CN107435817B - A kind of pressure pipeline two o'clock leak detection accurate positioning method - Google Patents
A kind of pressure pipeline two o'clock leak detection accurate positioning method Download PDFInfo
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- CN107435817B CN107435817B CN201710696458.9A CN201710696458A CN107435817B CN 107435817 B CN107435817 B CN 107435817B CN 201710696458 A CN201710696458 A CN 201710696458A CN 107435817 B CN107435817 B CN 107435817B
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D5/00—Protection or supervision of installations
- F17D5/02—Preventing, monitoring, or locating loss
- F17D5/06—Preventing, monitoring, or locating loss using electric or acoustic means
Abstract
The invention discloses a kind of pressure pipeline two o'clock leak detection accurate positioning methods, are carved at the same time, under same environment using sound emission leak detection system and correlator leak detection system, acquire pipeline leakage signal to same target.On the one hand blind source separating is carried out to the leakage source signal that sound emission leak detection system detects using the particle swarm optimization algorithm based on simulated annealing thought, it is embedded in memory simultaneously, it constructs and applies memory simulated annealing population blind separating method, eliminate Dispersion caused by pipeline multipoint leakage, isolate more accurate leakage source signal, greatly reduce disengaging time, determines that leakage source signal reaches the time of upstream and downstream two sensors with this；The spread speed of leakage sound wave in the duct is calculated using correlator detection data simultaneously；The position of source of leaks is finally calculated according to cross-correlation location algorithm.The accurate positioning for realizing pressure pipeline leakage, has many advantages, such as at low cost, easy to use.
Description
Technical field
The invention belongs to pipe leakage detection and localization technical fields, and it is accurate to be related to a kind of pressure pipeline two o'clock leak detection
Localization method.
Background technique
The advantages such as pipeline transportation is can continue to transport, convenient transport and transportation cost are low are welcome and are paid attention to by people.
But since equipment natural aging, climatic environment and artificial destruction etc. influence, caused pipe leakage happens occasionally.Not only make
It at the waste of resource, also can cause environmental pollution, or even threaten to people's lives and properties.Therefore effective pipe is found
Road leakage detection method finds out the hidden danger of pipeline, has good economic value and social effect.
For pipe detection and positioning, many technical methods have been developed both at home and abroad.In actual condition, pipeline section hair
It is usually all the leakage of multiple spot when raw leakage.Thus people also begin one's 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 detection data positions the two o'clock leakage of pipeline, however is unable to the leakage positioning of real-time perfoming two o'clock；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) it proposes to compare 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
Detect more leak positions 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 inaccurate,
Higher cost.There are also examine using small scale robot, infrared imaging, based on SCADA system etc. to pipeline multipoint leakage source
It surveys, but these methods are not higher costs, is exactly that system design is excessively complicated, without universality.
In field of non destructive testing, acoustic emission can continuously detect pipe leakage, be wanted to the real-time of diagnosis
It asks not high, can be detected when pipe leakage just occurs or after leakage generation, pipeline Small leak can also be found in time,
Greatly improve the convenience and correctness of diagnosis.But traditional Acoustic Emission location detection be not able to satisfy to multipoint leakage into
The pinpoint requirement of row, for example there are two leakage points for tested pipeline, due to influencing each other for two o'clock leakage source signal, and
The Dispersion of leakage signal, in addition the operating condition and ambient noise of pipeline complexity, cause pipeline leakage signal to be difficult to and mention
It takes, causes the positioning accuracy of source of leaks not high.
Thus the particle swarm 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, at the same time under same environment, to same target (pipeline) acquisition pipe leakage letter
Number；It is handled using the leakage signal that sound emission leak detection system detects, can eliminate pipeline multipoint leakage leads to letter
Dispersion between number is precisely separated out pipeline leakage signal, while being embedded in memory, constructs 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 acquisition leakage acoustic signals, solves 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 the accurate positioning of leakage multiple sources.
