed refined spectrum. Perform normalization processing on the obtained refined spectrum, and take the logarithm of the normalized amplitude spectrum.

[0010] S106. Perform smoothing filtering on the logarithmic spectrum to obtain the filtering result.

[0011] S107. Subtract the logarithmic spectrum from the filtering result corresponding to each other to obtain the resonance characteristics of the signal.

[0012] S108. Perform a fast Fourier transform on the resonance characteristics to obtain H(r). Calculate the correction amount using the three-spectral-line interpolation method based on the obtained H(r), and estimate the number of resonance peaks of the resonance characteristics according to the correction amount. Calculate the liquid level depth of the long-distance pipe string according to the number of resonance peaks.

[0013] Advantages of the present invention:

[0014] The method proposed by the present invention uses short-time linear frequency modulation acoustic wave excitation, which can effectively solve problems such as rapid attenuation of the excitation acoustic wave energy caused by noise excitation and difficulty in extracting weak resonance characteristics. The detection method is not limited by the pipe string arrangement method, has good anti-noise performance, can achieve rapid extraction of resonance characteristics, expands the measurement range, provides reliable technical support for the liquid level detection of long-distance pipe strings under complex noise backgrounds, and realizes accurate detection of the liquid level depth of long-distance pipe strings in multiple application scenarios. The present invention uses the plancktaper window function to perform windowing processing on the time-domain signal, and estimates the correction amount of the signal through the three-spectral-line interpolation method, thereby improving the accuracy of the liquid level detection of long-distance pipe strings. Description of the drawings

[0015] Figure 1 It is the flowchart of the method of the present invention;

[0016] Figure 2 It is the time-domain diagram of the acoustic signal collected by the acoustic sensor in the embodiment;

[0017] Figure 3 It is the signal diagram of the acoustic signal collected in the embodiment after time-varying band-pass filtering;

[0018] Figure 4 It is the signal diagram obtained by performing normalization processing on the filtered signal in the embodiment;

[0019] Figure 5 It is the time-domain signal diagram of the normalized signal plus the plancktaper window in the embodiment;

[0020] Figure 6 It is the refined spectrum diagram obtained by calculating the excitation frequency band using the discrete Fourier transform in the embodiment;

[0021] Figure 7 It is a comparison diagram between the result after smoothing filtering of the logarithmic spectrum obtained after refining the spectrum normalization in the embodiment and the logarithmic spectrum;

[0022] Figure 8 It is a signal resonance characteristic diagram obtained by subtracting the logarithmic spectrum from its smoothing filtering result in the embodiment in a spectrum-by-spectrum manner;

[0023] Figure 9 It is a schematic diagram of the calculation result of the number of resonance peaks obtained by estimating the three-spectrum line interpolation parameters after performing FFT on the resonance characteristics in the embodiment. Specific implementation manner

[0024] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0025] An efficient detection method for the liquid level depth of a long-distance pipe string based on short-time linear frequency modulation excitation, the method comprising:

[0026] S101. Set the measuring device at the port of the long-distance pipe string;

[0027] S102. Set the parameters of the measuring device, and the measuring device inputs the generated linear frequency modulation acoustic wave into the long-distance pipe string to continuously resonate the air column in the pipe;

[0028] S103. Collect the acoustic signal of the air column in the pipe, filter the acoustic signal, and perform normalization processing on the filtered signal to obtain the normalized time-domain signal;

[0029] S104. Window the normalized time-domain signal using the plancktaper window function;

[0030] S105. Calculate the frequency amplitudes at non-integer sequence numbers in the excitation frequency band according to the windowed time-domain signal using the discrete Fourier transform, add additional refined frequency points between every two adjacent spectral lines to obtain a more densely distributed refined spectrum; perform normalization processing on the obtained refined spectrum, and take the logarithm of the normalized amplitude spectrum;

[0031] S106. Smoothly filter the logarithmic spectrum to obtain a filtering result;

[0032] S107. Subtract the logarithmic spectrum from the filtering result correspondingly to obtain the resonance characteristics of the signal;

[0033] S108. Perform a fast Fourier transform on the resonance characteristics to obtain H(r); calculate the correction amount using the three-spectrum line interpolation method based on the obtained H(r), and estimate the number of resonance peaks of the resonance characteristics; calculate the liquid level depth of the long-distance pipe string according to the number of resonance peaks.

