CN103912791B - Underground pipe network leak detection method - Google Patents
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- CN103912791B CN103912791B CN201410038082.9A CN201410038082A CN103912791B CN 103912791 B CN103912791 B CN 103912791B CN 201410038082 A CN201410038082 A CN 201410038082A CN 103912791 B CN103912791 B CN 103912791B
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Abstract
The invention discloses a kind of underground pipe network leak detection method, comprise the following steps: a. carries out infrared, ultraviolet or Terahertz shooting to pipeline region; B. the image photographing is carried out to gray scale processing, utilize the graded of gray scale in edge detection method recognition image based on isopleth principle, with identification be taken temperature in region or the graded of inert gas concentration, and determine according to default gradient sudden change threshold value the inert gas concentration saltation zone border that has the border, temperature jump district of temperature jump or have inert gas concentration sudden change; C. descend definitely pipeline network leak region according to border, described temperature jump district or described inert gas concentration saltation zone border. This underground pipe network leak detection method can descend pipeline network leak point rapidly and accurately definitely.
Description
Technical field
The present invention relates to a kind of underground pipe network leak detection method.
Background technology
It is inevitable problem that underground pipe network material leaks, and the loss due to leakage of water supply network can produce water resource waste; SewagePipe network spill can polluted underground water matter, the infiltration of the underground water of same sewage network, increases again the running cost of sewage treatment plantWith; The leakage of coal gas and flow circuit can cause the loss of personnel and property; The leakage of heat distribution pipe network, can produce the energy equallyWaste. Therefore, the invention of underground pipe network leak detection method is very important.
The current groundwater supply pipe network detection means of leaking is that micro-judgment, audition method and correlation method detect substantially, knotClose region flow measurement, determine leakage situation, also have the leak automatic monitoring method of sound or the subregion leak detecting etc. of employing, conventional have byMoving leak detecting, sound are listened leak detecting, water balance probe method, Zhuan Biaofa region, region leak detecting, Zhuan Biaojian region, region leak hunting method, receiptsCollection formula leak detecting, free floating type leak detecting etc. But, effective detection that water supply network leaks, especially super buried depth, great KouThe detection of leaking of footpath, non-metallic pipe is global problem all the time, and international water assists within nearly 10 years, worldwide to enter continuouslyThe collection of row water leakage detecting method, but never find effective technology.
Summary of the invention
Main purpose of the present invention is exactly for the deficiencies in the prior art, and a kind of underground pipe network leak detection method is provided,Can descend definitely rapidly and accurately pipeline network leak point.
For achieving the above object, the present invention is by the following technical solutions:
A kind of underground pipe network leak detection method, comprises the following steps:
A. infrared, ultraviolet or Terahertz shooting are carried out in pipeline region;
B. the image photographing is carried out to gray scale processing, utilize in edge detection method recognition image based on isopleth principleThe graded of gray scale, to identify the temperature that is taken in region or the graded of inert gas concentration, and according to defaultGradient sudden change threshold value is determined the inert gas that has the border, temperature jump district of temperature jump or have inert gas concentration sudden changeConcentration saltation zone border;
C. descend definitely pipeline network leak according to border, described temperature jump district or described inert gas concentration saltation zone borderRegion.
Further:
In step b, described edge detection method comprises:
1) use Gaussian filter smoothing image;
2) by the finite difference of single order local derviation assign to amplitude and the direction of compute gradient;
3) gradient magnitude is carried out to non-maximum inhibition;
4) detect with dual threshold algorithm and be connected edge.
Described gradient sudden change threshold value is 0.00～0.2.
Described gradient sudden change threshold value is 0.1.
In step a, adopt manual shooting, vehicle-mounted instrument shooting, Aerial photography or satellite to take.
In step a, take continuously along pipeline trend, and adjacent image has overlay region, before step b, pass throughIdentification overlay region, splices and combines along pipeline trend the image of continuous shooting.
