CN110645483B - Urban buried pipeline early leakage diagnosis method based on spectrum analysis - Google Patents

Urban buried pipeline early leakage diagnosis method based on spectrum analysis Download PDF

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CN110645483B
CN110645483B CN201910902824.0A CN201910902824A CN110645483B CN 110645483 B CN110645483 B CN 110645483B CN 201910902824 A CN201910902824 A CN 201910902824A CN 110645483 B CN110645483 B CN 110645483B
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pipeline
leakage
pressure
frequency spectrum
signal
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CN110645483A (en
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朱一龙
郝永梅
蒋军成
邢志祥
毛小虎
马逸飞
严欣明
岳云飞
杨克
吴洁
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Changzhou University
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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
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M3/00—Investigating fluid-tightness of structures
    • G01M3/02—Investigating fluid-tightness of structures by using fluid or vacuum
    • G01M3/04—Investigating fluid-tightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point
    • G01M3/24—Investigating fluid-tightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point using infrasonic, sonic, or ultrasonic vibrations
    • G01M3/243—Investigating fluid-tightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point using infrasonic, sonic, or ultrasonic vibrations for pipes

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Abstract

The invention relates to a method for diagnosing early leakage of urban buried pipelines based on spectral analysis, which comprises a pre-test before leakage diagnosis, wherein spectral data of a sufficient number of pipeline systems in a leakage state is acquired through the pre-test, and a spectral library of the pipeline systems in the leakage state is established. And then, diagnosing the actual leakage of the pipeline, and judging whether the pipeline leaks or not by only acquiring frequency spectrum data once and comparing the frequency spectrum acquired by the actual leakage of the pipeline with the data in a frequency spectrum library established in a pre-test. If the pipeline is determined not to be leaked, recording the frequency spectrum data into a frequency spectrum library in a non-leakage state; and if the pipeline is determined to be leaked, recording the frequency spectrum data into a frequency spectrum library in a leakage state, and carrying out next pipeline leakage positioning. The leakage detection method is simple, convenient and easy to implement, has high accuracy, and effectively solves the problem of positioning early leakage of the urban buried pipeline.

Description

Urban buried pipeline early leakage diagnosis method based on spectrum analysis
Technical Field
The invention relates to a pipeline leakage diagnosis method, in particular to an early leakage diagnosis method for urban buried pipelines based on spectrum analysis.
Background
In China, along with the continuous improvement of urbanization level, the urban pipeline construction scale is further enlarged. In order to effectively utilize urban space resources, urban pipelines are mainly buried. However, the urban ground has complex terrain and variable environment, and as time goes on, pipelines buried underground for a long time are easy to leak due to external factors such as impact, oxidation, corrosion and the like. Under the general condition, the leakage amount of urban buried pipelines is small, sound is weak and is not easy to perceive, and whether the urban buried pipelines leak or not is difficult to visually judge through the surfaces of the pipelines. If not detected in time, the environment is polluted, resources are wasted, and even the personal and property safety of the crisis is suffered. Therefore, research on early leakage diagnosis of urban buried pipelines is particularly necessary.
Disclosure of Invention
Aiming at the problems that the leakage of the urban buried pipeline is not easy to be perceived and the positioning error is large at present, the invention provides a novel urban buried pipeline early leakage diagnosis technology based on frequency spectrum analysis, and aims to solve the problem of early leakage diagnosis of the urban buried pipeline. According to the invention, through pre-experiments, under various different working conditions, a pipeline leakage monitoring system is utilized to obtain a large amount of frequency spectrum data of a pipeline, and a frequency spectrum library of the pipeline system is established; then, carrying out actual leakage diagnosis, comparing the frequency spectrum acquired by actual leakage of the pipeline with the data in the frequency spectrum library, and judging whether the pipeline leaks or not; and finally, accurately positioning the pipeline with leakage by using an excitation response method.