[0034] The present invention provides a method for detecting the liquid level depth of a long-distance pipe string based on short-time linear frequency modulation excitation, as Figure 1 shown, including the following steps:

[0035] S1. Install the measurement device, including a signal generator, an excitation sound source, and a sound sensor, all installed on the same side of the pipe string port. The excitation sound source is installed at the pipe orifice, and the sound sensor is installed close to the excitation sound source;

[0036] S2. Set the sampling frequency f s , the total sampling time T, the starting frequency f L of the linear frequency modulation signal, the termination frequency f U . Use the signal generator to generate a linear frequency modulation signal, transmit it to the excitation sound source for continuous driving, and generate a linear frequency modulation sound wave;

[0037] S3. Input the linear frequency modulation sound wave into the pipe string to continuously resonate the air column in the pipe. The sound sensor collects the acoustic signal y0(n) under linear frequency modulation excitation, which mainly includes the linear frequency modulation sound wave signal generated by the excitation sound source and its higher-order responses, the resonance signal of the air column in the pipe, noise, and its interference;

[0038] S4. Construct a time-varying band-pass filter with a center frequency f c that tracks the instantaneous frequency change of the linear frequency modulation sound wave and a bandwidth F b . Filter the acoustic signal y0(n) to obtain y1(n), effectively extract the response signal components within the selected frequency range, and at the same time effectively suppress the higher-order response u(n) of the linear frequency modulation sound wave and the noise z(n) of the measurement system and the environment. Normalize the filtered time-domain signal to obtain y norm (n), and normalize the signal amplitude to the range of [-1, 1].

[0039] S5. For the signal y norm (n) normalized in step S4, use the plancktaper window function w p (n) for windowing to obtain the weighted signal y(n) = y norm (n) · w p (n). Through windowing, effectively reduce the Gibbs effect of the spectrum and reduce the spectrum amplitude distortion caused by endpoint discontinuity.

[0040] S6. Calculate the frequency amplitudes at non-integer sequence numbers within the excitation frequency band in the windowed signal y(n) using the discrete Fourier transform. Add additional refined frequency points between every two adjacent spectral lines to obtain a more densely distributed refined spectrum Y l (k), which makes the spectrum smoother while significantly reducing the computational amount of frequency-domain analysis. Perform frequency-domain normalization on the refined spectrum to obtain , and take the logarithm of the normalized spectrum to obtain the logarithmic spectrum Y(k).

[0041] S7. Perform smoothing filtering on Y(k) to obtain the filtering result Ω(k). Subsequently, subtract Y(k) from Ω(k) spectrally to extract the signal resonance characteristic G(k). G(k) contains a series of continuous resonance peaks and has very strong periodicity. The number of signal resonance peaks can be obtained through a parameter precise estimation algorithm.

[0042] S8. The number of resonance peaks η is also the normalized frequency of the periodic component in the resonance characteristic G(k). Perform a fast Fourier transform on the resonance characteristic G(k) to obtain H(r). Denote l as the largest spectral line number in H(r), and denote δ (-0.5 ≤ δ ≤ 0.5) as the normalized frequency correction amount. Use the highest spectral line in H(r) and the two adjacent sub-highest spectral lines on its left and right to calculate the correction amount δ using the three-spectral-line interpolation method, and finally calculate the precise estimated value of the number of resonance peaks.

[0043] S9. Calculate the liquid column liquid level depth at long distances based on the mathematical relationship between the number of resonance peaks obtained from precise estimation and the liquid level depth.

[0044] In this embodiment, a measurement device is installed. The excitation sound source is installed at the mouth of the experimental pipeline, and the sound sensor is installed at the front end of the excitation sound source. The inner diameter d of the experimental pipeline c = 0.46 m, and the actual distance from the pipe mouth to the liquid level is 956.29 m.

[0045] Set the signal sampling frequency f s = 5120 Hz, the starting frequency f of the chirp excitation L = 12 Hz, the termination frequency f U = 67 Hz, the frequency change speed is 0.5 Hz / s, the total sampling time T = 110 s, and the sound speed in the pipe is approximately c

[0046] = 348.8 m / s.

[0047] The sound sensor collects the acoustic signal under the chirp excitation. Its time-domain signal is as Figure 2 shown, and it can be seen that the useful signal is completely submerged. For the collected acoustic signal y0(n), construct a time-varying band-pass filter to filter it to obtain y1(n). The center frequency f of the filter c varies in the range of 12 - 67 Hz, and the bandwidth F b= 8 Hz. The time-domain signal after filtering is as Figure 3 shown. It can be seen that the acoustic signal components within the selected frequency range have been effectively extracted, and at the same time, the high-order response u(n) of the chirp sound wave and the noise z(n) of the measurement system and the environment have been effectively suppressed. The filtered time-domain signal is normalized to obtain y norm (n), and the calculation formula is expressed as:

[0048]

[0049] After normalization, the signal in the time range of 20 - 80 s is intercepted as Figure 4 shown, and the corresponding excitation frequency band range is 22 - 52 Hz. It can be seen that the signal amplitude has been normalized to the range of [-1, 1]. Construct the plancktaper window function ω p (n) to weight the time-domain signal. The window function ω p (n) is expressed as:

[0050]

[0051] where ε is the transition bandwidth control parameter of the window function, N is the number of window function points, and n is the sample sequence number.

