Efficient detection method for pipeline blockage position

Abstract

The invention belongs to the technical field of pipeline blockage detection, and particularly relates to an efficient detection method for a pipeline blockage position, which comprises the steps of installing a measuring device at a port of a to-be-detected pipeline, setting parameters of the measuring device, generating low-frequency linear frequency modulation sound waves and continuously inputting the sound waves into the to-be-detected pipeline; acoustic signals in the to-be-detected pipeline are collected through an acoustic sensor; carrying out filtering processing on the acoustic signal by adopting a band-pass filter to obtain a filtered signal; taking an upper envelope line from the filtering signal to obtain an envelope signal; performing smooth filtering on the envelope signal to obtain a smooth filtering signal, and performing corresponding subtraction on the smooth filtering signal and the envelope signal in a time domain to obtain a processing signal; after windowing the processing signal by adopting a window function, carrying out FFT to obtain a frequency spectrum, and then calculating a correction value by adopting a parameter estimation algorithm; obtaining an accurate estimation period number according to the correction value, calculating sound wave propagation time from the port of the to-be-measured pipeline to the blockage point, and finally calculating the position of the blockage point of the pipeline; the whole detection time is short, and the calculated amount in the detection process is small.

Description

Technical Field

[0001] The present invention belongs to the technical field of pipeline blockage detection, and in particular relates to an efficient method for detecting a pipeline blockage position. Background Art

[0002] Pipelines, as the primary means and critical infrastructure for the long-distance, large-scale transportation of resources such as gas, oil, water, coal slurry, and chemical liquids, directly impact the continuity and stability of the overall resource supply. For example, gas pipelines are the primary means of transporting gaseous energy, providing continuous power for industrial production, power generation, and heating, as well as ensuring energy security for daily life. Gas is typically dried, cleaned, and pressurized before being piped through purification equipment. When the pipeline is unobstructed, this ensures continuous and efficient gas transportation. However, when the gas is not completely dried or when purification equipment malfunctions, heavy hydrocarbons and free water may enter the pipeline along with the gas. Under certain temperature and pressure conditions, this free water and hydrocarbons in the gas form gas hydrates, causing deposition or adhesion of the media within the pipe. Furthermore, corrosion and wear of the pipe can also lead to scaling on the inner walls of the pipe. Continued blockage can cause a sharp increase in pipeline pressure, leading to rupture. This can be particularly true in environments rich in elements such as sulfur and hydrogen. Pipeline ruptures and leaks can lead to serious safety hazards such as explosions. Similarly, oil products in oil pipelines may condense due to excessive water content or low temperatures, causing waxy components to crystallize and precipitate, condensing with impurities to form massive deposits. Water pipelines may experience excessive water hardness, causing ions and carbonates in the water to form insoluble scale, and particulate impurities in the water may gradually accumulate in low-flow sections. Blockages in these pipeline systems that transport different resources will lead to abnormal pressure within the pipeline system, reduced pipeline transportation capacity, and even sudden serious accidents. Therefore, accurately locating the location of pipeline blockages will help to take targeted measures to maintain and repair the pipelines, effectively preventing the blockage from further deteriorating, thereby ensuring the safe and stable operation of the transportation pipeline network.

[0003] Acoustic detection methods are the most widely used for detecting pipeline blockages due to their relative ease of use and non-destructive testing capabilities. These methods primarily include ultrasonic guided wave (GUIW), acoustic reflection (AR), and continuous acoustic wave detection. The GUIW method is significantly affected by pipeline structure and material, and multiple blockage locations can produce a cumulative effect during detection, leading to misjudgment. The AR reflection method suffers from significant acoustic energy attenuation during detection due to the steep inclinations, multiple bends, and variable diameter sections inherent in complex pipeline terrain and process requirements, making it difficult to detect blockages over long distances. The continuous acoustic wave detection method continuously inputs acoustic waves into the pipeline, collects the acoustic signals, and accurately estimates key parameters. The location of the blockage is calculated based on the relationship between these parameters and the length of the air column. This method offers advantages such as strong noise immunity and unrestricted measurement capabilities based on pipeline layout. However, traditional GUIW methods primarily analyze frequency domain information, requiring multiple time-frequency transformations and computationally intensive processing. Furthermore, to achieve high-precision detection results, the signal processing requires sufficient frequency resolution, which directly increases sampling time, limiting its application in real-world industrial scenarios. Summary of the Invention

