A long-distance pipe column liquid level efficient detection method based on short-time linear frequency modulation excitation

Abstract

The application belongs to the field of liquid level detection, and relates to a long-distance pipe 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 pipe column to continuously resonate the air column in the pipe; collecting the acoustic signals of the air column in the pipe; filtering the acoustic signals by using a filter; performing windowing processing on the time domain signals by using a window function; calculating the frequency amplitude at non-integer sequence numbers in the excitation frequency band by using discrete Fourier transform to obtain a refined frequency spectrum; performing normalization processing on the refined frequency spectrum and taking a logarithm to obtain a logarithmic frequency spectrum; performing smooth filtering processing on the logarithmic frequency spectrum, subtracting the logarithmic frequency spectrum from the filtering result spectrum to obtain the resonance characteristics of the signal; performing fast Fourier transform on the resonance characteristics, calculating a correction amount by using a three-spectrum line interpolation method, and estimating the resonance peak number of the resonance characteristics; and calculating the liquid level depth of the long-distance pipe column according to the resonance peak number. The application has the advantages of strong noise resistance, measurement results not affected by the pipe column arrangement mode, and short measurement time.

Description

Technical Field

[0001] This invention belongs to the field of liquid level depth detection in long-distance tubular columns, specifically relating to an efficient method for liquid level depth detection in long-distance tubular columns based on short-time linear frequency modulation excitation. Background Technology

[0002] In fields such as petroleum engineering, chemical engineering, and aerospace, liquid level is a crucial control parameter. Real-time, rapid, and accurate liquid level detection is essential for assessing system operating status and conducting monitoring and maintenance, and has become a necessary task to ensure safe production. In practical applications in industrial scenarios such as oil well dynamic fluid level measurement, long-distance pipeline transportation, and large-scale water conservancy projects, the length of the tubing string often exceeds 500 meters, and even reaches several kilometers, highlighting the increasing demand for long-distance liquid level detection.

[0003] Currently, liquid level measurement methods based on a tubular acoustic field model excite the air column inside the tube by sending white noise and high-frequency linear acoustic waves. After acquiring the resonance signal, signal processing is performed, and the liquid level depth is measured based on the mathematical relationship between the resonance characteristics and the tube length. However, during long-distance propagation, the high-frequency components of the acoustic waves attenuate rapidly and are often completely attenuated before reaching the liquid surface, severely affecting the excitation effect. Secondly, the acoustic signal acquired by the acoustic sensor not only includes the resonance signal of the air column but also interference from the excitation source itself and complex background noise. Weak resonance signals are easily submerged, severely interfering with the extraction and identification of resonance characteristics, thus affecting the stability and accuracy of liquid level measurement, and even leading to large measurement errors. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention proposes a highly efficient method for detecting liquid level depth in long-distance tubular columns based on short-time linear frequency modulation excitation. This method includes:

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

[0006] S102. Set the parameters of the measuring device. The measuring device will input the generated linear frequency modulated sound wave into the long-distance tube column to continuously resonate the air column inside the tube.

[0007] S103. Acquire the acoustic signal of the air column inside the tube, filter the acoustic signal, normalize the filtered signal, and obtain the normalized time domain signal.

[0008] S104. The normalized time-domain signal is windowed using the plancktaper window function.

[0009] S105. Calculate the frequency amplitude at non-integer indexes 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. Normalize 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 corresponding logarithmic spectrum from the filtering result 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-line interpolation method based on the obtained H(r), and estimate the number of resonance peaks of the resonance characteristics based on the correction amount; calculate the liquid level depth of the long-distance tube column based on the number of resonance peaks.

[0013] The beneficial effects of this invention are:

[0014] The method proposed in this invention employs short-time linear frequency modulated acoustic wave excitation, which effectively solves the problems of rapid energy attenuation of excitation acoustic waves and difficulty in extracting weak resonance characteristics caused by noise excitation. The detection method is not limited by the arrangement of the tubing, has good noise resistance, enables rapid extraction of resonance characteristics, expands the measurement range, and provides reliable technical support for liquid level detection in long-distance tubing under complex noise backgrounds. It achieves accurate detection of liquid level depth in long-distance tubing under various application scenarios. This invention uses a plancktaper window function to window the time-domain signal and estimates the signal correction amount through three-spectral-line interpolation, thereby improving the accuracy of liquid level detection in long-distance tubing. Attached Figure Description

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

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

[0017] Figure 3 This is a signal diagram of the acoustic signal collected in the example after being filtered by a time-varying bandpass filter;

[0018] Figure 4 This is a signal diagram obtained by normalizing the filtered signal in the example.

[0019] Figure 5 This is a time-domain signal diagram of the normalized signal with a Plancktaper window applied in the embodiment.

