CN113048404B - Urban gas pipeline tiny leakage diagnosis method - Google Patents
Urban gas pipeline tiny leakage diagnosis method Download PDFInfo
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- CN113048404B CN113048404B CN202110271274.4A CN202110271274A CN113048404B CN 113048404 B CN113048404 B CN 113048404B CN 202110271274 A CN202110271274 A CN 202110271274A CN 113048404 B CN113048404 B CN 113048404B
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D5/00—Protection or supervision of installations
- F17D5/005—Protection or supervision of installations of gas pipelines, e.g. alarm
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D5/00—Protection or supervision of installations
- F17D5/02—Preventing, monitoring, or locating loss
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D5/00—Protection or supervision of installations
- F17D5/02—Preventing, monitoring, or locating loss
- F17D5/06—Preventing, monitoring, or locating loss using electric or acoustic means
Abstract
The invention belongs to the technical field of urban buried pipeline leakage detection, and discloses a method for diagnosing tiny leakage of an urban gas pipeline, which comprises the steps of acquiring infrasonic wave time domain signals of the urban pipeline and carrying out frequency spectrum conversion on the infrasonic wave time domain signals to obtain infrasonic wave frequency spectrums, and summarizing to form a judgment criterion for tiny leakage of the urban gas pipeline; acquiring infrasonic wave time domain signals of the urban pipeline to be tested, carrying out frequency spectrum conversion to obtain infrasonic wave signal frequency spectrums, and judging whether the test pipeline leaks or not according to judgment criteria; if the pipeline leaks, a pipeline leakage positioning model is established; determining a characteristic frequency band of a frequency spectrum through a coherent function, and extracting a leakage signal in the characteristic frequency band by using a band-pass filter; accurately calculating the time delay of the extracted infrasonic wave output leakage signals of the upstream and the downstream by adopting a generalized mutual time-frequency method; calculating the wave velocity of the infrasonic wave signal according to the pressure value of the pipeline; and substituting the time delay and the wave speed into a positioning model to obtain the positioning of the leakage point. The invention can diagnose tiny leakage and has high positioning accuracy.
Description
Technical Field
The invention relates to the technical field of urban buried pipeline leakage detection, in particular to a tiny leakage diagnosis method for an urban gas pipeline.
Background
With the acceleration of the urbanization process, the pipeline is rapidly developed as an urban infrastructure, and makes great contribution to the transportation of urban necessary energy and the improvement of the quality of the living standard of people. However, with the increase of the service life of the pipeline, construction defects, corrosion and artificial damage, urban pipeline leakage often occurs, further serious accidents such as fire, explosion and the like are caused, and personnel and property loss is caused. Moreover, compared with a long oil and gas transmission pipeline, the urban pipeline has the advantages of thinner pipe diameter, lower transmission pressure, weaker early leakage signal and more difficult leakage detection and positioning. Therefore, research on the diagnosis of the tiny leakage of the urban pipeline is a topic with great practical value and social significance.
In recent years, due to the high efficiency and convenience of the infrasonic wave detection technology, the infrasonic wave detection technology is widely applied to the field of pipeline leakage detection, certain theoretical knowledge and technical achievements are accumulated, and pipeline leakage detection and positioning technology based on infrasonic waves is mature. When the pipeline leaks, pressure difference is generated inside and outside the pipeline, and medium in the pipeline is ejected out of the leakage port. The fluid in the pipe interacts with the pipe wall to induce vibration with different frequencies, so that air vibration generates sound wave signals with different frequencies, the sound wave signals are transmitted to the two ends of the pipeline, the high-frequency signals are quickly attenuated in the transmission process, and when the sound wave signals are transmitted to the sensors on the two sides of the pipeline, the infrasound waves are used as main components. The infrasonic wave detection technology is a technology for collecting, recording and analyzing infrasonic wave signals in a pipeline by means of an infrasonic wave detection system and evaluating properties such as intensity, position, occurrence conditions and the like of a sound source. The detection principle is as follows: the acoustic signal at the leak will propagate up and down the pipe. The infrasonic wave sensors are arranged on the upstream and downstream of the leakage point and used for receiving infrasonic wave signals from the leakage point, and due to the fact that the distances between the infrasonic wave sensors and the leakage point are different, time difference can be generated when the same signal is detected to be suddenly changed, and the specific position of the leakage point can be determined according to the time difference. However, the problems that the urban pipeline tiny leakage (the leakage aperture is between 1mm and 5 mm) is not easy to be perceived and the positioning error is large exist at present.
Disclosure of Invention
The invention aims to provide a method for diagnosing the tiny leakage of an urban gas pipeline, aiming at solving the problem that the tiny leakage of the urban pipeline (including a metal pipeline and a nonmetal pipeline) is not easy to be perceived and has larger positioning error aiming at solving the problems of the existing tiny leakage of the urban pipeline (the tiny leakage is the leakage with the leakage aperture of 1 mm-5 mm).