[0052] The parameters of the plancktaper window function are set with the transition bandwidth control parameter ε = 0.2. The windowed signal y(n) is as Figure 5 shown. It can be seen that the two ends of the signal show smooth attenuation at the edges, effectively suppressing the Gibbs effect in the spectrum, suppressing the energy overshoot at the truncation boundary, and at the same time, better retaining the main components of the signal.

[0053] Considering that the excitation frequency band range in the windowed signal y(n) is 20 - 55 Hz, the discrete Fourier transform is used to calculate the frequency amplitudes at non-integer sequence numbers within this frequency band range. Additional refined frequency points are added between every two adjacent spectral lines to obtain a more densely distributed refined spectrum Y l (k), and the calculation formula is expressed as:

[0054]

[0055] where k1 and k2 are the upper and lower limit frequencies of the excitation frequency band respectively; k is the frequency sequence number.

[0056] The obtained refined spectrum is as Figure 6 shown. It can be seen that the considered excitation frequency band already includes the effective resonance characteristics of the pipe string.

[0057] After normalizing the refined spectrum, we get The calculation formula is expressed as:

[0058]

[0059] The logarithm of the normalization result is taken to obtain the logarithmic spectrum Y(k), and the calculation formula is expressed as:

[0060]

[0061] The logarithmic spectrum is smoothed and filtered, as Figure 7 shown. Figure 7 The red line part in is the result Ω(k) of the frequency band smoothing filter, which is an unknown interference imposed on the resonance characteristics due to the measurement system characteristics. Subtracting the logarithmic spectrum from its filtered result spectrally corresponding to each other realizes the extraction of resonance characteristics, and the calculation formula is:

[0062] G(k) = Y(k) - Ω(k) k1 < k < k2

[0063] where k1 and k2 are the upper and lower limit frequencies of the selected frequency band respectively. According to the considered excitation frequency band, k1 = 20 Hz and k2 = 55 Hz.. The extracted resonance characteristic G(k) is as Figure 8 shown. It can be seen that the extracted resonance characteristic already shows strong periodicity. Using FFT on the resonance characteristic G(k) to obtain H(r), it is calculated that the spectral line number l corresponding to the maximum spectral line in H(r) is 165. The calculation formula for the number of resonance peaks η is:

[0064] η = l + δ

[0065] where δ is the normalization frequency correction amount.

[0066] Through the three-spectral line interpolation method, the parameter δ is accurately estimated, and the calculation formula is:

[0067]

[0068] where |H(l)|, |H(l - 1)|, and |H(l + 1)| represent the modulus values corresponding to the highest spectral line in H(r) and its two adjacent sub-highest spectral lines on the left and right; E represents the coefficient related to the window function.

[0069] Since the window function transition bandwidth control parameter ε = 0.2, E = 1.08 is obtained. Then, the correction amount δ = -0.4815 can be obtained by substituting it into the three-spectral line interpolation formula. Finally, the calculation result of the number of resonance peaks can be obtained as Figure 9 shown, and the normalization frequency η = 164.5021.

[0070] According to the relationship between the number of resonance peaks and the liquid level depth of the pipe string, the liquid level depth L of the long-distance pipe string can be calculated, and the calculation formula is:

[0071]

[0072] Among them, c represents the average sound velocity in the pipe string; η represents the number of resonance peaks; N0 represents the total number of points of the acoustic signal y0(n); M represents the number of points included in the resonance characteristic G(k); f s represents the sampling frequency; d c represents the inner diameter of the pipe string. Substituting each parameter into the above formula for calculation, the experimental pipeline length L = 956.1839 m can be obtained, and the actual measurement error is only 10.6 cm.

