Method, device, medium and system for detecting leakage of underground cable

Abstract

The application provides a leakage detection method, device, medium and system of an underground cable, the method optimizes the thickness and the dielectric constant with a cost function as the target, obtains the optimal thickness and the optimal dielectric constant, constructs a received signal vector matrix of a final dilution CMP model, and in the case that at least one parameter in the received signal vector matrix is greater than the corresponding reference value, it is determined that the underground cable has a leakage fault, so that when the underground cable has a leakage, the current flowing through the area will be scattered and absorbed, causing the dielectric constant of the underground medium to change, the ground penetrating radar underground medium model inversion method is used to monitor the dielectric constant of the underground medium, so as to realize the leakage detection of the underground cable under the condition of nondestructive and high efficiency, and further solve the problems of low precision, low efficiency and poor stability when the existing scheme detects the leakage of the cable by using the inversion method.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electric leakage detection, in particular to an electric leakage detection method, device, medium and system for underground cable. BACKGROUND

[0002] Due to the limited technical means during construction, great dependence on manual work and other problems, the underground cable may be laid imprecisely, and there may be multiple safety hazards. Meanwhile, due to natural disasters, long service life or inadequate maintenance, the underground cable may be corroded or broken, which is prone to cause electric leakage accidents. Electric leakage of underground cable is a frequent problem in power operation, which may cause power loss, power outage, even casualties and other consequences. Therefore, it is of great significance to study the electric leakage detection method for underground cable.

[0003] Traditional electric leakage detection of underground cable mainly adopts the method of power outage and excavation, which needs to consume a large amount of manpower and material resources, and has a serious impact on residents' life and industrial production, and the detection efficiency is low, which cannot adapt to the fast pace of today's urban development. When electric leakage occurs in underground cable, current flows through underground medium, which will cause the dielectric constant of the medium to change. Ground penetrating radar, as a non-destructive detection means, can detect the dielectric constant of underground medium through the emission and reception of electromagnetic wave signals without power outage and excavation. Therefore, an electric leakage detection method for underground cable based on ground penetrating radar can be used, which improves the detection efficiency while being non-destructive.

[0004] Ground penetrating radar can obtain the dielectric constant model of underground medium through inversion of the received echo signal, so as to determine whether electric leakage occurs at the detection point based on the change of the dielectric constant. The existing inversion methods of ground penetrating radar dielectric constant mainly include full waveform inversion, common center point method, reverse time migration method, etc. At the same time, with the improvement of computer operation capacity, the inversion method of ground penetrating radar based on deep learning has gradually become the mainstream trend. However, the existing inversion methods still have problems such as low precision, low efficiency and poor stability. SUMMARY

[0005] The main purpose of the present application is to provide an electric leakage detection method, device, medium and system for underground cable, so as to at least solve the problem that the existing scheme still has low precision, low efficiency and poor stability when using inversion method to detect the electric leakage of cable.

[0006] In order to achieve the above-mentioned purpose, according to one aspect of the present application, an electric leakage detection method for underground cable is provided, which comprises:

[0007] acquiring thicknesses and dielectric constants of all A-Scan of each medium layer of the underground cable, determining reflection positions of each medium layer according to the thicknesses and the dielectric constants, and determining reflection propagation times of electromagnetic waves of each medium layer according to the reflection positions, the thicknesses and the dielectric constants;

[0008] constructing a cost function based on the reflection positions, the thicknesses, the dielectric constants and the reflection propagation times, and optimizing the thicknesses and the dielectric constants with the cost function as a target to obtain optimal thicknesses and optimal dielectric constants;

[0009] constructing a receiving signal vector matrix of a final dilution CMP model based on the optimal thicknesses, the optimal dielectric constants and reflection wave amplitude vectors;

[0010] determining that the underground cable has an electric leakage fault in a case where at least one parameter in the receiving signal vector matrix is greater than a corresponding reference value.

[0011] Optionally, constructing a receiving signal vector matrix of a final dilution CMP model based on the optimal thicknesses, the optimal dielectric constants and reflection wave amplitude vectors includes:

[0012] According to determining a propagation time construction mode vector;

[0013] substituting the optimal thicknesses and the optimal dielectric constants into the propagation time construction mode vector to form a modal vector;

[0014] constructing the receiving signal vector matrix of the final dilution CMP model based on the modal vector and the reflection wave amplitude vectors;

[0015] wherein a(t) is the propagation time construction mode vector, f M is a frequency of electromagnetic waves of the Mth medium layer, and t includes the optimal thicknesses and the optimal dielectric constants.

[0016] Optionally, constructing the receiving signal vector matrix of the final dilution CMP model based on the modal vector and the reflection wave amplitude vectors includes:

[0017] constructing the receiving signal vector matrix of the final dilution CMP model as follows:

[0018] r n,m = A n,m s n ;

[0019] wherein r n,mthe received signal vector matrix of the final dilution CMP model of the mth A-Scan of the medium layer of the nth layer, A n,m the modal vector of the mth A-Scan of the medium layer of the nth layer, s n the reflected wave amplitude vector of the medium layer of the nth layer.

