CN107435817A - A kind of 2 leak detection accurate positioning methods of pressure pipeline - Google Patents
A kind of 2 leak detection accurate positioning methods of pressure pipeline Download PDFInfo
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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
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Abstract
The invention discloses a kind of 2 leak detection accurate positioning methods of pressure pipeline, carved at the same time, under same environment using sound emission leak detection system and correlator leak detection system, pipeline leakage signal is gathered to same target.On the one hand the leakage source signal detected using the particle swarm optimization algorithm based on simulated annealing thought to sound emission leak detection system carries out blind source separating, embedded memory simultaneously, construct and apply memory simulated annealing population blind separating method, Dispersion caused by eliminating pipeline multipoint leakage, isolate more accurate leakage source signal, greatly reduce disengaging time, the time of upstream and downstream two sensorses is reached with this determination leakage source signal；Simultaneously the spread speed of leakage sound wave in the duct is calculated using correlator detection data；The position of source of leaks is finally calculated according to cross-correlation location algorithm.Being accurately positioned for pressure pipeline leakage is realized, has the advantages that cost is low, easy to use.
Description
Technical field
The invention belongs to pipe leakage detection and localization technical field, and it is accurate to be related to a kind of 2 leak detections of pressure pipeline
Localization method.
Background technology
The advantages such as pipeline transportation is can persistently transport, convenient transport and cost of transportation are low are welcome and paid attention to by people.
But because equipment natural aging, climatic environment and artificial destruction etc. influence, caused pipe leakage happens occasionally.Not only make
Into the waste of resource, environment can also be polluted, or even people's lives and properties are threatened.Therefore effective pipe is found
Road leakage detection method, the hidden danger of pipeline is found out, there is good economic value and social effect.
For pipe detection and positioning, many technical methods are had been developed for both at home and abroad.In actual condition, pipeline section hair
Generally all it is the leakage of multiple spot during raw leakage.Thus people also begin to study pipeline multipoint leakage orientation problem, earliest Verde
In " Multi-leak detection and isolation in fluid pipelines " (Control Engineering
Practice, 2001, the 6th phase of volume 9, the 673-682 pages) in a text according to water pipe section both ends flow sensor and pressure
Sensor detects data, and 2 points of leakages to pipeline position, but can not carry out 2 points of leakage positioning in real time；Lei Yang etc.
" the more leakage point fault location of oil pipeline based on wavelet analysis " (petroleum machinery, 2014, the 09th phase, 109-112
Page) propose to be contrasted the modulus maximum of pressure signal and the signal in pipeline fault model library in a text, pass through similarity
Detection positioning is carried out to the multipoint leakage of pipeline, but this method needs original pipeline fault model database；Chapter, which is punched in, " to be based on
More leak positions detection of optical fiber sensing signal spectrum analysis " (computer engineering and design, 2015, the 10th phase, the
2878-2881 pages) detection positioning is carried out to pipeline multipoint leakage source using fibre optical sensor in a text, but position it is not accurate enough,
Cost is higher.Also pipeline multipoint leakage source is examined using small scale robot, infrared imaging, based on SCADA systems etc.
Survey, but these methods are not that cost is higher, are exactly that system design is excessively complicated, without universality.
In field of non destructive testing, acoustic emission can continuously be detected to pipe leakage, will to the real-time of diagnosis
Ask not high, can be detected when pipe leakage just occurs or after leakage generation, pipeline Small leak can also be found in time,
Drastically increase the convenience and correctness of diagnosis.But traditional Acoustic Emission location detection can not meet to enter multipoint leakage
The pinpoint requirement of row, such as tested pipeline have two leakage points, due to influencing each other for 2 points of leakage source signals, and
The Dispersion of leakage signal, plus the operating mode and ambient noise that pipeline is complicated, pipeline leakage signal is caused to be difficult to and carry
Take, cause the positioning precision of source of leaks not high.
Thus the particle cluster algorithm based on simulated annealing thought is used for blind source separating by the present invention, is leaked using sound emission
Check system and correlator leak detection system are carved, under same environment at the same time, to same target (pipeline) collection pipe leakage letter
Number；The leakage signal detected using sound emission leak detection system is handled, and can eliminate pipeline multipoint leakage causes letter
Dispersion between number, pipeline leakage signal, while embedded memory are precisely separated out, constructed and using memory simulated annealing
Population blind separating method so that the searching of repetition optimal value is avoided in annealing process, when greatly reducing blind source separating
Between；And using correlator collection leakage acoustic signals, solve the problems, such as pipe leakage acoustic wave propagation velocity, extract accurate pass
Broadcast speed.It is applied to pipeline multipoint leakage source in this approach to position, and then realizes being accurately positioned for leakage multiple sources.
The content of the invention
To solve deficiency existing for prior art detection positioning pressure 2 source of leaks of pipeline, the present invention proposes one kind
2 points of pressure pipeline leakage accurate positioning methods, to realize the separation to 2 source of leaks and be accurately positioned.Apply in this approach
Positioned in pipeline multipoint leakage source, and then realize being accurately positioned for leakage multiple sources.