Summary of the invention
Deficiency existing for positioning pressure pipeline two o'clock source of leaks is detected to solve the prior art, the invention proposes one kind
Pressure pipeline two o'clock leaks accurate positioning method, to realize separation and accurate positioning to two o'clock source of leaks.It applies in this approach
It is positioned in pipeline multipoint leakage source, and then realizes the accurate positioning of leakage multiple sources.
The present invention solves its technical problem technical solution to be taken: a kind of pressure pipeline two o'clock leak detection essence
True localization method is known 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 letter
Time difference Δ t and acoustic emission signal the propagation precise speed v in the duct for number reaching upstream and downstream, that is, can determine leakage point
Position, to realize separation and accurate positioning to two o'clock source of leaks.
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).
Leakage locating method of the invention specifically includes following steps,
S1: detection system is built；
Two acoustic emission sensors are mounted on to the upstream and downstream of detected pipeline, and send out acoustic emission sensor and sound
It penetrates instrument connection and is built into sound emission leak detection system；Meanwhile by pairwise correlation instrument sensor be mounted on detected ducts upstream with
The same position in downstream, and connect two sensors with correlator and be built into correlator leak detection system；
S2: determine that leakage source signal reaches the time difference Δ t of two acoustic emission sensor of upstream and downstream；
S2.1: the source of leaks original signal of pipeline is acquired by sound emission leak detection system；
S2.2: sieve is filtered to the collected pipeline upstream and downstream source of leaks original signal of sound emission leak detection system
Choosing, extracts RMS voltage RMS value and average signal level ASL value is relatively high and the mixed positioning of peak value Relatively centralized letter
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 original signal detected is filtered extraction, obtains mixing coarse positioning signal data.
Detection and localization can be carried out to pipe leakage using sound emission leak detection system, obtain the thick fixed of leak detection
Position signal, but the coarse positioning signal often signals such as entrainment noise so that exist between detection locator value and actual value compared with
Big error must be handled pipe leakage coarse positioning signal data using suitable method thus.And multiple spot is let out
Leakage, then must first separate coarse positioning signal source, carry out more technological synthesis processing such as de-noising, obtain more accurate
Time difference Δ t, to obtain more accurate positioning.
Wavelet Denoising Technology is widely approved and is 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 are as follows:
S2.3.1: the wavelet decomposition of signal.Firstly, to select its suitable wavelet basis to different signals, and determine
Then the level to be decomposed well carries out decomposition computation again.
S2.3.2: the threshold value quantizing of wavelet decomposition high frequency coefficient.It needs to select a suitable threshold value to each decomposition
High frequency coefficient under scale is quantified, and herein, soft-threshold is selected to carry out quantification treatment to it.Specifically, utilizing
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 the tool box MATLAB, according to above-mentioned steps S2.3.1-S2.3.3 to data carry out wavelet decomposition,
Threshold value quantizing and wavelet reconstruction, the signal after exporting de-noising, as observation signal I1、I2, wherein I1Indicate that upstream sensor obtains
The signal obtained, I2Indicate the signal that downstream sensor obtains；
S2.4: the observation signal I that will be obtained after noise reduction1、I2, it is mixed to form with the matrix generated at random in Matlab new
Observation signal L1、L2；Since 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、L2It imports in Matlab and carries 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.
Using maximum likelihood function as objective function in the algorithm.Since maximum-likelihood method is very big for number of samples
When, it also can be progressive effective, an optimal solution is obtained, therefore optimizing is carried out to result using maximum likelihood algorithm；Simulated annealing
The blind source separating of the particle swarm algorithm of thought can improve and get rid of Local Extremum, the ability of local optimum, and separate essence
Degree is high, and stability is high.