The technical scheme adopted by the invention is as follows:
an early leakage diagnosis method for urban buried pipelines based on spectral analysis comprises the following steps
S01, collecting pipeline frequency spectrum data under a set pipeline pressure to obtain a frequency spectrum diagram of the pipeline in a non-leakage state;
s02, under the same pipeline pressure state as S01, opening the leakage ball valve to simulate the pipeline leakage state, and collecting pipeline frequency spectrum data under the leakage state to obtain a frequency spectrum diagram under the pipeline leakage state;
s03, changing the working condition of the pipeline, repeating the steps S01 and S02, obtaining frequency spectrum data of the pipeline in the non-leakage state and the leakage state under various working conditions, and establishing a frequency spectrum library of the pipeline in the non-leakage state and the leakage state;
s04, when actual leakage is detected, the frequency spectrum acquired by actual leakage of the pipeline is compared with the frequency spectrum data in the frequency spectrum library to judge whether the pipeline leaks or not;
s05, for the leaked pipeline, enabling the pipeline system to send out excitation response and collecting an excitation pressure signal of the pipeline system; then, taking the time as an abscissa and the ratio of the transient pressure to the average value of the excitation pressure as an ordinate to obtain a pressure time domain analysis graph of the pipeline system, and obtaining a time domain pressure signal graph of the pipeline system;
s06: and performing CEEMD processing on the acquired time domain pressure signal, removing signal noise, identifying the position of a singular value inflection point of the signal, and finally calculating the position of a leakage point by combining the velocity of the infrasonic wave.
Furthermore, the pipeline frequency spectrum data comprise pipeline infrasonic wave signals z (t) acquired by an infrasonic wave acquisition instrument and transient pressure signals p acquired by the intelligent pressure transmitter1(t) transient flow signal q read by turbine flowmeter1(t)。
Further, the method for obtaining the spectrogram of the pipeline in the non-leakage state through the pipeline frequency spectrum data comprises the following steps: a calculating the transfer function Z of the pipeline systemD：
As known, the continuous and momentum equations of a one-dimensional pipeline are:
Figure GDA0002695689830000021
wherein p is a pressure function; q is a flow function; x is the distance from the upstream section of the pipeline; t is time;
Figure GDA0002695689830000022
is unit length inductive reactance;
Figure GDA0002695689830000023
is unit length capacitive reactance;
Figure GDA0002695689830000024
impedance per unit length; g is the acceleration of gravity; a is the cross-sectional area of the pipeline; a is the velocity of the pressure wave; d is the inner diameter of the pipeline; f is the Darcy-Weibach friction coefficient;
in the frequency domain, the pressure function and flow function can be expressed as:
Figure GDA0002695689830000025
in the formula (I), the compound is shown in the specification,
Figure GDA0002695689830000026
is the average pressure; p is a radical of1(t) is the transient pressure;
Figure GDA0002695689830000027
is the average flow rate; q. q.s1(t) is the transient flow rate.
When formula (2) is substituted for formula (1), the following are provided:
Figure GDA0002695689830000028
in the formula, p1(t)＝P(x)est；q1(t)＝Q(x)est；
Figure GDA0002695689830000031
Is the dynamic flow resistance.
The functional expression of the pressure and the flow at the inlet and the outlet of the pipeline is as follows:
Figure GDA0002695689830000032
Figure GDA0002695689830000033
in the formula, PUIs the pressure at the inlet of the pipeline; pDIs the pressure at the outlet of the pipeline; qUIs the flow at the inlet of the pipeline; qDIs the flow at the outlet of the pipeline;
Figure GDA0002695689830000034
is the propagation constant;
Figure GDA0002695689830000035
is a characteristic impedance;
simultaneous equations (3), (4) and (5) are obtained to obtain the input and output impedances of the pipeline:
Figure GDA0002695689830000036
it is known that the upstream end of the conduit is a constant pressure source, i.e. the pressure at the inlet of the conduit fluctuates to zero and will therefore
Figure GDA0002695689830000037
Substituting formula (6), and obtaining a transfer function of the pipeline system in the time domain as follows:
ZD＝-ZC tanhγl
in the formula, ZDIs the transfer function value; zcIs a characteristic impedance; gamma is a propagation constant; l is the length of the pipeline; b to the transfer function ZDAnd performing Fourier transform to obtain a spectrogram of a transfer function in a frequency domain.
Further, the working conditions of the pipeline comprise pipeline pressure, leakage amount and leakage position in a leakage state, and the working conditions of the non-leakage state test are different pipeline pressures; the leakage state involves the following conditions: and recording the specific working conditions and time of each test at different pipeline pressures, leakage amounts and leakage positions, recording the spectrogram corresponding to each test into a frequency spectrum library, and establishing the frequency spectrum library in the non-leakage state and the leakage state of the pipeline.
