CN111022937B - Water pipe network leakage positioning system and positioning method - Google Patents
Water pipe network leakage positioning system and positioning method Download PDFInfo
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Abstract
A water pipe network management leakage positioning system and a positioning method comprise an initialization setting unit, a calculation module based on a hydraulic model, a comparison and judgment module, a multiplication iteration module and a circulation module. The initialization setting unit is used for setting any number of suspicious leakage points and setting iteration multiplication times or a fitness precision range. And the calculation module based on the hydraulic model is used for calculating and obtaining the adaptability value of the pipe network pressure and flow value of the suspected leakage point based on the hydraulic model simulation and the actually measured pipe network pressure and flow value nearest to the point. And the comparison and judgment module is used for comparing the fitness value with the fitness precision and judging whether the value is in the fitness precision range. And the breeding iteration module selects and crosses the suspicious leakage points, and finally performs variation to multiply propagate and iterate to generate a plurality of next-generation suspicious leakage points. And the circulation module executes the calculation module based on the hydraulic model and the comparison and judgment module aiming at a plurality of next generation suspicious leakage points.
Description
Technical Field
The invention belongs to the technical field of design of a water delivery pipe network, and particularly relates to a water delivery pipe network leakage positioning system and a positioning method.
Background
At present, most water supply enterprises have old equipment, the technical level is slowly improved, and a management system has a plurality of problems, so that the leakage rate of urban pipe networks in China does not reach 8 percent of targets specified in the 2000-year water supply industry planning target. The leakage control and evaluation of urban water supply pipe network CJJ 92-2002 standard which is currently executed in China is not more than 12%, and has a great gap from the advanced level of international developed countries. The leakage rate of most cities in China is about 20%, wherein about 70% of the urban leakage rate is caused by water leakage of pipelines. The annual water leakage of Chinese water business enterprises is about 102 hundred million tons, the annual domestic drinking water of 1.5 million urban population, if calculate with water price of 2 yuan per ton of water sold, the economic loss of the water leakage is up to more than 200 million yuan per year.
The leakage monitoring system based on DMA (partition metering) developed by most enterprises in the market can monitor the flow change and directly reflect the leakage amount, but cannot accurately position the leakage point, thereby bringing great trouble to the maintenance of water supply enterprises.
Disclosure of Invention
In view of the above, the present invention provides a system and a method for positioning the leakage of a water pipe network management, which can accurately position the leakage point on the water pipe network, so as to solve the above problems.
A water pipe network pipe leakage positioning system is characterized in that n sensors are arranged on a water pipe network to monitor the hydraulic conditions of the positions where the sensors are arranged. The water pipe network management leakage positioning system comprises an initialization setting unit, wherein the initialization setting unit is used for setting any number of suspicious leakage points in a simulation mode on the water pipe network and setting iteration multiplication times or a fitness precision range C, and any suspicious leakage point comprises a leakage node value and a leakage coefficient. And the calculation module based on the hydraulic model is used for substituting the leakage node value and the leakage coefficient of any suspicious leakage point into the hydraulic model for calculation so as to calculate and obtain the adaptability values of the pipe network pressure and the flow value of the suspicious leakage point based on the hydraulic model simulation and the actual pipe network pressure and flow value nearest to the point. The fitness value calculation uses the formula:
wherein: (x) is a fitness value;
x is the vector value of any suspected leakage point, i.e. X is [ leakage point location, leakage coefficient ];
n is the number of sensors;
m＝(p1,p2,p3,…pn) Is the measured value of the pressure;
A comparison and judgment module, configured to compare the value f (x) with the fitness precision range C and judge whether the value f (x) is within the fitness precision range C; and
a reproduction iteration module, which selects and crosses the suspected leakage points through a genetic algorithm when the value of f (x) is not in the fitness precision range C, and finally performs variation to generate a plurality of next generation suspected leakage points through reproduction iterations;
a cycle module, configured to execute the hydraulic model-based calculation module and the comparison and judgment module for a plurality of next-generation suspected leakage points when the value of f (x) is not within the fitness precision range C to obtain suspected leakage points within the fitness precision range C.
Furthermore, the leakage amount of any one leakage point is obtained by substituting a leakage coefficient into a leakage flow power law equation, wherein the leakage flow power law equation is as follows:
wherein Q is leakage flow;
ceis the pipe network leakage loss index;
eethe leakage injection index of the pipe network is obtained;
p is the calculated pressure at the node where the leak occurred.