Wherein specific step is as follows for the memory simulated annealing population blind source separating:
Due to the basic model of blind source separating are as follows:
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 the model of source signal s (t) are as follows:
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 initialize to each particle, weight
For w, perception factor and social learning's factor are respectively c1、c2, a certain number of solution hybrid matrix W (t) conducts will be randomly generated
Primary, can simultaneously be randomly generated 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: separating signal according to the position of particle, centralization and whitening operation is carried out to y (t), according to greatly seemingly
Right estimation function calculates the adaptive value of each particle with this as objective 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: judging whether to meet termination condition, terminates calculating if meeting, otherwise continues；
S2.5.5: by each particle adaptive value and individual extreme value piWith global extremum pgIt is compared, optimal value is taken 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 the range of given maximum speed and maximum position is limited respectively
It is interior, and calculate the adaptive value of each more new particle；
S2.5.7: calculating the variable Δ E of adaptive value caused by former and later two particle positions, if Δ E < 0, receives new
Position；If the random number between exp (- Δ E/T) < δ, δ ∈ (0,1), also receives new position, otherwise refuses and return to step
S2.5.2；
S2.5.8: being embedded in and memory variable initial position and adaptive value is arranged, the optimal location as recycled for the first time
With adaptive value；
S2.5.9: storage location and adaptive value in newer position and adaptive value and memory, if new position and adaptation
Position then return step S2.5.2 identical as adaptive value in value and memory, on the contrary it is recorded into memory；
S2.5.10: annealing operation, T are carried out(t+1)=λ Tt(t is the number of iterations)；
S2.5.11: if meeting termination condition, optimal solution is exported, otherwise return step S2.5.2；
S2.5.12: asking to obtain that W (t) is optimal, solves the optimal estimation of source signal s (t).
Memory is added to record to obtain optimal solution, the optimal solution obtained each time and record optimal solution before are compared,
Duplicate optimal solution is rejected, the way of search of detour is effectively prevented, and then reduces search time, solves annealing grain
Subgroup method the problem of 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；
Since the spread speed of acoustic emission signal in the material is by material type, anisotropy, planform and ruler
The influence of many factors such as very little, interior media, so that spread speed becomes a kind of easy variable.And also due to acoustic emission signal
With dispersion phenomenon, the frequency by wave is influenced, and causes the velocity of sound for being difficult to determine leakage sound wave in actual condition.
The pipe leakage velocity of sound is not only influenced by pipeline material, is also influenced by different medium, different operating conditions, and
There is difference using the velocity of wave that different methods detects, currently, a unified method calculating pipeline is let out not yet both at home and abroad
The velocity of wave of sound wave is leaked, researcher detects or calculates to obtain value of wave speed also inconsistent.Such as, University Of Tianjin Sun Li beautiful jade et al. " is filling
The propagation and attenuation Characteristics of acoustic emission wave 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 lower for 1500m/s；And Shen Gongtian is in " acoustic emission testing technology and application " (Science Press, version in 2015,242-243
Page) in a book in think, in the acoustic emission signal that steel pipe leakage generates when medium is air, velocity of wave is 880~
Between 960m/s；And Didem Ozevin is 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
Calculating the velocity of wave that sound emission medium in pvc pipe is air is 1479m/s.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 sensors of correlator place transmitting pipeline leakage detecting sensor placement location in unison.Using correlation
Instrument carries out detection and localization to pipe leakage, is usually 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) the cross-correlation function R in the available time domain τ of inverse Fourier transformAB
(τ):
In formula, GABIt (v) is the Fourier transform of A (t) B (t+ τ), wherein A (t) indicates that a wave, B (t+ τ) indicate another
The wave that one delay time is τ, GAB(v) the result is that leak position data.This method can to the leakage of tested pipeline single-point
Accurately positioning is obtained, it is also larger to multipoint leakage position error.But when its positioning result probability is greater than 4%, it can recognize
For as a result, more objective and accurate, this can be verified (see experimental data table 1) from many experiments result.Thus
We determine that the measurement that velocity of wave is carried out using correlator is determined.
Test 1 operating condition are as follows: the PE of the long 2030cm of pipeline is managed, and interior media is compressed air, pressure 0.5MPa, buried
Pipeline, leak leak at ducts upstream sensor 1600cm, leak aperture 2mm.