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

[0021] Figure 7 This is a comparison chart of the result after refining and normalizing the spectrum, taking the logarithmic spectrum, and then smoothing and filtering it, with the logarithmic spectrum in the example.

[0022] Figure 8 The image shows the signal resonance characteristics obtained by subtracting the corresponding spectrum from the logarithmic spectrum and the smoothing filter result in the embodiment.

[0023] Figure 9 This is a schematic diagram showing the calculation results of the number of resonance peaks obtained by estimating the three-spectral-line interpolation parameters after FFT of the resonance characteristics in the embodiment. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] A highly efficient method for detecting liquid level depth in long-distance tubular columns based on short-time linear frequency modulation excitation, the method comprising:

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

[0027] S102. Set the parameters of the measuring device. The measuring device will input the generated linear frequency modulated sound wave into the long-distance tube column to continuously resonate the air column inside the tube.

[0028] S103. Acquire the acoustic signal of the air column inside the tube, filter the acoustic signal, normalize the filtered signal, and obtain the normalized time domain signal.

[0029] S104. The normalized time-domain signal is windowed using the plancktaper window function.

[0030] S105. Calculate the frequency amplitude at non-integer indexes 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. Normalize the obtained refined spectrum and take the logarithm of the normalized amplitude spectrum.

[0031] S106. Perform smoothing filtering on the logarithmic spectrum to obtain the filtering result;

[0032] S107. Subtract the corresponding logarithmic spectrum from the filtering result 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-line interpolation method based on the obtained H(r), and estimate the number of resonance peaks of the resonance characteristics based on the correction amount; calculate the liquid level depth of the long-distance tube column based on the number of resonance peaks.

[0034] This invention provides a method for detecting liquid level depth in a long-distance tubular column based on short-time linear frequency modulation excitation, such as... Figure 1 As shown, it includes the following steps:

[0035] S1. Install the measuring device, including a signal generator, a vibration sound source and a sound sensor, all of which are installed on the same side of the tube end. The vibration sound source is installed at the tube end and the sound sensor is installed close to the vibration sound source.

[0036] S2. Set the sampling frequency f s Total sampling time T, starting frequency f of the linear frequency modulated signal L Termination frequency f U A linear frequency modulated signal is generated by a signal generator and transmitted to an excitation sound source for continuous driving, thereby generating a linear frequency modulated sound wave.

[0037] S3. A linear frequency modulated (LFM) sound wave is input into the tube column to induce continuous resonance in the air column inside the tube. The acoustic sensor collects the acoustic signal y0(n) under LFM excitation, which mainly includes the LFM sound wave signal generated by the excitation sound source and its higher-order response, the resonance signal of the air column inside the tube, noise and its interference;

[0038] S4. Construct the center frequency f c The bandwidth F tracks the instantaneous frequency change of a linear frequency modulated sound wave. b A time-varying bandpass filter is used to filter the acoustic signal y0(n) to obtain y1(n), effectively extracting the response signal components within a selected frequency range, while simultaneously suppressing the higher-order response u(n) of the linear frequency modulated sound wave and the noise z(n) of the measurement system and the environment. The filtered time-domain signal is then normalized to obtain y1(n). norm (n) normalizes the signal amplitude to the range [-1, 1].

[0039] S5. Normalize the signal y after step S4 norm (n), using the plancktaper window function w p (n) is windowed to obtain the weighted signal y(n) = y norm (n)·w p (n). By applying a windowing process, the Gibbs effect of the spectrum is effectively reduced, and the amplitude distortion of the spectrum caused by discontinuities at the endpoints is reduced.

[0040] S6. Calculate the frequency amplitude at non-integer indices within the excitation frequency band of the windowed signal y(n) using 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) significantly reduces the computational cost of frequency domain analysis while making the spectrum smoother. Frequency domain normalization is then applied to the refined spectrum to obtain... The logarithmic spectrum Y(k) is obtained by taking the logarithm of the normalized spectrum.

[0041] S7. Smooth the Y(k) to obtain the filtered result Ω(k). Then, subtract the corresponding spectrum of Y(k) from Ω(k) to extract the signal resonance characteristic G(k). G(k) contains a series of continuous resonance peaks and has a very strong periodicity. The number of signal resonance peaks can be obtained through a parameter 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). The resonance characteristic G(k) is subjected to a fast Fourier transform to obtain H(r). Let l be the number of the largest spectral line in H(r), and let δ (-0.5 ≤ δ ≤ 0.5) be the normalized frequency correction. Using the highest spectral line in H(r) and its two next-highest spectral lines, the correction δ is calculated using the three-line interpolation method, ultimately yielding an accurate estimate of the number of resonance peaks.