The present invention solves its technical problem technical scheme to be taken：A kind of 2 leak detection essences of pressure pipeline
True localization method, understood based on the ranging formula (1) that the waveform cross-correlation time difference calculates, it is only necessary to determine source of leaks sound emission is believed
Number reach time difference Δ t and acoustic emission signal the propagation precise speed v in the duct of upstream and downstream, you can determine leakage point
Position, to realize the separation to 2 source of leaks and be accurately positioned.
In formula：L is to be detected pipe leakage source position, i.e. distance (m) of the leakage point to upstream acoustic emission sensor；L is
The distance between two acoustic emission sensors (m).
The leakage locating method of the present invention specifically includes following steps,
S1：Build detecting system；
Two acoustic emission sensors are arranged on to the upstream and downstream for being detected pipeline, and acoustic emission sensor is sent out with sound
Penetrate instrument connection and be built into sound emission leak detection system；Meanwhile by pairwise correlation instrument sensor be arranged on be detected ducts upstream with
The same position in downstream, and two sensorses is connected with correlator and be built into correlator leak detection system；
S2：It is determined that leakage source signal reaches the time difference Δ t of the acoustic emission sensor of upstream and downstream two；
S2.1：The source of leaks primary signal of pipeline is gathered by sound emission leak detection system；
S2.2：The pipeline upstream and downstream source of leaks primary signal collected to sound emission leak detection system carries out sieves
Choosing, extract RMS voltage RMS value and average signal level ASL values are of a relatively high and the mixed positioning of peak value Relatively centralized is believed
Number is as coarse positioning signal data；It is right according to parameters such as RMS voltage (RMS), average signal level (ASL), energy
The pipe leakage source primary signal detected is filtered processing extraction, obtains mixing coarse positioning signal data.
Detection and localization can be carried out to pipe leakage, obtain the thick fixed of leak detection using sound emission leak detection system
Position signal, but the coarse positioning signal often signal such as entrainment noise so that exist between detection locator value and actual value compared with
Big error, suitable method must be applied to handle pipe leakage coarse positioning signal data for this.And let out for multiple spot
Leakage, then must separate to coarse positioning signal source first, carry out more technological synthesis processing such as de-noising, obtain more accurate
Time difference Δ t, so as to obtain more accurately positioning.
Wavelet Denoising Technology is widely approved and applied, and use is simple and convenient, and de-noising effect is preferable, because
This, carries out noise reduction process to coarse positioning signal data using Wavelet Denoising Technology in step S2.3, obtains observation signal.
The detailed process of wavelet noise is：
S2.3.1：The wavelet decomposition of signal.First, its suitable wavelet basis is selected different signals, and is determined
The level to be decomposed well, decomposition computation is then carried out again.
S2.3.2：The threshold value quantizing of wavelet decomposition high frequency coefficient.Need to select a suitable threshold value to each decomposition
High frequency coefficient under yardstick is quantified, and herein, selects soft-threshold to carry out quantification treatment to it.Specifically, utilize
Soft-threshold Denoising Method in Matlab in wavelet threshold denoising is handled.
S2.3.3：Wavelet reconstruction.One is carried out according to the low frequency coefficient of the high frequency coefficient of each layer of wavelet decomposition and the bottom
Tie up wavelet reconstruction.
Specifically including will lead from sound emission leak detection system in two coarse positioning signals that leakage pipe upstream and downstream obtains
Enter the wavelet analysis module in MATLAB tool boxes, according to above-mentioned steps S2.3.1-S2.3.3 to data carry out wavelet decomposition,
Threshold value quantizing and wavelet reconstruction, export the signal after de-noising, as observation signal I1、I2, wherein, I1Represent that upstream sensor obtains
The signal obtained, I2Represent the signal that downstream sensor obtains；
S2.4：The observation signal I that will be obtained after noise reduction1、I2, the matrix with being generated at random in Matlab is mixed to form new
Observation signal L1、L2；Because the number of observation signal is more than or equal to the number of source signal, it is allowed to using the step by original
Deficient determine blind source separating problem and change into positive definite blind source separating problem.
S2.5：By new observation signal L1、L2Import in Matlab and carry out whitening processing, recycle memory simulated annealing grain
The blind source separation method of subgroup carries out the leak position signal S of the upstream and downstream after blind source separating is separated1、S2；By white
Change processing can simplify blind source separating and improve blind source separation algorithm so that blind source separating processing is more convenient for.
In the algorithm object function is used as by the use of maximum likelihood function.Because maximum-likelihood method is very big for number of samples
When, also progressive an optimal solution effectively can be obtained, therefore using maximum likelihood algorithm to result progress optimizing；Simulated annealing
The blind source separating of the particle cluster algorithm of thought can improve and break away from Local Extremum, the ability of local optimum, and separate essence
Degree is high, and stability is high.
The wherein memory simulated annealing population blind source separating comprises the following steps that：
Because the basic model of blind source separating is：
L (t)=A (t) s (t) (2)
Wherein, L (t) is observation signal matrix, and A (t) is hybrid matrix, and s (t) is source signal matrix.
Solve source signal s (t) model be：
Y (t)=W (t) L (t) (3)
Wherein, the output signal matrix after y (t) separation, W (t) are solution hybrid matrix.