A method for diagnosing tiny leakage of an urban gas pipeline comprises the following steps:
s1: the practical operation condition of combining urban pipeline builds buried gas pipeline analogue test system (this application is applicable to the leakage diagnosis of metal pipeline and non-metal pipeline simultaneously, and the processing procedure is unanimous, therefore metal pipeline and non-metal pipeline in this application are collectively called gas pipeline), gathers buried gas pipeline analogue test system respectively under different pressure the pipeline not leak with the time domain signal of the intraductal infrasonic wave of small leakage, and right time domain signal carries out the infrasonic wave frequency spectrum that frequency spectrum conversion obtained analogue test system, summarizes the spectral characteristic law of the small leakage of urban gas pipeline, and then obtains the small leakage frequency spectrum judgement criterion of urban gas pipeline.
The specific process of spectrum conversion is as follows:
a. converting the acquired infrasonic time-domain signal x (t) into a frequency-domain spectral density function X (f):
in the formula: x (f) is a frequency domain spectral density function; ω is the simulated angular frequency, ω -2 π f, f denotes the frequency; e is a natural logarithm base; j is the imaginary unit; t represents the time.
b. Calculating an amplitude spectrum estimation function of the frequency domain spectral density function X (f)
Dividing the frequency domain spectral density function X (f) into M equal-length data segments, and observing M points of the frequency domain spectral density function X (f) by using the M points M (f) Considered as a finite signal; then to X M (f) Fourier transform to X M (k) (ii) a Finally taking X M (k) The square of the amplitude and the division by the number of data segments M as an amplitude spectrum estimation function of the frequency domain spectral density function X (f)
Namely:
c. estimating a function from an amplitude spectrum
Drawing an infrasonic signal frequency spectrum:
drawing amplitude spectrum estimation function by using drawing function of Matlab software
The corresponding infrasonic wave signal spectrogram is obtained.
Further, the judgment criterion of the micro-leakage frequency spectrum of the urban gas pipeline is that the frequency spectrum signal of the undisleaked infrasonic wave of the urban gas pipeline meets the characteristic of only one amplitude peak, and the corresponding frequency is not more than 5 Hz; when the urban gas pipeline leaks slightly, the infrasonic wave frequency spectrum has at least 2 amplitude peak fluctuation characteristics, and the corresponding frequency range is within 5 Hz-20 Hz.
S2: acquiring infrasonic time domain signals of the urban pipeline to be detected, performing frequency spectrum conversion on the acquired infrasonic time domain signals of the urban pipeline to be detected to obtain infrasonic frequency spectrums of the urban pipeline to be detected, and judging whether the urban pipeline to be detected leaks or not according to the urban gas pipeline tiny leakage frequency spectrum judgment criterion.
S3: if the pipeline leaks, the actual condition of the urban gas pipeline is comprehensively considered, and a pipeline leakage positioning model based on the infrasonic wave detection technology is established.
The pipeline leakage positioning model is as follows: let s (t), n 1 (t)，n 2 (t) Are not related to each other,
in the formula: l 1 Distance in m from the leak location to the upstream infrasonic sensor; l is the distance between the upstream infrasonic wave sensor and the downstream infrasonic wave sensor, and is the unit m; tau is 0 Is the time delay, in units of s; v is the wave speed of the infrasonic wave signal, unit m/s; s (t) is an unknown original leakage source signal; n is 1 (t) and n 2 (t) is a zero-mean random noise signal representing ambient noise, and t is time.
S4: and taking the interference of the noise signal to the infrasonic wave into consideration, extracting a frequency band corresponding to continuous peaks in a frequency spectrum as a characteristic frequency band by adopting a coherence function, taking a frequency band where a maximum value is located as the characteristic frequency band if at least 2 continuous peaks exist, and extracting a leakage signal in the characteristic frequency band by using a band-pass filter.
