Water network pipeline leakage positioning method and system

Abstract

The invention provides a water network pipeline leakage positioning method and system. The method comprises the steps that pressure data and flow data of a water network pipeline are collected; performing data analysis on the pressure data and the flow data, and judging whether the detected pipeline leaks or not; under the condition that the detected pipe leaks, dispersing a pipeline system in a pre-constructed leakage pipeline mathematical model, determining a calculation area, and selecting a pressure detection point position of a water network pipeline; calculating the obtained pressure values of each pressure detection point under different leakage conditions of the pipeline; performing sensitivity analysis on each node of the main pipeline and the branch pipelines of the water network by adopting a correlation function method, and comparing correlation coefficients of each node; determining the position of the pipeline leakage point based on the correlation coefficient; the synchronism and correlation of pressure change of each node of the pipeline are fully considered, noise and interference information are effectively filtered out, and leakage detection is more accurate and reliable.

Description

Technical Field

[0001] The present invention relates to the technical field of water network pipeline leakage locating, and in particular to a water network pipeline leakage locating method and system. Background Art

[0002] Thermal power plant boilers heat water into steam to drive steam turbines for power generation, requiring a continuous water supply. The steam after work still has a relatively high temperature and needs to be cooled through a cooling system to condense into water for recycling. In addition, thermal power plant generators, transformers and other equipment generate heat during operation, requiring water cooling to ensure normal operation and extend their service life. Thermal power plants usually draw water from water sources through water network pipes. Leakage in water network pipes is a major factor in water loss in thermal power plants. Once a leak occurs, it not only wastes water resources but also causes increased power consumption. In severe cases, it will cause non-stop accidents. In related technologies, the statistical probability of leakage is continuously calculated based on the fluid pressure and flow measured at the inlet and outlet of the pipe. Once the leak is confirmed, the leakage amount can be estimated by measuring the flow and pressure and their statistical average value, and the leak is located using the least squares method. However, there is a problem of low positioning accuracy for detecting water network pipe leaks. Summary of the Invention

[0003] In response to the above-mentioned problems, the present invention proposes a water network pipeline leakage positioning method and system, which solves the technical problem of low positioning accuracy in detecting water network pipeline leakage in the existing technology. It fully considers the synchronization and correlation of pressure changes at each node of the pipeline, effectively filters out noise and interference information, and makes leakage detection more accurate and reliable.

[0004] An embodiment of the present invention provides a method for locating a water network pipeline leak, comprising:

[0005] Collect pressure and flow data of water network pipelines;

[0006] Perform data analysis on pressure data and flow rate data to determine whether the pipeline under inspection has leaked;

[0007] In the event of a leak in the pipe being tested, the pipeline system in the pre-built mathematical model of the leaking pipeline is discretized to determine the calculation area and select the pressure detection point location of the water network pipeline;

[0008] The calculated pressure values of each pressure detection point under different pipeline leakage conditions;

[0009] The correlation function method is used to conduct sensitivity analysis on each node of the main pipeline and branch pipeline of the water network and compare the correlation coefficients of each node;

[0010] Based on the correlation coefficient, the location of the pipeline leak point is determined.

[0011] In some embodiments, analyzing the pressure data and the flow data to determine whether a leak occurs in the pipeline being inspected includes:

[0012] Calculate the mean and variance of pressure data and flow data;

[0013] The calculated mean and variance are compared with a preset threshold value. If the threshold value is exceeded, it is determined that the pipeline being tested has a leak.

[0014] In some embodiments, when a leak occurs in the pipe being tested, the pipeline system in the pre-built mathematical model of the leaking pipeline is discretized, a calculation area is determined, and the location of the pressure detection point of the water network pipeline is selected, including:

[0015] Determine the boundary conditions of the piping system, including the starting point, end point, branch point, and known pressure and flow conditions of the pipeline;

[0016] Dividing the pipeline system into a plurality of discrete computational units, wherein each computational unit has the same length;

[0017] Determine the calculation area, including the starting point, end point and key node positions of the pipeline;

[0018] A pressure detection point is selected at the node of each computing unit. The position of the pressure detection point is:

[0019] x j =x0+j·Δx;

[0020] Where x j represents the position of the jth pressure detection point, x0 represents the starting position of the pipeline, and Δx is the length of the calculation unit.