S2.5.1：Initial parameter sets：Population population is set as n, and each particle is initialized, weight
For w, perception factor and social learning's factor are respectively c1、c2, a number of solution hybrid matrix W (t) conduct will be randomly generated
Primary, can simultaneously randomly generate the initial velocity of each particle, and initialize individual extreme value and global extremum, give
Determine initial temperature T, final temperature T0With simulated annealing speed λ；
S2.5.2：Signal is separated according to the position of particle, centralization and whitening operation are carried out to y (t), according to greatly seemingly
Right estimation function calculates the adaptive value of each particle with this as object function；
S2.5.3：Using the adaptive value of each particle as the optimal extreme value p of particle individuali, and chosen most in individual extreme value
The figure of merit is as global extremum pg；
S2.5.4：Judge whether to meet end condition, terminate and calculate if meeting, otherwise continue；
S2.5.5：By each particle adaptive value and individual extreme value piWith global extremum pgIt is compared, takes optimal value to update
The individual extreme value p of each particleiWith global extremum pg；
S2.5.6：The speed of more new particle and position, and given maximal rate and the scope of maximum position are limited respectively
It is interior, and calculate the adaptive value of each more new particle；
S2.5.7：The variable Δ E of the adaptive value caused by former and later two particle positions is calculated, if Δ E ＜ 0, is received new
Position；If the random number between exp (- Δ E/T) ＜ δ, δ ∈ (0,1), also receives new position, otherwise refuse and return to step
S2.5.2；
S2.5.8：It is embedded in and memory variable initial position and adaptive value is set, is the optimal location of circulation for the first time
With adaptive value；
S2.5.9：Compare new position and storage location and adaptive value in adaptive value and memory, if new position and adaptation
Position then return to step S2.5.2 identical with adaptive value in value and memory, on the contrary it is recorded into memory；
S2.5.10：Carry out annealing operation, T(t+1)=λ Tt(t is iterations)；
S2.5.11：If meeting end condition, optimal solution is exported, otherwise return to step S2.5.2；
S2.5.12：Ask to obtain that W (t) is optimal, solve source signal s (t) optimal estimation.
Add memory to record to obtain optimal solution, the optimal solution obtained each time and record optimal solution before contrasted,
The optimal solution repeated is rejected, effectively prevent roundabout way of search, and then reduces search time, solves annealing grain
The problem of subgroup method consuming time is long.
S2.6：Pass through wavelet singular point analysis positioning signal S1、S2, obtain singular points；According to two singular points
Sampled point difference determine leakage source signal reach two acoustic emission sensors of upstream and downstream time difference Δ t；
Because the spread speed of acoustic emission signal in the material is by material type, anisotropy, planform and chi
The influence of many factors such as very little, interior media so that spread speed turns into a kind of easy variable.And due to acoustic emission signal also
With dispersion phenomenon, influenceed by the frequency of ripple, cause to be difficult to the velocity of sound for determining leakage sound wave in actual condition.
The pipe leakage velocity of sound is not only influenceed by pipeline material, is also influenceed by different medium, different operating modes, and
The velocity of wave detected using different methods has difference, at present, goes back the unified method calculating pipeline of neither one both at home and abroad and lets out
The velocity of wave of sound wave is leaked, researcher detects or that value of wave speed is calculated is also inconsistent.Such as, University Of Tianjin Sun Li beautiful jades et al. " are filling
The propagation of acoustic emission wave and attenuation Characteristics in liquid pipe road " (piezoelectricity and acousto-optic, in August, 2008, the 4th phase of volume 30, the
401-403 pages) acoustic emission wave is thought in steel pipe in a text, velocity of wave is 3300m/s when medium is air, is made in water ballast
With it is lower be 1500m/s；And Shen Gongtian exists《Acoustic emission testing technology and application》(Science Press, version in 2015,242-243
Page) in a book in think, in acoustic emission signal caused by steel pipe leakage when medium be air, its velocity of wave for 880~
Between 960m/s；And Didem Ozevin are in " Novel leak localization in pressurized pipeline
networks using acoustic emission and geometric connectivity”(International
Journal of Pressure Vessels＆Piping, 2012, the 2nd phase of volume 92, the 63-69 pages) in utilize mode meter
It is 1479m/s to calculate the velocity of wave that sound emission medium in pvc pipe is air.How to obtain one it is relatively objective and accurately let out
The velocity of sound for leaking sound wave is the important key of another to be solved of this patent.
Cross-correlation technique is not only suitable for the time difference or time delay measurement between discontinuous wave, is also applied between continuous wave
The time difference or time delay measurement, this technology have been successfully applied for the leak position of pipeline acoustic emission detection.It is related
Instrument carries out pipeline leakage testing according to cross-correlation technique principle, but should be noted that and use the correct velocity of sound.