[0004] To solve the above problems, the present invention provides an efficient method for detecting the location of pipeline blockage, comprising the following steps:

[0005] S1. Install a measuring device at the port of the pipe to be tested, set the measuring device parameters, generate a low-frequency linear frequency modulated sound wave and continuously input it into the pipe to be tested; the measuring device includes a signal generator, a power amplifier, an excitation sound source and an acoustic sensor;

[0006] S2. Acquiring acoustic signals from the pipe under test through an acoustic sensor;

[0007] S3. Filtering the acoustic signal using a bandpass filter to obtain a filtered signal;

[0008] S4. Take the upper envelope of the filtered signal to obtain an envelope signal;

[0009] S5. Smoothing the envelope signal to obtain a smoothed filtered signal, and subtracting the smoothed filtered signal from the envelope signal in the time domain to obtain a processed signal;

[0010] S6. Windowing the processed signal using a window function and performing FFT to obtain a spectrum, and then calculating the correction amount using a parameter estimation algorithm;

[0011] S7. After obtaining an accurate estimated number of cycles based on the correction amount, the acoustic wave propagation time from the port of the pipeline to be tested to the blockage point is calculated, and finally the location of the pipeline blockage point is calculated.

[0012] Furthermore, in step S1, a linear frequency modulation signal is generated by a signal generator, a power amplifier amplifies the linear frequency modulation signal, and an exciting sound source is driven by the amplified linear frequency modulation signal to generate a low-frequency linear frequency modulation sound wave.

[0013] Furthermore, the upper cutoff frequency and the lower cutoff frequency of the bandpass filter constructed in step S3 are f upper 、f lower , and the lower cutoff frequency f lower Equal to the starting frequency f of the linear FM signal generated by the signal generator L , upper cutoff frequency f upper Equal to the stop frequency f of the linear FM signal generated by the signal generator U .

[0014] Furthermore, step S5 subtracts the smoothed filtered signal from the envelope signal obtained in step S4 in the time domain, which is expressed as:

[0015] G(n)=e(n)-Ω(n)

[0016] Where G(n) represents the processed signal, e(n) represents the envelope signal, and Ω(n) represents the smoothed filtered signal.

[0017] Furthermore, the window function used in step S6 is the Tukey window function w tukey (n), expressed as

[0018]

[0019] Among them, α represents the shape parameter of the window function, N represents the number of window function points, and n represents the sample number.

[0020] Furthermore, the calculation of the correction amount Δl using a parameter estimation algorithm includes:

[0021]

[0022] γ=Re[H(l)H * (l)]

[0023] γ L =Re[H(l-1)H * (l)]

[0024] γ R =Re[H(l+1)H * (l)]

[0025] in, represents the intermediate quantity, γ represents the complex real part of the maximum spectrum line, γ L represents the complex real part of the left adjacent spectral line, γ Rrepresents the complex real part of the right adjacent spectral line, H(·) represents the Fourier coefficient obtained by FFT after windowing the processed signal, l is the highest spectral line number in the spectrum, H(l), H(l-1), and H(l+1) are the Fourier coefficients corresponding to the highest spectral line in the spectrum and the two next highest spectral lines on its left and right, respectively; * indicates taking the conjugate.

[0026] Further, accurate estimation of the number of cycles The calculation formula is

[0027]

[0028] Where l is the highest line number in the spectrum, and △l is the correction amount.

[0029] Furthermore, the calculation formula for the acoustic wave propagation time △T from the tested pipe port to the blockage point is:

[0030]

[0031] in, To accurately estimate the number of cycles, T is the total sampling time and k is the slope of the linear frequency modulation signal generated by the signal generator.