[0073] The above - mentioned embodiments further elaborate on the purpose, technical solution and advantages of the present invention. It should be understood that the above - mentioned embodiments are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made to the present invention within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An efficient detection method for the liquid level depth of long-distance pipe strings based on short-time linear frequency modulation excitation, characterized in that, Including: S101. Set the measuring device at the port of the long-distance pipe string; S102. Set the parameters of the measuring device. The measuring device inputs the generated chirp acoustic wave into the long-distance pipe string to continuously resonate the air column inside the pipe; S103. Collect the acoustic signal of the air column inside the pipe, filter the acoustic signal, and perform normalization processing on the filtered signal to obtain the normalized time-domain signal; S104. Perform windowing processing on the normalized time-domain signal using the plancktaper window function; S105. Calculate the frequency amplitude at non-integer serial numbers within the excitation frequency band based on the windowed time-domain signal using the discrete Fourier transform. Add additional refined frequency points between every two adjacent spectral lines to obtain a more densely distributed refined frequency spectrum; perform normalization processing on the obtained refined frequency spectrum, and take the logarithm of the normalized amplitude spectrum; S106. Perform smoothing filtering on the logarithmic frequency spectrum to obtain the filtering result; S107. Subtract the logarithmic frequency spectrum from the filtering result correspondingly to extract the resonance characteristics of the signal; S108. Perform fast Fourier transform on the resonance characteristics to obtain H(r); calculate the correction amount using the three-spectrum line interpolation method based on the obtained H(r), and estimate the number of resonance peaks of the resonance characteristics according to the correction amount; calculate the liquid level depth of the long-distance pipe string according to the number of resonance peaks.

2. The high-efficiency detection method for the liquid level depth of a long-distance pipe string based on short-time linear frequency modulation excitation according to claim 1, wherein The measuring device includes a signal generator, an excitation sound source, and a sound sensor; among them, the signal generator, the excitation sound source, and the sound sensor are installed on the same side of the port of the long-distance pipe string; the signal generator is used to generate a chirp signal; the excitation sound source is installed at the pipe orifice of the long-distance pipe string, the sound sensor is adjacent to the excitation sound source, the excitation sound source is used to generate a chirp acoustic wave, and the sound sensor is used to collect the acoustic signal.

3. An efficient method for detecting the liquid level depth of a long-distance pipe string based on short-time linear frequency modulation excitation according to claim 1, characterized in that, The measuring device generates a chirp acoustic wave including: the signal generator generates a chirp signal, converts the chirp signal into an analog signal by means of digital-to-analog conversion; inputs the analog signal into a power amplifier, and inputs the amplified analog signal into the excitation sound source to continuously drive the excitation sound source to generate a chirp acoustic wave.

4. An efficient method for detecting the liquid level depth of a long-distance pipe string based on short-time linear frequency modulation excitation according to claim 1, characterized in that, The filter has a center frequency f c and is a time-varying bandpass filter with a bandwidth of F b that varies with the instantaneous frequency of the tracked chirp acoustic wave.

5. The high-efficiency detection method for the liquid level depth of a long-distance pipe string based on short-time linear frequency modulation excitation according to claim 1, wherein The plancktaper window function is: Where ε is the transition bandwidth control parameter of the window function, N is the number of window function points, and n is the sample serial number.

6. The high - efficiency detection method for the liquid level depth of a long - distance pipe string based on short - time linear frequency - modulated excitation according to claim 1, characterized in that, Obtaining a more densely distributed refined frequency spectrum includes: Where k1 and k2 are the upper and lower limit frequencies of the excitation frequency band respectively; k is the frequency serial number; N is the number of window function points, and n is the sample serial number.

7. The high-efficiency detection method for the liquid level depth of a long-distance pipe string based on short-time linear frequency modulation excitation according to claim 1, characterized in that Calculating the correction amount using the three-spectrum line interpolation method includes: Where |H(l)|, |H(l - 1)|, and |H(l + 1)| represent the modulus values corresponding to the highest spectral line and its two adjacent lower spectral lines in H(r); E represents the coefficient related to the window function.

8. The high-efficiency detection method for the liquid level depth of a long-distance pipe string based on short-time linear frequency modulation excitation according to claim 1, wherein Estimating the number of resonance peaks of the resonance characteristics according to the correction amount includes: η = l + δ Where l is the maximum spectral line number in H(r); δ is the normalized frequency correction amount.

9. The high-efficiency detection method for the liquid level depth of a long-distance pipe string based on short-time linear frequency modulation excitation according to claim 1, characterized in that Calculating the liquid level depth of the long-distance pipe string includes: Among them, c represents the average sound velocity in the pipe string; η represents the number of resonance peaks; N0 represents the total number of points of the acoustic signal y0(n); M represents the number of points included in the resonance characteristic G(k); f s represents the sampling frequency; d c represents the inner diameter of the pipe string.

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