It is identical that the two sensorses of correlator place transmitting pipeline leakage detecting sensor placement location in unison.Using correlation
Instrument carries out detection and localization to pipe leakage, is generally analyzed by binary channels Fast Fourier Transform (FFT) (FFT) to realize cross-correlation letter
Number analysis, the coherence spectra G from frequency domain vAB(v) inverse Fourier transform can obtain the cross-correlation function R in time domain τAB
(τ)：
In formula, GAB(v) be A (t) B (t+ τ) Fourier transform, wherein, A (t) represents a ripple, and B (t+ τ) represents another
The ripple that one time delay is τ, GAB(v) result is leak position data.Leakage of this method to tested pipeline single-point can
Accurately positioning is obtained, it is also larger to multipoint leakage position error.But when its positioning result probability is more than 4%, it can recognize
For the result is that more objective and accurate, this can be verified (see experimental data table 1) from many experiments result.Thus
The measurement that we determine to carry out velocity of wave using correlator determines.
Testing 1 operating mode is：The long 2030cm of pipeline PE pipes, interior media is compressed air, pressure 0.5MPa, buried
Pipeline, leak leak at ducts upstream sensor 1600cm, leak aperture 2mm.
Testing 2 operating modes is：Pipe range 3600cm steel pipe, interior media are compressed air, pressure 0.57MPa, empty frame pipe
Road, leak leak at ducts upstream sensor 1600cm, leak aperture 1mm.
Testing 3 operating modes is：Pipe range 4275cm steel pipe, interior media are compressed air, pressure 0.28MPa, empty frame pipe
Road, leak leak at ducts upstream sensor 1706cm, and leakage aperture is 1mm.
The correlator pipe leakage positioning experiment data of table 1
Calculate and determine that the velocity of wave of leakage signal specifically comprises the following steps：
S3：It is determined that the spread speed v of leakage source signal in the duct；
S3.1：Pipeline source of leaks acoustical signal is gathered using correlator；
S3.2：According to the pipe leakage source acoustical signal collected, detected by correlator analyzing and positioning result and tied with positioning
Fruit probability analysis, determine spread speed v of the source of leaks acoustical signal in pipeline medium；In order to ensure the objectivity of data, to phase
The detection of instrument analyzing and positioning result and positioning result probability analysis are closed, under same operating mode, taking three batches of gathered datas, every batch 10
The average speed that group data analysis is drawnSpread speed v of the source of leaks acoustical signal in pipeline medium is finally calculated.
S4：The leakage source signal being calculated by step S2.6 travels to the time difference up to upstream and downstream acoustic emission sensor
The speed v that Δ t and the leakage source signal obtained by step S3.2 are propagated in pipeline medium, according to cross-correlation ranging formula
(1) leakage source position is calculated.
In formula：L is to be detected pipe leakage source position, i.e. distance (m) of the leakage point to upstream acoustic emission sensor；L is
The distance between two acoustic emission sensors (m).
Data above is analyzed and the process of processing passes through Matlab programming realizations.
The beneficial effects of the invention are as follows：2 leak detection accurate positioning methods of a kind of pressure pipeline provided by the invention,
This method is carved, under same environment at the same time using sound emission leak detection system and correlator leak detection system, to a pair
As gathering pipeline leakage signal；Upstream and downstream pipe leakage source signal is gathered by Acoustic radiating instrument, dropped by using Wavelet Denoising Technology
Influence of the low noise to leakage source signal, is arrived using the particle swarm optimization algorithm based on simulated annealing thought to detection signal
Leakage signal carries out blind source separating processing, while embedded memory, constructs and using memory simulated annealing population blind separation side
Method, can not only eliminate pipeline multipoint leakage causes the Dispersion of signal, isolates more accurate leakage source signal so that
Disengaging time greatly reduces, and the time of upstream and downstream two sensorses is reached with this determination leakage source signal；Recycle correlator leakage
The leakage signal of detecting system collection analyzes the propagation precise speed of acoustic signals in the duct；Finally determined according to cross-correlation
Position algorithm calculates the position of source of leaks.The present invention can be accurately positioned to pressure pipeline leakage, there is provided a kind of cost
It is low, easy to use, and minute leakage can be identified, pipeline multipoint leakage localization method.
Brief description of the drawings
The invention will be further described with reference to the accompanying drawings and examples.
Fig. 1 is the schematic flow sheet of preferred embodiment；
Fig. 2 is 2 leakage device schematic diagrames of pressure pipeline；
Fig. 3 is No. 1 spectrogram of sensor；
Fig. 4 is No. 2 spectrograms of sensor；
Fig. 5 is No. 1 oscillogram of sensor；
Fig. 6 is No. 2 oscillograms of sensor；
Fig. 7 is acoustic emission detection effective voltage RMS positioning figures；
Fig. 8 is acoustic emission detection average signal level ASL positioning figures；
Fig. 9 is the observation signal after No. 1 (upstream sensor) noise reduction of sensor；
Figure 10 is the observation signal after No. 2 (downstream sensor) noise reductions of sensor；
Figure 11 is 1, No. 2 two new observation signal of sensor；
Figure 12 is 1, No. 2 separation signal of sensor；
Figure 13 is the curve display figure that correlator detects to pipe leakage point；
Figure 14 is positioning result probability graph of the correlator to pipe leakage point.
Embodiment
Presently in connection with accompanying drawing, the present invention is described in detail.This figure is simplified schematic diagram, is only illustrated in a schematic way
The basic structure of the present invention, therefore it only shows the composition relevant with the present invention.
