Cable fault diagnosis method and system based on sequence square wave excitation

Abstract

The invention discloses a cable fault diagnosis method and system based on sequence square wave excitation, and the method employs a cascade converter composed of a GaN full-bridge module to output broadband signal excitation, not only ingeniously utilizes the high-frequency characteristic of GaN, but also employs a power electronic topology to overcome the defect that a GaN element cannot bear an overlarge voltage, and improves the reliability of the cable fault diagnosis. The amplitude of the output voltage is greatly enhanced on the excitation source, the high-frequency excitation attenuation effect is overcome, the noise interference resistance of the device is enhanced, and meanwhile the portability is improved.

Description

Technical Field

[0001] The invention relates to a cable fault diagnosis method and a system thereof for sequential square wave excitation, belonging to the technical field of a cable fault diagnosis method for sequential square wave excitation. Background Art

[0002] With the improvement of new power systems, the proportion of power cables in my country has increased rapidly. However, local aging faults and damaged shielding layers of power cables are often found in power cables, which are difficult to locate using traditional engineering maintenance methods. These two types of faults can easily develop into serious local breakdown, short circuit and open circuit faults, posing a threat to the operating area. The current broadband impedance spectrum method for cable defects has better sensitivity to local faults such as cable aging. However, its accuracy depends on the accuracy and bandwidth of the cable impedance spectrum. Due to the low output excitation of the current broadband impedance measuring instrument, the high-frequency signal is greatly attenuated in the transmission line, resulting in serious distortion of the high-frequency impedance spectrum carrying rich information. In addition, there is noise interference in the measurement, so this method is limited to a certain extent. Summary of the invention

[0003] The technical problem to be solved by the present invention is to overcome the defects of the prior art and provide a cable fault diagnosis method and system with sequential square wave excitation. The method utilizes a cascade converter composed of a GaN full-bridge module to output a broadband signal excitation, which not only cleverly utilizes the high-frequency characteristics of GaN, but also utilizes the power electronic topology to overcome the disadvantage that GaN components cannot withstand excessive voltage. The amplitude of the output voltage is greatly enhanced on the excitation source, the high-frequency excitation attenuation effect is overcome, and the anti-noise interference ability is enhanced, while the portability is increased.

[0004] Preferably, the present invention provides a cable fault diagnosis method using sequential square wave excitation, comprising:

[0005] Step 1: Measure the cross-sectional geometric parameters of the target cable, including the cable conductor radius r c and the inner radius r of the cable shield s ;

[0006] Step 2: According to the microelement distributed parameter model of the coaxial transmission line, the parameters including the distributed resistance R, the distributed inductance L, the distributed capacitance C and the distributed conductance G are calculated;

[0007] Step 3: Based on the parameters including distributed resistance R, distributed inductance L, distributed capacitance C and distributed conductance G, solve the partial differential equation of the coaxial transmission line to obtain the propagation coefficient γ and characteristic impedance Z of the intact cable 0 And the first-end input impedance spectrum phase spectrum Z inD .

[0008] Preferably, step 4: using a GaN full-bridge cascade module to output a high-frequency sequence square wave excitation;

[0009] Get the current response signal I under this excitation s And the excitation voltage signal U s ;

[0010] Step 5: Use a high-frequency current sensor to convert the current response signal I s Converted into voltage signal U c , for U s Sampling to obtain discrete data set U ms , for U c Sampling to obtain discrete data set U mc ;

[0011] Using the Hanning window function to process discrete data sets U ms and discrete data set U mc :

[0012] U' ms =U ms ×Hanning(N)

[0013] U' mc =U mc ×Hanning(N)

[0014] In the formula, U' ms For U ms The discrete data set obtained after windowing, U' mc For U mc The discrete data set obtained after windowing, Hanning(N) is the Hanning window function, and N is the length of the window function;

[0015] Step 6: Discrete data set U' mc Derivative, get the current response signal I s Discrete data set form I' ms ;

[0016] Using DFT Discrete Fourier Transform to I' ms and U' ms To break it down:

[0017]

[0018] Step 7: U DFT and I DFT Extract the real and imaginary parts to obtain the broadband phase spectrum of the target cable headend input, and calculate the complex voltage V at each frequency point k after harmonic decomposition. k and current I k Plural form of:

[0019]

[0020] Where U DFT [k] is the voltage at frequency point k obtained after discrete Fourier transform, Re(U DFT [k]) is the DFT [k] takes the real part, Im(U DFT [k]) is the DFT [k] takes the imaginary part;