In step b, be first GIS-Geographic Information System in conjunction with pipe network GIS() and the Image Mosaics of topographic map of urban area to continuous shootingCombination.
In step b, before being identified, image carries out noise reduction process.
In step a, by conjunction with pipeline network GIS, make a video recording along pipeline trend, in step c, the definite basis on borderUpper, by conjunction with pipeline network GIS, determine the leakage point of pipe network.
Described underground pipe network is water supply, air feed, heat supply or fuel feeding pipe network.
The technique effect that the present invention is useful is:
The present invention proposes that infrared, ultraviolet and Terahertz camera technique are applied to underground pipe network and visits and leak, and utilizes infrared ray, purpleOutside line and Terahertz are responded to sharp characteristic to temperature and inert gas, by infrared photography, ultraviolet shooting, Terahertz shooting inspectionTesting temperature and inert gas concentration change, and detect with the leakage loss situation such as coordinate detection of the leakage point that carries out underground pipe network, canDescend definitely rapidly and accurately pipeline network leak point, as water supply network leakage point, the present invention is the maintenance excavation to leakage point especiallyBe positioned with great practical value.
Leak detection method of the present invention, is not only applicable to urban water supply and sewerage, region plumbing, indoor water supply and drainage, plant areaThe leakage survey of gas network of the water supply and sewerage pipeline systems such as plumbing, is also applicable to the pipe of the liquid such as coal gas, heating power, oil transportation, chemical industry and gasNet leak detection, can be used for the buried pipes such as water supply network, sewage network, gaspipe network, heat distribution pipe network, petroleum pipeline and chemical industry pipe networkRegion and detection, leaking area identification, leak point positioning and leakage rate calculating etc. on a large scale that the liquids and gases of net leak.
The present invention jumps out the constraint of conventional sound-detection principle, proposes to utilize underground pipe network leakage to bring initiativelyThe inert gas concentration variation that surface temperature changes or leaks, adopts camera technique to carry out leak detection, has successfully solved lengthUnderground pipe network since the phase difficult problem of leaking hunting, application of the present invention is conducive to effectively carry out leakage point identification on a large scale, and raising is let outLeak discrimination and operating efficiency, there is important progressive meaning and wide application prospect.
Brief description of the drawings
Fig. 1 is the flow chart of the underground pipe network leak detection method embodiment according to the present invention;
Fig. 2 a and Fig. 2 b are that the non-maximum in embodiment of the present invention image recognition processes suppresses schematic diagram
The two width gray level images that Fig. 3 a and Fig. 3 b change into for the photo in the region that leaked by the pipe network of infrared shooting;
Fig. 4 a-Fig. 4 d illustrates gray level image shown in Fig. 3 a by edge detection method processing, threshold value is set be respectively0.00,0.01,0.05 and the border of 0.1 o'clock determine result;
Fig. 5 a-Fig. 5 d illustrates gray level image shown in Fig. 3 b by edge detection method processing, threshold value is set be respectively0.00,0.01,0.05 and the border of 0.1 o'clock determine result.
Detailed description of the invention
By reference to the accompanying drawings the present invention is described in further detail by the following examples.
Refer to Fig. 1, in one embodiment, carry out underground pipe network leak detection by following flow process.
According to the topographic map in the GIS information of underground pipe network, pipe network model and city, on the basis of analyzing at historical summary,Formulate work plan, the selected region that needs detecting leakage, the object of detection can be that the environment temperature that leakage point causes changesOr the ambient gas change in concentration that causes of inert gas of leaking.
Next selected region is taken. Style of shooting can adopt manual shooting, vehicle-mounted instrument shooting, aviationTake or satellite shooting. Capture apparatus can adopt thermal camera, ultraviolet video camera or Terahertz video camera. Can be according to gasTime condition, state of ground and shooting time, selected suitable shooting wavelength on experiment basis.
Can descend in combination pipeline network GIS and topographic map of urban area, according to weather condition and shooting time, along pipeline trend continuouslyTake.