Further, the hydraulic model is built based on epanet.
Further, when the fitness value f (x) is within the fitness precision range C, the suspected leakage point is the real leakage point.
Further, when the number of multiplication iterations is greater than the number of iteration multiplication set by the initialization setting unit, the water pipe network has no real leakage point.
Further, when the number of iterations of multiplication is less than or equal to the number of iterations of multiplication set by the initialization setting unit, and the fitness value f (x) corresponding to the suspected leakage point is within the fitness precision range C, the suspected leakage point is the real leakage point.
Further, the sensor is used for monitoring the pipe network pressure and flow value of the position where the sensor is located.
A method for positioning leakage of a water pipe network management is characterized in that n sensors are arranged on the water pipe network to monitor the hydraulic condition of the positions where the sensors are arranged, and the method comprises the following steps:
providing an initialization setting unit, wherein the initialization setting unit is used for setting any number of suspicious leakage points in a simulation mode on a water delivery pipe network and setting iteration reproduction times or a fitness precision range C, and any suspicious leakage point comprises a leakage node value and a leakage coefficient;
and providing a calculation module based on a hydraulic model, wherein the calculation module based on the hydraulic model is used for substituting the leakage node value and the leakage coefficient of any suspicious leakage point into the hydraulic model for calculation so as to calculate and obtain the adaptability values of the pipe network pressure and the flow value of the suspicious leakage point simulated based on the hydraulic model and the actually measured pipe network pressure and flow value nearest to the suspicious leakage point. The fitness value calculation uses the formula:
wherein: (x) is a fitness value;
x is the vector value of any suspected leakage point, i.e. X is [ leakage point location, leakage coefficient ];
n is the number of sensors;
m＝(p1,p2,p3,…pn) Is the measured value of the pressure;
providing a comparison and judgment module, wherein the comparison and judgment module is used for comparing the value of f (x) with the fitness precision range C and judging whether the value of f (x) is within the fitness precision range C;
providing a reproduction iteration module, wherein when the value of f (x) is not in the fitness precision range C, the reproduction iteration module selects and crosses the suspected leakage points through a genetic algorithm, and finally performs variation to reproduce iterations for multiple times to generate a plurality of next generation suspected leakage points; and
and providing a circulation module for executing the calculation module based on the hydraulic model and the comparison judgment module for a plurality of next generation suspicious leakage points when the value of f (x) is not in the fitness precision range C so as to obtain the suspicious leakage points in the fitness precision range C.
Further, when the fitness value f (x) is within the fitness precision range C, the suspected leakage point is the real leakage point.
Compared with the prior art, the method can accurately position the leakage point by utilizing the hydraulic model and the genetic algorithm, thereby being beneficial to a maintainer to arrive at the leakage point to maintain the water delivery pipe network as soon as possible.
Drawings
Fig. 1 is a prior art water supply network topology diagram.
Fig. 2 is a schematic structural principle diagram of a water pipe network management leakage positioning system provided by the invention.
Fig. 3 is a flowchart of the water pipe network pipe leakage positioning system of fig. 2.
Detailed Description
Specific examples of the present invention will be described in further detail below. It should be understood that the description herein of embodiments of the invention is not intended to limit the scope of the invention.
As shown in fig. 1 to fig. 3, which are schematic diagrams of the water pipe network leakage positioning system provided by the present invention. The water pipe network pipe leakage positioning system is used for positioning leakage points in the water pipe network. As is well known, a water transportation network typically includes a plurality of hydrant nodes 11, at least one water supply source node 12, and a plurality of pipes 13 connecting the plurality of hydrant nodes 11 and the water supply source node 12. As shown in fig. 1, each circle represents a fire hydrant node 11, i.e. a fire hydrant is needed to be installed therein according to actual needs. In the water supply network, the fire hydrant is provided with its inherent requirements, such as that the outdoor fire-fighting water supply pipe network is arranged into a ring pipe network, the minimum diameter of the fire-fighting water supply pipe of the outdoor fire hydrant is not less than 100mm, the number of water delivery pipes delivering water to the ring pipe network is not less than one, and the number of fire hydrants on the pipe between two valves is not more than 10, etc. Also, therefore, the number of pipes 13 is greater than the number of hydrant nodes 11. For this reason, it is highly representative to provide sensors at the hydrant for measuring actual hydraulic conditions, such as pipe network pressure and flow values, etc. The positioning principle of the invention is that a plurality of virtual leakage points are arbitrarily arranged on the water pipe network, the values of the virtual leakage points are close to the real values returned by the nearest sensors through calculation, and the real positions of the virtual leakage points can be known because the positions of the arranged sensors are known, so that the positions of the leakage points are positioned.
