Cable defect positioning and defect aging state detection method and equipment

Abstract

The embodiment of the invention discloses a cable defect positioning and defect aging state detection method and equipment, belongs to the technical field of cable defect detection, and solves the problem that cable defects are difficult to reliably position during cable defect diagnosis in the prior art. Comprising the steps of constructing an integral transformation kernel function based on cable initial characteristic parameters; based on the integral transformation kernel function, constructing an integral transformation function corresponding to the cable head end impedance spectrum data, obtaining a cable defect diagnosis function, and determining cable defect positioning information through the cable defect diagnosis function; inputting the obtained cable defect positioning information into a cable impedance spectrum calculation model containing a local defect section, and outputting an impedance spectrum calculation value; optimizing a difference value objective function corresponding to the impedance spectrum calculation value and the impedance spectrum measurement value through a particle swarm algorithm to obtain characteristic parameters of the defect section of the cable; and determining the aging state of the local defect of the cable based on a preset cable aging characteristic parameter threshold and the characteristic parameters of the defect section of the cable.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of cable defect detection, and in particular to a cable defect positioning and defect aging state detection method and device. BACKGROUND

[0002] With the development of urbanization construction, cable lines occupy an increasingly large proportion in power transmission and distribution systems. Cables play a key role in power transmission, rail transportation, aerospace, etc. If local latent defects are not diagnosed in time, permanent faults may be caused, resulting in serious economic losses and safety risks.

[0003] Existing cable defect diagnosis methods have many limitations. For example, traditional electrical quantity detection methods can only assess the overall state and cannot identify local latent defects. Local discharge monitoring technology is greatly disturbed by the scene, the signal propagation attenuation characteristics are not clear, and the positioning reliability is low. The time domain reflection method is not sensitive to the impedance mismatch of non-permanent faults, and it is difficult to effectively detect early defects.

[0004] In recent years, broadband impedance spectrum technology has gradually emerged, which realizes defect diagnosis by measuring the curve of the input impedance of the cable head end changing with frequency, but the diagnosis graphs obtained by the existing LIRA (Line Resonance Analysis) method and IFFT (Inverse Fast Fourier Transform) method still have many information that can easily lead to misjudgment, and cannot reliably realize the positioning of local cable defects. The LIRA method and the IFFT method cannot evaluate the severity of local defects. Therefore, the existing cable impedance spectrum data analysis technology still lacks a reliable impedance spectrum data analysis method, and it is difficult to effectively extract the local defect characteristic parameters of the cable from the impedance spectrum data, so it is difficult to reliably position the cable defects and evaluate the severity. SUMMARY

[0005] The embodiments of the present application provide a cable defect positioning and defect aging state detection method and device, which are used to solve the following technical problems: when the existing broadband impedance spectrum technology is used for cable defect diagnosis, it is difficult to effectively extract the local defect characteristic parameters of the cable from the impedance spectrum data, so it is difficult to reliably position the cable defects and evaluate the severity.

[0006] The embodiments of the present application adopt the following technical solutions: The embodiment of the application provides a cable defect positioning and defect aging state detection method. The method comprises the following steps: obtaining cable head-end impedance spectrum data, and constructing an integral transform kernel function based on initial characteristic parameters of the cable; constructing an integral transform function corresponding to the cable head-end impedance spectrum data based on the integral transform kernel function, obtaining a cable defect diagnosis function, and determining cable defect positioning information by the position of a mutation peak output by the cable defect diagnosis function; inputting the obtained cable defect positioning information into a cable impedance spectrum calculation model containing a local defect section, so as to output impedance spectrum calculation values by the cable impedance spectrum calculation model; optimizing a difference target function corresponding to the impedance spectrum calculation values and impedance spectrum measurement values by a particle swarm algorithm, so as to obtain cable defect section characteristic parameters; and determining the aging state of the local defect of the cable based on preset cable aging characteristic parameter thresholds and the cable defect section characteristic parameters.

[0007] In an implementation manner of the application, the integral transform kernel function is constructed based on the initial characteristic parameters of the cable, and specifically comprises the following steps: determining a cable intact section propagation coefficient based on the initial characteristic parameters of the cable; and constructing the integral transform kernel function based on the cable intact section propagation coefficient. ; Wherein, gamma h is the cable intact section propagation coefficient, f is the measurement frequency, x is the spatial position along the cable.

[0008] In an implementation manner of the application, the integral transform function corresponding to the cable head-end impedance spectrum data is constructed based on the integral transform kernel function, and the cable defect diagnosis function is obtained, and specifically comprises the following steps: The integral transform function is as follows: ; The integral transform is performed on the cable head-end impedance spectrum data; wherein, F ( x ) is the integral transform function, Z l ( f ) is the cable head-end impedance amplitude or phase spectrum with a length of l ; f up is the upper limit of the frequency of the impedance spectrum; f low is the lower limit of the frequency of the impedance spectrum; K ( f , x ) is the kernel function of the integral transform, which is the frequency f and the spatial position xa function of the integral transform function of the cable after the cable has a local defect; and comparing the integral transform function of the cable after the cable has the local defect with the integral transform function of the cable in a perfect state to obtain a cable defect diagnosis function: ; wherein, VA x is the cable defect diagnosis function; F d x is the integral transform function of the cable after the cable has the local defect; F h x is the integral transform function of the perfect cable.