Test 2 operating conditions are as follows: the steel pipe of pipe range 3600cm, interior media are compressed air, pressure 0.57MPa, empty frame pipe
Road, leak leak at ducts upstream sensor 1600cm, leak aperture 1mm.
Test 3 operating conditions are as follows: the steel pipe of pipe range 4275cm, interior media are compressed air, pressure 0.28MPa, empty frame pipe
Road, leak leak at ducts upstream sensor 1706cm, and leakage aperture is 1mm.
1 correlator pipe leakage positioning experiment data of table
Calculate determine the velocity of wave of leakage signal it is specific the following steps are included:
S3: the spread speed v of leakage source signal in the duct is determined；
S3.1: pipeline source of leaks acoustical signal is acquired using correlator；
S3.2: it according to collected pipe leakage source acoustical signal, is detected by correlator analyzing and positioning result and positions knot
Fruit probability analysis determines spread speed v of the source of leaks acoustical signal in pipeline medium；In order to guarantee the objectivity of data, to phase
The detection of instrument analyzing and positioning result and positioning result probability analysis are closed, under same operating condition, taking three batches of acquisition data, every batch of 10
Group data analyze the average speed obtainedSpread 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).
The process of above data analysis and processing, which is programmed by Matlab, to be realized.
The beneficial effects of the present invention are: a kind of pressure pipeline two o'clock leak detection accurate positioning method 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 same a pair
As acquiring pipeline leakage signal；Upstream and downstream pipe leakage source signal is acquired by Acoustic radiating instrument, by dropping using Wavelet Denoising Technology
Influence of the low noise to leakage source signal arrives detection signal using the particle swarm optimization algorithm based on simulated annealing thought
Leakage signal carries out blind source separating processing, while being embedded in memory, constructs and using memory simulated annealing population blind separation side
Method, can not only eliminate pipeline multipoint leakage leads to the Dispersion of signal, isolates more accurate leakage source signal, so that
Disengaging time greatly reduces, and determines that leakage source signal reaches the time of upstream and downstream two sensors with this；Recycle correlator leakage
The leakage signal of detection system acquisition analyzes the propagation precise speed of acoustic signals in the duct；It is finally fixed according to cross-correlation
Position algorithm calculates the position of source of leaks.The present invention can be accurately positioned pressure pipeline leakage, provide a kind of cost
It is low, easy to use, and can identify minute leakage, pipeline multipoint leakage localization method.
Detailed description of the invention
Present invention will be further explained below with reference to the attached drawings and examples.
Fig. 1 is the flow diagram of preferred embodiment；
Fig. 2 is pressure pipeline two o'clock leakage device schematic diagram；
Fig. 3 is No. 1 spectrogram of sensor；
Fig. 4 is No. 2 spectrograms of sensor；
Fig. 5 is No. 1 waveform diagram of sensor；
Fig. 6 is No. 2 waveform diagrams of sensor；
Fig. 7 is acoustic emission detection effective voltage RMS positioning figure；
Fig. 8 is acoustic emission detection average signal level ASL positioning figure；
Fig. 9 is the observation signal after sensor 1 (upstream sensor) noise reduction；
Figure 10 is the observation signal after sensor 2 (downstream sensor) noise reductions；
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 pipe leakage point；
Figure 14 is positioning result probability graph of the correlator to pipe leakage point.
Specific embodiment
Presently in connection with attached drawing, the present invention is described in detail.This figure is simplified schematic diagram, is only illustrated in a schematic way
Basic structure of the invention, therefore it only shows the composition relevant to the invention.
