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 PDFInfo
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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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Classifications

 F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
 F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
 F17D—PIPELINE SYSTEMS; PIPELINES
 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 fluidtightness of structures
 G01M3/02—Investigating fluidtightness of structures by using fluid or vacuum
 G01M3/04—Investigating fluidtightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point
 G01M3/24—Investigating fluidtightness 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 fluidtightness 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
Abstract
The invention relates to a method for diagnosing early leakage of urban buried pipelines based on spectral analysis, which comprises a pretest before leakage diagnosis, wherein spectral data of a sufficient number of pipeline systems in a leakage state is acquired through the pretest, 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 pretest. If the pipeline is determined not to be leaked, recording the frequency spectrum data into a frequency spectrum library in a nonleakage 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
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 preexperiments, 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 nonleakage 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 nonleakage state and the leakage state under various working conditions, and establishing a frequency spectrum library of the pipeline in the nonleakage 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 transmitter_{1}(t) transient flow signal q read by turbine flowmeter_{1}(t)。
Further, the method for obtaining the spectrogram of the pipeline in the nonleakage state through the pipeline frequency spectrum data comprises the following steps: a calculating the transfer function Z of the pipeline system_{D}：
As known, the continuous and momentum equations of a onedimensional pipeline are:
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;is unit length inductive reactance;is unit length capacitive reactance;impedance per unit length; g is the acceleration of gravity; a is the crosssectional area of the pipeline; a is the velocity of the pressure wave; d is the inner diameter of the pipeline; f is the DarcyWeibach friction coefficient;
in the frequency domain, the pressure function and flow function can be expressed as:
in the formula (I), the compound is shown in the specification,is the average pressure; p is a radical of_{1}(t) is the transient pressure;is the average flow rate; q. q.s_{1}(t) is the transient flow rate.
When formula (2) is substituted for formula (1), the following are provided:
in the formula, p_{1}(t)＝P(x)e^{st}；q_{1}(t)＝Q(x)e^{st}；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:
in the formula, P_{U}Is the pressure at the inlet of the pipeline; p_{D}Is the pressure at the outlet of the pipeline; q_{U}Is the flow at the inlet of the pipeline; q_{D}Is the flow at the outlet of the pipeline;is the propagation constant;is a characteristic impedance;
simultaneous equations (3), (4) and (5) are obtained to obtain the input and output impedances of the pipeline:
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 thereforeSubstituting formula (6), and obtaining a transfer function of the pipeline system in the time domain as follows:
Z_{D}＝Z_{C} tanhγl
in the formula, Z_{D}Is the transfer function value; z_{c}Is a characteristic impedance; gamma is a propagation constant; l is the length of the pipeline; b to the transfer function Z_{D}And 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 nonleakage 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 nonleakage 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 nonleakage 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 pipeline_{2}(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 longterm 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 pressureFinally, the time t is used as the abscissa and the transient pressure p is used_{1}(t) average value of excitation pressureThe 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 timedomain 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 timedomain pressure signal s (t)_{i}(t) for the target signal s (t) + ω_{i}(t) performing a 1 st CEEMD decomposition to obtain a first IMF_{1}
In the formula, E_{1}For the defined CEEMD operation symbol, the subscript "1" represents the first iteration operation;_{1}the signaltonoise ratio coefficient is set for each stage, and the corner mark '1' represents the 1 st stage; omega^{i}Is Gaussian white noise with unit variance as zero mean;
(2) calculating to obtain a first order residual error r_{1}(t)
r_{1}(t)＝s(t)IMF_{1}(t) (8)
(3) For the first order residual r_{1}(t) the white noise signal added thereto, and a structural signal r_{1}(t)+_{1}E_{1}(ω^{i}(t)) and decomposed again to obtain a second IMF_{2}；
(4) So on to calculate the kth residual r_{k}(t)r_{k}，k＝2,3...K
r_{k}(t)＝r_{k1}(t)IMF_{i}(t) (10)
(5) Then continue to decompose r_{k}(t)+_{k}E_{k}(ω^{i}(t)), i ═ 1, 2 … n, whose 1 st natural mode function component is the IMF of CEEMD_{k+1}
(6) Continuing decomposition until the end condition is met, otherwise, returning to the steps (4) to (5), and finally, expressing the result as:
in the formula, IMF_{k}(t) is the decomposed IMF function of each order;
(7) selecting the first threeorder signal component reconstruction after CEEMD decomposition to obtain an effective signal x (t) after denoising and reconstruction, namely:
x(t)＝im_{1}f+im_{2}f+im_{3}f (13)
wherein, x (t) is an effective leakage signal after denoising and reconstruction; imf_{1}，imf_{2}，imf_{3}The first threeorder 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 realtime 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 leakfree 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 pretest 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 pretest. 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 pretest, 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 nonleakage 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 Ushaped, 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 transmitter_{1}(t), as shown in FIG. 3; reading transient flow signal q of pipeline by vortex flowmeter_{1}(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 p_{1}(t) transient flow rate q_{1}(t) calculating to obtain a transfer function Z of the pipeline system_{C}The spectrogram under the normal operation (nonleakage) 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 realtime monitoring and field measurement method, as shown in table 1.