[0032] Furthermore, the calculation formula for the pipeline blockage point location L is:

[0033] L=c·ΔT

[0034] Where c represents the average sound velocity in the pipe, and △T is the sound wave propagation time from the port of the tested pipe to the blockage point.

[0035] Beneficial effects of the present invention:

[0036] The present invention adopts low-frequency linear frequency modulation sound waves as excitation sound waves, which can effectively solve the problem that traditional excitation sound waves propagate rapidly in the pipe, resulting in weak resonance characteristics and difficulty in extraction; by taking the envelope of the collected acoustic signal and calculating the pipeline blockage position based on the sound wave propagation time from the pipeline port to the blockage point, the signal is feature extracted and analyzed in the time domain, avoiding the multiple time-frequency domain transformation processes of the traditional continuous sound wave detection method, significantly reducing the amount of calculation, greatly reducing the dependence of the detection result on the signal frequency resolution, effectively shortening the overall detection time, and completing the detection in just a few seconds; at the same time, the key parameters are accurately estimated through the parameter estimation algorithm, thereby improving the accuracy of pipeline blockage detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 Flow chart of the method of the present invention;

[0038] Figure 2 is a time domain diagram of the acoustic signal collected in the embodiment;

[0039] Figure 3 : is a time domain diagram of the acoustic signal after bandpass filtering in the embodiment;

[0040] Figure 4 This is an envelope signal diagram obtained by taking the upper envelope curve of the signal after bandpass filtering in the embodiment;

[0041] Figure 5 This is a graph showing the result of performing time domain subtraction between the envelope signal and the filtering result after smoothing filtering in the embodiment;

[0042] Figure 6 This is a result diagram of the time domain subtraction result after windowing in the embodiment;

[0043] Figure 7 This is a schematic diagram of the maximum spectral line number value calculated after FFT of the windowed signal in the embodiment. DETAILED DESCRIPTION

[0044] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0045] The present invention provides an efficient method for detecting the location of pipeline blockage, such as Figure 1 As shown, the following steps are included:

[0046] S1. Install a measuring device at the port of the pipeline to be measured, set the parameters of the measuring device, and generate low-frequency linear frequency modulation sound waves to continuously input into the pipeline to be measured; the measuring device includes a signal generator, a power amplifier, an excitation sound source and an acoustic sensor.

[0047] Specifically, in step S1, the signal generator is used to generate a linear frequency modulation signal, the power amplifier is used to amplify the power of the linear frequency modulation signal, the excitation sound source is used to continuously drive and generate low-frequency linear frequency modulation sound waves, and the acoustic sensor is used to collect acoustic signals in the pipeline to be tested; the signal generator, power amplifier, excitation sound source, and acoustic sensor are all installed on the same side of the port of the pipeline to be tested.

[0048] S2. Collect the acoustic signal in the pipeline to be tested through the acoustic sensor.

[0049] S3. Filtering the acoustic signal using a bandpass filter to obtain a filtered signal;

[0050] S4. Take the upper envelope of the filtered signal to obtain an envelope signal;

[0051] S5. Smoothing the envelope signal to obtain a smoothed filtered signal, and subtracting the smoothed filtered signal from the envelope signal in the time domain to obtain a processed signal;

[0052] S6. Windowing the processed signal using a window function and performing FFT to obtain a spectrum, and then calculating the correction amount using a parameter estimation algorithm;

[0053] S7. After obtaining an accurate estimated number of cycles based on the correction amount, the acoustic wave propagation time from the port of the pipeline to be tested to the blockage point is calculated, and finally the location of the pipeline blockage point is calculated.

[0054] In one embodiment, the signal sampling frequency f is set s =2560Hz, the starting frequency f of the linear frequency modulation signal generated by the signal generator L =25Hz, end frequency f U =30Hz, ramp rate k = 1Hz / s, total sampling time T = 5s, and the sound velocity in the pipe is approximately c = 337.85m / s. Specifically, the acoustic sensor is installed in front of the excitation sound source, and the actual distance from the pipe opening to the blockage point is 469.85m.