As shown in figure 1, a kind of 2 leak detection accurate positioning methods of pressure pipeline of the present invention, are specifically included following
Step,
S1：Build detecting system；
Two acoustic emission sensors are arranged on to the upstream and downstream for being detected pipeline, and acoustic emission sensor is sent out with sound
Penetrate instrument connection and be built into sound emission leak detection system；Meanwhile by pairwise correlation instrument sensor be arranged on be detected ducts upstream with
The same position in downstream, and two sensorses is connected with correlator and be built into correlator leak detection system；
S2：It is determined that leakage source signal reaches the time difference Δ t of the acoustic emission sensor of upstream and downstream two；
S2.1：The source of leaks primary signal of pipeline is gathered by sound emission leak detection system；
S2.2：The pipeline upstream and downstream source of leaks primary signal collected to sound emission leak detection system is screened, and is carried
Take RMS voltage RMS value and average signal level ASL values are of a relatively high and the mixed positioning signal data of peak value Relatively centralized
As coarse positioning signal data；
S2.3：Noise reduction process is carried out to coarse positioning signal using Wavelet Denoising Technology, obtains observation signal；
Noise reduction process specifically includes,
S2.3.1：The wavelet decomposition of signal, to the different suitable wavelet basis of signal behavior, and determine and to decompose
Level, then carry out decomposition computation again；
S2.3.2：The threshold value quantizing of wavelet decomposition high frequency coefficient, a suitable threshold value is selected to each decomposition scale
Under high frequency coefficient quantified, threshold value selection soft-threshold carries out quantification treatment to it；
S2.3.3：Wavelet reconstruction, one is carried out according to the low frequency coefficient of the high frequency coefficient of each layer of wavelet decomposition and the bottom
Tie up wavelet reconstruction.
S2.4：The matrix generated at random in the observation signal and Matlab that are obtained after noise reduction is mixed to form new observation
Signal；
S2.5：New observation signal is imported in Matlab and carries out whitening processing, recycles memory simulated annealing population
Blind source separation method carry out blind source separating separated after upstream and downstream leak position signal S1、S2；
The specific steps of described memory simulated annealing population blind source separating include,
S2.5.1：Initial parameter sets：Population population is set as n, and each particle is initialized, weight
For w, perception factor and social learning's factor are respectively c1、c2, a number of solution hybrid matrix W (t) conduct will be randomly generated
Primary, can simultaneously randomly generate the initial velocity of each particle, and initialize individual extreme value and global extremum, give
Determine initial temperature T, final temperature T0With simulated annealing speed λ；
S2.5.2：Signal is separated according to the position of particle, centralization and whitening operation are carried out to y (t), according to greatly seemingly
Right estimation function calculates the adaptive value of each particle with this as object function；
S2.5.3：Using the adaptive value of each particle as the optimal extreme value p of particle individuali, and chosen most in individual extreme value
The figure of merit is as global extremum pg；
S2.5.4：Judge whether to meet end condition, terminate and calculate if meeting, otherwise continue；
S2.5.5：By each particle adaptive value and individual extreme value piWith global extremum pgIt is compared, takes optimal value to update
The individual extreme value p of each particleiWith global extremum pg；
S2.5.6：The speed of more new particle and position, and given maximal rate and the scope of maximum position are limited respectively
It is interior, and calculate the adaptive value of each more new particle；
S2.5.7：The variable Δ E of the adaptive value caused by former and later two particle positions is calculated, if Δ E ＜ 0, is received new
Position；If the random number between exp (- Δ E/T) ＜ δ, δ ∈ (0,1), also receives new position, otherwise refusal returns to step
S2.5.2；
S2.5.8：It is embedded in and memory variable initial position and adaptive value is set, is the optimal location of circulation for the first time
With adaptive value；
S2.5.9：Compare new position and storage location and adaptive value in adaptive value and memory, if new position and adaptation
Position then return to step S2.5.2 identical with adaptive value in value and memory, on the contrary it is recorded into memory；
S2.5.10：Carry out annealing operation, T(t+1)=λ Tt(t is iterations)；
S2.5.11：If meeting end condition, optimal solution is exported, otherwise return to step S2.5.2；
S2.5.12：Ask to obtain that W (t) is optimal, solve source signal s (t) optimal estimation.
S2.6：By wavelet singular point analysis positioning signal, singular points are obtained；According between two singular points
Sampled point difference determine leakage source signal reach two acoustic emission sensors of upstream and downstream time difference Δ t；
S3：It is determined that the propagation precise speed v of leakage source signal in the duct；
S3.1：Pipeline source of leaks acoustical signal is gathered using correlator；
S3.2：According to the pipe leakage source acoustic emission signal data collected, detected by correlator analyzing and positioning result
With positioning result probability analysis, spread speed v of the source of leaks acoustical signal in pipeline medium is determined；
S4：The leakage source signal being calculated by step S2.6 travels to the time difference up to upstream and downstream acoustic emission sensor
The speed v that Δ t and the leakage source signal obtained by step S3.2 are propagated in pipeline medium, according to cross-correlation ranging formula
(1) leakage source position is calculated.
In formula：L is to be detected pipe leakage source position, i.e. distance (m) of the leakage point to upstream acoustic emission sensor；L is
The distance between two acoustic emission sensors (m).
