CN114018500B - Three-dimensional positioning method for underground pipeline leakage point based on genetic algorithm - Google Patents
Three-dimensional positioning method for underground pipeline leakage point based on genetic algorithm Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 13
- 230000002068 genetic effect Effects 0.000 title claims abstract description 9
- 238000010187 selection method Methods 0.000 claims abstract description 5
- 230000035772 mutation Effects 0.000 claims description 9
- 238000001514 detection method Methods 0.000 claims description 5
- 238000012545 processing Methods 0.000 claims description 5
- 230000001902 propagating effect Effects 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 abstract description 5
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 3
- 238000010276 construction Methods 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 230000032683 aging Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M3/00—Investigating fluid-tightness of structures
- G01M3/02—Investigating fluid-tightness of structures by using fluid or vacuum
- G01M3/04—Investigating fluid-tightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point
- G01M3/24—Investigating fluid-tightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point using infrasonic, sonic, or ultrasonic vibrations
- G01M3/243—Investigating fluid-tightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point using infrasonic, sonic, or ultrasonic vibrations for pipes
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- 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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/12—Computing arrangements based on biological models using genetic models
- G06N3/126—Evolutionary algorithms, e.g. genetic algorithms or genetic programming
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/30—Assessment of water resources
Abstract
The invention discloses a three-dimensional positioning method of underground pipeline leakage points based on genetic algorithm, which relates to the technical field of exploration and comprises the steps of acquiring underground vibration signals by adopting a plurality of detectors, establishing a coordinate system, matching any one detector with all other detectors, acquiring the total number of leakage points and the time difference of arrival of each pulse between two groups of vibration signals in each pair of detectors, randomly generating a plurality of random coordinates of any leakage point, calculating the calculation time difference of all the random coordinates and all the detector pairs, counting the sum of variances corresponding to each random coordinate, judging, taking the random coordinates corresponding to the sum of the variances as calculation coordinate output, otherwise, selecting the random coordinates with the same number by a roulette selection method from the generated random coordinates, and carrying out iterative calculation after cross variation; the invention can effectively acquire the number of the underground seepage points and the coordinates of each seepage point.
Description
Technical Field
The invention relates to the technical field of exploration, in particular to a positioning method of an underground pipeline leakage point.
Background
In recent years, urban construction in China rapidly develops, and underground pipelines serve as important life line engineering of cities and play an important role in urban water supply and drainage.
However, the problem of leakage of underground pipelines is increasing due to aging of pipelines, construction accidents, untimely maintenance and the like. First, leakage of the water supply pipe may cause serious waste of water resources. Secondly, leakage of industrial wastewater and domestic sewage in the drainage pipeline can also cause environmental pollution. More importantly, the long-term leakage of the pipeline easily causes the formation of a leakage point to be soft, and underground holes are easily formed, so that accidents such as ground collapse and foundation subsidence are caused, and the trip safety of people is seriously influenced.
Therefore, the underground pipeline leakage points are accurately positioned, the basis can be provided for pipeline maintenance, the economic loss is effectively reduced, and the casualties are avoided. At present, the conventional method for detecting the pipeline leakage point by using vibration is less, and effective signals are difficult to distinguish mainly due to noise interference, and the specific position of the pipeline leakage point is difficult to obtain in a three-dimensional space.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides a three-dimensional positioning method for an underground pipeline leakage point based on a genetic algorithm, so as to solve the problem that the current underground pipeline leakage point is difficult to accurately position.