Further, the step S04 is specifically: when the actual leakage of the pipeline is detected, only once spectrum data is collected, then spectrum analysis is carried out, the obtained spectrogram is compared with the spectrogram in the spectrum library in a characteristic way, and if the actual leakage detection spectrum is matched with the spectrogram in a non-leakage state in the spectrum library, the pipeline is judged not to be leaked; and if the actual leakage detection spectrogram is matched with the spectrogram in the leakage state in the frequency spectrum library, judging that the pipeline leaks.
Further, step S5 specifically includes:
for a leaking pipe, the valve at the downstream end of the pipe is momentarily partially closed to the position 1/4, so that the excitation response is generated at the end of the pipe; then collecting the excitation pressure signal p of the pipeline2(t)。
Note: the 'instant' represents the operation which is as fast as possible, so that an obvious excitation signal is generated in the pipeline, and the problem of unobvious excitation caused by too slow operation is avoided. "partial closure" means incomplete closure, and if the valve is completely closed, the resulting activation signal can be large and the impact of the media can cause damage to the piping system. The '1/4 position' is the 1/4 position of the valve opening, which is the position summarized by long-term test and has practical engineering significance, and the position is convenient for manual operation, and can not only generate obvious excitation signals, but also cause no great damage to the pipeline system.
After the collection is finished, the valve at the downstream end of the pipeline is restored to a fully opened state, the operation is repeated after the pipeline runs stably, and the excitation pressure signals are collected for 5 times in total and averaged to obtain the average value of the excitation pressure
Figure GDA0002695689830000041
Finally, the time t is used as the abscissa and the transient pressure p is used1(t) average value of excitation pressure
Figure GDA0002695689830000042
The ratio of (a) to (b) is a time domain analysis graph of the pressure signal calculated by the ordinate, and a time domain pressure signal s (t) of the pipeline system is obtained.
Further, the method for denoising the time-domain pressure signal and identifying the position of the singular value inflection point by using the CEEMD in step S6 specifically includes:
(1) adding white Gaussian noise omega to time-domain pressure signal s (t)i(t) for the target signal s (t) + ωi(t) performing a 1 st CEEMD decomposition to obtain a first IMF1
Figure GDA0002695689830000043
In the formula, E1For the defined CEEMD operation symbol, the subscript "1" represents the first iteration operation;1the signal-to-noise ratio coefficient is set for each stage, and the corner mark '1' represents the 1 st stage; omegaiIs Gaussian white noise with unit variance as zero mean;
(2) calculating to obtain a first order residual error r1(t)
r1(t)＝s(t)-IMF1(t) (8)
(3) For the first order residual r1(t) the white noise signal added thereto, and a structural signal r1(t)+1E1(ωi(t)) and decomposed again to obtain a second IMF2；
Figure GDA0002695689830000044
(4) So on to calculate the kth residual rk(t)rk，k＝2,3...K
rk(t)＝rk-1(t)-IMFi(t) (10)
(5) Then continue to decompose rk(t)+kEk(ωi(t)), i ═ 1, 2 … n, whose 1 st natural mode function component is the IMF of CEEMDk+1
Figure GDA0002695689830000051
(6) Continuing decomposition until the end condition is met, otherwise, returning to the steps (4) to (5), and finally, expressing the result as:
Figure GDA0002695689830000052
in the formula, IMFk(t) is the decomposed IMF function of each order;
(7) selecting the first three-order signal component reconstruction after CEEMD decomposition to obtain an effective signal x (t) after de-noising and reconstruction, namely:
x(t)＝im1f+im2f+im3f (13)
wherein, x (t) is an effective leakage signal after denoising and reconstruction; imf1，imf2，imf3The first three-order signal component;
(8) the time of the infrasonic wave reflected to the downstream end is determined according to the position of the singular point of the effective signal x (t), and the position of the leakage point can be accurately calculated by combining the wave velocity of the infrasonic wave.
The beneficial effects produced by the invention comprise: the leakage detection method based on the frequency spectrum analysis is simple and easy to implement, has high accuracy, and can continuously perfect a frequency spectrum library through tests under various working conditions, so that the misjudgment rate of the leakage detection can be infinitely close to zero.
Drawings
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 a pipeline system transient pressure signal
FIG. 4 is a signal diagram of real-time flow rate of a piping system
FIG. 5 is a diagram of infrasonic signals of a piping system
FIG. 6 is a frequency spectrum diagram of a pipeline system in a leak-free state at a certain time;
FIG. 7 is a graph of the spectrum of a leak condition at a time in a piping system;
FIG. 8 is a frequency spectrum plot of a piping system acquired at actual leak detection;
FIG. 9 is a graph of a experimentally acquired time domain pressure signal for a piping system;
FIG. 10 is a CEEMD decomposition result graph;
fig. 11 is a pressure time domain analysis diagram after denoising and reconstruction.