[0021] In some embodiments, the pre-built mathematical model of the leaky pipeline is:

[0022]

[0023] Where q is the flow rate, t is the time, A is the pipe cross-sectional area, h is the water head height, x is the axial position of the pipe, ρ is the density of water, g is the acceleration due to gravity, f is the friction factor, D is the pipe diameter, and p is the pressure.

[0024] In some embodiments, the calculated pressure values of each pressure detection point under different pipeline leakage conditions include:

[0025] By introducing leakage parameters into the mathematical model of the leaking pipeline, the pressure values under different leakage conditions are calculated;

[0026] For each pressure detection point x j, record the pressure value p under different leakage conditions j (t) Construct the pressure data matrix P, where the dimension of P is M×N, M is the number of pressure detection points, and N is the length of the time series;

[0027] Normalize the pressure data matrix P;

[0028] Perform feature extraction on the normalized pressure data and calculate the pressure change rate Δp of each pressure detection point j :

[0029]

[0030] According to the pressure change rate Δp j , determine the leakage occurrence time x l , when Δp j Exceeding the set threshold p th When , it is determined that leakage occurs, and the leakage occurs at:

[0031] x l =min{t||Δp j (t)|>p th}.

[0032] In some embodiments, the use of the correlation function method to perform sensitivity analysis on each node of the water network trunk pipeline and branch pipeline and compare the correlation coefficients of each node includes:

[0033] Get the pressure data sequence p of each node j (t);

[0034] Select a reference point ref and obtain its pressure data sequence p rdf (t), the reference point ref is a known location node close to the suspected leakage area;

[0035] Calculate the correlation coefficient R between each node j and the reference point ref j :

[0036]

[0037] Where T is the time length of the pressure data sequence, are the means of the pressure data series of node j and reference point ref respectively;

[0038] Compare and analyze the correlation coefficients Rj of all nodes j to find the node j with a significantly higher correlation coefficient than other nodes max The node with the strongest correlation as the most likely leak.

[0039] In some embodiments, determining the location of the pipeline leakage point based on the correlation coefficient includes:

[0040]

[0041] Where x jmax is the position of the node with the largest correlation coefficient, and Δx is the distance between adjacent nodes.

[0042] An embodiment of the present invention provides a water network pipeline leakage locating system, comprising:

[0043] Acquisition module, used to collect pressure data and flow data of water network pipelines;

[0044] A judgment module is used to analyze the pressure data and flow rate data to determine whether a leak occurs in the pipeline being tested;

[0045] The selection module is used to discretize the pipeline system in the pre-built leaking pipeline mathematical model, determine the calculation area, and select the pressure detection point position of the water network pipeline when the pipeline under inspection leaks;

[0046] A calculation module, used to calculate the pressure values of each pressure detection point under different pipeline leakage conditions;

[0047] The analysis module is used to conduct sensitivity analysis on each node of the main pipeline and branch pipeline of the water network using the correlation function method and compare the correlation coefficients of each node;

[0048] The determination module is used to determine the location of the pipeline leakage point based on the correlation coefficient.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] By collecting pressure data and flow data of water network pipelines; analyzing the pressure data and flow data to determine whether the pipeline under inspection has leaked; in the case of a leak in the pipe under inspection, the pipeline system in the pre-built mathematical model of the leaking pipeline is discretized to determine the calculation area and the location of the pressure detection points of the water network pipeline; the pressure values of each pressure detection point under different pipeline leakage conditions are calculated; the correlation function method is used to perform sensitivity analysis on each node of the water network main pipeline and branch pipeline and compare the correlation coefficient of each node; based on the correlation coefficient, the location of the pipeline leakage point is determined; the synchronization and correlation of the pressure changes of each node of the pipeline are fully considered, and the noise and interference information are effectively filtered out, making the leakage detection more accurate and reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The embodiments of the present invention are further described below with reference to the accompanying drawings:

[0052] Figure 1A schematic diagram of a water network pipeline leakage locating method according to an embodiment of the present invention;

[0053] Figure 2 A schematic structural diagram of a water network pipeline leakage locating system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0054] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limiting the present invention. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0055] In the following description, reference is made to “some embodiments”, which describes a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0056] If similar descriptions of "first\second\third" appear in the application documents, the following explanation is added. In the following description, the terms "first\second\third" are only used to distinguish similar objects and do not represent a specific order of the objects. It can be understood that "first\second\third" can be interchanged with the specific order or sequence where permitted, so that the embodiments of the present invention described herein can be implemented in an order other than that illustrated or described herein.

[0057] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the present invention pertains. The terms used herein are for the purpose of describing embodiments of the present invention only and are not intended to limit the present invention.

[0058] Based on the problems existing in the related art, an embodiment of the present invention provides a method for locating water network pipeline leaks, and the execution subject of the positioning method can be an electronic device. The electronic device can be various types of terminals such as laptops, tablet computers, desktop computers, set-top boxes, mobile devices (for example, mobile phones, portable music players, personal digital assistants, dedicated messaging devices, portable gaming devices), etc., and can also be implemented as a server. The server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0059] In some embodiments, the functions implemented by the positioning method provided by the embodiments of the present invention may be implemented by a processor of an electronic device calling a program code, wherein the program code may be stored in a computer storage medium.

[0060] The embodiment of the present invention provides a method for locating a water network pipeline leak. Figure 1 A schematic diagram of a water network pipeline leakage location method according to an embodiment of the present invention is provided. Figure 1 Shown, including:

[0061] Step S1: Collecting pressure data and flow data of water network pipelines;

[0062] In the embodiment of the present invention, pressure data and flow data of the water network pipelines are collected in real time during operation by means of pressure sensors and flow sensors installed on the water network pipelines.

[0063] Step S2: performing data analysis on the pressure data and the flow rate data to determine whether a leak occurs in the pipeline being tested;

[0064] In some embodiments, step S2 includes:

[0065] Step S21: Calculate the mean and variance of the pressure data and flow data;

[0066] Step S22: Compare the calculated mean and variance with a preset threshold value. If the calculated mean and variance exceed the threshold value, it is determined that the pipeline being tested has a leak.

[0067] In this embodiment of the present invention, the collected pressure and flow data can be input into a pre-built leak identification model. This model, based on a machine learning algorithm, is trained by applying extensive pressure and flow data, both in the presence and absence of leaks. The model automatically extracts key features from the data, such as mean and variance, and compares them against pre-set thresholds. If the calculated feature value exceeds the threshold, a leak is detected in the pipeline.

[0068] Step S3: When a leak occurs in the pipe being tested, the pipe system in the pre-built mathematical model of the leaking pipe is discretized to determine the calculation area and select the pressure detection point position of the water network pipe;

[0069] In some embodiments, step S3 includes:

[0070] Step S31: Determine the boundary conditions of the pipeline system, including the starting point, end point, branch point, and known pressure and flow conditions of the pipeline;

[0071] Step S32: Divide the pipeline system into a plurality of discrete calculation units, wherein each calculation unit has the same length;

[0072] Step S33: determining the calculation area, including the starting position, the end position and the key node positions in the middle of the pipeline;

[0073] Step S34: Select a pressure detection point at the node of each calculation unit. The position of the pressure detection point is:

[0074] x j =x0+j·Δx;

[0075] Where x j represents the position of the jth pressure detection point, x0 represents the starting position of the pipeline, and Δx is the length of the calculation unit.