[0020] Optionally, based on the reflection position, the thickness, the dielectric constant and the reflection propagation time, a cost function is constructed, comprising:

[0021] The cost function is constructed as:

[0022]

[0023] wherein, δ(ε n ,d n ,x n,m ) is the cost of the cost function, ε n is the dielectric constant of the medium layer of the nth layer, d n is the thickness of the medium layer of the nth layer, x n,m is the reflection position of the medium layer of the nth layer, ε i,h is the dielectric constant of the mth A-Scan of the medium layer of the ith layer, x i,h is the reflection position of the mth A-Scan of the medium layer of the ith layer, d i,h is the thickness of the mth A-Scan of the medium layer of the ith layer, c is the propagation speed of electromagnetic wave in air, t i,h is the reflection propagation time of the electromagnetic wave of the mth A-Scan of the medium layer of the ith layer.

[0024] Optionally, according to the reflection position, the thickness and the dielectric constant, the reflection propagation time of electromagnetic wave of each medium layer is determined, comprising:

[0025] According to the reflection propagation time of the electromagnetic wave of each medium layer is determined;

[0026] wherein, t n,m is the reflection propagation time of the electromagnetic wave of the mth A-Scan of the medium layer of the nth layer, x i,m is the reflection position of the mth A-Scan of the medium layer of the ith layer, d i is the thickness of the medium layer of the ith layer, ε i is the dielectric constant of the medium layer of the ith layer, c is the propagation speed of the electromagnetic wave in air.

[0027] Optionally, the reflection positions of each of the dielectric layers are determined according to the thickness and the dielectric constant, comprising:

[0028] According to the reflection positions of each of the dielectric layers are determined,

[0029] wherein ε1 is the dielectric constant of the first layer of the dielectric layers, ε2 is the dielectric constant of the second layer of the dielectric layers, d1 is the thickness of the first layer of the dielectric layers, d2 is the thickness of the second layer of the dielectric layers, x1 is the reflection position of the first layer of the dielectric layers, and x2 is the reflection position of the second layer of the dielectric layers.

[0030] Optionally, the method further comprises:

[0031] In the case that all the parameters in the received signal vector matrix are less than or equal to the corresponding reference values, it is determined that the underground cable is normal.

[0032] According to another aspect of the present application, there is provided a leakage detection device for an underground cable, comprising:

[0033] a obtaining unit configured to obtain the thickness and the dielectric constant of all A-Scan of each dielectric layer of the underground cable, and determine the reflection positions of each of the dielectric layers according to the thickness and the dielectric constant, and determine the reflection propagation time of electromagnetic waves of each of the dielectric layers according to the reflection positions, the thickness and the dielectric constant;

[0034] a first processing unit configured to construct a cost function based on the reflection positions, the thickness, the dielectric constant and the reflection propagation time, and optimize the thickness and the dielectric constant with the cost function as the target to obtain optimal thickness and optimal dielectric constant;

[0035] a second processing unit configured to construct a received signal vector matrix of a final dilution CMP model based on the optimal thickness, the optimal dielectric constant and the reflection wave amplitude vector;

[0036] a third processing unit configured to determine that the underground cable has a leakage fault in the case that at least one parameter in the received signal vector matrix is greater than the corresponding reference value.

[0037] According to another aspect of the present application, there is provided a computer readable storage medium comprising a stored program, wherein the computer readable storage medium controls the device where the computer readable storage medium is located to execute any of the methods when the program is running.

[0038] According to another aspect of the present application, there is provided a leakage detection system for an underground cable, the system comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs comprising instructions for performing any of the methods described.

[0039] According to the technical solution of the present application, based on the reflection position, the thickness, the dielectric constant and the reflection propagation time, a cost function is constructed, and the thickness and the dielectric constant are optimized with the cost function as the target to obtain an optimal thickness and an optimal dielectric constant, and based on the optimal thickness, the optimal dielectric constant and the reflection wave amplitude vector, a received signal vector matrix of a final dilution CMP model is constructed, and in the case that at least one parameter in the received signal vector matrix is greater than the corresponding reference value, it is determined that the underground cable has a leakage fault, so that when the underground cable has a leakage, the current flows through the area and scattering and absorption occur, resulting in a change in the dielectric constant of the underground medium, and the dielectric constant of the underground medium is monitored in the manner of ground penetrating radar underground medium model inversion, so as to realize leakage detection of the underground cable under the condition of nondestructive and high efficiency, and further solve the problems of low precision, low efficiency and poor stability in the prior art when the leakage of the cable is detected by inversion. BRIEF DESCRIPTION OF DRAWINGS

[0040] The accompanying drawings, which form a part of the present description, are included to provide a further understanding of the present application, and are incorporated herein for purposes of explaining the present application and, taken with the description herein, serve to explain the present application. In the drawings:

[0041] Figure 1 Fig. 1 shows a flowchart of a leakage detection method for an underground cable according to an embodiment of the present application;

[0042] Figure 2 Fig. 2 shows a structural block diagram of a leakage detection device for an underground cable according to an embodiment of the present application. DETAILED DESCRIPTION

[0043] It should be noted that the embodiments and features in the present application can be combined with each other without conflict. The present application will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0044] In order to make the person skilled in the art better understand the scheme of the present application, the technical scheme in the embodiments of the present application will be clearly and completely described below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor should be within the scope of protection of the present application.

[0045] It should be noted that the terms "first", "second" and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily have to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0046] For ease of description, the following describes some nouns or terms related to the embodiments of the present application:

[0047] Sparse CMP (Common Midpoint) subsurface medium parameter model is a model used for seismic exploration, mainly used to describe the physical properties of subsurface medium, such as velocity, density, etc. This model is commonly used in the field of geological exploration such as seismic inversion and imaging.