The water pipe network management leakage positioning system comprises an initialization setting unit 20, a calculation module 21 based on a hydraulic model, a comparison judgment module 22, a multiplication iteration module 23 based on a genetic algorithm, and a circulation module 24.
The initialization setting unit 20 is configured to initialize the number of any suspicious leakage points set in simulation on the water pipe network, and set the number of iterative multiplication times B and the accuracy range C of the fitness. Any one of the suspected leakage points includes a leakage node value and a leakage coefficient. The leakage node value is a number representing a pipeline connection point in the pipe network hydraulic model, is used for representing a tee joint, a turning point, a fire hydrant, a valve and water flow, and is used for finding the connection point through the leakage node value and setting a leakage coefficient of the point in the pipe network hydraulic model. The leakage coefficient is used to calculate the amount of leakage at that location. The leakage amount of any one leakage point can be obtained by substituting a leakage coefficient into a leakage flow power law equation, wherein the leakage flow power law equation is as follows:
wherein Q is leakage flow;
ceis the pipe network leakage loss coefficient;
eethe leakage injection index of the pipe network is obtained;
p is the pipe network pressure at the node where the leak occurs.
When the calculation is carried out for the first time, the leakage coefficient c of the pipe networkeIs randomly set by the initialization setting unit 20. If calculated by the hydraulic model-based calculation module 21, c iseThe fitness of the corresponding leakage point falls into the set fitness precision range C, and then the step C is carried outeThe value of (d) is the random value. If the fitness of the leakage point does not fall within the set fitness precision range C, the calculation according to the genetic algorithm should be performed by the multiplication iteration module 23, at this time, C is describedeIs calculated by the spawn iteration module 23.
eeRefers to a pressure index, which is usually 0.5 by default, and can be set according to actual conditions.
And P is obtained by substituting the value measured by the sensor into a hydraulic model, namely the value is calculated by an epanet pipe network hydraulic model engine. The hydraulic model will be described in detail below.
The calculation module 21 based on the hydraulic model is configured to substitute the leakage node value and the leakage coefficient of any suspected leakage point into the hydraulic model to calculate, so as to calculate an adaptation value between a pipe network pressure and a flow value of the suspected leakage point based on the hydraulic model simulation and an actually measured pipe network pressure and flow value nearest to the point. The fitness value calculation uses the formula:
wherein: (x) is a fitness value;
x is a vector value of any suspected leakage point, that is, X ═ leakage point location, leakage coefficient ], which is initially set by the initialization setting unit 20.
n is the number of sensors;
m＝(p1,p2,p3,…pn) The pressure measured value can be calculated by substituting the measured value measured by the sensor into a hydraulic model;
It should be noted that the hydraulic model is a prior art, and the hydraulic model used in the present embodiment is based on EPANET, which is open source water supply pipe network simulation software EPANET2.0 developed and released by the u.s.environmental protection agency. The method can input various actual parameters obtained by actual measurement, establish a hydraulic model through the software, export the hydraulic model, use the hydraulic model file as input, and call an EPANET hydraulic calculation engine library through a program to obtain all node pressures and pipeline flow values of the pipe network model. The basic structure of the hydraulic model EPANET pipe network hydraulic model comprises two parts, namely the physical structure of the hydraulic model and the input parameters of the hydraulic model. For the physical constitution of the hydraulic model, nodes, pipe sections, at least one reservoir or pool and the like are required, but parameters such as water quality part, water pump energy consumption, pipe network construction cost and the like are not considered. For the input parameters of the hydraulic model, it is usually a multidimensional quantity. For example, the node comprises parameters such as coordinate values, elevation, basic water demand and the like. For a pipe section, the parameters include a start node, a stop node, a length, a diameter, a roughness coefficient and the like. The foregoing description is intended to be prior art and is well known to those skilled in the art. The EPANET hydraulic model can be used for providing complete and accurate hydraulic simulation capability, and the complete and accurate hydraulic simulation is a prerequisite for effective water quality simulation. The EPANET hydraulic model utilizes Hazen-Williams, Darcy-Weisbach or Chezy-Manning formulas to calculate the friction head loss, comprises the calculation of local head loss at elbows, accessories and the like, can simulate constant-speed and variable-speed water pumps, can analyze the lifting energy and cost of the water pumps and simulate various valves including a shielding valve, a check valve, a pressure regulating valve and a flow control valve. For a specific use method of the EPANET hydraulic model, a patent number 201711092872.5, named as a method for constructing a water supply network management and hydraulic model by an open source GIS and a database, discloses a related scheme. In addition, the water supply network modeling software based on EPANET and AreEngine, which is disclosed on page 35 of "computer engineering and applications" period 45(6) "in 2009, also discloses a use method thereof, and is not described herein again.