[0076] In the embodiments of the present invention, clear boundary conditions are set to provide basic constraints for the mathematical model of the leaking pipeline. These boundary conditions reflect the actual operating conditions of the pipeline system, enabling the mathematical model to more accurately simulate the hydraulic behavior of the actual pipeline. Discretization transforms the continuous pipeline into a series of discrete points, enabling complex partial differential equations to be numerically solved at these discrete points, reducing the complexity of the problem. By properly selecting the number and length of computational units, a balance can be achieved between computational accuracy and computational effort. Defining the computational region provides a clear scope for subsequent numerical calculations, avoiding the problem of ambiguous scopes during the calculation process. By marking key nodes, the hydraulic characteristic changes at these nodes can be focused on in subsequent calculations and analysis, improving the efficiency and accuracy of leak detection. The appropriate location of pressure monitoring points provides an effective data foundation for subsequent leak monitoring. This data is crucial for determining whether a pipeline is leaking and locating the leak point. A reasonable distribution of pressure monitoring points can improve the accuracy of leak location. Evenly distributed monitoring points ensure that hydraulic changes caused by leaks are captured on long, straight pipelines. Monitoring points at key nodes provide important reference information, helping to more accurately determine the location of the leak.

[0077] In some embodiments, the mathematical model of the leaking pipeline is constructed based on the water hammer wave theory, including the continuity equation and the momentum equation. The pre-constructed mathematical model of the leaking pipeline is:

[0078]

[0079] Where q is the flow rate, t is the time, A is the pipe cross-sectional area, h is the water head height, x is the axial position of the pipe, ρ is the density of water, g is the acceleration due to gravity, f is the friction factor, D is the pipe diameter, and p is the pressure.

[0080] Step S4: Calculate the pressure values of each pressure detection point under different pipeline leakage conditions;

[0081] In some embodiments, step S4 includes:

[0082] Step S41: Calculating pressure values under different leakage conditions by introducing leakage parameters into the mathematical model of the leaking pipeline;

[0083] Step S42: For each pressure detection point x j , record the pressure value p under different leakage conditions j (t), construct the pressure data matrix P, where the dimension of P is M×N, M is the number of pressure detection points, and N is the length of the time series;

[0084] Step S43: normalizing the pressure data matrix P;

[0085] Step S44: Extract features from the normalized pressure data and calculate the pressure change rate Δp at each pressure detection point. j :

[0086]

[0087] Step S45: According to the pressure change rate Δp j , determine the leakage occurrence time x l , when Δp j Exceeding the set threshold p th When , it is determined that leakage occurs, and the leakage occurs at:

[0088] x l =min{t||Δp j (t)|>p th}.

[0089] In this embodiment of the present invention, by introducing and solving leakage parameters in the mathematical model of the leaking pipeline, it is possible to accurately simulate pressure changes under different leakage conditions, providing accurate data support for subsequent leak detection and location. The pressure data of each detection point is integrated into a matrix format to facilitate subsequent data processing and analysis. Normalization eliminates the influence of different dimensions and orders of magnitude, making the data comparable and enhancing the robustness and generalization ability of the model. By calculating the pressure change rate, the abnormal pressure changes when a leak occurs are effectively captured, providing a key basis for accurately determining the leak. Setting a reasonable threshold can quickly determine the moment of leak occurrence.

[0090] Step S5: using the correlation function method to perform sensitivity analysis on each node of the water network trunk pipeline and branch pipeline and compare the correlation coefficient of each node;

[0091] In some embodiments, step S5 includes:

[0092] Step S51: Obtain the pressure data sequence p of each node j (t);

[0093] Step S52: Select a reference point ref and obtain its pressure data sequence p ref (t), the reference point ref is a known location node close to the suspected leakage area;

[0094] Step S53: Calculate the correlation coefficient R between each node j and the reference point ref j :

[0095]

[0096] Where T is the time length of the pressure data sequence, are the means of the pressure data series of node j and reference point ref respectively;

[0097] Step S54: Compare and analyze the correlation coefficients Rj of all nodes j to find the node j with a significantly higher correlation coefficient than other nodes. max The node with the strongest correlation as the most likely leak.