Further, a specific method of extracting the leakage signal is as follows:
let x be infrasonic time domain signals received by infrasonic microphones at upstream and downstream of pipeline 1 (t) and x 2 (t), then:
in the formula: x is the number of 1 (t) and x 2 (t) are respectively time domain signals output by the upstream and downstream infrasonic wave sensors; s (t) is the unknown original leakage source signal; n is 1 (t) and n 2 (t) is a zero-mean random noise signal representing ambient noise; a is the acoustic wave attenuation coefficient; tau is 0 The unit is the time delay of transmitting the infrasonic wave to the upstream end and the downstream end of the pipeline; t is the time;
x 1 (t) and x 2 (t) the cross-correlation function of the signal is defined by:
in the formula:
is a cross-correlation function between the output time domain signals; e [. C]Is a desired operator; τ is a time delay;
fourier transform is carried out on the formula (5) to obtain a signal x 1 (t) and x 2 (t) cross-spectral formula:
in the formula:
is a cross-spectrum function of the two output time domain signals; s ss (f) Is a cross-spectral function of the leakage source signals received by the two sensors, j is an imaginary unit, f is a frequency,
is the phase difference of the two output signals:
from the formula (7): if the time delays of the two output time domain signals are the same in the frequency band of the signal source, then
Linearly varying with frequency and having a slope of 2 pi tau 0 ；
Time domain signal x to be output 1 (t) and x 2 (t) dividing the data into M equal-length data segments, and adding a cosine cone window to each data segment to inhibit side lobe leakage in frequency spectrum estimation; then, Fourier transform is carried out on each segment of data, and if i is the number of segments, x is 1i (t) and x 2i (t) Fourier transform to X 1i (f) And
then the cross-spectrum of the ith segment of data is
The cross-spectral function of the two signals is calculated as:
using cross-spectral functions
Representing a single-sided cross spectrum
In the formula:
as a function of the cross-spectral density,
is a function of the intensity of the orthogonal spectrum, which are respectively
The real and imaginary parts of (c); the corresponding phase difference is expressed as:
single-side self-spectrum G of two output time domain signals obtained by Welch average periodogram method I And G II Two output time domain signals x 1 (t) and x 2 The coherence function of (t) is expressed as:
the relationship between the self-spectrum of the leakage output signal, the self-spectrum of the source signal and the self-spectrum of the noise is:
in the formula: g ss (f) In order to be self-spectral of the source signal,
is a noise self-spectrum;
the coherence function can be converted from equations (6) and (10):
in the formula:
and
respectively represent signals x 1 (t) and x 2 (t), assuming that the signal-to-noise ratios of the source signals of the two groups of output time domain signals at the frequency f are respectively as follows: SNR 1 And SNR 2 SNR of the received signal 1 And SNR 2 Instead of equation (13), the coherence function can be expressed as:
if x is assumed 1 (t) no noise signal, SNR 1 Infinity.
Converting into:
according to the coherence function, the minimum signal-to-noise ratio of the source signal of frequency f is thus the SNR 2 (ii) a In the same way, when x 2 (t) in the absence of noise signals, the minimum signal-to-noise ratio of the source signal at frequency f is SNR 1 (ii) a Thus, it proves that: the minimum signal-to-noise ratio of a source signal of frequency f is:
as can be seen from equation (16): the coherent function measures the degree of correlation of the two signals in a frequency domain, the larger the coherent function in one frequency band is, the higher the signal-to-noise ratio of the source signal in the frequency band is, therefore, the frequency band of the source signal is extracted according to the amplitude of the source signal, and the characteristic frequency band of the output time domain signal is obtained;
extracting leakage signal in characteristic frequency band by using band-pass filter, and setting upper and lower limits of characteristic frequency band as upper and lower cut-off frequencies f of band-pass filter 0 And f 1 Calculating the frequency bandwidth of the band-pass filter 1 -f 0 Center frequency of
Band-pass filter G (f) is:
s5: and calculating the time delay of the extracted infrasonic waves at the upstream and the downstream by adopting a generalized mutual time-frequency method.
Further, a specific method for accurately calculating the time delay of the extracted upstream and downstream infrasonic wave output leakage signals by adopting a generalized mutual time-frequency method is as follows:
the correction weighting function psi is solved by calculating the cross power spectrum of the infrasonic wave signal and combining the band-pass filter and the cross spectrum function 12 (f) Weighting in a frequency domain range, strengthening the spectral components in the signals, improving the signal-to-noise ratio of the signals, and obtaining a generalized mutual time-frequency function; and then, reversely transforming the frequency domain to the time domain by utilizing a generalized mutual time-frequency function, and calculating the time difference of the infrasonic wave signal according to a signal correlation principle to obtain the time delay of the infrasonic wave signal.
Further, the specific steps of calculating the time delay of the extracted output leakage signals of the upstream infrasonic waves and the downstream infrasonic waves are as follows:
infrasonic time domain signal x received by pipeline up and down infrasonic microphone 1 (t)、x 2 The cross-power spectrum of (t) is:
in the formula: x, (f), S, (f), N and (f) are respectively time domain signals x, (t), s, (t), frequency domain representation of n and (t), j is an imaginary number unit, tau 1 Time taken for a leak signal to travel from the leak location to the upstream infrasonic sensor, τ 2 The time at which the leak signal propagates from the leak location to the downstream infrasonic sensor;
since x (t), s (t), n (t) are not related to each other, equation (18) is simplified as:
solving the modified weighting function Ψ in combination with the bandpass filters G (f) and the cross-spectral function 12 (f)：
For cross power spectrum function
Are weighted, x 1 (t)、x 2 (t) is expressed as:
drawing a generalized mutual time-frequency analysis graph according to the formula (21), and solving the time delay tau of transmitting the infrasonic wave signals to the upstream and downstream ends of the pipeline according to the sampling point number and the signal sampling frequency corresponding to the maximum value of the correlation function in the graph 0 ；
τ 0 ＝Nf s (22)
In the formula: n is sampling time corresponding to the maximum amplitude point, mu s; f. of s Is the signal sampling frequency, Hz.