As shown in Figure 1, a kind of pressure pipeline two o'clock leak detection accurate positioning method of the invention, specifically includes following
Step,
S1: detection system is built；
Two acoustic emission sensors are mounted on to the upstream and downstream of detected pipeline, and send out acoustic emission sensor and sound
It penetrates instrument connection and is built into sound emission leak detection system；Meanwhile by pairwise correlation instrument sensor be mounted on detected ducts upstream with
The same position in downstream, and connect two sensors with correlator and be built into correlator leak detection system；
S2: determine that leakage source signal reaches the time difference Δ t of two acoustic emission sensor of upstream and downstream；
S2.1: the source of leaks original signal of pipeline is acquired by sound emission leak detection system；
S2.2: the collected pipeline upstream and downstream source of leaks original signal of sound emission leak detection system is screened, is mentioned
It takes RMS voltage RMS value and average signal level ASL value is 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 is determined and to be decomposed
Level, then carry out decomposition computation again；
S2.3.2: the threshold value quantizing of wavelet decomposition high frequency coefficient selects a suitable threshold value 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 carries out one 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 obtain after noise reduction is mixed to form new observation
Signal；
S2.5: new observation signal being 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 the memory simulated annealing population blind source separating include,
S2.5.1: Initial parameter sets: population population is set as n, and initialize to each particle, weight
For w, perception factor and social learning's factor are respectively c1、c2, a certain number of solution hybrid matrix W (t) conducts will be randomly generated
Primary, can simultaneously be randomly generated 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: separating signal according to the position of particle, centralization and whitening operation is carried out to y (t), according to greatly seemingly
Right estimation function calculates the adaptive value of each particle with this as objective 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: judging whether to meet termination condition, terminates calculating if meeting, otherwise continues；
S2.5.5: by each particle adaptive value and individual extreme value piWith global extremum pgIt is compared, optimal value is taken 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 the range of given maximum speed and maximum position is limited respectively
It is interior, and calculate the adaptive value of each more new particle；
S2.5.7: calculating the variable Δ E of adaptive value caused by former and later two particle positions, if Δ E < 0, receives 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: being embedded in and memory variable initial position and adaptive value is arranged, the optimal location as recycled for the first time
With adaptive value；
S2.5.9: storage location and adaptive value in newer position and adaptive value and memory, if new position and adaptation
Position then return step S2.5.2 identical as adaptive value in value and memory, on the contrary it is recorded into memory；
S2.5.10: annealing operation, T are carried out(t+1)=λ Tt(t is the number of iterations)；
S2.5.11: if meeting termination condition, optimal solution is exported, otherwise return step S2.5.2；
S2.5.12: asking to obtain that W (t) is optimal, solves the optimal estimation of source signal s (t).
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: the propagation precise speed v of leakage source signal in the duct is determined；
S3.1: pipeline source of leaks acoustical signal is acquired using correlator；
S3.2: it according to collected pipe leakage source acoustic emission signal data, is 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, firstly, detection system is built, in the present embodiment
Use one section of caliber for the steel pipe of DN150, nominal diameter 150mm, a length of 44m of experimental channel, pressure is
0.1MPa, pipeline interior media are tap water；Downstream acoustic emission sensor is individually positioned at 1m and 43m, such as sound emission in figure
Sensor No. 1 and acoustic emission sensor 2, two leaks are separately positioned at 19m and 33m apart from zero point, and leakage aperture is equal
For 1mm, simulated leakage experiment is carried out.
It is acquired through leak test, Fig. 3-Fig. 6 is sound emission leakage detector in this liquid-filling pipe two o'clock leakage experiment
In pressure 0.1MPa, leaking aperture is all the signal spectrum figure (Fig. 3, Fig. 4) and waveform diagram (Fig. 5, figure obtained in the case of 1mm
6) and RMS voltage RMS positioning figure (Fig. 7), average signal level ASL positioning scheme (Fig. 8).