The invention is realized by the following technical scheme:
in order to achieve the above purpose, the invention provides a three-dimensional positioning method of underground pipeline leakage points based on a genetic algorithm, which comprises the following steps:
step 1, horizontally arranging n detectors with detection directions vertically downward on the ground surface, wherein n is more than or equal to 3;
step 2, establishing a three-dimensional coordinate system, obtaining the three-dimensional coordinate of each wave detector, and enabling each wave detector to receive a vibration signal;
step 3, pairing any one of the detectors with all other detectors to form the same detector, reserving only one pair to obtain n (n-1)/pair of detectors in total, numbering 1, 2 and 3......... N (n-1)/2 for each pair of detectors, performing cross-correlation processing on two groups of vibration signals received by the two detectors in each pair of detectors to obtain the pulse number generated between the two groups of vibration signals in each pair of detectors and the reaching time of each pulse, wherein the pulse number generated by the same leakage point in any pair of detectors is the same, so that the obtained pulse number is the number m of the leakage points, and numbering 1, 2 and 3 ji ；
Step 4, randomly generating the coordinates of the ith leakage point, numbering the coordinates of the ith leakage point by 1, 2 and 3Calculated time difference between two detectors in all detector pairs in the n (n-1)/2 pairs in sequence +.>The coordinates of two detectors in the j-th pair of detectors are respectively (x) j1 ,y j1 ,z j1 ) And (x) j2 ,y j2 ,z j2 ) Where j1 represents one detector of the j-th pair of detectors and j2 is the other detector, then the k-th random coordinate of the i-th leak point is compared with the calculated time difference between the two detectors in the j-th pair of detectors:
wherein v is the average velocity of the seismic wave propagating on the shallow earth surface;
acquisition ofObtaining corresponding +.A variance sum of the difference variance between the calculated time differences and the corresponding time differences between the kth random coordinates of the ith leak point and the two detectors in all detector pairs>For meeting->Ordering the sum of variances of the smallest sum of variances to +.>Let->Corresponding random coordinatesCalculating coordinates for an ith leakage point, and entering a step 7, wherein a is a given threshold value; if there is no->Step 5 is performed;
step 5, selecting the coordinates of the h ith leakage points randomly generated in the step 4 by adopting a roulette selection method, whereinThe smaller random coordinates have larger probability of being selected, and h new random coordinates corresponding to the ith leakage point are selected;
step 6, performing crossing and mutation operation on h new random coordinates corresponding to the ith leakage point, wherein the crossing probability is B, and the mutation probability is C, so that h new random coordinates corresponding to the ith leakage point are obtained, and the h new random coordinates are brought into the step 4 for the next iteration;
and 7, outputting the calculated coordinates of the ith leakage point.
Further, b=0.9, c=0.01.
Compared with the prior art, the invention has the following advantages:
the invention provides a three-dimensional positioning method of an underground pipeline leakage point based on a genetic algorithm, which can effectively acquire the number of the leakage point and the coordinate of the leakage point for output by establishing the coordinate, performing vibration signal cross-correlation processing and the like, thereby avoiding the defects of traditional noise interference and the like and improving the detection accuracy and efficiency.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in conjunction with the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
A three-dimensional positioning method of underground pipeline leakage points based on a genetic algorithm comprises the following steps:
step 1, horizontally arranging n detectors with detection directions vertically downward on the ground surface, wherein n is more than or equal to 3;
step 2, establishing a three-dimensional coordinate system, obtaining the three-dimensional coordinate of each wave detector, and enabling each wave detector to receive a vibration signal;
step 3, pairing any one of the detectors with all other detectors to form a same detector, reserving only one pair to obtain n (n-1)/pair of detectors in total, numbering 1, 2 and 3......... N (n-1)/2 for each pair of detectors, performing cross-correlation processing on two groups of vibration signals received by the two detectors in each pair of detectors to obtain the number of pulses generated between the two groups of vibration signals in each pair of detectors and the reaching time of each pulse, wherein the obtained number of pulses is leakage because the pulses generated by the same leakage point in any pair of detectors are the sameThe number of the points is m, and the leakage points are numbered 1, 2 and 3 ji ；