The fitness value f (x) of the leakage point can be calculated by calculation based on the EPANET hydraulic model and a pipe network simulation software EPANET 2.0. It is of course conceivable that the fitness value f (x) is not a value, but a fitness value f (x) corresponding to an arbitrary number of leakage points.
The comparison and judgment module 22 is configured to compare the value of the fitness value f (x) with the fitness precision range C and judge whether the value of f (x) is within the fitness precision range C. When the value of the fitness value f (x) is within the fitness precision range C, the leakage point corresponding to the fitness value f (x) can be estimated as the best individual, that is, the leakage point corresponding to the fitness value f (x) is the real leakage point. And when the value of the fitness value f (x) is not within the fitness precision range C, it indicates that the leakage point corresponding to the fitness value f (x) is not a real leakage point, and the calculation needs to be performed again. However, it is usually impossible to simulate by assuming another set of virtual leakage points through the initialization setting unit 20, so the success rate is too low, and a large amount of calculation time is required, which may cause a large amount of leakage. Since the water transportation pipe network is longer and longer as the city is bigger and bigger, the length of the water transportation pipe network generally reaches thousands of kilometers, which obviously makes it impossible to assume some leakage points each time, and then calculate through a hydraulic model to find out whether the leakage points are the leakage points. Because of the many points of leakage, the calculation takes a lot of time, and the amount of leakage water is undoubtedly large in the lot of time. Therefore, the non-real leakage point needs to be further processed to obtain a further approximation of the real leakage point on the basis of the non-real leakage point.
And the breeding iteration module 23 selects, crosses and finally performs variation on the suspected leakage points through a genetic algorithm when the value of f (x) is not within the fitness precision range C so as to multiply and generate a plurality of next generation suspected leakage points. The genetic algorithm itself should be a prior art, which is a computational model of the biological evolution process simulating natural selection and genetic mechanism of darwinian biological evolution theory, and is a method for searching an optimal solution by simulating the natural evolution process. By using the biological evolution theory for reference, the problem to be solved by the genetic algorithm is simulated into a biological evolution process, the next generation solution is generated through operations such as copying, crossing, mutation and the like, the solution with low fitness function value is gradually eliminated, and the solution with high fitness function value is increased. Therefore, the evolution of N generations can be used for further developing individuals with high fitness function values. The specific algorithm steps of the genetic algorithm may include steps such as encoding; randomly generating a population; selecting parents according to the fitness; crossing parent chromosomes according to a certain method to generate offspring; and (5) carrying out mutation on the offspring chromosome. In the encoding step, the solved leakage node and leakage coefficient are encoded into a symbol string, which is represented by unsigned binary integers. For example, the leakage nodes and the leakage amount are respectively expressed as integers between 0 and 7, so that the leakage nodes and the leakage amount are respectively expressed by 3-bit unsigned binary integers, and the 6-bit unsigned binary numbers formed by connecting the leakage nodes and the leakage amount together form the genotype of an individual to express a feasible solution. For example, a phenotype corresponding to genotype X101110 is: x ═ 5, 6], where 5 can be denoted as the leakage node id and 6 can be denoted as the leakage coefficient. The individual's phenotype X and genotype X are interconverted by coding and decoding programs. The encoded amounts are then subjected to random population generation, e.g. the size of the population is taken to be 4, i.e. the population consists of 4 individuals, each of which can be generated by a random method. Such as: 011101, 101011, 011100, 111001. And then calculating through the hydraulic model to obtain a leakage point with the fitness value f (x) out of the fitness precision range C, forming a parent, finally performing intersection according to a genetic algorithm to generate offspring, and performing variation on the offspring chromosomes to form the leakage point of the next generation.