S6: and collecting the average value of the pressure at each position in the pipeline leakage state Ts as a pipeline pressure value P, and solving the wave velocity of the infrasonic wave signal according to the pipeline pressure value P.
S6.1: set up a plurality of pressure sensor on city gas pipeline, the average value of each pressure measurement position pressure is transferred as the pipeline pressure value in gathering pipeline leakage state Ts through pressure monitoring platform again, establishes the time step and is 1s, and the position step is 2.5m, promptly:
in the formula: t is the pipeline leakage time, s; t is time, s; l is the distance between the upstream infrasonic wave sensor and the downstream infrasonic wave sensor, m; l 0 Is the pipeline pressure sensor position, m; [. the]Is a rounded symbol.
S6.2: in the actual operation process of urban pipelines, the propagation speed of infrasonic waves in the pipeline is not the sound speed in an ideal state, and although the propagation speed of infrasonic waves in the pipeline is not different from the sound speed in the ideal state in terms of numerical values, errors caused by the positioning of pipeline leakage cannot be ignored. Therefore, considering the factors of medium compression coefficient in the pipe, medium density, pipe size and the like, the wave speed of the pipe leakage infrasonic wave signal is as follows:
in the formula: delta is a medium compression coefficient and is dimensionless; rho is the density of the medium, kg/m 3 (ii) a E is the elastic modulus of the pipeline, Pa; d is the diameter of the pipeline, mm; e is the pipe wall thickness, mm; c is a correction coefficient and is dimensionless.
Wherein, the calculation formula of the gas compression coefficient delta is as follows:
in the formula: z is the compression factor, P is the pressure in the tube, Pa. For medium and low pressure dry gas, the compression factor Z is 1.
S7: and finally, substituting the accurate time delay and the sound wave speed into a positioning formula to accurately position the leakage point.
The invention has the beneficial effects that: the diagnosis method is high in accuracy, simple and easy to implement, the frequency spectrum characteristic rule of the urban pipeline tiny leakage is summarized through the infrasonic wave frequency spectrum analysis tests under different working conditions, the urban pipeline tiny leakage frequency spectrum judgment criterion is established, the leakage judgment efficiency is high, and the misjudgment rate is low; determining a characteristic frequency band in a frequency spectrum by adopting a coherent function, and extracting a leakage signal in the characteristic frequency band by using a band-pass filter, wherein the step can effectively filter environmental noise; the time delay of the infrasonic wave signal is further accurately calculated by adopting a generalized mutual time-frequency method, and the time delay is substituted into a pipeline leakage calculation model, so that the pipeline leakage accurate positioning is realized.
Drawings
The invention is described in detail below with reference to the following figures and detailed description:
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a diagram of a test tube and sensor meter layout;
FIG. 3 is a graph of infrasonic spectra in a test pipe leak-free scenario;
FIG. 4 is a graph of infrasonic spectra in the context of a test pipeline leak;
fig. 5 is a graph of infrasonic wave spectrum at the time of leak detection of example 1;
FIG. 6 is a graph of a coherence function of the upstream and downstream leaked infrasonic signals of example 1;
FIG. 7 is a generalized mutual time-frequency analysis diagram of embodiment 1;
FIG. 8 is the pipe pressure profile of example 1;
fig. 9 is a time domain waveform diagram of the upstream and downstream leakage signals of embodiment 1.
Fig. 10 is a graph of infrasonic wave spectrum at the time of leak detection of example 2;
FIG. 11 is a graph showing the correlation function of the infrasonic signals leaked upstream and downstream in example 2;
FIG. 12 is a generalized mutual time-frequency analysis diagram of embodiment 2;
FIG. 13 is the pipe pressure distribution diagram of example 2;
fig. 14 is a time domain waveform diagram of the upstream and downstream leakage signals of embodiment 2.
FIG. 15 is a graph showing the infrasonic wave spectrum at the time of leak detection in example 3;
FIG. 16 is a graph showing the correlation function of the infrasonic signals leaked upstream and downstream in example 3;
FIG. 17 is a generalized mutual time-frequency analysis diagram of embodiment 3;
FIG. 18 is the pipe pressure distribution diagram of example 3;
fig. 19 is a time domain waveform diagram of the upstream and downstream leakage signals of embodiment 3.
The reference numerals in the figures have the meaning: 1-inlet ball valve, 2-upstream infrasonic wave sensor, 3-first pressure sensor, 4-second pressure sensor, 5-third pressure sensor, 6-fourth pressure sensor, 7-leakage hole, 8-fifth pressure sensor, 9-sixth pressure sensor, 10-downstream infrasonic wave sensor and 11-outlet ball valve.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further described with the specific embodiments.