Step 4, randomly generating the coordinates of the ith leakage point, numbering the coordinates of the ith leakage point by 1, 2 and 3Calculated time difference between two detectors in all detector pairs in the n (n-1)/2 pairs in sequence +.>The coordinates of two detectors in the j-th pair of detectors are respectively (x) j1 ,y j1 ,z j1 ) And (x) j2 ,y j2 ,z j2 ) Where j1 represents one detector of the j-th pair of detectors and j2 is the other detector, then the k-th random coordinate of the i-th leak point is compared with the calculated time difference between the two detectors in the j-th pair of detectors:
wherein v is the average velocity of the seismic wave propagating on the shallow earth surface;
acquisition ofObtaining corresponding +.A variance sum of the difference variance between the calculated time differences and the corresponding time differences between the kth random coordinates of the ith leak point and the two detectors in all detector pairs>For meeting->Is ranked by the sum of the variances of (a),let the smallest sum of variances be +.>Let->Corresponding random coordinatesCalculating coordinates for an ith leakage point, and entering a step 7, wherein a is a given threshold value; if there is no->Step 5 is performed;
step 5, selecting the coordinates of the h ith leakage points randomly generated in the step 4 by adopting a roulette selection method, whereinThe smaller random coordinates have larger probability of being selected, and h new random coordinates corresponding to the ith leakage point are selected;
step 6, performing crossing and mutation operation on h new random coordinates corresponding to the ith leakage point, wherein the crossing probability is B, in the embodiment, B=0.9, and the mutation probability is C, in the embodiment, C=0.01, so as to obtain h brand new random coordinates corresponding to the ith leakage point, and carrying out the next iteration in the step 4;
and 7, outputting the calculated coordinates of the ith leakage point.
Example 2
In this embodiment, a three-dimensional positioning method for a leakage point of an underground pipeline based on a genetic algorithm is provided, including the following steps:
step 1, horizontally arranging n detectors with detection directions vertically downward on the ground surface, wherein n is more than or equal to 3;
in this embodiment, n=9, which is arranged on the ground in a cross shape, i.e., 1 in the middle, two in front, back, left and right;
step 2, establishing a three-dimensional coordinate system, obtaining the three-dimensional coordinate of each wave detector, and enabling each wave detector to receive a vibration signal;
step 3, pairing any one of the detectors with all other detectors to form the same detector, and reserving only one pair to obtain n (n-1)/2 pairs of detectors, namely 9*8/2=36 pairs of detectors, numbering 1, 2 and 3.......... N (n-1)/2 for each pair of detectors, performing cross-correlation processing on two sets of vibration signals received by two detectors in each pair of detectors to obtain the pulse number generated between the two sets of vibration signals in each pair of detectors and the arrival time of each pulse, wherein the pulse number generated between the two sets of vibration signals in each pair of detectors is the same as the pulse generated by the same leakage point in any pair of detectors, so that the obtained pulse number is the number m of leakage points, m is 1 in the embodiment, and the calculation process of a plurality of leakage points is the same as the calculation process of the leakage points is omitted in the embodiment, and numbering 1, 2 and 3 ji ；
That is, if the true coordinates of the seepage point are (x, y, z), there are:
step 4, randomly generating the coordinates of the h ith leakage points, and numbering the coordinates of the h ith leakage points by 1, 2 and 3And->
Setting the iteration number as N and 5, and obtaining the kth random coordinate of the ith leakage pointCalculated time difference between two detectors in all detector pairs in the n (n-1)/2 pairs in sequence +.>The coordinates of two detectors in the j-th pair of detectors are respectively (x) j1 ,y j1 ,z j1 ) And (x) j2 ,y j2 ,z j2 ) Where j1 represents one detector of the j-th pair of detectors and j2 is the other detector, then the k-th random coordinate of the i-th leak point is compared with the calculated time difference between the two detectors in the j-th pair of detectors:
wherein v is the average velocity of the seismic wave propagating on the shallow earth surface;
acquisition ofObtaining corresponding +.A variance sum of the difference variance between the calculated time differences and the corresponding time differences between the kth random coordinates of the ith leak point and the two detectors in all detector pairs>I.e. < ->