In the figure: 1. trunk line, 2, first branch pipe, 3, second branch pipe, 4, diffuse mouthful, 5, infrasonic wave sensor, 6, intelligent pressure transmitter, 7, turbine flowmeter.
Detailed Description
The invention is explained in further detail below with reference to the figures and the embodiments, but it should be understood that the scope of protection of the invention is not limited to the embodiments and figures.
The invention is roughly divided into two parts. The first part is a pre-test before leakage diagnosis, and a frequency spectrum library of the leakage state of the pipeline system is established by acquiring the frequency spectrum data of the leakage state of a sufficient number of pipeline systems through the pre-test. And the second part is the actual leakage diagnosis of the pipeline, and when the actual leakage of the pipeline is detected, the frequency spectrum data is acquired only once, and the frequency spectrum acquired by the actual leakage of the pipeline is compared with the data in a frequency spectrum library established in advance by virtue of a pre-test, so that whether the pipeline leaks or not can be judged. If the pipeline is determined not to be leaked, recording the frequency spectrum data into a frequency spectrum library in a non-leakage state; and if the pipeline is determined to be leaked, recording the frequency spectrum data into a frequency spectrum library in a leakage state, and carrying out next pipeline leakage positioning.
As shown in fig. 1, the method for diagnosing early leakage of an urban buried pipeline based on spectrum analysis of the invention comprises the following steps:
step S1: as shown in fig. 2, the test piping system related to the present invention is composed of buried nonmetallic piping, a leakage valve and related instrumentation. Wherein, the main pipeline (1) is U-shaped, the straight section of the main pipeline (1) is connected with a first branch pipe (2), a second branch pipe (3) is connected between the first branch pipe (2) and the top end of the main pipeline (1), two straight sections and the top end of the main pipeline (1) are respectively provided with a scattering port (4) for simulating leakage points, the distance between the scattering port (4) and the head end of the pipeline is 8.91 meters, the starting section and the terminal section of the main pipeline (1) are respectively provided with an infrasonic wave sensor (5), intelligence pressure transmitter (6) and turbine flowmeter (7), first branch pipe (2) are gone up to divide and are equipped with turbine flowmeter (7) and intelligent pressure transmitter (6), are equipped with intelligent pressure transmitter (6) on second branch pipe (3), are located diffusion mouth (4) on two straight sections of trunk line (1) and locate to be equipped with turbine flowmeter (7), are located diffusion mouth (4) of trunk line (1) top department and are equipped with intelligent pressure transmitter (6).
Firstly, a pipeline system is started, a pressure pump is connected to the first section of a pipeline, a throttle valve at the tail end of the pipeline is completely opened, an alternating current motor is started, and the working pressure of the pump is adjusted to 0.4MPa, leading the pipeline system to enter a medium conveying state. After the pipeline runs stably, acquiring transient pressure signal p of the pipeline through the intelligent pressure transmitter1(t), as shown in FIG. 3; reading transient flow signal q of pipeline by vortex flowmeter1(t), as shown in FIG. 4; an infrasonic wave signal z (t) of the pipeline is obtained through the infrasonic wave acquisition instrument, and whether the pipeline runs stably is judged by observing an infrasonic wave signal diagram of the pipeline as shown in fig. 5.
Carrying out spectrum analysis on the acquired data by using Matlab software, and acquiring the transient pressure p1(t) transient flow rate q1(t) calculating to obtain a transfer function Z of the pipeline systemCThe spectrogram under the normal operation (non-leakage) state of the pipeline is obtained by Fourier transform of the transfer function, as shown in FIG. 6.
Step S2: and (3) opening the pipeline leakage ball valve, controlling the inclination angle of the leakage ball valve to be 15 degrees, simulating the tiny leakage state of the pipeline, then collecting all parameters of the pipeline system again and carrying out spectrum analysis on the parameters to obtain a spectrogram of the pipeline system in the leakage state, as shown in fig. 7.
Step S3: and repeating the steps S1 and S2, performing a plurality of tests, respectively obtaining the frequency spectrum data of a sufficient number of pipeline systems with or without leakage states, and establishing a frequency spectrum library of the pipeline systems with or without leakage states.