The loop module 24 is configured to execute the hydraulic model-based calculation module 21 and the comparison and judgment module 22 for the plurality of next-generation suspected leakage points calculated by the spawning iteration module 23 to obtain suspected leakage points located in the fitness precision range C when the value of f (x) is not in the fitness precision range C. It is of course conceivable that when the number of iterations completed by the iteration multiplying module 23, that is, the number of iterations multiplying is greater than the number B of iterations multiplying set by the initialization setting unit 20, or when no suspected leakage point located within the fitness precision range C is found, it may be considered that there is no real leakage point in the suspected leakage points, that is, there is no leakage in the water transportation network.
The invention also provides a positioning method, which comprises the following steps:
s101: providing the initialization setting unit 20, where the initialization setting unit 20 is configured to set any number of suspicious leakage points in a simulation manner on the water delivery pipe network, and set iteration and multiplication times or a fitness precision range C, where any suspicious leakage point includes a leakage node value and a leakage coefficient;
s102: and providing the calculation module 21 based on the hydraulic model, wherein the calculation module 21 based on the hydraulic model is used for substituting the leakage node value and the leakage coefficient of any suspicious leakage point into the hydraulic model for calculation so as to calculate and obtain the adaptation value of the pipe network pressure and flow value of the suspicious leakage point simulated based on the hydraulic model and the actual pipe network pressure and flow value nearest to the suspicious leakage point. The fitness value calculation uses the formula:
wherein: (x) is a fitness value;
x is the vector value of any suspected leakage point, i.e. X is [ leakage point location, leakage coefficient ];
n is the number of sensors;
m＝(p1,p2,p3,…pn) Is the measured value of the pressure;
s103: providing a comparison and judgment module 22, wherein the comparison and judgment module 22 is configured to compare the value f (x) with the fitness precision range C and judge whether the value f (x) is within the fitness precision range C;
s104: providing a breeding iteration module 23, wherein the breeding iteration module 23 selects, crosses and finally performs variation on the suspected leakage points through a genetic algorithm when the value of f (x) is not within the fitness precision range C to generate a plurality of next generation suspected leakage points through breeding iterations for a plurality of times; and
s105: a loop module 24 is provided, and the loop module 24 is configured to execute the hydraulic model-based calculation module 21 and the comparison and judgment module 22 for a plurality of next generation suspected leakage points when the value of f (x) is not within the fitness precision range C to obtain suspected leakage points within the fitness precision range C.
In step S103: when the fitness value f (x) is within the fitness precision range C, the suspicious leakage point is the real leakage point.
Compared with the prior art, the method can accurately position the leakage point by utilizing the hydraulic model and the genetic algorithm, thereby being beneficial to a maintainer to arrive at the leakage point to maintain the water delivery pipe network as soon as possible.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the scope of the present invention, and any modifications, equivalents or improvements that are within the spirit of the present invention are intended to be covered by the following claims.
Claims (9)
1. The utility model provides a raceway pipe network management leakage positioning system, be provided with n sensor on the raceway pipe network in order to monitor the water conservancy situation of sensor setting position, its characterized in that: the utility model discloses a raceway network management leakage positioning system, including the initial setting unit, the initial setting unit is used for simulating on the raceway network and sets up arbitrary number of suspicious leakage point to and set up iteration number of multiplying or adaptability precision range C, arbitrary suspicious leakage point is including leakage node value and leakage coefficient, a calculation module based on hydraulic model, calculation module based on hydraulic model is used for calculating the leakage node value and the leakage coefficient substitution hydraulic model of arbitrary suspicious leakage point, calculates the adaptation value of this suspicious leakage point based on the pipe network pressure and the flow value of hydraulic model simulation and the actual measurement pipe network pressure and the flow value of this point nearest, the formula that the adaptation value calculation used:
wherein: (x) is a fitness value;
x is the vector value of any suspected leakage point, i.e. X is [ leakage point location, leakage coefficient ];
n is the number of sensors;
m＝(p1,p2,p3,…pn) Is the measured value of the pressure;
a comparison and judgment module, configured to compare the value f (x) with the fitness precision range C and judge whether the value f (x) is within the fitness precision range C; and
a reproduction iteration module, which selects and crosses the suspected leakage points through a genetic algorithm when the value of f (x) is not in the fitness precision range C, and finally performs variation to generate a plurality of next generation suspected leakage points through reproduction iterations;
a cycle module, configured to execute the hydraulic model-based calculation module and the comparison and judgment module for a plurality of next-generation suspected leakage points when the value of f (x) is not within the fitness precision range C to obtain suspected leakage points within the fitness precision range C.