[0048] Finite Difference Time Domain (FDTD) method is a numerical simulation method used to solve partial differential equations. In the field of geophysics, FDTD method is commonly used to simulate the propagation process of seismic waves in subsurface medium. This method can simulate the propagation path and speed of seismic waves, helping seismologists better understand the structure and properties of subsurface medium.

[0049] Pattern search (PS) is a method used to find specific patterns or rules. In the field of computer science and data analysis, pattern search is commonly used to find specific patterns or keywords in text, image, audio and other data. This technology can be used in data mining, information retrieval, image recognition and other fields. Pattern search can be implemented through various algorithms and techniques, such as KMP algorithm, Boyer-Moore algorithm, regular expression, etc.

[0050] A-Scan is an imaging technique used to measure the internal structure of an object. It works by sending a beam of sound or ultrasound waves into the object and then generating an image based on the time and intensity of the sound wave reflections or transmissions. A-Scan images are commonly used in the medical field, such as in ophthalmology and ultrasonography, to observe and diagnose the condition of the eyeball and other tissues.

[0051] As introduced in the background, ground penetrating radar can obtain the dielectric constant model of the underground medium through inversion of the received echo signal, so as to judge whether the detection point has electric leakage based on the change of the dielectric constant. The existing ground penetrating radar dielectric constant inversion methods mainly include full waveform inversion, common midpoint method, reverse time migration method, etc. At the same time, with the improvement of computer operation ability, the ground penetrating radar inversion method based on deep learning has gradually become the mainstream trend. However, the existing inversion method still has problems such as low precision, low efficiency and poor stability. In order to solve the problems of low precision, low efficiency and poor stability of the existing scheme in detecting the electric leakage of the cable by using the inversion method, the embodiments of the present application provide a method, device, medium and system for detecting electric leakage of underground cable.

[0052] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application.

[0053] In the present embodiment, a method for detecting electric leakage of underground cable is provided. It should be noted that the steps shown in the flowchart of the drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that here.

[0054] Figure 1 is a flowchart of a method for detecting electric leakage of underground cable according to an embodiment of the present application.

[0055] As shown in Figure 1 , the method comprises the following steps:

[0056] In step S101, the thickness and dielectric constant of all A-Scan of each medium layer of the underground cable are obtained, and the reflection position of each medium layer is determined according to the thickness and dielectric constant, and the reflection transmission time of electromagnetic wave of each medium layer is determined according to the reflection position, thickness and dielectric constant.

[0057] Specifically, a CMP medium model is constructed, and in the CMP medium model, the antenna to ground surface distance is set as air thickness, the transmitting antenna and receiving antenna distance is L, and the bottom is connected with the absorbing boundary to absorb clutter.

[0058] In an embodiment of the present application, the reflection position of each medium layer is determined according to the reflection position, the thickness and the dielectric constant, comprising:

[0059] According to determining the reflection position of each medium layer,

[0060] wherein t n,m is the reflection propagation time of the electromagnetic wave of the mth A-Scan of the nth medium layer, x i,m is the reflection position of the mth A-Scan of the ith medium layer, d i is the thickness of the ith medium layer, ε i is the dielectric constant of the ith medium layer, and c is the propagation speed of the electromagnetic wave in air.

[0061] In an embodiment of the present application, the reflection position of each medium layer is determined according to the thickness and the dielectric constant, comprising:

[0062] According to determining the reflection position of each medium layer,

[0063] wherein ε1 is the dielectric constant of the first medium layer, ε2 is the dielectric constant of the second medium layer, d1 is the thickness of the first medium layer, d2 is the thickness of the second medium layer, x1 is the reflection position of the first medium layer, and x2 is the reflection position of the second medium layer.

[0064] Specifically, according to Snell's law, taking medium layer 1 and medium layer 2 as an example, x is the projection distance of the electromagnetic wave emission or receiving point to the plane (i.e. the reflection position), and the theoretical relationship between the dielectric constants of the two medium layers is:

[0065]

[0066] Considering that when the underground medium environment is complex and the number of medium layers is large, the electromagnetic wave refraction is complex, the distance between the transmitting antenna and the receiving antenna in the ground penetrating radar is reduced, and the above relationship is simplified to the first formula:

[0067]

[0068] In this model, the electromagnetic wave reflection propagation time of the mth A-Scan is the second formula:

[0069]

[0070] Step S102, based on the above reflection position, the above thickness, the above dielectric constant and the above reflection propagation time, a cost function is constructed, and the above thickness and the above dielectric constant are optimized based on the above cost function to obtain an optimal thickness and an optimal dielectric constant;

[0071] In an embodiment of the present application, based on the above reflection position, the above thickness, the above dielectric constant and the above reflection propagation time, a cost function is constructed, including:

[0072] The cost function is constructed as:

[0073]

[0074] Wherein, δ(ε n ,d n ,x n,m ) is the cost of the above cost function, ε n is the above dielectric constant of the nth layer of the above medium layer, d n is the above thickness of the nth layer of the above medium layer, x n,m is the above reflection position of the nth layer of the above medium layer, ε i,h is the above dielectric constant of the ith layer of the above medium layer, x i,h is the above reflection position of the ith layer of the above medium layer, d i,h is the above thickness of the ith layer of the above medium layer, c is the propagation speed of electromagnetic wave in air, t i,h is the above reflection propagation time of the electromagnetic wave of the ith layer of the above medium layer.

[0075] According to the above sparse CMP underground medium parameter model, the simulation signal echo is obtained by the finite difference time domain (FDTD) method, and the sum of squares of the difference between the simulation signal echo and the actual echo signal is taken as the objective function. When the objective function is optimized to the minimum value, it is indicated that the simulation and actual fitting effect is good, that is, the underground dielectric constant change is obtained.