[0009] In an implementation form of the present application, the cable defect positioning information is determined by the position of the mutation peak output by the cable defect diagnosis function, and specifically includes: determining a mutation peak that meets a preset mutation peak determination threshold condition based on the cable defect diagnosis function; wherein the number of the mutation peaks corresponds to the number of the cable defects, and the vertex of each mutation peak corresponds to the preliminary positioning position of each cable defect; wherein the cable defect positioning information at least includes one of the defect number and the defect position.

[0010] In an implementation form of the present application, before the impedance spectrum calculation value is output by the cable impedance spectrum calculation model, the method further includes: determining the range and type of each defect based on the positioned cable defect position; wherein each defect section corresponds to a preset defect characteristic parameter; dividing the cable into a perfect section and at least one defect section along the length direction, assigning an initial characteristic parameter to the perfect section, and assigning a preset defect characteristic parameter to each defect section; respectively constructing a transmission line model of the perfect section and the defect section, establishing the voltage transfer relationship and the current transfer relationship of each section by a reflection coefficient formula; taking the cable end load as a starting point, iteratively calculating the input impedance of each section in sequence according to the section order, and outputting the cable head end impedance spectrum calculation value under different frequencies; determining the relative error between the cable head end impedance spectrum calculation value and the cable head end impedance spectrum measured value, adjusting the preset defect characteristic parameter corresponding to the defect section based on the relative error until the relative error meets a preset error condition, to obtain the cable impedance spectrum calculation model.

[0011] ​​​In an implementation manner of the present application, the difference function corresponding to the impedance spectrum calculation value and the measured value is optimized by the particle swarm algorithm, and the cable defect section characteristic parameter is obtained, specifically comprising: constructing a difference objective function based on the sum of the absolute value of the difference between the impedance spectrum calculation value and the measured value of the cable containing the defect section; initializing the particle swarm parameters, obtaining the impedance spectrum calculation value based on the position parameters of each particle and the cable impedance spectrum calculation model containing the local defect section, determining the objective function value based on the impedance spectrum calculation value, and taking it as the particle fitness; updating the speed and position of the particle according to the preset speed update formula and position update formula based on the global optimal position and the global optimal position of the particle itself; when the maximum iteration number is reached or the global optimal fitness value is less than the preset threshold, stopping iteration, and outputting the parameter combination corresponding to the global optimal position as the cable defect section characteristic parameter.

[0012] In an implementation manner of the present application, the aging state of the cable local defect is determined based on the preset cable aging characteristic parameter threshold and the cable defect section characteristic parameter, specifically comprising: determining the cable defect type based on the parameter type corresponding to the cable defect section characteristic parameter; wherein the cable defect type at least includes one of the cable local aging defect type and the cable local damage defect type; when the cable defect type is the cable local aging defect type, matching the corresponding preset cable aging characteristic parameter threshold based on the cable defect section characteristic parameter; comparing the cable defect section characteristic parameter with the matched preset cable aging characteristic parameter threshold, and determining the cable aging grade based on the comparison result.

[0013] In an implementation manner of the present application, after the position of the mutation peak output by the cable defect diagnosis function is determined, the method further comprises constructing a micro-element equivalent model, specifically comprising: constructing a cable micro-element equivalent model based on the cable core resistance per unit length, the cable core inductance per unit length, the cable metal shielding layer resistance per unit length, the cable metal shielding layer inductance per unit length and the cable insulation capacitance per unit length. Based on the formula: ; The AC resistance is determined; wherein, R AC The AC resistance is determined; wherein, R DC The DC resistance is determined; wherein, y s The skin effect factor is determined; wherein, y p The proximity effect factor is determined; wherein,

[0014] In an implementation form of the present application, after the cable defect positioning information is determined by the position of the mutation peak in the cable defect diagnosis function, the method further comprises: inputting different preset aging level complex permittivity reference values into the cable micro-unit equivalent model respectively, outputting the cable head-end impedance spectrum calculation values corresponding to each aging level respectively to obtain the impedance spectrum variation intervals corresponding to different aging levels respectively; comparing the mutation peak difference obtained from the position of the mutation peak with the impedance spectrum variation intervals corresponding to different aging levels respectively to determine the aging level of the cable local defect.

[0015] The embodiment of the present application provides a cable defect positioning and defect aging state detection device, which comprises at least one processor and a memory in communication connection with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to: acquire cable head-end impedance spectrum data, and construct an integral transform kernel function based on cable initial characteristic parameters; construct an integral transform function corresponding to the cable head-end impedance spectrum data based on the integral transform kernel function, obtain a cable defect diagnosis function, and determine cable defect positioning information through the position of a mutation peak output by the cable defect diagnosis function; input the obtained cable defect positioning information into a cable impedance spectrum calculation model containing a local defect section, and output impedance spectrum calculation values through the cable impedance spectrum calculation model; optimize a difference target function corresponding to the impedance spectrum calculation values and impedance spectrum measurement values through a particle swarm algorithm to obtain cable defect section characteristic parameters; and determine the aging state of the cable local defect based on preset cable aging characteristic parameter thresholds and the cable defect section characteristic parameters.