[0043] S9. The liquid level depth in the tubular column over long distances is calculated by using the mathematical relationship between the number of resonance peaks obtained from accurate estimation and the liquid level depth.

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

[0045] Set the signal sampling frequency f s =5120Hz, linear frequency modulation excitation starting frequency f L =12Hz, termination frequency f U =67Hz, frequency change rate is 0.5Hz / s, total sampling time T = 110s, and the speed of sound inside the tube is approximately c.

[0046] = 348.8 m / s.

[0047] The acoustic sensor acquires acoustic signals under linear frequency modulation excitation, and its time-domain signal is as follows: Figure 2 As shown, the useful signal is completely submerged. The acquired acoustic signal y0(n) is filtered by a time-varying bandpass filter to obtain y1(n), with the filter's center frequency f... c The frequency range is 12–67 Hz, and the bandwidth is F. b=8Hz. The time-domain signal after filtering is as follows: Figure 3 As shown, the acoustic signal components within the selected frequency range have been effectively extracted, while simultaneously achieving effective suppression of the higher-order response u(n) of the linear frequency modulated sound wave and the noise z(n) of the measurement system and the environment. The filtered time-domain signal is then normalized to obtain y. norm (n), the calculation formula is expressed as:

[0048]

[0049] After normalization, signals with a cutoff time range of 20–80 seconds are extracted, such as… Figure 4 As shown, the corresponding excitation frequency band is 22–52 Hz. It can be seen that the signal amplitude has been normalized to the range [-1, 1]. The plancktaper window function ω is constructed. p (n) Weighting the time-domain signal, using the window function ω p (n) is represented as:

[0050]

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

[0052] The window function parameter of plancktaper is set to the transition bandwidth control parameter ε = 0.2. The windowed signal y(n) is as follows: Figure 5 As shown, the signal exhibits smooth attenuation at both ends, effectively suppressing the Gibbs effect in the spectrum and the energy overshoot at the truncation boundary, while also preserving the main components of the signal well.

[0053] Considering the excitation frequency band of the windowed signal y(n) is in the range of 20–55 Hz, the frequency amplitude at non-integer indices within this frequency band is calculated using the Discrete Fourier Transform. Additional refined frequency points are added between every two adjacent spectral lines to obtain a more densely distributed refined spectrum Y. l (k), the calculation formula is expressed as:

[0054]

[0055] Where k1 and k2 are the upper and lower limits of the excitation frequency band, respectively; k is the frequency number.

[0056] The refined spectrum obtained is as follows Figure 6 As shown, the considered excitation frequency band already includes the effective resonance characteristics of the tubular column.

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

[0058]

[0059] Taking the logarithm of the normalized result yields the logarithmic spectrum Y(k), which is expressed by the following formula:

[0060]

[0061] Smoothing filter is applied to the logarithmic spectrum, such as... Figure 7 As shown. Figure 7 The red line represents the result Ω(k) of the band smoothing filter, which is an unknown interference applied to the resonance characteristics due to the measurement system's features. Resonance feature extraction is achieved by subtracting the corresponding spectral values ​​from the logarithmic spectrum and its filtering result. The calculation formula is as follows:

[0062] G(k)=Y(k)-Ω(k)k1<k<k2

[0063] Where k1 and k2 are the upper and lower limits of the selected frequency band, respectively. Based on the considered excitation frequency band, k1 = 20Hz and k2 = 55Hz. The extracted resonance characteristic G(k) is as follows: Figure 8 As shown, the extracted resonance characteristics exhibit strong periodicity. FFT is applied to the resonance characteristic G(k) to obtain H(r), and the spectral line number corresponding to the largest spectral line in H(r) is calculated to be l = 165. The formula for calculating the number of resonance peaks η is:

[0064] η=l+δ

[0065] Where δ is the normalized frequency correction value.

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

[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 the two second-highest spectral lines to its left and right; E represents the coefficients related to the window function.

[0069] Since the window function transition bandwidth control parameter ε = 0.2, we obtain E = 1.08. Substituting this into the three-line interpolation formula, we can obtain the correction δ = -0.4815. Finally, the result of the resonance peak count calculation is as follows: Figure 9 As shown, the normalized frequency η = 164.5021.

[0070] Based on the relationship between the number of resonance peaks and the liquid level depth in the tubing, the liquid level depth L of a long-distance tubing can be calculated using the following formula:

[0071]

[0072] Where c represents the average sound velocity inside the tubular column; η represents the number of resonance peaks; N0 represents the total number of points in the acoustic signal y0(n); M represents the number of points contained in the resonance characteristic G(k); f s Indicates the sampling frequency; d c This represents the inner diameter of the tubing. Substituting the parameters into the above formula, we can calculate the experimental pipe length L = 956.1839 m, with an actual measurement error of only 10.6 cm.