[0076] Wherein, the relationship between the dielectric constant and the refractive point position (i.e. the reflection position) can be obtained from the established CMP model, therefore, the optimization of the cost function by three parameters becomes the optimization of the dielectric constant and the thickness by two parameters.

[0077] Based on the objective function, a pattern search algorithm is added to search for results with large step size and few optimization variables. During the pattern search process, the first layer parameters are estimated using the sparse CMP model, and then a series of consecutive points are searched based on the alternation between exploratory moves and pattern moves, so that the objective function continuously approaches the minimum value. Since the two-parameter optimization is seriously affected by the initial value, the traditional enumeration method is used to obtain the approximate initial value, and then the approximate value is refined based on the PS algorithm to realize inversion and obtain the change of the dielectric constant of the underground medium.

[0078] In step S103, based on the optimal thickness, the optimal dielectric constant, and the reflection wave amplitude vector, a received signal vector matrix of the final dilution CMP model is constructed.

[0079] In an embodiment of the present application, based on the optimal thickness, the optimal dielectric constant, and the reflection wave amplitude vector, the received signal vector matrix of the final dilution CMP model is constructed, including:

[0080] According to The propagation time is determined to construct a mode vector.

[0081] The optimal thickness and the optimal dielectric constant are substituted into the propagation time to form a mode vector.

[0082] Based on the mode vector and the reflection wave amplitude vector, the received signal vector matrix of the final dilution CMP model is constructed.

[0083] Where a(t) is the propagation time to construct a mode vector, f M is the frequency of the electromagnetic wave of the Mth medium layer, t includes the optimal thickness and the optimal dielectric constant.

[0084] Specifically, when detecting underground leakage, it is necessary to detect the change of the underground dielectric constant and the position of the leakage point. Therefore, d n,m and ε n,m are a series of A-Scan thickness and dielectric constant of the nth medium layer. The reflection position is calculated according to the first formula to obtain the approximate position, and the propagation time matrix T n,m is calculated according to the second formula. Then, the mode vector is constructed according to the propagation time, where t is the value in the matrix T, and the mode vector constitutes the matrix A n,m ;

[0085] In an embodiment of the present application, based on the mode vector and the reflection wave amplitude vector, the received signal vector matrix of the final dilution CMP model is constructed, including:

[0086] The received signal vector matrix of the final dilution CMP model is constructed as follows:

[0087] r n,m =A n,m s n ;

[0088] wherein, r n,m is the received signal vector matrix of the final sparse CMP model of the mth A-Scan of the nth layer of the medium layer, A n,m is the modal vector of the mth A-Scan of the nth layer of the medium layer, s n is the reflected wave amplitude vector of the nth layer of the medium layer.

[0089] Combined with the reflected wave amplitude vector s, the final received signal vector matrix of the sparse CMP model is obtained as follows:

[0090] r n,m =A n,m s n ;

[0091] According to the received signal vector matrix of the final sparse CMP model of the mth A-Scan of the nth layer of the medium layer, it is determined whether the underground cable has a leakage fault.

[0092] In step S104, if at least one parameter in the received signal vector matrix is greater than the corresponding reference value, it is determined that the underground cable has a leakage fault.

[0093] By comparing each parameter in the received signal vector matrix with the corresponding reference value, it is determined whether the underground cable has a leakage fault.

[0094] In the above steps, based on the reflection position, the thickness, the dielectric constant and the reflection propagation time, a cost function is constructed, and the thickness and the dielectric constant are optimized based on the cost function, to obtain an optimal thickness and an optimal dielectric constant. Based on the optimal thickness, the optimal dielectric constant and the reflected wave amplitude vector, a received signal vector matrix of the final sparse CMP model is constructed. If at least one parameter in the received signal vector matrix is greater than the corresponding reference value, it is determined that the underground cable has a leakage fault. Thus, when the underground cable has a leakage, the current flowing through the area will be scattered and absorbed, causing the dielectric constant of the underground medium to change. By using the ground penetrating radar underground medium model inversion method, the dielectric constant of the underground medium is monitored, so that the underground cable leakage detection is realized under the conditions of non-destructive and high efficiency. Thus, the problems of low precision, low efficiency and poor stability in the existing scheme using inversion method to detect the leakage of the cable are solved.

[0095] Judgment of underground cable leakage:

[0096] Based on the obtained underground dielectric constant in the above steps, it is judged whether the dielectric constant of a region is suddenly changed, and whether the leakage occurs is judged in combination with the original paper of laying the underground cable, so that the leakage detection of the underground cable is realized.

[0097] The present application proposes a leakage detection method of underground cable by using ground penetrating radar, which judges whether the leakage accident occurs based on the change of the dielectric constant of underground medium. Meanwhile, considering that the existing inversion method of underground medium parameter model still has problems of low precision, large memory occupation and low efficiency, the traditional CMP model is improved, and the sparsity and the correspondence of medium characteristics are considered to form a sparse common midpoint CMP model. Based on the model, the simulated echo signal can be forwardly obtained and the objective function can be established. In order to improve the optimization efficiency, the pattern search algorithm is introduced, and at the same time, the initial value is preliminarily approximated by using the enumeration method, and finally the underground medium parameter model is obtained, so that the leakage detection of underground cable is realized. The problem that the traditional leakage detection method needs to be powered off and excavated, which seriously affects the normal life of users, is solved.