[0016] The above at least one technical solution adopted by the embodiment of the present application can achieve the following beneficial effects: the embodiment of the present application converts the impedance spectrum data in the frequency domain into a diagnostic function in the spatial domain through integral transform, solves the limitation that the traditional method cannot directly extract the spatial defect position from the frequency domain data. The diagnostic function is constructed by comparing the integral transform functions of the defect section and the intact section, can amplify the influence of the local defect on the impedance spectrum, makes the defect characteristics more prominent, and reduces the missed detection probability of the small defect. The impedance spectrum calculation model containing the local defect section is constructed based on the defect positioning information, which can assign characteristic parameters in a targeted manner, so that the model can truly restore the actual structure and electrical characteristics of the cable, accurately calculate the cable head-end impedance spectrum containing multiple defects, and solve the problem that the traditional overall model cannot represent the influence of the local defect. The particle swarm algorithm is used to quickly minimize the difference between the impedance spectrum calculation values and the measurement values, accurately determine the key parameters such as the complex permittivity and the damage coefficient of the defect section, realize the automatic and high-precision extraction of the defect characteristic parameters, and improve the accuracy of the cable aging state evaluation. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to make the technical solutions in the embodiments of the present application or the prior art clearer, the accompanying drawings needed in the embodiments or prior art description will be briefly introduced. Obviously, the accompanying drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor on the basis of these drawings. In the drawings: Figure 1 A flow chart of a cable defect positioning and defect aging state detection method provided by the embodiment of the present application; Figure 2 A diagnostic function image schematic diagram provided by the embodiment of the present application; Figure 3 A search iteration algorithm flow chart provided by the embodiment of the present application; Figure 4 An improved cable micro-element equivalent model schematic diagram provided by the embodiment of the present application; Figure 5 A structure schematic diagram of a cable defect positioning and defect aging state detection device provided by the embodiment of the present application.

[0018] Reference signs: 200: a cable defect positioning and defect aging state detection device, 201: a processor, 202: a memory. DETAILED DESCRIPTION

[0019] The embodiment of the present application provides a cable defect positioning and defect aging state detection method and device.

[0020] In order to make the technical solutions in the embodiments of the present application or the prior art clearer, the accompanying drawings needed in the embodiments or prior art description will be briefly introduced. Obviously, the accompanying drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor on the basis of these drawings. In the drawings:

[0021] The technical solutions provided by the embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0022] Figure 1 A flow chart of a cable defect positioning and defect aging state detection method provided by the embodiment of the present application; S101, acquiring cable head-end impedance spectrum data, and constructing an integral transformation kernel function based on cable initial characteristic parameters.

[0023] In an implementation form of the present application, cable head-end impedance spectrum data is acquired, and a cable intact section propagation coefficient is determined based on cable initial characteristic parameters, and an integral transform kernel function is constructed based on the cable intact section propagation coefficient: ; wherein, gamma h is the cable intact section propagation coefficient, f is the measurement frequency, x is the spatial position along the cable.

[0024] Specifically, the embodiment of the present application adopts a broadband impedance analyzer to build a cable head-end impedance spectrum measurement system, the measurement frequency range covers 5.5MHz~40MHz, the analyzer test port is connected with the cable head-end through a coaxial cable, and a standard matching load is connected at the end. During the measurement, the instrument automatically scans the impedance amplitude and phase data in the set frequency range, the sampling interval is dynamically adjusted according to the frequency interval, the sampling interval is 0.5MHz in the high frequency band (20MHz~40MHz), and the sampling interval is 0.2MHz in the low frequency band (5.5MHz~20MHz), so as to ensure that the data resolution meets the defect identification requirement. After the measurement is completed, the cable head-end impedance spectrum data containing the frequency, impedance amplitude and impedance phase are exported.

[0025] Based on the initial characteristic parameters of the cable (such as the core radius, the inner radius of the shielding layer, the conductor conductivity, the complex permittivity of the insulating medium, etc.), the intact state under different frequencies f corresponding to R , L , G , C are calculated, and the propagation coefficient formula is substituted: ; The cable intact section propagation coefficient under different measurement frequencies gamma is obtained; wherein, R is the resistance per unit length of the transmission line, L is the inductance per unit length of the transmission line, C is the capacitance per unit length of the transmission line, G represents the conductance per unit length of the transmission line.

[0026] Further, in order to realize the conversion of the frequency domain impedance spectrum data to the spatial domain position information, an integral transform kernel function K ( f , x ) needs to be constructed. Specifically, the generalized orthogonality of the function is used to make the integral transform value appear obvious difference at the defect and at the non-defect, so as to locate the defect position.

[0027] Specifically, the periodicity of impedance spectrum mainly reflects the characteristics of the cable itself, and the periodicity of impedance spectrum is determined by the operator e -2γl . The periodicity of impedance spectrum of the cable containing local defect section is also affected by the operator e -2γdld of the defect section, therefore, the main properties of impedance spectrum of the cable containing local defect section can be expressed by the function z( e -2γl , e -2γdld ), wherein gamma h is the propagation coefficient of the intact part of the cable, gamma d is the propagation coefficient of the defect section of the cable, l d is the position of the defect point. Since any two functions in the orthogonal function system have similar forms and properties, and gamma d and ld are unknown numbers, but gamma h can be obtained in advance by measurement or calculation, and gamma h is a function of frequency, therefore, z( K ( f , x ) can have the following form: .