[0021] The impedance phase spectrum is calculated using the following formula:

[0022] θ k =arg(V k )-arg(I k )

[0023] Step 8: Determine whether there is a fault:

[0024] Judge(f)=|Z inF -θ k |,

[0025] Where Judge(f) is the fault index, Z inF is the calculated cable impedance phase spectrum under healthy conditions, θ k is the impedance phase spectrum obtained based on the above steps;

[0026] If Judge(f) is 0 in the whole frequency domain, it means that the cable is in good condition and there is no fault. Otherwise, it means there is a fault and go to step 9;

[0027] Step 9: Perform smooth fitting on the faulty cable impedance phase spectrum to obtain θ(f,l), where f is the frequency and l is the cable length. The diagnosis of the cable fault includes:

[0028] Establish the orthogonal integral function H(x) about the distance x:

[0029]

[0030] In the formula, f max is the upper limit of the sweep frequency, f min is the lower limit of the frequency sweep, σ is the Gaussian smoothing factor, G(x,σ) is the Gaussian filter function, β is the phase constant, df is the infinitesimal element of the frequency independent variable; the propagation coefficient γ=α+jβ, where α is the attenuation coefficient that characterizes the amplitude attenuation characteristics of the voltage wave and the current wave; β=2π / λ is the phase constant;

[0031] The expression of the Gaussian filter function is:

[0032]

[0033] In the formula, the propagation coefficient γ = α + jβ, where α is the attenuation coefficient that characterizes the amplitude attenuation characteristics of the voltage wave and the current wave; β = 2π / λ is the phase constant.

[0034] Preferably, a diagnostic function graph with respect to x is plotted, the fault point corresponding to the extreme point of the mutation peak of the diagnostic function graph is observed, and the fault type is determined by the polarity of the mutation peak of the diagnostic function graph.

[0035] Preferably, the polarity of the mutation peak includes minimum-maximum, maximum-minimum, "minimum-maximum" is the fault type of aging fault, "maximum-minimum" is the fault type of local defect fault, and the extreme point corresponds to the starting position or the end position of the fault.

[0036] Preferably, sampling data is obtained after sampling by an ADC sampling module;

[0037] The sampled data is used as discrete data of the host computer;

[0038] Use the sequence to perform Fourier transform to process discrete data and obtain the frequency ω corresponding to the high-frequency sequence square wave excitation m :

[0039]

[0040] Among them, 1≤m≤n, Δf is the step frequency 100Hz, ω 1 is the frequency corresponding to the first sequence square wave, ω n is the frequency corresponding to the nth sequence square wave;

[0041] The high-frequency sequence square wave excitation at each frequency is decomposed by Fourier to obtain the information corresponding to the 1st to 15th harmonics; the repeated values ​​in the information of the 1st to 15th harmonics are eliminated, and all the sweep frequency points in the impedance spectrum are arranged from small to large.

[0042] Preferably, a cable fault diagnosis system with sequential square wave excitation is used to execute any of the above methods, comprising:

[0043] It includes a GaN full-bridge cascade module, a high-frequency current sensor based on magnetic induction, a digital signal control center DSP module, an ADC sampling module and a host computer real-time image result processing module. The GaN full-bridge cascade module is electrically connected to the high-frequency current sensor and the digital signal control center DSP module, the high-frequency current sensor is electrically connected to the ADC sampling module, and the ADC sampling module is electrically connected to the host computer real-time image result processing module.

[0044] Among them, the GaN full-bridge cascade module includes a full-bridge sub-module, and the full-bridge sub-module includes a wide-bandgap semiconductor GaN switch device.

[0045] Preferably, the GaN full-bridge cascade module includes a wide bandgap semiconductor GaN HFET, and the GaN full-bridge cascade module receives a high-frequency sequence square wave excitation output after receiving a sequence PWM signal amplified by a driving circuit, and approximates the high-frequency sequence square wave excitation to a square wave U s :

[0046]

[0047] Where U dc is the DC side voltage of each submodule,

[0048] The starting frequency ω of the high-frequency sequence square wave excitation 1 The corresponding f 1 Set to 100KHz, step frequency to 100Hz, and stop frequency to 4MHz;

[0049] The Fourier transform is used to decompose the high-frequency sequence square wave excitation preset harmonics, and the impedance bandwidth is increased to 60MHz;

[0050] The Nyquist sampling theorem is used to set the sampling rate of the ADC sampling module to more than twice the highest frequency in the high-frequency sequence square wave excitation.