[0098] Firstly, the common midpoint CMP underground medium model is established, and the sparse CMP model is formed based on the improvement of the refraction approximation method. The forward simulation of the established model can obtain the simulated echo signal. Then, the objective function is established by using the simulated echo signal and the actual echo signal, which is used to evaluate the fitting effect of the sparse CMP model. In order to improve the accuracy of the underground medium model, the objective function optimization method based on PS algorithm is adopted to optimize the objective function, so that the difference between the simulated echo signal and the actual echo signal is minimized, and the underground medium model at this time is the optimal medium model. Based on the final underground medium model, the change of the dielectric constant of underground medium can be obtained, so as to judge whether the leakage occurs at the detection point.

[0099] In an embodiment of the present application, the above method further comprises:

[0100] In the case that all the parameters in the received signal vector matrix are less than or equal to the corresponding reference value, it is determined that the underground cable is normal.

[0101] Specifically, in the case that all the parameters in the received signal vector matrix are less than or equal to the corresponding reference value, it is considered that there is no abnormality, and it is determined that the underground cable is normal.

[0102] The problems of needing to stop power supply and dig in the traditional leakage detection method are solved: in the traditional leakage detection, the area needs to be powered off and the ground needs to be dug to judge whether leakage occurs by measuring the voltage of two points. This method needs to consume a lot of manpower and material resources, and there are inevitable safety hazards in the steps of power-off and digging. Therefore, when the underground cable leaks, the current flows through the area and causes scattering and absorption, so that the dielectric constant of the underground medium changes. The underground medium model inversion of the ground penetrating radar is adopted to realize the monitoring of the dielectric constant of the underground medium, so that the leakage detection of the underground cable is realized under the conditions of non-damage and high efficiency.

[0103] Improvement of the common midpoint CMP model: in the step of establishing the underground medium parameter model, the CPML condition is set as the absorption boundary condition, so that the calculation efficiency is improved without splitting the time step in the calculation process. Meanwhile, in order to improve the traditional CMP model, the transmitting antenna and the receiving antenna are set to be close to each other, so that the Snell relation is converted from a nonlinear relation to a linear relation, and the sparsity and the correspondence of the underground medium parameter characteristics are combined to form a sparse CMP underground medium model.

[0104] Objective function optimization combining the enumeration method and the pattern search algorithm: in order to improve the model establishment accuracy and the calculation efficiency, in the objective function optimization process, the multi-parameter optimization problem is converted into a double-parameter optimization problem based on the Snell relation. Meanwhile, the pattern search algorithm is introduced to search the model with large step length and few optimization variables. In order to solve the problem that the initial value is strongly dependent in the multi-variable optimization problem, the first layer parameter is calculated by using the sparse CMP underground medium model before the pattern search algorithm is used, the approximate initial value is obtained by using the enumeration method, and the objective function is further optimized based on the pattern search algorithm.

[0105] It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a group of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown herein.

[0106] The underground cable leakage detection device provided by the embodiment of the present application can be used to execute the underground cable leakage detection method provided by the embodiment of the present application. The device is used to realize the above-mentioned embodiment and preferred embodiment, and will not be described again. As used below, the term "module" can be a combination of software and / or hardware that realizes a predetermined function. Although the device described in the following embodiment is preferably realized in software, the realization of hardware, or a combination of software and hardware, is also possible and conceived.

[0107] The underground cable leakage detection device provided by the embodiment of the present application is introduced below.

[0108] Figure 2 is a structural block diagram of an underground cable leakage detection device according to the embodiment of the present application. As shown in the figure, the device comprises: Figure 2

[0109] The acquisition unit 21 is configured to acquire the thickness and dielectric constant of all A-Scan of each medium layer of the underground cable, determine the reflection position of each medium layer according to the thickness and dielectric constant, and determine the reflection propagation time of electromagnetic waves of each medium layer according to the reflection position, thickness and dielectric constant;

[0110] The first processing unit 22 is configured to construct a cost function based on the reflection position, thickness, dielectric constant and reflection propagation time, optimize the thickness and dielectric constant based on the cost function, and obtain optimal thickness and optimal dielectric constant;

[0111] The second processing unit 23 is configured to construct a receiving signal vector matrix of the final dilution CMP model based on the optimal thickness, optimal dielectric constant and reflection wave amplitude vector;

[0112] The third processing unit 24 is configured to determine that the underground cable has a leakage fault when at least one parameter in the receiving signal vector matrix is greater than a corresponding reference value.

[0113] In the device, the cost function is constructed based on the reflection position, thickness, dielectric constant and reflection propagation time, the thickness and dielectric constant are optimized based on the cost function, and the optimal thickness and optimal dielectric constant are obtained. The receiving signal vector matrix of the final dilution CMP model is constructed based on the optimal thickness, optimal dielectric constant and reflection wave amplitude vector. When at least one parameter in the receiving signal vector matrix is greater than a corresponding reference value, it is determined that the underground cable has a leakage fault. Therefore, when the underground cable has a leakage, the current flows through the area and causes scattering and absorption, resulting in a change in the dielectric constant of the underground medium. The ground penetrating radar underground medium model inversion method is used to monitor the dielectric constant of the underground medium, thereby realizing the leakage detection of the underground cable under the conditions of non-destructive and high efficiency. Furthermore, the problems of low precision, low efficiency and poor stability in the existing scheme using the inversion method to detect the leakage of the cable are solved.