Example 1:
as shown in fig. 1, the method for diagnosing a minute leakage in a pipe according to the present invention includes the steps of:
s1: the invention combines the actual running condition of the urban pipeline to establish a test pipeline system consisting of a gas pipeline system, an infrasonic wave acquisition system and a pressure monitoring system. A gas pipeline system model as shown in fig. 2 is built in a laboratory, the pipeline is a U-shaped PE pipe, the model of the pipeline is phi 63 multiplied by 1.5mm, and the total length is 12.8 m; an inlet ball valve 1, an upstream infrasonic wave sensor 2, a first pressure sensor 3 and a second pressure sensor 4 are sequentially arranged on the left straight line section of the pipeline from the inlet end of the pipeline; an outlet ball valve 11, a downstream infrasonic wave sensor 10, a sixth pressure sensor 9, a fifth pressure sensor 8 and a leakage hole 7 are sequentially arranged on the right straight-line section of the pipeline from the outlet end of the pipeline; a third pressure sensor 5 and a fourth pressure sensor 6 are sequentially arranged at the bent line section of the pipeline; the 6 pressure sensors are respectively arranged on the pipeline for two adjacent pressure sensors to be adjacent for 2.5 meters.
The leakage hole 7 is 9.05m away from the upstream infrasonic wave sensor 2, the adjustable leakage hole 7 is adopted to simulate the urban pipeline to generate tiny leakage, and the air compressor is adopted to deliver air to simulate the running process of the urban gas pipeline. The two ends of the pipeline are respectively provided with an upstream infrasonic wave sensor and a downstream infrasonic wave sensor, and the sensors are connected to an infrasonic wave acquisition instrument through cables and then transmitted to analysis software at a PC end through network cables. Pressure sensors are arranged on the pipeline every two meters, and acquired pressure data are uploaded to a GPRS (general packet radio service) module (an Internet of things network card) through a gateway and then uploaded to a pressure monitoring platform at a PC (personal computer) end through the Internet of things technology.
S1.1: and acquiring multiple groups of infrasonic time domain signals x (t) with no pipeline leakage and 1-5 mm micro leakage under the pipeline pressures of 0.1MPa, 0.2MPa and 0.3MPa respectively.
S1.2: the acquired infrasonic wave time domain signal is subjected to spectrum conversion to obtain a spectrum corresponding to the infrasonic wave time domain signal, and a set of data of non-leakage and leakage of the pipeline under different pressures is taken as an example, as shown in fig. 3 and 4. By means of a large amount of comparison and analysis, the frequency spectrum characteristic rules of the infrasonic wave signals without leakage and tiny leakage of the pipeline are summarized, and finally the urban pipeline tiny leakage frequency spectrum judgment criterion is established as follows: the urban pipeline non-leakage infrasonic wave frequency spectrum signal meets the characteristic that only one amplitude peak exists, and the corresponding frequency is not more than 5 Hz; and when the leakage is small, the infrasonic wave frequency spectrum has at least 2 amplitude peak fluctuation characteristics, and the corresponding frequency range is within 5 Hz-20 Hz.
S2: the operation pressure of the test pipeline is adjusted to 0.2MPa, the leakage hole 7 is opened to simulate 2mm tiny leakage of the pipeline after the pipeline operates stably, pipeline pass acoustic time domain signals are collected and subjected to frequency spectrum conversion, and the infrasonic signal frequency spectrum of the urban pipeline is obtained and is shown in figure 5. As can be seen from FIG. 5, the amplitude fluctuation of the infrasonic signal spectrum is mainly concentrated at 5Hz and 8.5Hz, and in addition, weak amplitude fluctuation exists at 13.5Hz and 24Hz, i.e. the spectrum has multi-peak fluctuation characteristics and is located in the frequency range of 5Hz to 20 Hz. And comparing the spectrum judgment criterion in S1.2, and judging that the pipeline is in the micro leakage at the moment.
S3: the actual condition of the urban gas pipeline is comprehensively considered, and a pipeline leakage positioning model based on the infrasonic wave detection technology is established.
S4: the extraction of the characteristic bands in the spectrum using the coherence function is shown in fig. 6. As can be seen from FIG. 6, the function has a maximum value at 14.5Hz, and the frequency band of the function is 12-16 Hz as the characteristic frequency band. Then, a band-pass filter is used for extracting leakage signals in the characteristic frequency band, and the upper limit and the lower limit of the characteristic frequency band are used as the upper cutoff frequency and the lower cutoff frequency f of the band-pass filter 0 12Hz and f 1 16Hz, center frequency f c ＝14Hz。
S5: the generalized mutual time-frequency method accurately calculates the time delay of the infrasonic signal, as shown in fig. 7.
As can be seen from FIG. 7, the correlation function of the infrasonic wave leakage signals at upstream and downstream takes the maximum value in the frequency range of 0 to 200Hz, and the sampling time N corresponding to the maximum value of the correlation function is 100 mus, the signal sampling frequency f s 187 accurately calculates the time difference of transmitting the infrasonic wave signal to the upstream and downstream ends of the pipeline according to the number of the sampling points: tau is 0 ＝187×10 -4 ＝0.0187s。
S6: and acquiring the average value of the pressure of each pressure measuring position in the pipeline leakage state Ts as a pipeline pressure value, and calculating the wave speed of the infrasonic wave signal according to the pipeline pressure value.