Simulated leakage experiment is carried out according to above-mentioned steps, as shown in Fig. 2 first, builds detecting system, in the present embodiment
Use steel pipe of one section of caliber for DN150, its nominal diameter is 150mm, a length of 44m of experimental channel, and pressure is
0.1MPa, pipeline interior media are running water；Downstream acoustic emission sensor is individually positioned at 1m and 43m, such as sound emission in figure
Sensor 1 and acoustic emission sensor 2, two leaks are separately positioned at the 19m and 33m of zero point, and leakage aperture is equal
For 1mm, simulated leakage experiment is carried out.
Gathered through leak test, Fig. 3-Fig. 6 is sound emission leakage detector in 2 leakage experiments of this liquid-filling pipe
In pressure 0.1MPa, signal spectrum figure (Fig. 3, Fig. 4) and oscillogram (Fig. 5, figure of the leakage aperture all to be obtained in the case of 1mm
6), and RMS voltage RMS positioning figures (Fig. 7), average signal level ASL positioning scheme (Fig. 8).
Wherein, the abscissa of signal spectrum figure represents frequency (Hz), and ordinate represents power (dB)；Oscillogram
Abscissa represents the time (s), and ordinate represents voltage (mV)；The abscissa of RMS voltage RMS positioning figures represents that leakage point arrives
The distance (mm) of upstream acoustic emission sensor, ordinate represent RMS voltage RMS (V)；Average signal level ASL positioning figures
Abscissa represent leakage point arrive upstream acoustic emission sensor distance (mm), ordinate expression average signal level (dB).
RMS voltage RMS positioning figure is extraction tube road sound emission leakage signal ginseng with average signal level ASL positioning figures
Number provides reference frame, to extract part signal as coarse positioning signal data.
As can be seen from Figures 7 and 8 at the 19m and 33m two near have amplitude higher and the mixing of peak value Relatively centralized is determined
Position signal, but more noise signal is there are simultaneously；Pass through these mixed positionings of pipeline sound emission leakage signal parameter extraction
Part signal data are as coarse positioning signal data (being shown in Table 2) in signal data.
2 pipeline of table, 2 source of leaks experiment positioning coarse positioning signal data tables
The above is S2.1-S2.2 content.
S2.3 carries out noise reduction process using Wavelet Denoising Technology to coarse positioning signal, obtains observation signal.
To reduce the influence of ambient noise, noise reduction process is carried out to primary signal by wavelet noise, the step passes through
Matlab softwares are realized.
The process of small echo signal de-noising is divided into following steps：
S2.3.1：The wavelet decomposition of signal.First, its suitable wavelet basis is selected different signals, and is determined
The level to be decomposed well, decomposition computation is then carried out again.
S2.3.2：The threshold value quantizing of wavelet decomposition high frequency coefficient.Need to select a suitable threshold value to each decomposition
High frequency coefficient under yardstick is quantified, and selects soft-threshold in the present invention to carry out quantification treatment to it.
S2.3.3：Wavelet reconstruction.One is carried out according to the low frequency coefficient of the high frequency coefficient of each layer of wavelet decomposition and the bottom
Tie up wavelet reconstruction.
MATLAB will be imported from sound emission leak detection system in two coarse positioning signals that leakage pipe upstream and downstream obtains
Wavelet analysis module in tool box, by above step S2.3.1-S2.3.3, to obtained pipeline leakage acoustic emission signals
Drop processing of making an uproar is carried out, it is observation signal I to obtain the signal after noise reduction1、I2, wherein, I1Represent the letter that upstream sensor obtains
Number, I2Represent the signal that downstream sensor obtains.As shown in Fig. 9 and Figure 10, respectively pipeline upstream and downstream acoustic emission sensor connects
Observation signal figure after the coarse positioning signal de-noising received.Wherein Fig. 9 and Figure 10 abscissa represents sampled point, indulges and sits
Mark represents range value (V).
The observation signal I that S2.4 will be obtained after noise reduction1、I2, the matrix with being generated at random in Matlab is mixed to form new
Observation signal L1、L2；Because the number of observation signal is more than or equal to the number of source signal, it is allowed to using the step by original
Deficient determine blind source separating problem and change into positive definite blind source separating problem.
The step makes the number of observation signal be more than or equal to the number of source signal, is allowed to by original deficient fixed blind source
Separation problem changes into positive definite blind source separating problem.As shown in figure 11, two new observation signal L are obtained1、L2, be respectively on
The observation signal figure that downstream signal and the hybrid matrix generated at random are formed.
S2.5 is by new observation signal L1、L2Import in Matlab and carry out whitening processing, recycle memory simulated annealing grain
The blind source separation method of subgroup carries out the leak position signal S of the upstream and downstream after blind source separating is separated1、S2；By white
Change processing can simplify blind source separating and improve blind source separation algorithm so that blind source separating processing is more convenient for.
S2.6 is according to the singularity analysis positioning signal S of upstream and downstream positioning signal1、S2, obtain source of leaks acoustic emission signal
Reach the time difference Δ t of upstream and downstream sensor.It can be learnt (Figure 12) by the singular point of the positioning signal of upstream and downstream, upstream 1
Near the 270th sampled point, the singular point of No. 2 sensor positioning signals in downstream exists the singular point of number sensor positioning signal
Near 890th sampled point, it can thus be concluded that, the time difference Δ t that signal reaches between upstream and downstream sensor is 0.0062s.Its
In, Figure 11 and Figure 12 abscissa represent sampled point, and ordinate represents range value (V).