Step S4: and detecting the actual leakage of the pipeline.
Firstly, various parameters of the pipeline to be measured are obtained by adopting a real-time monitoring and field measurement method, as shown in table 1.
TABLE 1 pipe System parameters
Figure GDA0002695689830000071
Then, the operations of steps S1 and S2 are repeated, the pressure and flow rate of the pipeline are collected, and the Matlab is used to perform a spectrum analysis on the collected pipeline system parameters, and the result is shown in fig. 8. And comparing the frequency spectrum analysis result graph 8 with the data (shown in figures 6 and 7) in the frequency spectrum library to judge whether the pipeline leaks.
As can be seen from fig. 6, the trend of the spectrogram fluctuation in the non-leakage state of the pipeline is as follows: the amplitude corresponding to the low-frequency state is higher, while the amplitude corresponding to the high-frequency state tends to be stable; as can be seen from fig. 7, the trend of the fluctuation of the spectrogram in the pipeline leakage state is as follows: there is a large amplitude fluctuation in a certain frequency range due to the influence of the leakage sound wave.
In fig. 8, when the normalized frequency of the abscissa is between 0.15 and 0.85, the amplitude of the ordinate has large fluctuation, and the characteristics thereof are relatively matched with those of fig. 7, so that it is determined that the pipeline is in a leakage state at this time, and the next pipeline leakage positioning is performed.
Step S5: for a pipe in a leakage state, the downstream end valve is momentarily partially closed to 1/4, so that the pipe system sends out an excitation response and collects an excitation pressure signal p of the pipe system2(t), repeating 5 times to obtain the average value of the excitation pressure
Figure GDA0002695689830000081
Then the time is used as the abscissa and the transient pressure p is used1(t) average value of excitation pressure
Figure GDA0002695689830000082
Ratio of
Figure GDA0002695689830000083
On the ordinate, a time domain pressure signal diagram of the piping system is plotted, as shown in fig. 9.
Step S6: denoising the acquired time domain pressure signal by using a CEEMD algorithm, identifying the position of a singular value inflection point of the signal, and finally calculating the position of a leakage point by combining the infrasonic wave speed;
denoising the time domain pressure signal s (t) by applying a CEEMD algorithm in Matlab software, calling a threshold function to calculate to obtain a threshold value of the time domain pressure signal, and decomposing the signal in a self-adaptive manner.
As shown in FIG. 10, the time domain pressure signal s (t) is decomposed into a form of 1-8 order IMF from low frequency to high frequency. Wherein, the lower the IMF order, the more effective leakage signals it carries; the higher the IMF order, the more noise signals it is entrained with. Therefore, 1-3 order signal reconstruction is selected to obtain a denoised and reconstructed effective signal x (t), as shown in fig. 11.
As can be seen from fig. 11, the reconstructed signal has an obvious characteristic singular value inflection point, and the time for transmitting the infrasonic wave to the downstream end sensor can be obtained according to the singular value inflection point. The abscissa corresponding to the maximum ordinate is the obtained time t, which is 0.0513 s.
Calculating the infrasonic wave velocity under the working condition according to a fluid sound velocity equation:
Figure GDA0002695689830000084
where v is the subsonic wave velocity, rho, under the corresponding working conditiontTo correspond to the density of air at temperature, PxThe measured pressure in the pipe is obtained.
The pressure P in the pipe under the working condition is measured simultaneously through the intelligent pressure transmitter arranged on the outer wall of the pipelinex0.15MPa and the temperature t in the tube is 24 ℃. Therefore, referring to the air density table, it can be seen that t is the air density ρ corresponding to 24 ℃t＝1.32kg/m3。
Will Px,ρtSubstituting into fluid sound velocity equation to obtain infrasonic wave velocity
Figure GDA0002695689830000085
Substituting the obtained infrasonic wave velocity v and the time t for transmitting the infrasonic wave to a downstream end sensor into a leakage positioning formula to obtain a positioning result
Figure GDA0002695689830000086
Comparing the positioning result with the actual leakage position to obtain the relative error of positioning
Figure GDA0002695689830000091
The result shows that the urban buried pipeline early leakage diagnosis method based on the spectrum analysis can effectively judge leakage and accurately position the leakage.