S6.1: the pressure data collected by each pressure sensor on the pipeline is retrieved through the pressure monitoring platform, as shown in fig. 8. Then, taking the average value of the pressure at each pressure measuring position in the pipeline acquisition state of 30s as a pipeline pressure value, wherein the time step is 1s, and the position step is 2.5m, namely:
s6.2: from the equation (24), it is known that the wall thickness e is 1.5mm and the air density ρ is 1.29kg/m 3 The elastic modulus E is 2.9GPa, the diameter D of the leakage hole 7 is 2mm, the correction coefficient c is 0.91, the delta is that the gas compression coefficient is related to the pressure in the pipe, and the infrasonic wave signal wave velocity is obtained by combining the vertical type (24) and the vertical type (25) and substituting the parameter values:
s7: and finally, substituting the accurate time delay and the infrasonic velocity into a positioning formula to accurately position the leakage point.
The positioning error is calculated as:
and comparing the result with the unprocessed upstream and downstream leakage signal rough positioning result. Time domain waveforms of the infrasonic wave leakage signals upstream and downstream are shown in fig. 9.
As can be seen from FIG. 9, amplitude spikes appear in the time domain waveforms of the upstream and downstream leakage signalsThe peak times are t' 1 ＝0.0279，t′ 2 0.0492, the infrasonic signal time difference is tau '═ t' 2 -t′ 1 0.0213s, a coarse localization result is thus obtained according to the infrasonic localization principle: l' 1 ＝(12.8+0.0213×340)/2＝10.02m。
The positioning error is calculated as:
the calculation result shows that the positioning precision of the method is improved by 3.29 percent compared with the coarse positioning precision.
Example 2:
this example differs from example 1 in that: after the pipeline runs stably, the leakage hole 7 is opened to simulate 1mm tiny leakage of the pipeline. The diagnostic method of the present invention was validated as follows:
the pipe pass acoustic time domain signals are collected and subjected to spectrum conversion as shown in fig. 10. As can be seen from FIG. 10, the amplitude fluctuation of the infrasonic signal spectrum is mainly concentrated at 10.5Hz and 18.5Hz, i.e. the spectrum has a multi-peak fluctuation characteristic and is located in a frequency range of 5Hz to 20 Hz. And comparing with the urban pipeline tiny leakage frequency spectrum judgment criterion, and judging that the pipeline is in tiny leakage at the moment.
The extraction of the characteristic bands in the spectrum using the coherence function is shown in fig. 11. As can be seen from FIG. 11, the function has a maximum value at 13.5Hz, and the frequency band of the function is 12-15 Hz as the characteristic frequency band. Then, a band-pass filter is used for extracting leakage signals in the characteristic frequency band, and the upper limit and the lower limit of the characteristic frequency band are used as the upper cutoff frequency and the lower cutoff frequency f of the band-pass filter 0 12Hz and f 1 15Hz, center frequency f c ＝13.5Hz。
For further accurately calculating the time difference of the infrasonic wave signals, the leakage signals x at the upstream and the downstream of the pipeline are subjected to 1 (t)，x 2 (t) generalized mutual time-frequency analysis is performed, as shown in FIG. 12.
As can be seen from FIG. 12, the correlation function of the infrasonic leakage signals at upstream and downstream positions has a maximum value within the frequency range of 0-200 Hz, and the maximum value of the correlation function corresponds to the maximum valueWith a sampling time N of 527 μ s and a signal sampling frequency f s When the frequency is 34Hz, the time difference of transmitting the infrasonic wave signal to the upstream and downstream ends of the pipeline is accurately calculated according to the number of the sampling points: tau is 0 ＝527×34×10 -6 ＝0.0179s。
The pressure data collected by each pressure sensor on the pipeline is retrieved through the pressure monitoring platform, as shown in fig. 13. Then, taking the average value of the pressure at each pressure measuring position in the pipeline collecting state of 30s as the pipeline pressure value, namely:
substituting the pressure value of the pipeline into a secondary sound wave velocity calculation formula to obtain:
and substituting the accurate time delay and the infrasonic velocity into a positioning formula to accurately position the leakage point.
The positioning error is calculated as:
and comparing the result with the unprocessed upstream and downstream leakage signal rough positioning result. Time domain waveforms of the infrasonic wave leakage signals upstream and downstream are shown in fig. 14.
As can be seen from FIG. 14, the time of occurrence of amplitude spikes in the time domain waveforms of the upstream and downstream leakage signals is t' 1 ＝0.0315s，t′ 2 0.0565s, the infrasonic signal time difference is tau '═ t' 2 -t′ 1 0.025s, so the coarse localization result is obtained according to the infrasonic localization principle: l' 1 ＝(12.8+0.025×340)/2＝10.65m。
The positioning error is calculated as:
the calculation result shows that the positioning precision of the method is improved by 8 percent compared with the coarse positioning precision.