Wherein, the abscissa of signal spectrum figure indicates frequency (Hz), and ordinate indicates power (dB)；Waveform diagram
Abscissa indicates time (s), and ordinate indicates voltage (mV)；The abscissa of RMS voltage RMS positioning figure indicates that leakage point arrives
The distance (mm) of upstream acoustic emission sensor, ordinate indicate RMS voltage RMS (V)；Average signal level ASL positioning figure
Abscissa indicate 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 figure
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 fixed
Position signal, but exist simultaneously more noise signal；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 two o'clock source of leaks of table experiment positioning coarse positioning signal data table
Above content is the content of S2.1-S2.2.
S2.3 carries out noise reduction process to coarse positioning signal using Wavelet Denoising Technology, obtains observation signal.
For the influence for reducing ambient noise, noise reduction process is carried out to original signal by wavelet noise, which passes through
Matlab software realization.
The process of small echo signal de-noising is divided into following steps:
S2.3.1: the wavelet decomposition of signal.Firstly, to select its suitable wavelet basis to different signals, and determine
Then the level to be decomposed well carries out decomposition computation again.
S2.3.2: the threshold value quantizing of wavelet decomposition high frequency coefficient.It needs to select a suitable threshold value to each decomposition
High frequency coefficient under scale 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, the signal after obtaining noise reduction is observation signal I1、I2, wherein I1Indicate the letter that upstream sensor obtains
Number, I2Indicate the signal that downstream sensor obtains.As shown in Fig. 9 and Figure 10, respectively pipeline upstream and downstream acoustic emission sensor is connect
Observation signal figure after the coarse positioning signal de-noising received.Wherein the abscissa of Fig. 9 and Figure 10 indicates sampled point, indulges and sits
Mark indicates range value (V).
The observation signal I that S2.4 will be obtained after noise reduction1、I2, it is mixed to form with the matrix generated at random in Matlab new
Observation signal L1、L2；Since 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, respectively on
The observation signal figure that downstream signal is formed with the hybrid matrix generated at random.
S2.5 is by new observation signal L1、L2It imports in Matlab and carries 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, thus, it is 0.0062s that signal, which reaches the time difference Δ t between upstream and downstream sensor,.Its
In, the abscissa of Figure 11 and Figure 12 indicate that sampled point, ordinate indicate range value (V).
S3: the propagation precise speed v of acoustic emission signal in the duct is determined；
S3.1: the two sensors of correlator are placed in the upstream and downstream of detected pipeline, the two sensors position of correlator
It is identical as 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 acquire pipe leakage acoustical signal；
S3.2: according to collected pipe leakage acoustical signal, pass through the detection of correlator analyzing and positioning result and positioning result
Probability analysis；To the average speed under same operating condition, three batches of analysiss of data collected being taken to obtainAs source of leaks sound emission
Spread speed v in pipeline medium.
Parameter is set using correlator, positioning probability results are greater than with 4% velocity of wave, which is analyzed, and mentions
Take out corresponding velocity of wave.The curve display that pipe leakage point detects is schemed by analysis correlator and correlator is to pipe leakage
The positioning result probability of point shows (such as Figure 13 and Figure 14), wherein the abscissa of Figure 13 and Figure 14 indicates leakage point to upstream phase
The distance (cm) of instrument sonic sensor is closed, ordinate indicates range value (V), extracts in correlator to go out in three batches of location datas
The existing higher locator value of probability and corresponding velocity of wave v, as shown in table 3.
3 correlator location data table of table
The velocity of wave that the leakage sound wave under such operating condition 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), available one of leakage anchor point is
19.44m.And other leakage anchor points are calculated 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 4 19m of table
| Serial number | Coarse positioning leak position (m) | It measures 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 5 33m of table
By the analysis processing to all data, the position of leakage point after analyzing can be seen that by table 4 and table 5 substantially
With design when 19m and 33m match, and setting accuracy than Acoustic radiating instrument and correlator detection leak result it is more preferable.?
It is 7.7% that relative error is measured at 19m leakage point, and relative error is 4.1% after processing；Opposite miss is measured at 33m leakage point
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 is at low cost, easy to use.