[0098] In this embodiment of the present invention, by calculating the correlation coefficient between each node and a reference point and identifying the node with the strongest correlation, the area in the pipeline with the greatest potential for leaks can be quickly and accurately located. This correlation analysis fully considers the synchronization and correlation of pressure changes at each node in the pipeline, effectively filtering out noise and interference, making leak detection more accurate and reliable, and reducing false positives and missed negatives.

[0099] Step S6: Determine the location of the pipeline leakage point based on the correlation coefficient.

[0100] In some embodiments, step S6 includes:

[0101]

[0102] Where x jmax is the position of the node with the largest correlation coefficient, and Δx is the distance between adjacent nodes.

[0103] In an embodiment of the present invention, by comprehensively considering the correlation difference between the node with the largest correlation coefficient and its previous node, the location of the leakage point can be determined more accurately, avoiding the positioning error that may be caused by relying solely on the correlation coefficient of a single node, thereby achieving more accurate leakage point positioning.

[0104] Based on the foregoing embodiments, an embodiment of the present invention provides a water network pipeline leakage locating system, wherein the modules included in the system and the units included in each module can be implemented by a processor in a computer device; of course, they can also be implemented by a specific logic circuit; in the implementation process, the processor can be a central processing unit (CPU, Central Processing Unit), a microprocessor (MPU, Microprocessor Unit), a digital signal processor (DSP, Digital Signal Processing) or a field programmable gate array (FPGA, Field Programmable Gate Array), etc.

[0105] The embodiment of the present invention provides a water network pipeline leakage positioning system, Figure 2 A schematic diagram of a water network pipeline leakage locating system provided by an embodiment of the present invention is shown in FIG. Figure 2 Shown, including:

[0106] Acquisition module, used to collect pressure data and flow data of water network pipelines;

[0107] A judgment module is used to analyze the pressure data and flow rate data to determine whether a leak occurs in the pipeline being tested;

[0108] The selection module is used to discretize the pipeline system in the pre-built leaking pipeline mathematical model, determine the calculation area, and select the pressure detection point position of the water network pipeline when the pipeline under inspection leaks;

[0109] A calculation module, used to calculate the pressure values of each pressure detection point under different pipeline leakage conditions;

[0110] The analysis module is used to conduct sensitivity analysis on each node of the main pipeline and branch pipeline of the water network using the correlation function method and compare the correlation coefficients of each node;

[0111] The determination module is used to determine the location of the pipeline leakage point based on the correlation coefficient.

[0112] In some embodiments, the judgment module includes:

[0113] A first calculation unit, configured to calculate the mean and variance of the pressure data and the flow data;

[0114] The judgment unit is used to compare the calculated mean and variance with a preset threshold value. If the calculated mean and variance exceed the threshold value range, it is judged that the pipeline being tested has a leak.

[0115] In some embodiments, the selection module includes:

[0116] A first determining unit is used to determine the boundary conditions of the pipeline system, including the starting point, end point, branch point of the pipeline and known pressure and flow conditions;

[0117] A division unit, used for dividing the pipeline system into a plurality of discrete calculation units, wherein each calculation unit has the same length;

[0118] The second determining unit is used to determine the calculation area, including the starting position, the end position and the key node position in the middle of the pipeline;

[0119] The selection unit is used to select a pressure detection point at the node of each calculation unit. The position of the pressure detection point is:

[0120] x j =x0+j·Δx;

[0121] Where x j represents the position of the jth pressure detection point, x0 represents the starting position of the pipeline, and Δx is the length of the calculation unit.