[0051] Preferably, the high-frequency current sensor adopts a high-frequency Rogowski coil with ultra-high bandwidth, uses a high-frequency operational amplifier integration circuit to convert the response current signal into a voltage signal, and uses the operational amplifier to compensate the phase difference to 0 before entering the ADC sampling module.

[0052] Preferably, the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any one of the methods described in the first aspect when executing the program.

[0053] Preferably, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any one of the methods described in the first aspect.

[0054] The beneficial effects achieved by the present invention are:

[0055] (1) Compared with other methods for obtaining broadband impedance spectra, this method uses a cascade converter composed of GaN full-bridge modules to output broadband signal excitation. It not only cleverly utilizes the high-frequency characteristics of GaN, but also uses power electronic topology to overcome the disadvantage that GaN components cannot withstand excessive voltage. It greatly enhances the amplitude of the output voltage on the excitation source, overcomes the high-frequency excitation attenuation effect, and enhances its own anti-noise interference ability, while increasing portability.

[0056] (2) Compared with the current signal obtained by other methods, the system of the present invention can conveniently obtain the shielding layer current by using the high-frequency Rogowski coil, without disassembling the shielding layer, thus enhancing the practicality. At the same time, the fault location function is constructed by using the impedance phase spectrum, and the Gaussian function is introduced to reduce the ripple interference wave caused by the pole misjudgment and insufficient frequency band. The present invention uses the window function to reduce the leakage of the spectrum signal before data processing, and at the same time, when obtaining the impedance spectrum by using the high-order harmonic response of the square wave signal, the frequency domain characteristics of the serial square wave can be used to extend the high-order harmonics, so that the positioning is more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solution of the present application, the drawings required for use in the embodiments are briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0058] Figure 1 It is a system structure diagram of the present invention;

[0059] Figure 2 It is a microelement distribution parameter model diagram of the coaxial cable transmission line in the present invention;

[0060] Figure 3 It is the distribution diagram of the frequency sweep points after the harmonic decomposition and arrangement of the serial square wave excitation;

[0061] Figure 4 It is an approximate diagram of the sequential square wave excitation in the present invention. DETAILED DESCRIPTION

[0062] See also Figure 1 , the present application discloses a system structure diagram of a broadband impedance measurement system and method with sequential square wave excitation, such as Figure 1 As shown, the specific steps are as follows:

[0063] Step 1: First, use a micrometer to measure the cross-sectional geometric parameters of the target cable. The cross-sectional geometric parameters of the target cable include the cable conductor radius r c and the inner radius r of the cable shield s Here we take a XLPE cable as an example and assume that the total length of the cable is L.

[0064] Step 2 Figure 2 The microelement distributed parameter model shown in the figure includes four parts: distributed resistance R, distributed inductance L, distributed capacitance C and distributed conductance G. Its electrical connection diagram is shown in Figure 2 As shown, the respective calculation formulas are as follows:

[0065] The current is conducted freely in the conductor, so the current density near the surface of the conductor is greater than that in the center of the conductor. This phenomenon is called the skin effect, which will cause the conductor inductance in the AC circuit to increase and the conductivity to decrease.

[0066] The conductor skin depth δ decreases as the frequency increases, satisfying the following relationship:

[0067]

[0068] Where μ is the magnetic permeability of the metal. For copper and aluminum metal conductors, their magnetic permeability and vacuum permeability μ 0 Similarly, σ is the conductivity, ω is the angular frequency, that is, the frequency f of the electromagnetic wave is converted into angular frequency, ω=2πf, and the unit is rad / s.

[0069] Due to the magnetic flux between the conductors, the leaving and returning currents also attract each other, which is called the proximity effect. The current through the conductor is concentrated in the area determined by the skin depth. Therefore, due to the decrease in skin depth, the effective unit length resistance of the phase conductor and the metal screen will increase with the increase of frequency. The resistance R per unit length of the cable can be approximated as:

[0070]

[0071] Where r c and r s is the phase cable conductor radius and the inner radius of the cable shield; δ c and δ s are the skin effect coefficients of the core wire and the metal shielding layer respectively; σ c and σ s is the conductivity of the conductor and shield.