[0028] S102, based on the integral transform kernel function, construct the integral transform function corresponding to the cable head-end impedance spectrum data, obtain the cable defect diagnosis function, and determine the cable defect positioning information by the position of the mutation peak output by the cable defect diagnosis function.

[0029] In an implementation manner of the present application, for analyzing the cable impedance spectrum to realize local defect positioning, the integral transform needs to realize the conversion between the frequency domain and the spatial domain, and has the following form: ; wherein, Z l (f) is the impedance amplitude or phase spectrum of the head-end of the cable with the length of l , f up and f low are the upper and lower limits of the frequency of the impedance spectrum, K ( f , x ) is the kernel function of the integral transform, F ( x ) is the integral transform function, and the final form and characteristics of the integral transform function depend on the kernel function K ( f, x ) is selected.

[0030] F ( x ) represents the product integral of the impedance spectrum along the spatial position x of the cable and the kernel function K ( f , x ) with respect to frequency, and after the integral transform F ( x ) is determined only by the characteristics and position of the cable itself. If the value of F ( x ) has a significant difference between the defective and non-defective parts of the cable, the location of the local defect can be realized. That is, if there is a defect segment in a cable, and there is a x = l d , if there is a K ( f , x ) such that the product integral of the cable impedance spectrum Z l (f) and K ( f , x ) has a significant numerical difference between x = l d and x ≠ l d , then the local defect point can be located by drawing the function curve of F ( x ).

[0031] The numerical difference of the product integral of the two functions in the two cases is a basic characteristic of the orthogonal function system in mathematics. For a function system { f i ,… i =1,2… n}, if the product integral of any two functions in the system on a certain closed interval [ a , b ] satisfies the following relationship: ; , then the system { f i ,… i =1,2… n} is called an orthogonal function system.

[0032] The trigonometric function system is a widely used orthogonal function system, which has the following form: {1,cos xsin x sin2 x sin2 x cos nx sin nx}; The above function system is orthogonal on [-π, π], that is, the integral of the product of any two functions is zero on [-π, π], while the integral of the product of two identical functions is not zero. On this basis, the analysis of the trigonometric function f ( y ) = a cos3 y ( a is a constant) and the double variable function g ( n , y ) =cos( n , y ), ( n= 1, 2,3..... ) on [-π, π] can be obtained: ; From the properties of orthogonal functions, a generalized orthogonal theory can be extended, that is, if the product integral values of two functions under two different conditions have obvious differences, then the two functions are called generalized orthogonal functions. If a certain kernel function K (f, x), is selected Z l (f) and K(f, x) exist generalized orthogonality at x = l d , then through the integral transform function, the defect points and non-defect points can be distinguished.

[0033] Further simplification, take K ( f , x )= e -2γhx , the basic principle of realizing the positioning of local defect segment through the integral transform formula is: ; When x = l d , due to the propagation coefficient gamma d ≠ gamma h of the cable local defect segment, the above product integral value a and bThe difference is great, so the point where the cable propagation coefficient changes can be found by integral transform method, thereby realizing the positioning of the local defect point. The cable in good condition can be taken as a reference state, and its impedance spectrum can be measured before the cable is put into operation or the same type of cable is measured, or calculated by the characteristic impedance and propagation coefficient of the cable. Comparing the integral transform function of the impedance spectrum of the cable after local defect with the integral transform function of the cable in good condition can further highlight the difference between the defect section and the good part. The function is defined as VA(x) F d x F h x VA x VA x

[0034] In an implementation manner of the present application, based on the cable defect diagnosis function, a mutation peak meeting the preset mutation peak determination threshold condition is determined; the number of the mutation peaks corresponds to the number of cable defects, and the vertex of each mutation peak corresponds to the positioning position of each cable defect; wherein the cable defect positioning information at least includes one of the defect number, the defect position and the positioning confidence.

[0035] Specifically, if it is a normal state, the propagation coefficients of the cable at all positions are consistent, VA x = 1.0, and there is no mutation peak. If it is a local defect state: the propagation coefficient at the defect position gamma d ≠ gamma h VA x , a mutation peak appears at the defect position, that is, VA x The difference between the oscillation peak value deviating from 1.0 and 1.0 is defined as the mutation peak value, which represents the influence degree of the defect on the transmission characteristics of the cable, and the difference between the two intersection points of the oscillation pulse of the mutation peak and the stable value 1.0 is taken as the peak width. x

[0036] ​​​​​​​​​​​​​​​​Further, the embodiment of the present application is provided with a mutation peak judgment threshold condition to exclude noise interference. Specifically, the basic judgment threshold is: mutation peak value > 0.05 (i.e. | Δf | > 0.05). After considering the field electromagnetic interference and measurement error, it can be determined that it is a real defect signal. Sensitivity band reinforcement: preferentially select the effective points with impedance phase spectrum absolute value in the range of 5°~80° to participate in integral transformation. If the effective point ratio is > 70%, the threshold can be appropriately reduced to 0.03. If the effective point ratio is < 50%, the threshold needs to be increased to 0.08. VA ( x )-1.0∣>0.05), at this time, after considering the field electromagnetic interference and measurement error, it can be determined that it is a real defect signal. Sensitivity band reinforcement: preferentially select the effective points with impedance phase spectrum absolute value in the range of 5°~80° to participate in integral transformation, if the effective point ratio is > 70%, the threshold can be appropriately reduced to 0.03; if the effective point ratio is < 50%, the threshold needs to be increased to 0.08.