2. The water pipe network management leakage positioning system of claim 1, wherein: the leakage quantity of any one leakage point is obtained by substituting a leakage coefficient into a leakage flow power law equation, wherein the leakage flow power law equation is as follows:
wherein Q is leakage flow;
ceis the pipe network leakage loss index;
eethe leakage injection index of the pipe network is obtained;
p is the calculated pressure at the node where the leak occurred.
3. The water pipe network management leakage positioning system of claim 1, wherein: the hydraulic model is built based on epanet.
4. The water pipe network management leakage positioning system of claim 1, wherein: when the fitness value f (x) is within the fitness precision range C, the suspicious leakage point is the real leakage point.
5. The water pipe network management leakage positioning system of claim 1, wherein: when the number of reproduction iterations is larger than the number of iteration reproduction set by the initialization setting unit, the water delivery pipe network has no real leakage point.
6. The water pipe network management leakage positioning system of claim 1, wherein: when the number of iterations of multiplication is less than or equal to the number of iterations of multiplication set by the initialization setting unit, and the fitness value f (x) corresponding to the suspected leakage point is within the fitness precision range C, the suspected leakage point is the real leakage point.
7. The water pipe network management leakage positioning system of claim 1, wherein: the sensor is used for monitoring the pipe network pressure and flow value of the position where the sensor is located.
8. A method for positioning leakage of a water pipe network management is characterized in that n sensors are arranged on the water pipe network to monitor the hydraulic condition of the positions where the sensors are arranged, and the method comprises the following steps:
providing an initialization setting unit, wherein the initialization setting unit is used for setting any number of suspicious leakage points in a simulation mode on a water delivery pipe network and setting iteration reproduction times or a fitness precision range C, and any suspicious leakage point comprises a leakage node value and a leakage coefficient;
providing a calculation module based on a hydraulic model, wherein the calculation module based on the hydraulic model is used for substituting a leakage node value and a leakage coefficient of any suspicious leakage point into the hydraulic model for calculation so as to calculate the fitness value of the suspicious leakage point based on the pipe network pressure and flow value simulated by the hydraulic model and the actual pipe network pressure and flow value nearest to the suspicious leakage point, and the fitness value is calculated by using the formula:
wherein: (x) is a fitness value;
x is the vector value of any suspected leakage point, i.e. X is [ leakage point location, leakage coefficient ];
n is the number of sensors;
m＝(p1,p2,p3,…pn) Is the measured value of the pressure;
providing a comparison and judgment module, wherein the comparison and judgment module is used for comparing the value of f (x) with the fitness precision range C and judging whether the value of f (x) is within the fitness precision range C;
providing a reproduction iteration module, wherein when the value of f (x) is not in the fitness precision range C, the reproduction iteration module selects and crosses the suspected leakage points through a genetic algorithm, and finally performs variation to reproduce iterations for multiple times to generate a plurality of next generation suspected leakage points; and
and providing a circulation module for executing the calculation module based on the hydraulic model and the comparison judgment module for a plurality of next generation suspicious leakage points when the value of f (x) is not in the fitness precision range C so as to obtain the suspicious leakage points in the fitness precision range C.
9. The water pipe network pipe leakage positioning method according to claim 8, characterized in that: when the fitness value f (x) is within the fitness precision range C, the suspicious leakage point is the real leakage point.
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| CN104930355A (en) * | 2015-06-09 | 2015-09-23 | 段焕丰 | Online nondestructive detection method and device applicable to urban water supply pipeline system |
| CN105546361A (en) * | 2016-03-08 | 2016-05-04 | 钱昊铖 | Acoustic-wave-method gas pipeline leakage monitoring method based on ANN (Artificial Neural Network) |
| CN108665068A (en) * | 2017-03-27 | 2018-10-16 | 中国科学院沈阳计算技术研究所有限公司 | The improved adaptive GA-IAGA of water distribution hydraulic model automatic Check problem |
| CN107355688A (en) * | 2017-07-14 | 2017-11-17 | 水联网技术服务中心（北京）有限公司 | A kind of LeakView urban water supplies pipe network model Control management system |
| CN108591836A (en) * | 2018-04-13 | 2018-09-28 | 中国石油大学(北京) | The detection method and device of pipe leakage |
| CN110108328A (en) * | 2019-04-03 | 2019-08-09 | 同济大学 | A kind of acquisition methods of water supply network leakage loss region water leakage |
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