In light of the foregoing description of preferred embodiments in accordance with the invention, it is to be understood that numerous changes and modifications may be made by those skilled in the art without departing from the scope of the invention. The technical scope of the present invention is not limited to the contents of the specification, and must be determined according to the scope of the claims.

Claims (7)

1. A method for diagnosing early leakage of an urban buried pipeline based on spectral analysis is characterized by comprising the following steps: the method comprises the following steps:
s01, collecting pipeline frequency spectrum data under a set pipeline pressure to obtain a frequency spectrum diagram of the pipeline in a non-leakage state;
s02, under the condition that the pressure of the pipeline is the same as the pressure of the pipeline set in the step S01, opening the leakage ball valve to simulate the leakage state of the pipeline, and collecting the frequency spectrum data of the pipeline under the leakage state to obtain a frequency spectrum diagram under the leakage state of the pipeline;
s03, changing the working condition of the pipeline, repeating the steps S01 and S02, obtaining frequency spectrum data of the pipeline in the non-leakage state and the leakage state under various working conditions, and establishing a frequency spectrum library of the pipeline in the non-leakage state and the leakage state;
s04, when actual leakage is detected, the frequency spectrum data acquired by actual leakage of the pipeline is compared with the frequency spectrum data in the frequency spectrum library to judge whether the pipeline leaks or not;
s05, for the pipeline with leakage, closing the downstream end valve to make the pipeline system send out excitation response and collect the excitation pressure signal of the pipeline system; then, taking the time as an abscissa and taking the ratio of the transient pressure to the average value of the excitation pressure as an ordinate to obtain a time-domain pressure signal diagram of the pipeline system;
s06, CEEMD processing is carried out on the obtained time domain pressure signal, signal noise is removed, the position of a singular value inflection point of the signal is identified, and finally the position of a leakage point is calculated by combining the velocity of infrasonic waves;
the method for obtaining the spectrogram of the pipeline in the non-leakage state through the pipeline frequency spectrum data comprises the following steps:
a calculating the transfer function Z of the pipeline systemD：
As known, the continuous and momentum equations of a one-dimensional pipeline are:
Figure FDA0002695689820000011
wherein p is a pressure function; q is a flow function; x is the distance from the upstream section of the pipeline; t is time;
Figure FDA0002695689820000012
is unit length inductive reactance;
Figure FDA0002695689820000013
is unit length capacitive reactance;
Figure FDA0002695689820000014
impedance per unit length; g is the acceleration of gravity; a is the cross-sectional area of the pipeline; a is the velocity of the pressure wave; d is the inner diameter of the pipeline; f is the Darcy-Weibach friction coefficient;
in the frequency domain, the pressure function and flow function are expressed as:
Figure FDA0002695689820000015
in the formula (I), the compound is shown in the specification,
Figure FDA0002695689820000021
is the average pressure; p is a radical of1(t) is the transient pressure;
Figure FDA0002695689820000022
is the average flow rate; q. q.s1(t) is the transient flow rate;
when formula (2) is substituted for formula (1), the following are provided:
Figure FDA0002695689820000023
in the formula, p1(t)＝P(x)est；q1(t)＝Q(x)est；
Figure FDA0002695689820000024
Is a dynamic flow resistance;
the functional expression of the pressure and the flow at the inlet and the outlet of the pipeline is as follows:
Figure FDA0002695689820000025
Figure FDA0002695689820000026
in the formula, PUIs the pressure at the inlet of the pipeline; pDIs the pressure at the outlet of the pipeline; qUIs the flow at the inlet of the pipeline; qDIs the flow at the outlet of the pipeline;
Figure FDA0002695689820000027
is the propagation constant;
Figure FDA0002695689820000028
is a characteristic impedance;
simultaneous equations (3), (4) and (5) are obtained to obtain the input and output impedances of the pipeline:
Figure FDA0002695689820000029
it is known that the upstream end of the conduit is a constant pressure source, i.e. the pressure at the inlet of the conduit fluctuates to zero and will therefore
Figure FDA00026956898200000210
Substituting formula (6), and obtaining a transfer function of the pipeline system in the time domain as follows:
ZD＝-ZC tanhγl
in the formula, ZDIs a transfer function; zcIs a characteristic impedance; gamma is a propagation constant; l is the length of the pipeline; b to the transfer function ZDAnd performing Fourier transform to obtain a spectrogram of a transfer function in a frequency domain.