[0055] The acoustic sensor collects the acoustic signal y(n) in the pipeline to be tested. The signal time domain diagram is as follows: Figure 2 As shown, it can be seen that there is a lot of interference in the acoustic signal and the signal regularity is not strong. Construct a bandpass filter to filter the acoustic signal y(n). The upper cutoff frequency f of the bandpass filter is upper =f U =30Hz, lower cutoff frequency f lower =f L =25Hz. The time domain diagram of the filtered signal y1(n) is as follows: Figure 3 As shown in the figure, it can be seen that the high-order response of the linear frequency modulation sound waves originating from the measurement system and the complex environmental noise have been effectively suppressed.

[0056] Take the upper envelope of the filtered signal y1(n) to obtain the envelope signal e(n), such as Figure 4 As shown. It can be seen that the envelope signal at this time still contains unknown interference components and the periodicity is not obvious. The envelope signal e(n) is smoothed and filtered to filter out the low-frequency trend term in the signal to obtain the smoothed filtered signal Ω(n). The smoothed filtered signal Ω(n) is subtracted from the envelope signal e(n) in the time domain to obtain G(n). The calculation formula is:

[0057] G(n)=e(n)-Ω(n)(1)

[0058] The corresponding subtraction results in the time domain are as follows Figure 5 As shown. It can be seen that the signal has shown strong periodicity at this time, but due to the endpoint effect, the energy overshoot phenomenon appears at both ends of the signal. Construct Tukey window function w tukey(n) adds window processing to G(n), the window function w tukey (n) is calculated as:

[0059]

[0060] Where α represents the shape parameter of the window function, and is set to α = 0.4; N represents the number of window function points, and n represents the sample number. The signal after windowing is as follows Figure 6 As shown, it can be seen that the signal has been smoothly attenuated at both ends, which effectively reduces the endpoint effect, effectively suppresses spectrum leakage, and better preserves the structure of the main components of the signal.

[0061] Perform FFT on the windowed signal to obtain the spectrum |H(·)|, and the spectral line number l corresponding to the maximum (high) spectral line in the spectrum can be calculated, as follows: Figure 7 As shown, we can get l = 14. The formula for accurately estimating the number of cycles is:

[0062]

[0063] Among them, △l is the correction amount, and △l is estimated by the parameter estimation algorithm. The calculation formula is:

[0064]

[0065] in, Represents the intermediate quantity, and its calculation formula is

[0066]

[0067] γ represents the complex real part of the maximum spectral line, γ L represents the complex real part of the left adjacent spectral line, γ R represents the complex real part of the right adjacent spectral line, which is calculated as follows

[0068]

[0069] H(·) represents the Fourier coefficient obtained by FFT of the windowed signal, l is the highest spectral line number in the spectrum |H(·)|, H(l), H(l-1), and H(l+1) are the Fourier coefficients corresponding to the highest spectral line and the two next highest spectral lines on its left and right, respectively; * represents conjugation, and Re[] represents the operation of taking the real part of the complex number.

[0070] Substituting each parameter into formula (4) can obtain the correction value △l = -0.09. Further substituting it into formula (3) can obtain the accurate estimated cycle number Based on the accurate estimation of the number of cycles, the acoustic wave propagation time from the pipe port to the blockage point can be further calculated as △T = 1.391s, as shown in formula (7):

[0071]

[0072] Finally, according to the obtained sound wave propagation time △T, the location L of the pipeline blockage point can be calculated, as shown in formula (8):

[0073] L=c·ΔT(8)

[0074] Substituting each parameter into formula (8), we can obtain L = 469.9494m, and the actual measurement error is only 0.0994m.

[0075] In the present invention, unless otherwise clearly stipulated and limited, the terms "installation", "setting", "connection", "fixation", "rotation" and the like should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be the internal connection of two elements or the interaction relationship between two elements. Unless otherwise clearly defined, ordinary technicians in this field can understand the specific meanings of the above terms in the present invention according to the specific circumstances.