Preferably, along pipeline trend, selected region is taken continuously with certain speed. The density of taking is preferredDetermine in such a way: photo covers floor area substantially, adjacent two photos have overlay region, and overlay region to the greatest extentMeasure littlely, ensure can identify splicing in subsequent step.
Take after image, carried out graphic joining and combination. Can topographic map of urban area be background, in conjunction with pipe network GIS system,Identify overlay region by image recognition technology, several figure are spliced into a width or a few width figure. This mode can improve the knowledge of leakingOther degree of accuracy and efficiency.
Next carry out image processing.
First cromogram is carried out to gray scale and noise processed, make the impacts such as river, pond, marshland leak judgement physics because ofElement is removed to greatest extent.
Application isopleth principle, carries out image recognition by the image-recognizing method of rim detection, identification temperature jump districtWith inert gas concentration saltation zone, determine region, corresponding image border, determine abrupt boundary. Determine the substantially square of fringe regionMethod is, identifies the fringe region that in image, shade of gray is undergone mutation, its can by arrange different sudden change threshold values come rightWhether shade of gray suddenlys change is differentiated, and detects step edge, thereby obtains boundary image.
On definite basis, border, combine with pipeline network GIS, can determine the accurate leakage point of pipe network.
The pixel can by finding out in image with local greatest gradient amplitude detects step edge. PreferablyEmbodiment adopts following edge detection method, can improve the sensitiveness of edge, accurately determines marginal position, can carry again simultaneouslyThe high sensitivity to noise, effectively suppresses noise.
In the present embodiment, adopt edge detection filter, preferably adopt single order differential filter, with two-dimensional Gaussian functionFirst directional derivative on any direction is noise filter, by carrying out filtering with image convolution; Then to filtered figurePicture is found the local maximum of image gradient, determines image border with this. According to signal to noise ratio and location product are estimated,Obtain optimization Approximation Operator. Specifically, this edge detection method comprises the following steps:
Step 1: use Gaussian filter smoothing image;
Step 2: by the finite difference of single order local derviation assign to amplitude and the direction of compute gradient;
Step 3: the amplitude of gradient is carried out to non-maximum inhibition;
Step 4: use dual threshold algorithm detect and be connected edge.
The concrete mathematical description of above steps is as follows:
Step 1:
Two dimension for Gaussian function is:
The first directional derivative that is G (x, y) on a direction n is:
In formula: n formula direction vector, ▽ G is gradient vector.
By image f (x, y) and GnMake convolution, change the direction of n, G simultaneouslyn* n when f (x, y) obtains maximum is just exactlyMeet at the direction of Edge detected.
Step 2:
A (x, y) has reflected the edge strength at image (x, y) some place, and θ is the normal vector at image (x, y) some place.
Step 3:
Utilize the direction of gradient, retain the point of partial gradient maximum, and suppress non-maximum.
As shown in Figure 2 a and 2 b, the label of four sectors is 0 to 3, and four kinds of corresponding 3*3 neighborhood may be combined. OftenA bit upper, the center pixel M of neighborhood is compared with two pixels along gradient line. If the Grad of M is unlike along gradient lineTwo neighbor Grad are large, make M=0.
Step 4:
The typical method that reduces false edge section quantity is that G (x, y) is used to a threshold value. All values lower than threshold value is composedNull value.
Can pass through dual threshold algorithm, determine gradient sudden change threshold value, carry out edge differentiation and be connected edge. First increase defaultGradient sudden change threshold value, there is discontinuous situation in the border of image recognition, by reducing the threshold value in discontinuous scope, realizesThe closed on image recognition border, is called dual threshold and detects.
1. be first that edge is differentiated: what every edge strength was greater than high threshold must be marginal point; Every edge strength is littleIn low threshold value is marginal point scarcely; If edge strength is greater than low threshold value and is less than again high threshold, see the neighbour of this pixelConnect the marginal point that whether exceedes high threshold in pixel, if had, it is exactly marginal point, if do not had, it is not just marginal point.