Above to a kind of pinpoint method of pressure pipeline two o'clock source of leaks detection provided by the present invention, and to this
It is described in detail.It applies specific experiment example to be expounded the principle of the present invention and embodiment, be illustrated
, the foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention.It is all in spirit of the invention
With any modifications, equivalent replacements, and improvements made within principle etc., should all be included in the protection scope of the present invention.
Claims (3)
1. a kind of pressure pipeline two o'clock leak detection accurate positioning method, it is characterised in that: include the following steps,
S1: detection system is built；
Two acoustic emission sensors are mounted on to the upstream and downstream of detected pipeline, and connect acoustic emission sensor and Acoustic radiating instrument
It connects and is built into sound emission leak detection system；Meanwhile pairwise correlation instrument sensor is mounted on detected ducts upstream and downstream
The same position of acoustic emission sensor, and connect pairwise correlation instrument sensor with correlator and be built into correlator leak detection system
System；
S2: determine that leakage source signal reaches the time difference Δ t of two acoustic emission sensor of upstream and downstream；
S2.1: the source of leaks original signal of pipeline is acquired by sound emission leak detection system；
S2.2: screening is filtered to the collected pipeline upstream and downstream source of leaks original signal of sound emission leak detection system, is mentioned
It takes RMS voltage RMS value and average signal level ASL value is 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 obtain after noise reduction is mixed to form new observation signal；
S2.5: new observation signal being 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；Sampled point according to two singular points is poor
Value determines that leakage source signal reaches the time difference Δ t of two acoustic emission sensors of upstream and downstream；
S3: the spread speed v of leakage source signal in the duct is determined；
S3.1: pipeline source of leaks acoustical signal is acquired using correlator；
S3.2: it according to collected pipe leakage source acoustical signal data, is detected by correlator analyzing and positioning result and positions knot
Fruit probability analysis determines 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, calculates leakage according to cross-correlation ranging formula (1)
Source position；
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. pressure pipeline two o'clock leak detection accurate positioning method as described 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 determines 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 selects a suitable threshold value 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 carries out one-dimensional small according to the low frequency coefficient of the high frequency coefficient of each layer of wavelet decomposition and the bottom
Reconstructed wave.
3. pressure pipeline two o'clock leak detection accurate positioning method as described in claim 1, it is characterised in that: the step
Described in S2.5 remember simulated annealing population blind source separating specific steps include,
S2.5.1: Initial parameter sets: setting population population as n, and initialize to each particle, and weight w recognizes
Know that the factor and social learning's factor are respectively c1、c2, a certain number of solution hybrid matrix W (t) will be randomly generated and be used as initial grain
Son, can simultaneously be randomly generated 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: separating signal according to the position of particle, centralization and whitening operation is carried out to y (t), according to Maximum-likelihood estimation
Function calculates the adaptive value of each particle with this as objective 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: judging whether to meet termination condition, terminates calculating if meeting, otherwise continues；
S2.5.5: by each particle adaptive value and individual extreme value piWith global extremum pgIt is compared, optimal value is taken 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 maximum speed and maximum position respectively, and
Calculate the adaptive value of each more new particle；
S2.5.7: calculating the variable Δ E of adaptive value caused by former and later two particle positions, if Δ E < 0, receives new position；
If the random number between exp (- Δ E/T) < δ, δ ∈ (0,1), also receives new position, otherwise refuses and return to step
S2.5.2；
S2.5.8: being embedded in and memory variable initial position and adaptive value is arranged, as the optimal location of circulation and suitable for the first time
It should be worth；
S2.5.9: storage location and adaptive value in newer position and adaptive value and memory, if new position and adaptive value and
Position then return step S2.5.2 identical as adaptive value in memory, on the contrary it is recorded into memory；
S2.5.10: annealing operation, T are carried out(t+1)=λ Tt(t is the number of iterations)；
S2.5.11: if meeting termination condition, optimal solution is exported, otherwise return step S2.5.2；
S2.5.12: asking to obtain that W (t) is optimal, solves the optimal estimation of source signal s (t).
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