[0072] The self-inductance per unit length of coaxial cable is L in It can be approximated as:

[0073]

[0074] where μ 0 is the vacuum permeability. The external inductance can be derived directly by considering the enclosed magnetic flux Φ between the center conductor and the shield in the surface s, which is caused by the current through the center conductor I (using Ampere's law for the transverse magnetic field):

[0075]

[0076] Among them B t is the transverse magnetic flux density. In composite insulated cables, semiconducting layers usually exist between the insulating material and the two conductors (phase conductor and metal screen). However, since these layers have little effect on the magnetic field, their effect on inductance can be ignored. The external inductance per unit length parameter can be described as:

[0077]

[0078] Therefore, the distributed inductance per unit length of the coaxial cable is:

[0079]

[0080] The distributed capacitance and distributed conductance correspond to the imaginary part and real part of the distributed admittance respectively:

[0081] C(ω)=imag(Y / ω)(2-7)

[0082] G(ω)=real(Y)(2-8)

[0083] Where Y is the distributed admittance, which is a function of frequency and is expressed as: Y(ω)=G(ω)+jωC(ω);

[0084] The admittance per unit length of each layer of the cable is calculated as follows:

[0085]

[0086] where Y i is the dielectric admittance of the i-th layer, ε(ω) is the complex dielectric constant of the composite insulating material, r i With r i+1 are the inner and outer radii of the i-th layer of dielectric, respectively. The total admittance of N layers of insulating dielectric is:

[0087]

[0088] The complex dielectric constant ε(ω) can be fitted by the Cole-Cole formula:

[0089]

[0090] Where A, B and p are fitting parameters respectively;

[0091] Step 3: Based on the cable distribution parameters obtained in step 2 Figure 3 The partial differential equations are established using the cable distribution parameters in the infinitesimal element. The voltage and current expressions solved using Kirchhoff's law are:

[0092]

[0093] Taking the derivative of both sides of the equation, we get:

[0094]

[0095] Solve to get the exact propagation coefficient γ and characteristic impedance Z 0 :

[0096]

[0097] The propagation coefficient γ = α + jβ, where α is the attenuation coefficient, which characterizes the amplitude attenuation characteristics of the voltage wave and the current wave; β = 2π / λ is the phase constant, which characterizes the phase change characteristics of the voltage wave and the current wave. Substituting equation (3-3) into (3-2), the solution of the second-order differential equation can be obtained as:

[0098]

[0099] By solving the transmission line equation and combining the boundary conditions, the voltage and current at any point of the transmission line can be determined. In the theoretical analysis of transmission lines, the origin of the spatial coordinate system is often taken at the load, and the positive direction points to the power supply end. If x is the distance from the load end, then formula (3-4) can be expressed at the load end (x = 0) as:

[0100]

[0101] If the load impedance is Z L ,because Substituting into (3-5) we get:

[0102]

[0103] where Γ L is the reflection coefficient at the load end, which is the ratio of the reflected voltage to the forward voltage. If the load is open circuit, the reflection coefficient is a real number 1.0. If the reflection coefficient is -1.0, Γ L Substituting into (3-5) we get:

[0104]

[0105] Based on the above formula, the input impedance at a distance x from the load end is:

[0106]

[0107] In the above formula, Z x That is, the impedance of the cable line at a distance x from the load end. Its value is the ratio of the voltage and current flowing through this point. It is a function of the cable distribution parameters and the load reflection coefficient, and has nothing to do with the external voltage and current. If x is equal to the total length of the cable l, then the input impedance expression of the cable head end is:

[0108]

[0109] The derivation of the cable head end input impedance calculation (3-10) is based on differential analysis, that is, the line is equivalent to a distributed parameter, so that the voltage and current at any point on the line can be calculated. This analysis method is not limited to the medium and high frequency bands, and the head end input impedance phase spectrum Z is obtained. inF.

[0110]

[0111] Step 4: Use the built GaN full-bridge cascade module to output high-frequency sequence square wave excitation and obtain the current response signal I under the excitation s And the excitation voltage signal U s :

[0112]

[0113] The image of the sequence square wave excitation is as follows Figure 3 As shown, the frequency corresponding to each sequence of square waves is:

[0114]

[0115] Wherein, Δf is the step frequency 100Hz.