S3：Determine the propagation precise speed v of acoustic emission signal in the duct；
S3.1：The two sensorses of correlator are positioned over to the upstream and downstream of detected pipeline, the two sensorses position of correlator
It is identical with sound emission Instrument sensor placement location, two sensors (correlator sonic sensor 1 and the correlation of correlator
Instrument sonic sensor 2) placement location as shown in Figure 2, and using correlator collection pipe leakage acoustical signal；
S3.2：According to the pipe leakage acoustical signal collected, pass through the detection of correlator analyzing and positioning result and positioning result
Probability analysis；To the average speed under same operating mode, taking three batches of analysiss of data collected to drawAs source of leaks sound emission
Spread speed v in pipeline medium.
Using correlator arrange parameter, to velocity of wave of the positioning probability results more than 4%, the data are analyzed, and carries
Take out corresponding velocity of wave.By analyzing curve display figure that correlator detects to pipe leakage point with correlator to pipe leakage
The positioning result probability of point shows (such as Figure 13 and Figure 14), wherein, Figure 13 and Figure 14 abscissa represent leakage point to upstream phase
The distance (cm) of instrument sonic sensor is closed, ordinate represents range value (V), extracts in correlator to go out in three batches of location datas
The higher locator value of existing probability, and corresponding velocity of wave v, as shown in table 3.
The correlator location data table of table 3
The velocity of wave that the leakage sound wave under such a operating mode can be calculated in we by table 3 is 1150m/s.
S4：The leakage source signal being calculated by step S2.6 travels to the time difference up to upstream and downstream acoustic emission sensor
The speed v that Δ t and the leakage source signal obtained by step S3.2 are propagated in pipeline medium, according to cross-correlation ranging formula
(1) leakage source position is calculated.
Thus the velocity of wave v of acquisition and time difference Δ t are brought into formula (1), can obtain one of leakage anchor point is
19.44m.And calculate other leakage anchor points with the method and calculate the relative error before and after data processing, such as table
4 and table 5 shown in.
Leak position result and relative error at the 19m of table 4
| Sequence number | Coarse positioning leak position (m) | Measure relative error (%) | Leakage point (m) after processing | Relative error (%) after processing |
| 1 | 15.96 | 16.0 | 17.25 | 9.2 |
| 2 | 21.02 | 10.6 | 19.78 | 4.1 |
| 3 | 19.84 | 4.4 | 19.55 | 2.9 |
| 4 | 19.42 | 2.2 | 19.32 | 1.7 |
| 5 | 19.47 | 2.5 | 19.26 | 1.4 |
| 6 | 20.33 | 7.0 | 19.67 | 3.5 |
| 7 | 20.71 | 9.0 | 19.44 | 2.3 |
| 8 | 20.98 | 10.4 | 19.9 | 4.7 |
| 9 | 19.16 | 0.8 | 19.21 | 1.1 |
| 10 | 21.18 | 11.5 | 20.13 | 5.9 |
| 11 | 17.41 | 8.4 | 17.65 | 7.1 |
| 12 | 16.55 | 12.9 | 17.37 | 8.6 |
| 13 | 21.01 | 10.6 | 19.78 | 4.1 |
| 14 | 19.39 | 2.1 | 19.21 | 1.1 |
| Average value | 19.5 | 7.7 | 19.1 | 4.1 |
Leak position result and relative error at the 33m of table 5
By the analyzing and processing to all data, the position of leakage point after analyzing is can be seen that by table 4 and table 5 substantially
Matched with 19m during design and 33m, and setting accuracy is more preferable than Acoustic radiating instrument and correlator detection leakage result.
It is 7.7% that relative error is measured at 19m leakage points, and relative error is 4.1% after processing；Relative miss is measured at 33m leakage points
Difference is 76.4%, and relative error is 4.0% after processing.It is therefore seen that after carrying out data processing with the method, Ke Yi great
The big error reduced when leakage positions, and this method cost is low, easy to use.
Pinpoint method is detected to a kind of 2 source of leaks of pressure pipeline provided by the present invention above, and to this
It is described in detail.Apply specific experiment example to be set forth the principle and embodiment of the present invention, to be illustrated
, the foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention.All spirit in the present invention
With all any modification, equivalent and improvement made within principle etc., it should be included in the scope of the protection.