Example 3:
this example differs from example 2 in that: after the pipeline runs stably, the leakage hole 7 is opened to simulate the 5mm tiny leakage of the pipeline, and the diagnosis method is verified, and specifically comprises the following steps:
the pipe pass acoustic time domain signals are collected and subjected to spectrum conversion as shown in fig. 15. As can be seen from FIG. 15, the amplitude fluctuation of the infrasonic signal spectrum is mainly concentrated at 6Hz and 18Hz, i.e. the spectrum has a multi-peak fluctuation characteristic and is located in a frequency range of 5Hz to 20 Hz. And comparing with the urban pipeline tiny leakage frequency spectrum judgment criterion, and judging that the pipeline is in tiny leakage at the moment.
The extraction of the characteristic bands in the spectrum using the coherence function is shown in fig. 16. As can be seen from FIG. 11, the function has a maximum value at 11.7Hz, and the frequency band at which the function is located is 11.5-15 Hz as the characteristic frequency band. Then, a band-pass filter is used for extracting leakage signals in the characteristic frequency band, and the upper limit and the lower limit of the characteristic frequency band are used as the upper cutoff frequency and the lower cutoff frequency f of the band-pass filter 0 11.5Hz and f 1 15Hz, center frequency f c ＝13.25Hz。
For further accurately calculating the time difference of the infrasonic wave signals, the leakage signals x at the upstream and the downstream of the pipeline are subjected to 1 (t)，x 2 (t) generalized mutual time-frequency analysis was performed, as shown in FIG. 17.
As can be seen from fig. 17, the correlation function of the infrasonic leakage signals at upstream and downstream positions has a maximum value in the frequency range of 0 to 200Hz, the sampling time N corresponding to the maximum value of the correlation function is 840 μ s, and the signal sampling frequency f is set to be the same as the signal sampling frequency f s And (3) accurately calculating the time difference of transmitting the infrasonic wave signal to the upstream and downstream ends of the pipeline according to the number of the sampling points: tau is 0 ＝840×27×10 -6 ＝0.0227s。
The pressure data collected by each pressure sensor on the pipeline is retrieved by the pressure monitoring platform, as shown in fig. 18. Then, taking the average value of the pressure at each pressure measuring position in the pipeline acquisition state of 30s as a pipeline pressure value, namely:
substituting the pressure value of the pipeline into a secondary sound wave velocity calculation formula to obtain:
and substituting the accurate time delay and the infrasonic velocity into a positioning formula to accurately position the leakage point.
The positioning error is calculated as:
and comparing the result with the unprocessed upstream and downstream leakage signal rough positioning result. Time domain waveforms of the infrasonic wave leakage signals upstream and downstream are shown in fig. 19.
As can be seen from FIG. 19, the time at which the amplitude spike appears in the time domain waveforms of the upstream and downstream leakage signals is t' 1 ＝0.039s，t′ 2 0.058s, the infrasonic wave signal time difference is tau '═ t' 2 -t′ 1 0.019s, therefore the coarse localization result is obtained according to the infrasonic localization principle: l' 1 ＝(12.8+0.019×340)/2＝9.63m。
The positioning error is calculated as:
the calculation result shows that the positioning precision of the method is improved by 3.23 percent compared with the coarse positioning precision.
Examples 1-3 show that: the method can improve the positioning precision of the pipeline leakage to a greater extent and can realize the accurate positioning of the pipeline leakage.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (8)
1. A tiny leakage diagnosis method for an urban gas pipeline is characterized by comprising the following steps: the method comprises the following steps:
respectively collecting time domain signals of infrasonic waves in pipelines of a buried gas pipeline simulation test system under different pressures, wherein the pipelines are not leaked and slightly leaked, carrying out frequency spectrum conversion on the time domain signals to obtain an infrasonic wave frequency spectrum of the simulation test system, and further obtaining a judgment criterion of the urban gas pipeline micro-leakage frequency spectrum;
acquiring infrasonic time domain signals of the urban pipeline to be detected, performing frequency spectrum conversion on the acquired infrasonic time domain signals of the urban pipeline to be detected to obtain infrasonic frequency spectrums of the urban pipeline to be detected, and judging whether the urban pipeline to be detected leaks or not according to the urban gas pipeline tiny leakage frequency spectrum judgment criterion;
if the pipeline leaks, establishing a pipeline leakage positioning model;
the method comprises the steps of taking the interference of a noise signal to a source signal into consideration, extracting a characteristic frequency band in an infrasonic wave frequency spectrum, and further extracting a leakage signal in the characteristic frequency band;
calculating the time delay of the extracted infrasonic wave output leakage signals of the upstream and the downstream;
collecting a pipeline pressure value in a pipeline leakage state Ts, and calculating the wave velocity of the infrasonic wave signal according to the pipeline pressure value;
and substituting the time delay and the wave speed into a positioning model to obtain the positioning of the leakage point.