[0076] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. An efficient method for detecting the location of pipeline blockage, characterized in that: The following steps are involved: S1. Install a measuring device at the port of the pipe to be tested, set the measuring device parameters, generate a low-frequency linear frequency modulated sound wave and continuously input it into the pipe to be tested; the measuring device includes a signal generator, a power amplifier, an excitation sound source and an acoustic sensor; S2. Acquiring acoustic signals from the pipe under test through an acoustic sensor; S3. Filtering the acoustic signal using a bandpass filter to obtain a filtered signal; S4. Take the upper envelope of the filtered signal to obtain an envelope signal; S5. Smoothing the envelope signal to obtain a smoothed filtered signal, and subtracting the smoothed filtered signal from the envelope signal in the time domain to obtain a processed signal; S6. Windowing the processed signal using a window function and performing FFT to obtain a spectrum, and then calculating the correction amount using a parameter estimation algorithm; S7. After obtaining an accurate estimated number of cycles based on the correction amount, the acoustic wave propagation time from the port of the pipeline to be tested to the blockage point is calculated, and finally the location of the pipeline blockage point is calculated.

2. The efficient detection method for pipeline blockage position according to claim 1, characterized in that: In step S1, a linear frequency modulation signal is generated by a signal generator, a power amplifier amplifies the linear frequency modulation signal, and an exciting sound source is driven by the amplified linear frequency modulation signal to generate a low-frequency linear frequency modulation sound wave.

3. The efficient detection method for pipeline blockage position according to claim 1 is characterized in that: The upper cutoff frequency and lower cutoff frequency of the bandpass filter constructed in step S3 are f upper 、f lower , and the lower cutoff frequency f lower Equal to the starting frequency f of the linear FM signal generated by the signal generator L , upper cutoff frequency f upper Equal to the stop frequency f of the linear FM signal generated by the signal generator U .

4. The efficient detection method for pipeline blockage position according to claim 1, characterized in that: Step S5 subtracts the smoothed filtered signal from the envelope signal obtained in step S4 in the time domain, which is expressed as: G(n)=e(n)-Ω(n) Where G(n) represents the processed signal, e(n) represents the envelope signal, and Ω(n) represents the smoothed filtered signal.

5. The efficient detection method for pipeline blockage position according to claim 1, characterized in that: The window function used in step S6 is the Tukey window function w tukey (n), expressed as Among them, α represents the shape parameter of the window function, N represents the number of window function points, and n represents the sample number.

6. The efficient detection method for pipeline blockage position according to claim 1, characterized in that: The calculation of the correction amount △l using the parameter estimation algorithm includes: γ=Re[H(l)H * (l)] γ L =Re[H(l-1)H * (l)] γ R =Re[H(l+1)H * (l)] in, represents the intermediate quantity, γ represents the complex real part of the maximum spectrum line, γ L represents the complex real part of the left adjacent spectral line, γ R represents the complex real part of the right adjacent spectral line, H(·) represents the Fourier coefficient obtained by FFT after windowing the processed signal, l is the highest spectral line number in the spectrum, H(l), H(l-1), and H(l+1) are the Fourier coefficients corresponding to the highest spectral line in the spectrum and the two next highest spectral lines on its left and right, respectively; * indicates taking the conjugate.

7. The efficient detection method for pipeline blockage position according to claim 1, characterized in that: Accurately estimate the number of cycles The calculation formula is Where l is the highest line number in the spectrum, and △l is the correction amount.

8. The efficient detection method for pipeline blockage position according to claim 1, characterized in that: The calculation formula for the sound wave propagation time △T from the tested pipe port to the blockage point is: in, To accurately estimate the number of cycles, T is the total sampling time and k is the slope of the linear frequency modulation signal generated by the signal generator.

9. The efficient detection method for pipeline blockage position according to claim 1, characterized in that: The calculation formula for the pipeline blockage point location L is: L=c·ΔT Where c represents the average sound velocity in the pipe, and △T is the sound wave propagation time from the port of the tested pipe to the blockage point.

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