To satisfy the followingOrdering the sum of variances of the smallest sum of variances to +.>Let->Corresponding random coordinates>Step 7 is entered for calculating coordinates of the ith leak point, where a is a given thresholdThe value, namely, the corresponding variance sum is calculated for all the generated 5 random coordinates, and then the 5 random coordinates are ranked, wherein the ranking is carried out when a plurality of random coordinates smaller than a given threshold value are met, the random coordinates corresponding to the minimum variance sum are taken as the calculated coordinates, then the step 7 is carried out, and if the number is only one, the ranking is not needed, and the direct output is carried out; if there is no->Step 5 is carried out, namely, all random coordinates are not satisfied, and step 5 is carried out;
step 5, selecting the coordinates of the h ith leakage points randomly generated in the step 4 by adopting a roulette selection method, whereinThe smaller random coordinates have larger probability of being selected, and h new random coordinates corresponding to the ith leakage point are selected;
step 6, performing crossing and mutation operation on h new random coordinates corresponding to the ith leakage point, wherein the crossing probability is B, in the embodiment, B=0.9, and the mutation probability is C, in the embodiment, C=0.01, so as to obtain h brand new random coordinates corresponding to the ith leakage point, and carrying out the next iteration in the step 4; the crossover is to exchange some values of any two coordinates, and the mutation is to change the number of a certain coordinate value into other numbers so as to generate new coordinate data;
and 7, outputting the calculated coordinates of the ith leakage point.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (2)
1. The three-dimensional positioning method for the leakage point of the underground pipeline based on the genetic algorithm is characterized by comprising the following steps of:
step 1, horizontally arranging n detectors with detection directions vertically downward on the ground surface, wherein n is more than or equal to 3;
step 2, establishing a three-dimensional coordinate system, obtaining the three-dimensional coordinate of each wave detector, and enabling each wave detector to receive a vibration signal;
step 3, pairing any one of the detectors with all other detectors to form the same detector, reserving only one pair to obtain n (n-1)/pair of detectors in total, numbering 1, 2 and 3......... N (n-1)/2 for each pair of detectors, performing cross-correlation processing on two groups of vibration signals received by the two detectors in each pair of detectors to obtain the pulse number generated between the two groups of vibration signals in each pair of detectors and the reaching time of each pulse, wherein the pulse number generated by the same leakage point in any pair of detectors is the same, so that the obtained pulse number is the number m of the leakage points, and numbering 1, 2 and 3 ji ；
Step 4, randomly generating the coordinates of the ith leakage point, numbering the coordinates of the ith leakage point by 1, 2 and 3Calculated time difference between two detectors in all detector pairs in the n (n-1)/2 pairs in sequence +.>The coordinates of two detectors in the j-th pair of detectors are respectively (x) j1 ,y j1 ,z j1 ) And (x) j2 ,y j2 ,z j2 ) Where j1 represents one detector of the j-th pair of detectors and j2 is the other detector, then the k-th random coordinate of the i-th leak point is compared with the calculated time difference between the two detectors in the j-th pair of detectors:
wherein v is the average velocity of the seismic wave propagating on the shallow earth surface;
acquisition of Obtaining corresponding +.A variance sum of the difference variance between the calculated time differences and the corresponding time differences between the kth random coordinates of the ith leak point and the two detectors in all detector pairs>For meeting->Ordering the sum of variances of the smallest sum of variances to +.>Let->Corresponding random coordinatesCalculating coordinates for an ith leakage point, and entering a step 7, wherein a is a given threshold value; if there is no->Step 5 is performed;
step 5, selecting the coordinates of the h ith leakage points randomly generated in the step 4 by adopting a roulette selection method, whereinThe smaller random coordinates have larger probability of being selected, and h new random coordinates corresponding to the ith leakage point are selected;
step 6, performing crossing and mutation operation on h new random coordinates corresponding to the ith leakage point, wherein the crossing probability is B, and the mutation probability is C, so that h new random coordinates corresponding to the ith leakage point are obtained, and the h new random coordinates are brought into the step 4 for the next iteration;
and 7, outputting the calculated coordinates of the ith leakage point.