[0037] Further, the number of mutation peaks corresponding to the threshold condition of the diagnostic function is determined, that is, the number of local defects of the cable. The vertex coordinates of the mutation peak, i.e. VA ( x ) oscillation peak value, are the positioning positions of the cable defects. x

[0038] Figure 2 A diagnostic function image provided by the embodiment of the present application is shown in FIG. 1. As shown in FIG. 1, after integral transformation, Figure 2 VA ( x ) appears a sharp oscillation at 20.0 m, and a change peak point appears, which indicates that the cable propagation coefficient starts to change significantly at 20.0 m.

[0039] S103, input the obtained cable defect positioning information into the cable impedance spectrum calculation model containing the local defect section, to output the impedance spectrum calculation value through the cable impedance spectrum calculation model.

[0040] In an implementation manner of the present application, based on the positioned cable defect positions, the range and type of each defect are determined; wherein each defect section corresponds to preset defect characteristic parameters, and the preset defect characteristic parameters at least include one of the characteristic impedance of the local aging section, the characteristic impedance of the local damage section and the propagation coefficient. The cable is divided into an intact section and at least one defect section along the length direction, the intact section is assigned with initial characteristic parameters, and each defect section is assigned with preset defect characteristic parameters. The transmission line model of the intact section and the defect section is respectively constructed, the voltage transfer relationship and the current transfer relationship of each section are established through the reflection coefficient formula. Taking the cable end load as the starting point, the input impedance of each section is iteratively calculated in sequence according to the section order, and the cable head end impedance spectrum calculation value under different frequencies is output. The relative error between the cable head end impedance spectrum calculation value and the cable head end impedance spectrum measured value is determined, and the preset defect characteristic parameters corresponding to the defect section are adjusted based on the relative error until the relative error meets the preset error condition.

[0041] ​​Specifically, the defect type is determined by the correlation between the trend of changes in the diagnostic map and defect characteristics. Localized aging is classified as a gradual defect; localized damage is classified as an abrupt defect. Each defect segment corresponds to preset defect characteristic parameters: the characteristic impedance associated with the localized aging segment. Z 0d Characteristic impedance associated with locally damaged segments Z 0d and propagation coefficient gamma d The cable is divided along its length into intact sections and at least one defective section: the characteristic parameters of the intact section are the initial characteristic impedance and the propagation coefficient, and the defective section is assigned preset defect characteristic parameters, that is, the locally aged section has a preset characteristic impedance, and the locally damaged section has a preset characteristic impedance and the propagation coefficient.

[0042] Furthermore, transmission line models for intact and defective segments are constructed separately, and the voltage and current transmission relationships for each segment are established based on the reflection coefficient formula: If the characteristic impedance and propagation coefficient of the intact section of the cable are respectively Z 0h and gamma h , l The distance from the reflection point, therefore from the coordinates l a Impedance viewed from the load end Z la for: ; in Gamma 1 represents the end reflection coefficient, which is obtained by the following formula: ; From coordinates l a arrive l b This is a defective section; at this point, it can be... l a impedance at Z la Equivalent to a load, then from the coordinates l b Looking l a impedance Z lb for: ; in Gamma 2 is l a The reflection coefficient at a given location is obtained by the following formula: ; By analogy, the impedance at the beginning of the cable can be obtained as follows: ; in Gamma 3 is l b The reflection coefficient at a given location is obtained by the following formula: ; Furthermore, starting with the load at the cable end, the input impedance is iteratively calculated by sequentially substituting the load, intact end section, defective section, and intact beginning section into the transmission line model for each segment. For different frequencies, the frequency-dependent parameters of each segment are updated synchronously, outputting the calculated cable beginning impedance spectrum across the entire frequency range. Based on the relative error, the preset characteristic parameters of the defective section are adjusted. If the error exceeds the preset conditions, the characteristic impedance or propagation coefficient of the defective section is re-assumed; this iteration is repeated until the relative error meets the preset requirements. At this point, the defective characteristic parameters are those that match the actual state.

[0043] S104. Using the particle swarm optimization algorithm, the objective function for the difference between the calculated impedance spectrum value and the measured impedance spectrum value is optimized to obtain the characteristic parameters of the cable defect section.

[0044] In one implementation of this application, a difference objective function is constructed based on the sum of the absolute values ​​of the differences between the calculated and measured impedance spectrum values ​​of the cable containing the defective section. Particle swarm parameters are initialized, and the impedance spectrum is calculated based on the position parameters of each particle and the impedance spectrum calculation model of the cable containing the local defective section. The objective function value is then determined based on the impedance spectrum calculation value and used as the particle fitness. The particle velocity and position are iteratively updated according to preset velocity and position update formulas, based on the particle's own optimal position and the global optimal position. The iteration stops when the maximum number of iterations is reached or the global optimal fitness value is less than a preset threshold, and the parameter combination corresponding to the global optimal position is output as the characteristic parameters of the cable defective section.

[0045] Specifically, the objective function for optimizing the assessment of local aging conditions of cables is: ; in, Z computed ( f i )and Z measured ( f i The frequencies are respectively f i The calculated and measured impedance values ​​at that time.

[0046] If the cable contains n In the aging phase, the optimization search objective function contains 4... n One unknown quantity needs to be determined, so the particle swarm optimization algorithm is used to optimize the objective function.