[0114] In an embodiment of the present application, the second processing unit comprises a first processing module, a second processing module and a third processing module,

[0115] The first processing module is configured to determine the optimal thickness and optimal dielectric constant according to the reflection position, thickness and dielectric constant of each medium layer of the underground cable.​ determining a propagation time construction mode vector;

[0116] The second processing module is configured to substitute the optimal thickness and the optimal dielectric constant into the propagation time construction mode vector to form a mode vector.

[0117] The third processing module is configured to construct the received signal vector matrix of the final dilution CMP model based on the mode vector and the reflected wave amplitude vector.

[0118] wherein a(t) is the propagation time construction mode vector, f M is the frequency of the electromagnetic wave of the Mth medium layer, t includes the optimal thickness and the optimal dielectric constant.

[0119] In an embodiment of the present application, the third processing module includes a construction submodule,

[0120] The construction submodule is configured to construct the received signal vector matrix of the final dilution CMP model as follows:

[0121] r n,m = A n,m s n ;

[0122] wherein r n,m is the received signal vector matrix of the final dilution CMP model of the mth A-Scan of the nth medium layer, A n,m is the mode vector of the mth A-Scan of the nth medium layer, s n is the reflected wave amplitude vector of the nth medium layer.

[0123] In an embodiment of the present application, the first processing unit includes a construction module,

[0124] The construction module is configured to construct the cost function as follows:

[0125]

[0126] wherein δ(ε n ,d n ,x n,m ) is the cost of the cost function, ε n is the dielectric constant of the nth medium layer, d n is the thickness of the nth medium layer, x n,m is the reflection position of the nth medium layer, ε i,h is the dielectric constant of the hth A-Scan of the ith medium layer, x i,his the reflection position of the hth A-Scan of the medium layer of the ith layer, d i,h is the thickness of the hth A-Scan of the medium layer of the ith layer, c is the propagation speed of the electromagnetic wave in air, t i,h is the reflection propagation time of the electromagnetic wave of the hth A-Scan of the medium layer of the ith layer.

[0127] In an embodiment of the present application, the acquisition unit comprises a fourth processing module,

[0128] The fourth processing module is configured to determine the reflection position of each of the medium layers according to determine the reflection propagation time of the electromagnetic wave of each of the medium layers;

[0129] wherein t n,m is the reflection propagation time of the electromagnetic wave of the mth A-Scan of the medium layer of the nth layer, x i,m is the reflection position of the mth A-Scan of the medium layer of the ith layer, d i is the thickness of the medium layer of the ith layer, ε i is the dielectric constant of the medium layer of the ith layer, c is the propagation speed of the electromagnetic wave in air.

[0130] In an embodiment of the present application, the acquisition unit comprises a fifth processing module,

[0131] The fifth processing module is configured to determine the reflection position of each of the medium layers according to

[0132] wherein ε1 is the dielectric constant of the medium layer of the first layer, ε2 is the dielectric constant of the medium layer of the second layer, d1 is the thickness of the medium layer of the first layer, d2 is the thickness of the medium layer of the second layer, x1 is the reflection position of the medium layer of the first layer, and x2 is the reflection position of the medium layer of the second layer.

[0133] In an embodiment of the present application, the device further comprises a fourth processing unit,

[0134] The fourth processing unit is configured to determine that the underground cable is normal when all the parameters in the received signal vector matrix are less than or equal to the corresponding reference values.

[0135] ​The leakage detection device of the underground cable comprises a processor and a memory, the acquisition unit, the first processing unit, the second processing unit and the third processing unit are all stored in the memory as program units, and the corresponding functions are realized by executing the program units stored in the memory by the processor. The modules are located in the same processor; or the modules are located in different processors in any combination.

[0136] The processor comprises a core, and the core calls the corresponding program unit in the memory. The core can be one or more, and the low precision, low efficiency and poor stability of the existing scheme in detecting the leakage of the cable by using the inversion method can be solved by adjusting the core parameters.

[0137] The memory can include non-permanent memory in a computer readable medium, random access memory (RAM) and / or non-volatile memory such as read-only memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip.

[0138] The embodiment of the present application provides a computer readable storage medium, the computer readable storage medium comprises a stored program, wherein the computer readable storage medium controls the device to execute the leakage detection method of the underground cable when the program runs.

[0139] The embodiment of the present application provides a processor, the processor is used for running a program, wherein the program executes the leakage detection method of the underground cable when the program runs.

[0140] The embodiment of the present application provides a device, the device comprises a processor, a memory and a program stored in the memory and executable on the processor, and the processor executes the program to realize at least the following steps: acquiring the thickness and the dielectric constant of all A-Scan of each medium layer of the underground cable, determining the reflection position of each medium layer according to the thickness and the dielectric constant, and determining the reflection propagation time of the electromagnetic wave of each medium layer according to the reflection position, the thickness and the dielectric constant; constructing a cost function based on the reflection position, the thickness, the dielectric constant and the reflection propagation time, optimizing the thickness and the dielectric constant with the cost function as the target to obtain the optimal thickness and the optimal dielectric constant; constructing a receiving signal vector matrix of the final dilution CMP model based on the optimal thickness, the optimal dielectric constant and the reflection wave amplitude vector; and determining that the underground cable has a leakage fault in the case that at least one parameter in the receiving signal vector matrix is greater than the corresponding reference value. The device in the present application can be a server, a PC, a PAD, a mobile phone and the like.