2. A method according to claim 1, characterized in that b=0.9 and c=0.01.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5333501A (en) * | 1989-09-19 | 1994-08-02 | Tokyo Gas Co., Ltd. | Abnormality monitoring apparatus for a pipeline |
| JP2000055771A (en) * | 1998-08-07 | 2000-02-25 | Babcock Hitachi Kk | Leaked position detection device |
| JP2010025715A (en) * | 2008-07-18 | 2010-02-04 | Nippon Oil Corp | Pipe crack diagnosing apparatus and pipe crack diagnosing method |
| JP2012002697A (en) * | 2010-06-17 | 2012-01-05 | Tokyo Gas Co Ltd | Acoustic leak position detection device |
| CN107436969A (en) * | 2017-07-03 | 2017-12-05 | 四川大学 | A kind of three-dimensional multi-target orientation method based on genetic algorithm |
| CN108333623A (en) * | 2018-01-29 | 2018-07-27 | 中国科学院声学研究所 | A kind of buried pipeline detection device and method based on sound wave reflection |
| CN110617404A (en) * | 2019-09-09 | 2019-12-27 | 安徽理工大学 | Gas pipeline leakage point positioning method based on sound wave frequency shift inversion |
| CN112179566A (en) * | 2019-07-03 | 2021-01-05 | 中国石油化工股份有限公司 | Gun array seismic source air leakage early warning method and system for marine streamer acquisition |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB2475014B8 (en) * | 2008-08-15 | 2013-08-14 | Adelaide Res & Innovation Pty | Method and system for assessment of pipeline condition |
| WO2017188074A1 (en) * | 2016-04-28 | 2017-11-02 | 日本電気株式会社 | Leakage site analyzing system, leakage site analyzing method, leakage site analyzing device, and computer-readable recording medium |
| US10309861B2 (en) * | 2017-02-27 | 2019-06-04 | Pro-Fin Engineering Inc. | Intelligent pipeline small leaks and thefts detection methods and systems |
| US11099290B2 (en) * | 2019-06-12 | 2021-08-24 | Emerson Paradigm Holding Llc | Attenuating surface waves in common shot gathers of seismic data collected by a set of geophones |
-
2021
- 2021-11-05 CN CN202111306810.6A patent/CN114018500B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5333501A (en) * | 1989-09-19 | 1994-08-02 | Tokyo Gas Co., Ltd. | Abnormality monitoring apparatus for a pipeline |
| JP2000055771A (en) * | 1998-08-07 | 2000-02-25 | Babcock Hitachi Kk | Leaked position detection device |
| JP2010025715A (en) * | 2008-07-18 | 2010-02-04 | Nippon Oil Corp | Pipe crack diagnosing apparatus and pipe crack diagnosing method |
| JP2012002697A (en) * | 2010-06-17 | 2012-01-05 | Tokyo Gas Co Ltd | Acoustic leak position detection device |
| CN107436969A (en) * | 2017-07-03 | 2017-12-05 | 四川大学 | A kind of three-dimensional multi-target orientation method based on genetic algorithm |
| CN108333623A (en) * | 2018-01-29 | 2018-07-27 | 中国科学院声学研究所 | A kind of buried pipeline detection device and method based on sound wave reflection |
| CN112179566A (en) * | 2019-07-03 | 2021-01-05 | 中国石油化工股份有限公司 | Gun array seismic source air leakage early warning method and system for marine streamer acquisition |
| CN110617404A (en) * | 2019-09-09 | 2019-12-27 | 安徽理工大学 | Gas pipeline leakage point positioning method based on sound wave frequency shift inversion |
Non-Patent Citations (2)
| Title |
|---|
| Modeling and locating underground water pipe leak with microseismic data;Jing Wang 等;Journal of Applied Geophysics;第136卷;第1-8页 * |
| 埋地压力输水管道渗漏噪声监测试验;陈春浩 等;水利水电技术;第47卷(第10期);第88-90页 * |
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