[0073] The above-described embodiments further illustrate the purpose, technical solution, and advantages of the present invention. It should be understood that the above-described embodiments are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made to the present invention within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for efficient detection of liquid level depth in a long-distance tubular column based on short-time linear frequency modulation excitation, characterized in that, include: S101. Set the measuring device at the port of the long-distance tubing; S102. Set the parameters of the measuring device. The measuring device will input the generated linear frequency modulated sound wave into the long-distance tube column to continuously resonate the air column inside the tube. S103. Acquire the acoustic signal of the air column inside the tube, filter the acoustic signal, normalize the filtered signal, and obtain the normalized time domain signal. S104. The normalized time-domain signal is windowed using the plancktaper window function. S105. Calculate the frequency amplitude at non-integer indexes 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. Normalize the obtained refined spectrum and take the logarithm of the normalized amplitude spectrum. S106. Perform smoothing filtering on the logarithmic spectrum to obtain the filtering result; S107. Subtract the corresponding logarithmic spectrum from the filtering result to extract the resonance characteristics of the signal; S108. Perform a fast Fourier transform on the resonance characteristics to obtain... According to the obtained The correction amount was calculated using the three-line interpolation method, and the number of resonance peaks of the resonance characteristics was estimated based on the correction amount; the liquid level depth of the long-distance tubing was calculated based on the number of resonance peaks.

2. The efficient method for detecting liquid level depth in a long-distance tubular column based on short-time linear frequency modulation excitation according to claim 1, characterized in that, The measuring device includes a signal generator, an excitation sound source, and an acoustic sensor; wherein the signal generator, the excitation sound source, and the acoustic sensor are installed on the same side of the port of the long-distance tubing; the signal generator is used to generate a linear frequency modulated signal; the excitation sound source is installed at the port of the long-distance tubing, and the acoustic sensor is adjacent to the excitation sound source. The excitation sound source is used to generate linear frequency modulated sound waves, and the acoustic sensor is used to collect acoustic signals.

3. The efficient method for detecting liquid level depth in a long-distance tubular column based on short-time linear frequency modulation excitation according to claim 1, characterized in that, The measurement device generates linear frequency modulated sound waves by: a signal generator generating a linear frequency modulated signal, converting the linear frequency modulated signal into an analog signal through digital-to-analog conversion; inputting the analog signal into a power amplifier, and then inputting the amplified analog signal into an excitation sound source to continuously drive the excitation sound source to generate linear frequency modulated sound waves.

4. The efficient method for detecting liquid level depth in a long-distance tubular column based on short-time linear frequency modulation excitation according to claim 1, characterized in that, The filter is the center frequency. The bandwidth varies with the instantaneous frequency of the tracking linear frequency modulated sound wave. A time-varying bandpass filter.

5. The efficient method for detecting liquid level depth in a long-distance tubular column based on short-time linear frequency modulation excitation according to claim 1, characterized in that, The plancktaper window function is: ； in, This is the transition bandwidth control parameter for the window function. For the number of points of the window function, This is the sample number.

6. The efficient method for detecting liquid level depth in a long-distance tubular column based on short-time linear frequency modulation excitation according to claim 1, characterized in that, Obtaining a more densely distributed, refined spectrum includes: ； ； ； in, , These are the upper and lower limit frequencies of the excitation frequency band, respectively; Frequency number; For the number of points of the window function, For sample serial number, The normalized time-domain signal, For the plancktaper window function, Acoustic signal, This is the signal after weighted processing.

7. The efficient method for detecting liquid level depth in a long-distance tubular column based on short-time linear frequency modulation excitation according to claim 1, characterized in that, The correction amount calculated using the three-line interpolation method includes: ； in, , , express The modulus values ​​corresponding to the highest spectral line and the two second-highest spectral lines to its left and right; This represents the coefficients associated with the window function.

8. The efficient method for detecting liquid level depth in a long-distance tubular column based on short-time linear frequency modulation excitation according to claim 1, characterized in that, The number of resonance peaks in the resonance characteristics estimated based on the correction amount includes: ； in, for The largest spectral line number in; This is the normalized frequency correction value.

9. The efficient method for detecting liquid level depth in a long-distance tubular column based on short-time linear frequency modulation excitation according to claim 1, characterized in that, Calculating the liquid level depth in a long tubing string includes: ； in, This represents the average sound velocity within the tubular column; Indicates the number of resonance peaks; Representing acoustic signals Total points; Indicates resonance characteristics The number of points contained in it; Indicates the sampling frequency; Indicates the inner diameter of the tubular column.

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