2. be secondly to connect edge: dual threshold algorithm suppresses image to non-maximum and introduces two threshold tau 1 and τ 2, and 2 τ 1≈ τ 2, thus two threshold value edge image G1 (x, y) and G2 (x, y) can be obtained. Because using high threshold, G2 (x, y) obtains,Thereby contain little false edge, but there is interruption (not closed). Dual threshold method will connect into profile edge in G2 (x, y),In the time arriving the end points of profile, this algorithm is just found the edge that can be connected on profile in the 8 adjoint point positions of G1 (x, y), thisSample, algorithm is constantly collected edge in G1 (x, y), until till G1 (x, y) is coupled together.
The advantage of above-mentioned edge detection method: low error rate, seldom marginal point is thought by mistake to non-marginal point; High positioning accurateDegree, is accurately positioned at marginal point in the pixel of grey scale change maximum; Can suppress false edge.
Certainly, except above-mentioned preferred detection method, can also with known sobel, prewitt, roberts,Log, zeroscross scheduling algorithm, can realize the Boundary Detection based on shade of gray sudden change that the present invention proposes.
Fig. 3 a and Fig. 3 b are depicted as by the captured pipe network of infrared photography two width that the photo in region changes into that leakGray level image. Can see at this two width image, have leak source in pipeline, when pipeline is intake continuously, the temperature of surrounding soil becomesChange. Because water specific heat capacity is large, around soil, absorb heat, so leak source environment temperature is lower.
As shown in Fig. 4 a to Fig. 4 d, by above-mentioned edge detection method, gray level image is processed, threshold value is set respectively0.00,0.01,0.05 and 0.1 carries out border determines, the seepage region obtaining is closed curve. Can according to Fig. 3 a to Fig. 3 bFollowing result detected: along with the increase of picture processing threshold value, picture noise reduction capability strengthens, and for example threshold value=0.00 o'clock, makes an uproar in figureThe point of articulation is obvious, and along with threshold value increases to 0.01, noise and background value all decline, and image leakage loss scope is clear; In the time of threshold value=0.1,Image boundary is high-visible; But when threshold value continuation increase, although background and level of noise continue decline, the leakage loss obtainingRegion starts not closed. Preferred threshold value=0.1 of embodiments of the invention, obtains best leakage loss scope recognition result. Fig. 5 a is to figureSituation shown in 5d is that similarly it will not go into details. According to actual conditions, it is above-mentioned specific that the choosing of gradient sudden change threshold value is also not limited toValue, for example, can choose in 0.00～0.2 scope.
In addition, the inert gas concentration that the indifferent gas of leakage is known from experience around leakage point causes changes, with variations in temperature oneSample, gas concentration changes in the grey scale change that also can be reflected in the captured images of mode such as infrared, ultraviolet, therefore, said methodBe equally applicable to the leak detection of inert gas.
Above content is in conjunction with concrete preferred embodiment further description made for the present invention, can not assertSpecific embodiment of the invention is confined to these explanations. For general technical staff of the technical field of the invention,Do not depart under the prerequisite of the present invention's design, can also make some simple deduction or replace, all should be considered as belonging to of the present inventionProtection domain.
Claims (10)
1. a underground pipe network leak detection method, is characterized in that, comprises the following steps:
A. infrared, ultraviolet or Terahertz shooting are carried out in pipeline region;
B. the image photographing is carried out to gray scale processing, utilize gray scale in edge detection method recognition image based on isopleth principleGraded, to identify the temperature that is taken in region or the graded of inert gas concentration, and according to default gradientSudden change threshold value is determined the inert gas concentration that has the border, temperature jump district of temperature jump or have inert gas concentration sudden changeSaltation zone border;
C. descend definitely pipeline network leak region according to border, described temperature jump district or described inert gas concentration saltation zone border.