[0116] Step 5: Decompose the discrete signal data of each sequence square wave obtained above by using DFT discrete Fourier transform, and then decompose each sequence square wave into the 15th harmonic of its frequency based on the harmonic components contained in the sequence square wave excitation. All harmonic frequencies are the sweeping points. The decomposed and reconstructed sweeping points are as follows: Figure 4 As shown, phase error is avoided. Before Fourier transform, the sampled discrete signal U ms and I ms Apply a Hanning window function to reduce spectral leakage:

[0117]

[0118] Discrete Fourier Transform:

[0119]

[0120] Step 6: Extract the real and imaginary parts of the above transformation results to obtain the cable head end and input the broadband phase spectrum. For each frequency point k after harmonic decomposition, the complex numbers of voltage and current are expressed as:

[0121]

[0122] Impedance spectrum phase expression:

[0123] θ k =arg(V k )-arg(I k )(3-17)

[0124] Step 7: Determine whether there is a fault. The judgment formula is as follows:

[0125] Judge(f)=|Z inF -θk |(3-18)

[0126] If Judge(f) is 0 in the entire frequency domain, it means that the cable is in good condition and has no faults. Otherwise, there is a fault and the process goes to step 8.

[0127] Step 8: The established diagnostic function H(x) is a function of the distance variable x. When a fault occurs at one point, different mutation peaks will appear. First, the propagation coefficient γ of a healthy cable is obtained based on steps 2 and 3.

[0128] Establish the orthogonal integral function H(x) about the distance x:

[0129]

[0130] The Gaussian filter function G(x,σ):

[0131]

[0132] Where σ is the Gaussian smoothing coefficient and β is the imaginary part of the propagation coefficient γ.

[0133] Plot the function graph of H(x) with respect to the distance variable. The local extreme point of the mutation peak in the graph is the corresponding fault point. The type of fault in the local area is determined by the transition of the polarity of the mutation peak. For example, the transition from "minimum to maximum" indicates that there is a local aging fault in the area, and the extreme point corresponds to the starting and ending position of the fault. If the transition from "maximum to minimum" occurs, a local defect fault occurs in the area, and the extreme point corresponds to the starting and ending position of the fault.

[0134] In an embodiment of the present application, the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any of the above methods when executing the program.

[0135] In an embodiment of the present application, the present invention provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of any of the above methods are implemented.

[0136] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0137] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention invented herein. This application is intended to cover any modification, use or adaptation of the present invention, which follows the general principles of the present invention and includes common knowledge or customary technical means in the art not invented by the present invention, and the specification and examples are only considered as exemplary.

[0138] The above specific implementation methods further illustrate the purpose, technical solutions and beneficial effects of the present application in detail. It should be understood that the above are only specific implementation methods of the present application and are not used to limit the protection scope of the present application. Any modifications, equivalent substitutions, improvements, etc. made on the basis of the technical solutions of the present application should be included in the protection scope of the present application.

Claims

1. A cable fault diagnosis method using sequential square wave excitation, characterized in that: include: Step 1: Measure the cross-sectional geometric parameters of the target cable; Step 2: According to the microelement distributed parameter model of the coaxial transmission line, the parameters including the distributed resistance R, the distributed inductance L, the distributed capacitance C and the distributed conductance G are calculated; Step 3: Based on the parameters including distributed resistance R, distributed inductance L, distributed capacitance C and distributed conductance G, solve the partial differential equation of the coaxial transmission line to obtain the propagation coefficient γ and characteristic impedance Z0 of the intact cable and the phase spectrum Z of the input impedance spectrum at the head end. inD .