2. The urban buried pipeline early leakage diagnosis method based on spectral analysis according to claim 1, characterized in that: the pipeline frequency spectrum data comprises an infrasonic wave signal z (t) of the pipeline acquired by an infrasonic wave acquisition instrument, and transient pressure p of the pipeline acquired by an intelligent pressure transmitter1(t) reading the transient flow q of the pipeline by means of a turbine flowmeter1(t)。
3. The urban buried pipeline early leakage diagnosis method based on spectral analysis according to claim 1, characterized in that: the working conditions of the pipeline comprise pipeline pressure, leakage amount and leakage position in a leakage state, and the working conditions of the non-leakage state test are different pipeline pressures; the leakage state involves the following conditions: and recording the specific working conditions and time of each test at different pipeline pressures, leakage amounts and leakage positions, recording the spectrogram corresponding to each test into a frequency spectrum library, and establishing the frequency spectrum library in the non-leakage state and the leakage state of the pipeline.
4. The urban buried pipeline early leakage diagnosis method based on spectral analysis according to claim 1, characterized in that: step S04 specifically includes: when the actual leakage of the pipeline is detected, only once spectrum data is collected, then spectrum analysis is carried out, the obtained spectrogram is compared with the spectrogram in the spectrum library in a characteristic way, and if the actual leakage detection spectrogram is matched with the spectrogram in a non-leakage state in the spectrum library, the pipeline is judged not to be leaked; and if the actual leakage detection spectrogram is matched with the spectrogram in the leakage state in the frequency spectrum library, judging that the pipeline leaks.
5. The urban buried pipeline early leakage diagnosis method based on spectral analysis according to claim 1, characterized in that: step S5 specifically includes:
for a leaking pipe, the valve at the downstream end of the pipe is momentarily partially closed to the position 1/4, so that the excitation response is generated at the end of the pipe; then collecting the excitation pressure signal p of the pipeline2(t)；
After the collection is finished, the valve at the downstream end of the pipeline is restored to a fully opened state, the operation is repeated after the pipeline runs stably, the excitation pressure signals are collected for n times in total and averaged to obtain the average value of the excitation pressure
Figure FDA0002695689820000031
Finally, the time t is used as the abscissa and the transient pressure p is used1(t) average value of excitation pressure
Figure FDA0002695689820000032
The ratio of (a) to (b) is a time domain analysis graph of the pressure signal calculated by the ordinate, and a time domain pressure signal s (t) of the pipeline system is obtained.
6. The urban buried pipeline early leakage diagnosis method based on spectral analysis according to claim 5, characterized in that: the number n is 5.
7. The urban buried pipeline early leakage diagnosis method based on spectral analysis according to claim 1, characterized in that: the method for denoising the time domain pressure signal and identifying the position of the singular value inflection point by using the CEEMD in the step S6 specifically includes:
1) adding white Gaussian noise omega to time-domain pressure signal s (t)i(t) for the target signal s (t) + ωi(t) performing a 1 st CEEMD decomposition to obtain a first IMF1
Figure FDA0002695689820000041
In the formula, E1For the defined CEEMD operation symbol, the subscript "1" represents the first iteration operation;1the signal-to-noise ratio coefficient is set for each stage, and the corner mark '1' represents the 1 st stage; omegaiIs Gaussian white noise with unit variance as zero mean;
2) calculating to obtain a first order residual error r1(t)
r1(t)＝s(t)-IMF1(t) (8)
3) For the first order residual r1(t) the white noise signal added thereto, and a structural signal r1(t)+1E1(ωi(t)) and decomposed again to obtain a second IMF2；
Figure FDA0002695689820000042
4) So on to calculate the kth residual rk(t)rk，k＝2，3…K
rk(t)＝rk-1(t)-IMFi(t) (10)
5) Then continue to decompose rk(t)+kEk(ωi(t)), i ═ 1, 2 … n, whose 1 st natural mode function component is the IMF of CEEMDk+1
Figure FDA0002695689820000043
6) Continuing to decompose until the end condition is met, otherwise returning to the steps 4) to 5), and expressing the final result as:
Figure FDA0002695689820000044
in the formula, IMFk(t) is the decomposed IMF function of each order;
7) selecting the first three-order signal component reconstruction after CEEMD decomposition to obtain an effective signal x (t) after de-noising and reconstruction, determining the time of reflecting the infrasonic wave to the downstream end through the position of a singular point of the effective signal x (t), and then combining the velocity of the infrasonic wave to obtain the position of the leakage point.
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