[0047] Figure 3 A flowchart of a search iteration algorithm provided for embodiments of this application is shown below. Figure 3 As shown, after the process starts, particle swarm initialization is performed first. At this time, the initial positions and initial moving velocities of the particles are randomly generated. Each position corresponds to a set of candidate solutions for cable defect parameters. The fitness of each particle is calculated: the particle's position parameters are substituted into the cable impedance spectrum calculation model containing the local defect segment to obtain the calculated impedance spectrum value. Then, the objective function is constructed using the difference between the calculated and measured values; this function value is the particle fitness. The optimal solution is updated: both the individual optimal solution of each particle and the global optimal solution are updated. The particle state is iteratively updated: based on the preset velocity update formula and position update formula, combined with the individual optimal solution and the global optimal solution, the moving velocity and spatial position of each particle are updated respectively. It is checked whether the maximum number of iterations has been reached, or whether the global optimal fitness value is less than a preset threshold, i.e., the difference between the calculated and measured values ​​meets the accuracy requirements. If the termination condition is met, the global optimal solution is output. The parameter combination corresponding to this solution is the characteristic parameter of the cable defect segment, and the process ends. If not, the process returns to the particle fitness calculation step and repeats the iteration until the condition is met.

[0048] Specifically, if g (x) is the objective function to be minimized, and its independent variable is one. m The function is a vector, and the output is a real number representing the function value. There exists a group of particles in the space of independent variables, and the properties of each particle are determined by its position. p i and speed v i In this characterization, a particle's position represents a candidate solution within the search space, while its velocity represents its movement in the next iteration. The particles are assigned random positions and velocities during initialization, and each particle is assigned a fitness value. g ( p i The size of the solution is continuously updated to reflect its optimal solution. p bi At the same time, update the optimal solution for the entire particle swarm. g b Based on this, each particle determines its optimal solution. p bi and the optimal solution of particle swarm optimization g b Update its own speed, every dimension d =1… m Below, the particles are k The speed of +1 iteration cycle is determined by the following formula: ; in,delta an inertia weight between 0 and 1; c 1 and c 2 are acceleration constants, ranging between 0 and 4; r 1 and r 2 are random numbers between 0 and 1. The position of a particle is then updated with the following equation: ; The velocity of each particle in the next iteration is determined by its velocity in the current iteration and the distance of the particle from the optimal solution. In the application of cable aging state assessment, the objective function to be minimized is the difference between the calculated and measured impedance, and the position of each particle is a d l vector representing n the complex permittivity and length of the aging section. Since the impedance spectrum can be very sensitive to the changes in the operating state of the cable, by optimizing the search to minimize the difference between the calculated and measured impedance, the complex permittivity and length of the aging section obtained will be very close to the true value.

[0049] S105, based on the preset cable aging characteristic parameter threshold and the cable defect section characteristic parameter, the aging state of the local defect of the cable is determined.

[0050] In an implementation manner of the present application, the cable defect type is determined based on the parameter type corresponding to the cable defect section characteristic parameter; wherein the cable defect type at least includes one of the cable local aging defect type and the cable local damage defect type. When the cable defect type is the cable local aging defect type, the corresponding preset cable aging characteristic parameter threshold is matched based on the cable defect section characteristic parameter. The cable defect section characteristic parameter is compared with the matched preset cable aging characteristic parameter threshold, and the cable aging grade is determined based on the comparison result.

[0051] Specifically, the cable defect type is determined based on the parameter type corresponding to the cable defect section characteristic parameter. The defect section characteristic parameter corresponding to the local aging defect is the insulation complex permittivity and the dielectric loss tangent, the characteristic impedance is derived from the dielectric parameter, and only the insulation dielectric property is changed without affecting the conductor geometric structure. The defect section characteristic parameter corresponding to the local damage defect is the shielding layer damage coefficient, the damage mutual inductance coefficient, and the damage capacitance coefficient, and the characteristic impedance and the propagation coefficient are derived from the geometric structure change, which is directly related to the conductor and shielding layer structure change.

[0052] Further, when the cable defect type is the local aging defect type, the corresponding preset cable aging characteristic parameter threshold is matched. The real part of the complex permittivity increases after aging, and the dielectric loss increases significantly, based on which three threshold standards are set. For example, it can include the normal state, the light defect state, and the heavy defect state.

[0053] Further, the cable defect section characteristic parameter is compared with a matched preset cable aging characteristic parameter threshold value, and a cable aging grade is determined.

[0054] In an implementation manner of the present application, the embodiments of the present application can also apply a micro-element equivalent model to directly calculate the unit of the positioning position according to the empirical values of the complex dielectric constant of three different aging degrees, obtain the impedance spectrum change interval of the defect at different aging degrees, and judge the interval according to the field test value, so as to quickly evaluate the interval to which the cable state belongs.

[0055] Specifically, the embodiments of the present application construct an improved matlab cable micro-element equivalent model, change the complex dielectric constant under different frequencies and calculate the cable parameters of the skin effect through matlab command statements; change the calculation formula of the complex dielectric constant, and set the unit length of the micro-element equivalent model to calculate the cable impedance under different degrees of aging and different sizes of local defects.