[0141] The application also provides a computer program product, when executed on a data processing device, is adapted to execute a program that initializes at least the following method steps: obtaining thicknesses and dielectric constants of all A-Scans of each medium layer of an underground cable, and determining reflection positions of each of the medium layers according to the thicknesses and the dielectric constants, and determining reflection propagation times of electromagnetic waves of each of the medium layers according to the reflection positions, the thicknesses and the dielectric constants; constructing a cost function based on the reflection positions, the thicknesses, the dielectric constants and the reflection propagation times, and optimizing the thicknesses and the dielectric constants with the cost function as the target to obtain optimal thicknesses and optimal dielectric constants; constructing a received signal vector matrix of a final dilution CMP model based on the optimal thicknesses, the optimal dielectric constants and reflection wave amplitude vectors; and determining that the underground cable has a leakage fault in a case where at least one parameter in the received signal vector matrix is greater than a corresponding reference value.

[0142] The application also provides a leakage detection system for an underground cable, which includes one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include a program for executing any of the above methods. A cost function is constructed based on the reflection positions, the thicknesses, the dielectric constants and the reflection propagation times, and the thicknesses and the dielectric constants are optimized with the cost function as the target to obtain optimal thicknesses and optimal dielectric constants, a received signal vector matrix of a final dilution CMP model is constructed based on the optimal thicknesses, the optimal dielectric constants and reflection wave amplitude vectors, and it is determined that the underground cable has a leakage fault in a case where at least one parameter in the received signal vector matrix is greater than a corresponding reference value, so that when the underground cable has a leakage, the current flowing through the area will be scattered and absorbed, causing the dielectric constant of the underground medium to change, the dielectric constant of the underground medium is monitored by using a ground penetrating radar underground medium model inversion method, the leakage detection of the underground cable is realized under the conditions of non-destructive and high efficiency, and the problems of low precision, low efficiency and poor stability in the prior art are solved.

[0143] It should be apparent to those skilled in the art that the modules or steps of the application described above can be implemented with a general purpose computer, and can be centralized in a single computer or distributed among a network of computers, and can be implemented with program code executable by a computer, and thus can be stored in a storage device and executed by a computer, and in some cases, the steps shown or described can be executed in a different order than shown or described, or can be implemented as separate integrated circuit modules or as a single integrated circuit module, and thus the application is not limited to any particular combination of hardware and software.

[0144] Those skilled in the art will appreciate that embodiments of the application can be devised for a method, a system, or a computer program product. Accordingly, the application can be embodied in the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the application can be in the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk memory, CD-ROMs, optical storage media, etc.) embodying computer readable program code.

[0145] The present application is described herein with reference to the flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0146] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0147] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart illustrations and / or block diagrams.Figure 1 one or more processes and / or functions specified in one or more blocks Figure 1 one or more processes and / or functions specified in one or more blocks

[0148] In one typical arrangement, the computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0149] The memory can include non-persistent memory and / or volatile memory, such as random access memory (RAM) and / or cache memory, non-volatile memory, such as read-only memory (ROM), EPROM, and / or flash memory. The memory is an example of computer readable media.

[0150] Computer readable media includes permanent and non-permanent, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD), or other optical storage, magnetic cassette, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to a computing device. According to the definition herein, computer readable media does not include transitory media, such as modulated data signals and carrier waves.

[0151] It should also be noted that the terms "comprising", "containing", or any other variant thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article or apparatus that comprises a list of elements does not only include those elements, but can also include other elements not expressly listed or inherent to such process, method, article or apparatus. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, method, article or apparatus that includes the element.

[0152] From the above description, it can be seen that the above-mentioned embodiments of the present application achieve the following technical effects:

[0153] 1)、the underground cable of the application, based on the above reflection position, the above thickness, the above dielectric constant and the above reflection propagation time, the cost function is constructed, and the above thickness and the above dielectric constant are optimized based on the above cost function, the optimal thickness and the optimal dielectric constant are obtained, based on the optimal thickness, the optimal dielectric constant and the reflection wave amplitude vector, the receiving signal vector matrix of the final dilution CMP model is constructed, in the case that at least one parameter in the above receiving signal vector matrix is greater than the corresponding reference value, it is determined that the underground cable has a leakage fault, so as to consider that when the underground cable has a leakage, the current flowing through the region will be scattered and absorbed, resulting in a change in the dielectric constant of the underground medium, the dielectric constant of the underground medium is monitored by using the ground penetrating radar underground medium model inversion, so as to realize the leakage detection of the underground cable under the condition of nondestructive and high efficiency, and further solve the problems of low precision, low efficiency and poor stability in the existing scheme using inversion method to detect the leakage of the cable.

[0154] 2)、the underground cable of the application, based on the above reflection position, the above thickness, the above dielectric constant and the above reflection propagation time, the cost function is constructed, and the above thickness and the above dielectric constant are optimized based on the above cost function, the optimal thickness and the optimal dielectric constant are obtained, based on the optimal thickness, the optimal dielectric constant and the reflection wave amplitude vector, the receiving signal vector matrix of the final dilution CMP model is constructed, in the case that at least one parameter in the above receiving signal vector matrix is greater than the corresponding reference value, it is determined that the underground cable has a leakage fault, so as to consider that when the underground cable has a leakage, the current flowing through the region will be scattered and absorbed, resulting in a change in the dielectric constant of the underground medium, the dielectric constant of the underground medium is monitored by using the ground penetrating radar underground medium model inversion, so as to realize the leakage detection of the underground cable under the condition of nondestructive and high efficiency, and further solve the problems of low precision, low efficiency and poor stability in the existing scheme using inversion method to detect the leakage of the cable.