[0122] In some embodiments, the pre-built mathematical model of the leaky pipeline is:

[0123]

[0124] Where q is the flow rate, t is the time, A is the pipe cross-sectional area, h is the water head height, x is the axial position of the pipe, ρ is the density of water, g is the acceleration due to gravity, f is the friction factor, D is the pipe diameter, and p is the pressure.

[0125] In some embodiments, the computing module includes:

[0126] a second calculation unit, for calculating pressure values under different leakage conditions by introducing leakage parameters into a mathematical model of the leaking pipeline;

[0127] Construct a unit for each pressure detection point x j , record the pressure value p under different leakage conditions j (t) Construct the pressure data matrix P, where the dimension of P is M×N, M is the number of pressure detection points, and N is the length of the time series;

[0128] A normalization unit, used to normalize the pressure data matrix P;

[0129] The third calculation unit is used to extract features from the normalized pressure data and calculate the pressure change rate Δp at each pressure detection point. j :

[0130]

[0131] The third determining unit is used to determine the pressure change rate Δp j , determine the leakage occurrence time x l , when Δp j Exceeding the set threshold p th When , it is determined that leakage occurs, and the leakage occurs at:

[0132] x l =min{t||Δp j (t)|>p th}.

[0133] In some embodiments, the analysis module comprises:

[0134] The first acquisition unit is used to obtain the pressure data sequence p of each node j (t);

[0135] The second acquisition unit is used to select a reference point ref and obtain its pressure data sequence p ref (t), the reference point ref is a known location node close to the suspected leakage area;

[0136] The fourth calculation unit is used to calculate the correlation coefficient R between each node j and the reference point ref j :

[0137]

[0138] Where T is the time length of the pressure data sequence, are the means of the pressure data series of node j and reference point ref respectively;

[0139] The analysis unit is used to compare and analyze the correlation coefficient Rj of all nodes j and find the node j with a significantly higher correlation coefficient than other nodes max The node with the strongest correlation as the most likely leak.

[0140] In some embodiments, the determining module includes:

[0141]

[0142] Where x jmax is the position of the node with the largest correlation coefficient, and Δx is the distance between adjacent nodes.

[0143] It should be noted that, in the embodiment of the present invention, if the above-mentioned positioning method is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a U disk, a mobile hard disk, a read-only memory (ROM, Read Only Memory), a magnetic disk or an optical disk. In this way, the embodiment of the present invention is not limited to any specific combination of hardware and software.

[0144] It should be understood that "one embodiment" or "an embodiment" mentioned throughout the specification means that the specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present invention. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention. The serial numbers of the above-mentioned embodiments of the present invention are for description only and do not represent the advantages and disadvantages of the embodiments.

[0145] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, object, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, object, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not preclude the presence of other identical elements in the process, method, object, or apparatus comprising the element.

[0146] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0147] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed across multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the scheme of this embodiment.

[0148] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0149] Those skilled in the art will understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above-mentioned method embodiments; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROMs), magnetic disks, optical disks, and other media that can store program codes.

[0150] Alternatively, if the integrated unit of the present invention is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiments of the present invention, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes a number of instructions for causing a controller to execute all or part of the methods described in various embodiments of the present invention. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0151] The above description is merely an embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A method for locating water network pipeline leakage, characterized in that: include: Collect pressure and flow data of water network pipelines; Perform data analysis on pressure data and flow rate data to determine whether the pipeline under inspection has leaked; In the event of a leak in the pipe being tested, the pipeline system in the pre-built mathematical model of the leaking pipeline is discretized to determine the calculation area and select the pressure detection point location of the water network pipeline; The calculated pressure values of each pressure detection point under different pipeline leakage conditions; The correlation function method is used to conduct sensitivity analysis on each node of the main pipeline and branch pipeline of the water network and compare the correlation coefficients of each node; Based on the correlation coefficient, the location of the pipeline leak point is determined.