[0056] Specifically, Figure 4 An improved cable micro-element equivalent model provided by the embodiments of the present application is shown in FIG. 1. Figure 4 R c ，L c ，R s ，L s and C I are the cable core resistance per unit length, the cable core inductance, the cable metal shielding layer resistance, the cable metal shielding layer inductance and the cable insulation capacitance, respectively.

[0057] According to IEC60287, the alternating current resistance of the conductor R AC and the direct current resistance R DC have the following relationship: wherein, y s is the skin effect factor, y p is the proximity effect factor.

[0058] In most cases x p will not exceed 2.8, and the coefficient k s and k p is obtained by experience, for the cable with XLPE as the insulation material, k s = 1,​​k p = 0.8. For single core cable, there is no proximity effect factor y p With for loop statement, change the frequency in power_cable param one by one and calculate the complex permittivity at this frequency, and get the cable parameters, according to the skin effect factor y s and proximity effect factor y p correct the resistance parameters, and only calculate the cable impedance at the corresponding frequency in impedance measurement.

[0059] In an implementation of the present application, different preset aging level complex permittivity reference values are respectively input into the cable micro-element equivalent model, and cable head-end impedance spectrum calculation values corresponding to each aging level are output, so as to obtain impedance spectrum change intervals corresponding to different aging levels. The sudden peak difference obtained from the position of the sudden peak is compared with the impedance spectrum change intervals corresponding to different aging levels, so as to determine the aging level of the cable local defect.

[0060] Specifically, different preset aging level complex permittivity reference values are respectively input into the cable micro-element equivalent model, and cable head-end impedance spectrum calculation values corresponding to each aging level are output, so as to obtain impedance spectrum change intervals of different aging levels. The sudden peak difference obtained from the position of the sudden peak is calculated, and the difference is compared with the impedance spectrum change intervals corresponding to different aging levels, so as to determine the aging level of the cable local defect. The sudden peak difference is the amplitude or phase difference of the impedance spectrum of the cable with defect and the impedance spectrum of the intact cable at the position of the sudden peak. By comparing the interval into which the difference falls, it is determined to be normal, slightly aged or severely aged.

[0061] Figure 5 A cable defect positioning and defect aging state detection device is provided for the embodiments of the present application, such as Figure 5As shown, the cable defect positioning and defect aging state detection device 200 comprises: at least one processor 201; and a memory 202 connected in communication with the at least one processor 201; wherein the memory 202 stores instructions executable by the at least one processor 201, and the instructions are executed by the at least one processor 201 to enable the at least one processor 201 to: acquire cable head-end impedance spectrum data, and construct an integral transform kernel function based on cable initial characteristic parameters; construct an integral transform function corresponding to the cable head-end impedance spectrum data based on the integral transform kernel function, obtain a cable defect diagnosis function, and determine cable defect positioning information by a position of a sudden change peak output by the cable defect diagnosis function; input the obtained cable defect positioning information into a cable impedance spectrum calculation model containing a local defect section, to output impedance spectrum calculation values by the cable impedance spectrum calculation model; optimize a difference target function corresponding to the impedance spectrum calculation values and impedance spectrum measurement values by a particle swarm algorithm, to obtain cable defect section characteristic parameters; and determine an aging state of the cable local defect based on preset cable aging characteristic parameter thresholds and the cable defect section characteristic parameters.

[0062] Each of the embodiments in the present application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other. Each of the embodiments focuses on the difference from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the part of the method embodiments.

[0063] The above only describes the embodiments of the present application and is not intended to limit the present application. The embodiments of the present application can be variously changed and modified by those skilled in the art. The modifications or replacements do not make the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for detecting a defect location and a defect aging state of a cable, characterized by, The method comprises: Obtaining cable head-end impedance spectrum data, and constructing integral transform kernel function based on initial characteristic parameters of the cable; Based on the integral transform kernel function, the integral transform function corresponding to the cable head-end impedance spectrum data is constructed to obtain the cable defect diagnosis function, and the position of the mutation peak output by the cable defect diagnosis function is determined to obtain the cable defect positioning information; The obtained cable defect positioning information is input into the cable impedance spectrum calculation model containing the local defect section, and the impedance spectrum calculation value is output by the cable impedance spectrum calculation model; The difference value target function corresponding to the impedance spectrum calculation value and the impedance spectrum measurement value is optimized by the particle swarm algorithm to obtain the characteristic parameters of the cable defect section; Based on the preset cable aging characteristic parameter threshold and the characteristic parameters of the cable defect section, the aging state of the cable local defect is determined.

2. The method of claim 1, wherein, The integral transform kernel function is constructed based on the initial characteristic parameters of the cable, specifically comprising: Based on the initial characteristic parameters of the cable, the propagation coefficient of the cable intact section is determined; Based on the propagation coefficient of the cable intact section, the integral transform kernel function is constructed: ； wherein, The integral transform function corresponding to the cable head-end impedance spectrum data is constructed based on the integral transform kernel function to obtain the cable defect diagnosis function, specifically comprising: h is the propagation coefficient for the cable perfect section, f is the measurement frequency, x is the spatial position along the cable.