2. The urban gas pipeline tiny leakage diagnosis method according to claim 1, characterized in that: the specific method of the frequency spectrum conversion is as follows: converting the acquired infrasonic time-domain signal x (t) into a frequency-domain spectral density function X (f):
in the formula: x (f) is a frequency domain spectral density function; ω is the simulated angular frequency, ω -2 π f, f denotes the frequency; e is a natural logarithm base; j is an imaginary unit; t represents a time;
calculating an amplitude spectrum estimation function of the frequency domain spectral density function X (f)
Dividing the frequency domain spectral density function X (f) into M equal-length data segments, and observing M points of the frequency domain spectral density function X (f) by using the M points M (f) Considered as a finite signal; then to X M (f) Fourier transform to X M (k) (ii) a Finally taking X M (k) The square of the amplitude and the division by the number of data segments M as an amplitude spectrum estimation function of the frequency domain spectral density function X (f)
Namely:
estimating a function from an amplitude spectrum
And drawing a spectrum diagram of the infrasonic wave signal.
3. The method for diagnosing the tiny leakage of the urban gas pipeline according to claim 1, wherein: the urban gas pipeline tiny leakage frequency spectrum judgment criterion is as follows: when the urban gas pipeline is not leaked, the infrasonic wave frequency spectrum signal meets the characteristic that only one amplitude peak exists, and the corresponding frequency is not more than 5 Hz; when the urban gas pipeline leaks slightly, the infrasonic wave frequency spectrum has at least 2 amplitude peak fluctuation characteristics, and the corresponding frequency range is within 5 Hz-20 Hz.
4. The urban gas pipeline tiny leakage diagnosis method according to claim 1, characterized in that: the pipeline leakage positioning model is as follows: let s (t), n 1 (t)，n 2 (t) are not related to each other,
in the formula: l 1 Distance in m from the leak location to the upstream infrasonic sensor; l is the distance between the upstream infrasonic wave sensor and the downstream infrasonic wave sensor, and is the unit m; tau is 0 Is the time delay, in units of s; v is the wave speed of the infrasonic wave signal, unit m/s; s (t) is an unknown original leakage source signal; n is a radical of an alkyl radical 1 (t) and n 2 (t) is a zero-mean random noise signal representing ambient noise, and t is time.
5. The urban gas pipeline tiny leakage diagnosis method according to claim 1, characterized in that: the method for extracting the characteristic frequency band in the infrasonic wave frequency spectrum and further extracting the leakage signal in the characteristic frequency band comprises the steps of extracting the frequency band corresponding to the continuous peak value in the infrasonic wave frequency spectrum as the characteristic frequency band by adopting a coherent function, taking the frequency band where the maximum value is located as the characteristic frequency band if at least 2 continuous peak values exist, and then extracting the leakage signal in the characteristic frequency band by using a band-pass filter.
6. The method for diagnosing the tiny leakage of the urban gas pipeline according to claim 1, wherein: the method for calculating the time delay of the extracted infrasonic wave output leakage signals of the upstream and the downstream adopts a generalized mutual time-frequency method, and the specific method is as follows: tong (Chinese character of 'tong')Calculating the cross power spectrum of the infrasonic wave signal, and then combining a band-pass filter and a cross spectrum function to solve a modified weighting function psi 12 (f) Weighting in a frequency domain range, strengthening the spectral components in the signals, improving the signal-to-noise ratio of the signals, and obtaining a generalized mutual time-frequency function; and then, reversely transforming the frequency domain to the time domain by utilizing a generalized mutual time-frequency function, and calculating the time difference of the infrasonic wave signal according to a signal correlation principle to obtain the time delay of the infrasonic wave signal.
7. The urban gas pipeline tiny leakage diagnosis method according to claim 1, characterized in that: pipeline pressure value P sets up a plurality of pressure sensor on the pipeline, and the average value of each pressure measurement position pressure is transferred as pipeline pressure value P in gathering pipeline leakage state Ts through pressure monitoring platform, establishes the time step and is 1s, and the position step is 2.5m, promptly:
in the formula: t is the pipeline leakage time, s; t is time, s; l is the distance between the upstream infrasonic wave sensor and the downstream infrasonic wave sensor, m; l 0 Is the pipeline pressure sensor position, m; [. the]Is a rounded symbol.
8. The urban gas pipeline tiny leakage diagnosis method according to claim 1, characterized in that: the method for calculating the wave velocity of the infrasonic wave signal leaked from the pipeline comprises the following steps: considering the factors of medium compression coefficient, medium density and pipeline size in the pipe, the calculation formula of the wave velocity v of the infrasonic wave signal leaked from the pipeline is as follows:
in the formula: rho is the density of the medium and the unit kg/m 3 (ii) a E is the elastic modulus of the pipeline, unit Pa; d is the diameter of the pipeline in mm; e is the wall thickness of the pipeline in mm; c isThe correction coefficient is dimensionless, and P is the pressure value in the pipe.
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