TABLE 1 pipe System parameters
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 nonleakage state of the pipeline is as follows: the amplitude corresponding to the lowfrequency state is higher, while the amplitude corresponding to the highfrequency 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 system_{2}(t), repeating 5 times to obtain the average value of the excitation pressureThen the time is used as the abscissa and the transient pressure p is used_{1}(t) average value of excitation pressureRatio ofOn 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 selfadaptive manner.
As shown in FIG. 10, the time domain pressure signal s (t) is decomposed into a form of 18 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, 13 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:
where v is the subsonic wave velocity, rho, under the corresponding working condition_{t}To correspond to the density of air at temperature, P_{x}The 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 pipeline_{x}0.15MPa 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/m^{3}。
Will P_{x},ρ_{t}Substituting into fluid sound velocity equation to obtain infrasonic wave velocity
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 resultComparing the positioning result with the actual leakage position to obtain the relative error of positioning
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 nonleakage 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 nonleakage state and the leakage state under various working conditions, and establishing a frequency spectrum library of the pipeline in the nonleakage 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 timedomain 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 nonleakage state through the pipeline frequency spectrum data comprises the following steps:
a calculating the transfer function Z of the pipeline system_{D}：
As known, the continuous and momentum equations of a onedimensional pipeline are:
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;is unit length inductive reactance;is unit length capacitive reactance;impedance per unit length; g is the acceleration of gravity; a is the crosssectional area of the pipeline; a is the velocity of the pressure wave; d is the inner diameter of the pipeline; f is the DarcyWeibach friction coefficient;
in the frequency domain, the pressure function and flow function are expressed as:
in the formula (I), the compound is shown in the specification,is the average pressure; p is a radical of_{1}(t) is the transient pressure;is the average flow rate; q. q.s_{1}(t) is the transient flow rate;
when formula (2) is substituted for formula (1), the following are provided:
in the formula, p_{1}(t)＝P(x)e^{st}；q_{1}(t)＝Q(x)e^{st}；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:
in the formula, P_{U}Is the pressure at the inlet of the pipeline; p_{D}Is the pressure at the outlet of the pipeline; q_{U}Is the flow at the inlet of the pipeline; q_{D}Is the flow at the outlet of the pipeline;is the propagation constant;is a characteristic impedance;
simultaneous equations (3), (4) and (5) are obtained to obtain the input and output impedances of the pipeline:
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 thereforeSubstituting formula (6), and obtaining a transfer function of the pipeline system in the time domain as follows:
Z_{D}＝Z_{C} tanhγl
in the formula, Z_{D}Is a transfer function; z_{c}Is a characteristic impedance; gamma is a propagation constant; l is the length of the pipeline; b to the transfer function Z_{D}And 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 transmitter_{1}(t) reading the transient flow q of the pipeline by means of a turbine flowmeter_{1}(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 nonleakage 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 nonleakage 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 nonleakage 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 pipeline_{2}(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
Finally, the time t is used as the abscissa and the transient pressure p is used_{1}(t) average value of excitation pressureThe 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 timedomain pressure signal s (t)_{i}(t) for the target signal s (t) + ω_{i}(t) performing a 1 st CEEMD decomposition to obtain a first IMF_{1}
In the formula, E_{1}For the defined CEEMD operation symbol, the subscript "1" represents the first iteration operation;_{1}the signaltonoise ratio coefficient is set for each stage, and the corner mark '1' represents the 1 st stage; omega^{i}Is Gaussian white noise with unit variance as zero mean;
2) calculating to obtain a first order residual error r_{1}(t)
r_{1}(t)＝s(t)IMF_{1}(t) (8)
3) For the first order residual r_{1}(t) the white noise signal added thereto, and a structural signal r_{1}(t)+_{1}E_{1}(ω^{i}(t)) and decomposed again to obtain a second IMF_{2}；
4) So on to calculate the kth residual r_{k}(t)r_{k}，k＝2，3…K
r_{k}(t)＝r_{k1}(t)IMF_{i}(t) (10)
5) Then continue to decompose r_{k}(t)+_{k}E_{k}(ω^{i}(t)), i ═ 1, 2 … n, whose 1 st natural mode function component is the IMF of CEEMD_{k+1}
6) Continuing to decompose until the end condition is met, otherwise returning to the steps 4) to 5), and expressing the final result as:
in the formula, IMF_{k}(t) is the decomposed IMF function of each order;
7) selecting the first threeorder signal component reconstruction after CEEMD decomposition to obtain an effective signal x (t) after denoising 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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