3. The method of claim 1, wherein the method further comprises: The integral transform function of the cable after the local defect occurs is compared with the integral transform function of the cable in the intact state to obtain the cable defect diagnosis function: The position of the mutation peak output by the cable defect diagnosis function is determined to obtain the cable defect positioning information, specifically comprising: ； integrating the cable head-end impedance spectrum data; wherein F x is an integrating transform function, Z l f is a cable head-end impedance magnitude or phase spectrum of length l f up is an upper limit of the frequency of the impedance spectrum; f low is a lower limit of the frequency of the impedance spectrum; K f x is a kernel function of the integrating transform, which is a function of frequency f and spatial position x along the cable.​​​​​ Based on the cable defect diagnosis function, the mutation peak meeting the preset mutation peak judgment threshold condition is determined; wherein the number of the mutation peaks corresponds to the number of the cable defects, and the vertex of each mutation peak corresponds to the preliminary positioning position of each cable defect; ； wherein The cable defect positioning information at least includes one of the defect number and the defect position. x is a cable defect diagnosis function; F d x is an integral transform function of a cable having a partial defect; F h x is an integral transform function of a perfect cable.​​​ 4. The method of claim 1, wherein the method further comprises: Before the impedance spectrum calculation value is output by the cable impedance spectrum calculation model, the method further comprises: Based on the positioned cable defect position, the range and type of each defect are determined; wherein each defect section corresponds to a preset defect characteristic parameter; The cable is divided into an intact section and at least one defect section along the length direction, the initial characteristic parameters are assigned to the intact section, and the preset defect characteristic parameters are assigned to each defect section; 5. The method of claim 1, wherein the method further comprises: The transmission line model of the intact section and the defect section is constructed respectively, and the voltage transfer relationship and the current transfer relationship of each section are established by the reflection coefficient formula; Taking the cable end load as the starting point, the input impedance of each section is iteratively calculated in sequence according to the segmentation order, and the cable head-end impedance spectrum calculation value under different frequencies is output; The relative error between the cable head-end impedance spectrum calculation value and the cable head-end impedance spectrum measured value is determined, the preset defect characteristic parameters corresponding to the defect section are adjusted based on the relative error until the relative error meets the preset error condition, so as to obtain the cable impedance spectrum calculation model. The difference value function corresponding to the impedance spectrum calculation value and the measurement value is optimized by the particle swarm algorithm to obtain the characteristic parameters of the cable defect section, specifically comprising: ​ ​ 6. The method of claim 1, wherein the method further comprises: ​ A difference target function is constructed based on the sum of absolute values of differences between the calculated values and the measured values of the impedance spectrum of the cable with the defective section; Particle swarm parameters are initialized, the impedance spectrum calculation value is obtained based on the position parameters of each particle and the cable impedance spectrum calculation model with the local defect section, and the target function value is determined based on the impedance spectrum calculation value to serve as the particle fitness; The velocity and position of the particle are iteratively updated based on the preset velocity update formula and position update formula according to the optimal position of the particle itself and the global optimal position; When the maximum number of iterations is reached or the global optimal fitness value is less than the preset threshold, the iteration is stopped, and the parameter combination corresponding to the global optimal position is output as the characteristic parameter of the cable defect section.

7. The method of claim 1, wherein the method further comprises: determining the location of the defect in the cable; and determining the aging state of the defect in the cable. The aging state of the local defect of the cable is determined based on the preset cable aging characteristic parameter threshold and the characteristic parameter of the cable defect section, and specifically includes: The cable defect type is determined based on the parameter type corresponding to the characteristic parameter of the cable defect section, wherein the cable defect type at least includes one of the cable local aging defect type and the cable local damage defect type; When the cable defect type is the cable local aging defect type, the corresponding preset cable aging characteristic parameter threshold is matched based on the characteristic parameter of the cable defect section; The characteristic parameter of the cable defect section is compared with the matched preset cable aging characteristic parameter threshold, and the cable aging grade is determined based on the comparison result.

8. The method of claim 1, wherein the method further comprises: After the position of the mutation peak output by the cable defect diagnosis function determines the cable defect positioning information, the method further includes constructing a micro-element equivalent model, specifically including: A cable micro-element equivalent model is constructed based on the cable core resistance per unit length, the cable core inductance per unit length, the cable metal shielding layer resistance, the cable metal shielding layer inductance, and the cable insulation capacitance; The parameters of the cable micro-element equivalent model are updated through a loop logic for each frequency, and the number of micro-element cascades is determined according to the total length of the cable and the upper limit of the target frequency to ensure that the number of impedance spectrum extreme points in the upper limit range of the frequency is not less than a preset number. ； determining the AC resistance; wherein R AC is the AC resistance of the conductor; R DC is the DC resistance; y s is the skin effect factor, y p is the proximity effect factor; After the micro-element equivalent model is constructed, the method further includes:

9. The method of claim 8, wherein the method further comprises: Different preset aging grade complex permittivity reference values are input into the cable micro-element equivalent model, and the cable head end impedance spectrum calculation values corresponding to each aging grade are output to obtain the impedance spectrum change intervals corresponding to different aging grades respectively; The mutation peak difference obtained from the position of the mutation peak is compared with the impedance spectrum change intervals corresponding to different aging grades respectively to determine the aging grade of the local defect of the cable. The device includes a memory for storing computer program instructions and a processor for executing the program instructions, wherein when the computer program instructions are executed by the processor, the device is triggered to execute the method of any one of claims 1-9.

10. A device for detecting a defect location and a defect aging state of a cable, characterized by comprising: a cable defect location and defect aging state detecting unit according to any one of claims 1 to 9. ​

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