Claims (3)
- A kind of 1. 2 leak detection accurate positioning methods of pressure pipeline, it is characterised in that：Comprise the following steps,S1：Build detecting system；Two acoustic emission sensors are arranged on to the upstream and downstream for being detected pipeline, and acoustic emission sensor is connected with Acoustic radiating instrument Connect and be built into sound emission leak detection system；Meanwhile pairwise correlation instrument sensor is arranged on and is detected ducts upstream and downstream Same position, and two sensorses is connected with correlator and be built into correlator leak detection system；S2：It is determined that leakage source signal reaches the time difference Δ t of the acoustic emission sensor of upstream and downstream two；S2.1：The source of leaks primary signal of pipeline is gathered by sound emission leak detection system；S2.2：The pipeline upstream and downstream source of leaks primary signal collected to sound emission leak detection system carries out filtering screening, carries Take RMS voltage RMS value and average signal level ASL values are of a relatively high and the mixed positioning signal data of peak value Relatively centralized As coarse positioning signal data；S2.3：Noise reduction process is carried out to coarse positioning signal using Wavelet Denoising Technology, obtains observation signal；S2.4：The matrix generated at random in the observation signal and Matlab that are obtained after noise reduction is mixed to form new observation signal；S2.5：New observation signal is imported in Matlab and carries out whitening processing, recycles the blind of memory simulated annealing population Source separation method carries out the leak position signal S of the upstream and downstream after blind source separating is separated1、S2；S2.6：By wavelet singular point analysis positioning signal, singular points are obtained；It is poor according to the sampled point of two singular points Value determines that leakage source signal reaches the time difference Δ t of two acoustic emission sensors of upstream and downstream；S3：It is determined that the spread speed v of leakage source signal in the duct；S3.1：Pipeline source of leaks acoustical signal is gathered using correlator；S3.2：According to the pipe leakage source acoustical signal data collected, detected by correlator analyzing and positioning result and tied with positioning Fruit probability analysis, determine spread speed v of the source of leaks acoustical signal in pipeline medium；S4：The leakage source signal being calculated by step S2.6 travel to upstream and downstream acoustic emission sensor time difference Δ t and The spread speed v of the leakage source signal obtained by step S3.2 in the duct, leakage is calculated according to cross-correlation ranging formula (1) Source position；<mrow> <mi>l</mi> <mo>=</mo> <mfrac> <mrow> <mi>L</mi> <mo>-</mo> <mi>&Delta;</mi> <mi>t</mi> <mo>&CenterDot;</mo> <mi>v</mi> </mrow> <mn>2</mn> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow>In formula：L is to be detected pipe leakage source position, i.e. distance (m) of the leakage point to upstream acoustic emission sensor；L is two sound The distance between emission sensor (m).
- 2. 2 leak detection accurate positioning methods of pressure pipeline as claimed in claim 1, it is characterised in that：The step Noise reduction process in S2.3 specifically includes,S2.3.1：The wavelet decomposition of signal, to the different suitable wavelet basis of signal behavior, and determine the layer to be decomposed It is secondary, decomposition computation is then carried out again；S2.3.2：The threshold value quantizing of wavelet decomposition high frequency coefficient, a suitable threshold value is selected under each decomposition scale High frequency coefficient is quantified, and the threshold value selects soft-threshold to carry out quantification treatment to it；S2.3.3：Wavelet reconstruction, carried out according to the low frequency coefficient of the high frequency coefficient of each layer of wavelet decomposition and the bottom one-dimensional small Reconstructed wave.
- 3. 2 leak detection accurate positioning methods of pressure pipeline as claimed in claim 1, it is characterised in that：The step The specific steps of memory simulated annealing population blind source separating described in S2.5 include,S2.5.1：Initial parameter sets：Population population is set as n, and each particle is initialized, weight w, is recognized Know that the factor and social learning's factor are respectively c1、c2, a number of solution hybrid matrix W (t) will be randomly generated and be used as initial grain Son, can simultaneously randomly generate the initial velocity of each particle, and initialize individual extreme value and global extremum, give starting temperature Spend T, final temperature T0With simulated annealing speed λ；S2.5.2：Signal is separated according to the position of particle, centralization and whitening operation are carried out to y (t), according to Maximum-likelihood estimation Function calculates the adaptive value of each particle with this as object function；S2.5.3：Using the adaptive value of each particle as the optimal extreme value p of particle individuali, and choose optimal value in individual extreme value and make For global extremum pg；S2.5.4：Judge whether to meet end condition, terminate and calculate if meeting, otherwise continue；S2.5.5：By each particle adaptive value and individual extreme value piWith global extremum pgIt is compared, takes optimal value to update each grain The individual extreme value p of soniWith global extremum pg；S2.5.6：The speed of more new particle and position, and in the range of limiting given maximal rate and maximum position respectively, and Calculate the adaptive value of each more new particle；S2.5.7：The variable Δ E of the adaptive value caused by former and later two particle positions is calculated, if Δ E ＜ 0, receive new position； If the random number between exp (- Δ E/T) ＜ δ, δ ∈ (0,1), also receives new position, otherwise refuse and return to step S2.5.2；S2.5.8：It is embedded in and memory variable initial position and adaptive value is set, the optimal location as circulated for the first time is with fitting It should be worth；S2.5.9：Compare storage location and adaptive value in new position and adaptive value and memory, if new position and adaptive value and Position then return to step S2.5.2 identical with adaptive value in memory, on the contrary it is recorded into memory；S2.5.10：Carry out annealing operation, T(t+1)=λ Tt(t is iterations)；S2.5.11：If meeting end condition, optimal solution is exported, otherwise return to step S2.5.2；S2.5.12：Ask to obtain that W (t) is optimal, solve source signal s (t) optimal estimation.
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