[0155] The above only describes the preferred embodiments of the application and does not limit the application. For those skilled in the art, the application can have various changes and variations. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of the application shall be included in the protection scope of the application.

Claims

1. A method for detecting leakage current in underground cables, characterized in that, include: Obtain the thickness and dielectric constant of all A-Scan values ​​of each dielectric layer of the underground cable, and determine the reflection position of each dielectric layer based on the thickness and dielectric constant, and determine the electromagnetic wave reflection propagation time of each dielectric layer based on the reflection position, the thickness and the dielectric constant; Based on the reflection location, the thickness, the dielectric constant, and the reflection propagation time, a cost function is constructed, and the thickness and the dielectric constant are optimized with the cost function as the objective to obtain the optimal thickness and the optimal dielectric constant. Based on the optimal thickness, the optimal dielectric constant, and the reflected wave amplitude vector, the received signal vector matrix of the final diluted CMP model is constructed; If at least one parameter in the received signal vector matrix is ​​greater than the corresponding reference value, it is determined that the underground cable has a leakage fault.

2. The method according to claim 1, characterized in that, Based on the optimal thickness, the optimal dielectric constant, and the reflected wave amplitude vector, the received signal vector matrix of the final diluted CMP model is constructed, including: according to Determine the propagation time to construct the pattern vector; Substituting the optimal thickness and the optimal dielectric constant into the propagation time constructs the mode vector, thus forming the mode vector; Based on the mode vector and the reflected wave amplitude vector, the received signal vector matrix of the final diluted CMP model is constructed; Where a(t) is the propagation time construction mode vector, f M Let t be the frequency of the electromagnetic wave in the Mth dielectric layer, where t includes the optimal thickness and the optimal dielectric constant.

3. The method according to claim 2, characterized in that, Based on the mode vector and the reflected wave amplitude vector, the received signal vector matrix of the final diluted CMP model is constructed, including: The received signal vector matrix for constructing the final diluted CMP model is as follows: r n,m =A n,m s n ; Where, r n,m For the received signal vector matrix of the final diluted CMP model of the m-th A-Scan of the n-th dielectric layer, A n,m Let s be the mode vector of the m-th A-Scan in the n-th dielectric layer. n Let be the amplitude vector of the reflected wave of the nth dielectric layer.

4. The method according to claim 1, characterized in that, Based on the reflection location, the thickness, the dielectric constant, and the reflection propagation time, a cost function is constructed, including: The construction cost function is: Wherein, δ(ε) n ,d n ,x n,m ) represents the cost of the cost function, ε n d is the dielectric constant of the nth dielectric layer. n x is the thickness of the nth dielectric layer. n,m ε represents the reflection position of the nth dielectric layer. i,h x is the dielectric constant of the h-th A-Scan of the i-th dielectric layer. i,h d represents the reflection position of the h-th A-Scan in the i-th dielectric layer. i,h The thickness of the h-th A-Scan of the i-th dielectric layer, c is the propagation speed of electromagnetic waves in air, and t i,h The reflection propagation time of the electromagnetic wave of the h-th A-Scan of the i-th dielectric layer.

5. The method according to claim 1, characterized in that, The reflection propagation time of electromagnetic waves in each dielectric layer is determined based on the reflection location, the thickness, and the dielectric constant, including: according to Determine the reflection propagation time of the electromagnetic wave in each of the aforementioned dielectric layers; Among them, t n,m x is the reflection propagation time of the electromagnetic wave of the m-th A-Scan in the n-th dielectric layer. i,m Let d be the reflection position of the m-th A-Scan in the i-th dielectric layer. i ε is the thickness of the i-th dielectric layer. i Let be the dielectric constant of the i-th dielectric layer, and c be the propagation speed of the electromagnetic wave in air.

6. The method according to claim 1, characterized in that, Determining the reflection position of each dielectric layer based on the thickness and the dielectric constant includes: according to Determine the reflection position of each of the aforementioned dielectric layers. Wherein, ε1 is the dielectric constant of the first dielectric layer, ε2 is the dielectric constant of the second dielectric layer, d1 is the thickness of the first dielectric layer, d2 is the thickness of the second dielectric layer, x1 is the reflection position of the first dielectric layer, and x2 is the reflection position of the second dielectric layer.

7. The method according to any one of claims 1 to 6, characterized in that, The method further includes: If all parameters in the received signal vector matrix are less than or equal to their corresponding reference values, the underground cable is considered to be functioning normally.

8. A leakage current detection device for underground cables, characterized in that, include: The acquisition unit is used to acquire the thickness and dielectric constant of all A-Scans of each dielectric layer of the underground cable, and determine the reflection position of each dielectric layer according to the thickness and dielectric constant, and determine the reflection propagation time of the electromagnetic wave of each dielectric layer according to the reflection position, the thickness and the dielectric constant. The first processing unit is configured to construct a cost function based on the reflection location, the thickness, the dielectric constant, and the reflection propagation time, and optimize the thickness and the dielectric constant with the cost function as the objective to obtain the optimal thickness and the optimal dielectric constant. The second processing unit is used to construct the received signal vector matrix of the final diluted CMP model based on the optimal thickness, the optimal dielectric constant, and the reflected wave amplitude vector. The third processing unit is used to determine that the underground cable has a leakage fault if at least one parameter in the received signal vector matrix is ​​greater than the corresponding reference value.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the method according to any one of claims 1 to 7.

10. A leakage current detection system for underground cables, characterized in that, include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs comprising methods for performing any one of claims 1 to 7.

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