2. A water network pipeline leakage locating method according to claim 1, characterized in that: The data analysis of the pressure data and the flow rate data to determine whether a leak occurs in the pipeline being tested includes: Calculate the mean and variance of pressure data and flow data; The calculated mean and variance are compared with a preset threshold value. If the threshold value is exceeded, it is determined that the pipeline being tested has a leak.

3. A water network pipeline leakage locating method according to claim 1, characterized in that: In the case that the pipe under inspection leaks, the pipeline system in the pre-built mathematical model of the leaking pipeline is discretized, the calculation area is determined, and the pressure detection point position of the water network pipeline is selected, including: Determine the boundary conditions of the piping system, including the starting point, end point, branch point, and known pressure and flow conditions of the pipeline; Dividing the pipeline system into a plurality of discrete computational units, wherein each computational unit has the same length; Determine the calculation area, including the starting point, end point and key node positions of the pipeline; A pressure detection point is selected at the node of each computing unit. The position of the pressure detection point is: x j =x0+j·Δx; Where x j represents the position of the jth pressure detection point, x0 represents the starting position of the pipeline, and Δx is the length of the calculation unit.

4. A water network pipeline leakage locating method according to claim 1, characterized in that: The pre-built mathematical model of the leaking pipe is: Where q is the flow rate, t is the time, A is the pipe cross-sectional area, h is the water head height, x is the axial position of the pipe, ρ is the density of water, g is the acceleration due to gravity, f is the friction factor, D is the pipe diameter, and p is the pressure.

5. A water network pipeline leakage locating method according to claim 1, characterized in that: The pressure values of each pressure detection point obtained by the calculation under different pipeline leakage conditions include: By introducing leakage parameters into the mathematical model of the leaking pipeline, the pressure values under different leakage conditions are calculated; For each pressure detection point x j , record the pressure value p under different leakage conditions j (t), construct the pressure data matrix P, where the dimension of P is M×N, M is the number of pressure detection points, and N is the length of the time series; Normalize the pressure data matrix P; Perform feature extraction on the normalized pressure data and calculate the pressure change rate Δp of each pressure detection point j : According to the pressure change rate Δp j , determine the leakage occurrence time x l , when Δp j Exceeding the set threshold p th When , it is determined that leakage occurs, and the leakage occurs at: x l =min{t||Δp j (t)|>p th }。 6. A water network pipeline leakage locating method according to claim 5, characterized in that: The correlation function method is used to perform sensitivity analysis on each node of the main pipeline and branch pipeline of the water network and compare the correlation coefficients of each node, including: Get the pressure data sequence p of each node j (t); Select a reference point ref and obtain its pressure data sequence p ref (t), the reference point ref is a known location node close to the suspected leakage area; Calculate the correlation coefficient R between each node j and the reference point ref j : Where T is the time length of the pressure data sequence, are the means of the pressure data series of node j and reference point ref respectively; Compare and analyze the correlation coefficients Rj of all nodes j to find the node j with a significantly higher correlation coefficient than other nodes max The node with the strongest correlation as the most likely leak.

7. A water network pipeline leakage locating method according to claim 6, characterized in that: The method of determining the location of the pipeline leakage point based on the correlation coefficient includes: Where, is the position of the node with the largest correlation coefficient, and Δx is the distance between adjacent nodes.

8. A water network pipeline leakage positioning system, characterized in that: include: Acquisition module, used to collect pressure data and flow data of water network pipelines; A judgment module is used to analyze the pressure data and flow rate data to determine whether a leak occurs in the pipeline being tested; The selection module is used to discretize the pipeline system in the pre-built leaking pipeline mathematical model, determine the calculation area, and select the pressure detection point position of the water network pipeline when the pipeline under inspection leaks; A calculation module, used to calculate the pressure values of each pressure detection point under different pipeline leakage conditions; The analysis module is used to conduct sensitivity analysis on each node of the main pipeline and branch pipeline of the water network using the correlation function method and compare the correlation coefficients of each node; The determination module is used to determine the location of the pipeline leakage point based on the correlation coefficient.

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