2. underground pipe network leak detection method as claimed in claim 1, is characterized in that, in step b, and described side edge detectionMethod comprises the following steps:
1) use Gaussian filter smoothing image;
2) by the finite difference of single order local derviation assign to amplitude and the direction of compute gradient;
3) amplitude of gradient is carried out to non-maximum inhibition;
4) detect with dual threshold algorithm and connect edge.
3. underground pipe network leak detection method as claimed in claim 1, is characterized in that, described gradient sudden change threshold value is 0.00～0.2。
4. underground pipe network leak detection method as claimed in claim 3, is characterized in that, described gradient sudden change threshold value is 0.1.
5. the underground pipe network leak detection method as described in claim 1 to 4 any one, is characterized in that, in step a, adoptsManual shooting, vehicle-mounted instrument shooting, Aerial photography or satellite are taken.
6. the underground pipe network leak detection method as described in claim 1 to 4 any one, is characterized in that, in step a, along pipeLine trend is taken continuously, and adjacent image has overlay region, before step b, by identification overlay region, to continuous shootingImage splice and combine along pipeline trend.
7. underground pipe network leak detection method as claimed in claim 6, is characterized in that, in step b, first in conjunction with pipeline network GISWith the Image Mosaics combination of topographic map of urban area to continuous shooting.
8. the underground pipe network leak detection method as described in claim 1 to 4 any one, is characterized in that, in step b, rightImage carries out noise reduction process before identifying.
9. the underground pipe network leak detection method as described in claim 1 to 4 any one, is characterized in that, in step a, passes throughIn conjunction with pipeline network GIS, make a video recording along pipeline trend, in step c, on definite basis, border, by conjunction with pipeline network GIS, trueThe leakage point of fixed tube net.
10. the underground pipe network leak detection method as described in claim 1 to 4 any one, is characterized in that, described underground pipe networkFor water supply, air feed, heat supply or fuel feeding pipe network.
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Families Citing this family (11)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104279425A (en) * | 2014-09-05 | 2015-01-14 | 河南汉威电子股份有限公司 | Pipeline-leakage detecting system and method on basis of infrared imaging and unmanned aircraft |
| CN106981084B (en) * | 2016-10-28 | 2020-11-06 | 创新先进技术有限公司 | Method and device for drawing contour line |
| CN106644292A (en) * | 2016-12-28 | 2017-05-10 | 宁波市鄞州磁泰电子科技有限公司 | Heat distribution pipeline leakage magnetic temperature integration detection method |
| GB201711412D0 (en) * | 2016-12-30 | 2017-08-30 | Maxu Tech Inc | Early entry |
| CN106594528A (en) * | 2017-01-12 | 2017-04-26 | 杭州原创软件有限公司 | Pipeline on-line leakage monitoring instrument |
| CN107462689A (en) * | 2017-08-24 | 2017-12-12 | 新疆国利衡清洁能源科技有限公司 | Calibration system and calibration method for coal underground gasification gas dissipation boundary |
| CN109488888B (en) * | 2018-11-06 | 2020-07-17 | 沈阳天眼智云信息科技有限公司 | Metal pipeline leakage monitoring method based on infrared temperature field multivariate analysis |
| CN109764248A (en) * | 2019-01-03 | 2019-05-17 | 湖南力乐利环保科技有限公司 | A kind of terminal and system to detect water supply pipe leakage loss |
| CN109915736B (en) * | 2019-03-15 | 2020-07-17 | 山东建筑大学 | Thermal pipe network system and leakage detection method thereof |
| CN111383423B (en) * | 2020-02-13 | 2021-11-23 | 江苏大学 | Road collapse early warning method and system based on drainage pipe network flow monitoring |
| FR3133696A1 (en) * | 2022-03-21 | 2023-09-22 | Ceneau | MOBILE DEVICE, SCOOTER AND METHOD FOR DETECTING ANOMALIES IN AN UNDERGROUND WATER NETWORK |
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