2. A cable fault diagnosis method using sequential square wave excitation according to claim 1, characterized in that: include: Step 4: Use the GaN full-bridge cascade module to output high-frequency sequence square wave excitation; Get the current response signal I under this excitation s And the excitation voltage signal U s ; Step 5: Use a high-frequency current sensor to convert the current response signal I s Converted into voltage signal U c , for U s Sampling to obtain discrete data set U ms , for U c Sampling to obtain discrete data set U mc ; Using the Hanning window function to process discrete data sets U ms and discrete data set U mc : U' ms =U ms ×Hanning(N) U' mc =U mc ×Hanning(N) In the formula, U' ms For U ms The discrete data set obtained after windowing, U' mc For U mc The discrete data set obtained after windowing, Hanning(N) is the Hanning window function, and N is the length of the window function; Step 6: Discrete data set U' mc Derivative, get the current response signal I s Discrete data set form I' ms ; Using DFT Discrete Fourier Transform to I' ms and U' ms To break it down: Step 6: U DFT and I DFT Extract the real and imaginary parts to obtain the broadband phase spectrum of the target cable headend input, and calculate the complex voltage V at each frequency point k after harmonic decomposition. k and current I k Plural form of: Where U DFT [k] is the voltage at frequency point k obtained after discrete Fourier transform, Re(U DFT [k]) is the DFT [k] takes the real part, Im(U DFT [k]) is the DFT [k] takes the imaginary part; The impedance phase spectrum is calculated using the following formula: θ k =arg(V k )-arg(I k ) Step 7: Determine whether there is a fault: Judge(f)=|Z inF -θ k |, Where Judge(f) is the fault index, Z inF is the calculated cable impedance phase spectrum under healthy conditions, θ k is the impedance phase spectrum obtained based on the above steps; If Judge(f) is 0 in the whole frequency domain, it means that the cable is in good condition and there is no fault. Otherwise, it means there is a fault and go to step 8; Step 8: Smooth fitting of the faulty cable impedance phase spectrum is performed to obtain θ(f,l), where f is the frequency and l is the cable length. The diagnosis of the cable fault includes: Establish the orthogonal integral function H(x) about the distance x: In the formula, f max is the upper limit of the sweep frequency, f min is the lower limit of the frequency sweep, σ is the Gaussian smoothing factor, G(x,σ) is the Gaussian filter function, β is the phase constant, df is the infinitesimal element of the frequency independent variable; the propagation coefficient γ=α+jβ, where α is the attenuation coefficient that characterizes the amplitude attenuation characteristics of the voltage wave and the current wave; β=2π / λ is the phase constant; The expression of the Gaussian filter function is: In the formula, the propagation coefficient γ = α + jβ, where α is the attenuation coefficient that characterizes the amplitude attenuation characteristics of the voltage wave and the current wave; β = 2π / λ is the phase constant.

3. The cable fault diagnosis method using sequential square wave excitation according to claim 2 is characterized in that: include: Draw the diagnostic function graph about x, observe the fault point corresponding to the extreme point of the mutation peak of the diagnostic function graph, and judge the fault type by the polarity of the mutation peak of the diagnostic function graph.

4. The cable fault diagnosis method using sequential square wave excitation according to claim 3 is characterized in that: include: The polarity of the mutation peak includes minimum-maximum and maximum-minimum. "Minimum-maximum" is the fault type of aging fault, and "maximum-minimum" is the fault type of local defect fault. The extreme point corresponds to the starting position or the end position of the fault.

5. The cable fault diagnosis method using sequential square wave excitation according to claim 3 is characterized in that: include: The sampling data is obtained after sampling by using the ADC sampling module; The sampled data is used as discrete data of the host computer; Use the sequence to perform Fourier transform to process discrete data and obtain the frequency ω corresponding to the high-frequency sequence square wave excitation m : Among them, 1≤m≤n, Δf is the step frequency 100Hz, ω1 is the frequency corresponding to the first sequence square wave, ω n is the frequency corresponding to the nth sequence square wave; The high-frequency sequence square wave excitation at each frequency is decomposed by Fourier to obtain the information corresponding to the 1st to 15th harmonics; the repeated values ​​in the information of the 1st to 15th harmonics are eliminated, and all the sweep frequency points in the impedance spectrum are arranged from small to large.

6. A cable fault diagnosis system with sequential square wave excitation, characterized in that: The method for executing any one of claims 1 to 5 comprises: It includes a GaN full-bridge cascade module, a high-frequency current sensor based on magnetic induction, a digital signal control center DSP module, an ADC sampling module and a host computer real-time image result processing module. The GaN full-bridge cascade module is electrically connected to the high-frequency current sensor and the digital signal control center DSP module, the high-frequency current sensor is electrically connected to the ADC sampling module, and the ADC sampling module is electrically connected to the host computer real-time image result processing module. Among them, the GaN full-bridge cascade module includes a full-bridge sub-module, and the full-bridge sub-module includes a wide-bandgap semiconductor GaN switch device.

7. A cable fault diagnosis system with sequential square wave excitation according to claim 6, characterized in that: include: The GaN full-bridge cascade module includes a wide bandgap semiconductor GaN HFET. The GaN full-bridge cascade module receives a sequence PWM signal amplified by a driving circuit and outputs a high-frequency sequence square wave excitation, which approximates the high-frequency sequence square wave excitation to a square wave U s : Where U dc is the DC side voltage of each submodule, Set the f1 corresponding to the starting frequency ω1 of the high-frequency sequence square wave excitation to 100KHz, the step frequency to 100Hz, and the end frequency to 4MHz; The Fourier transform is used to decompose the high-frequency sequence square wave excitation preset harmonics, and the impedance bandwidth is increased to 60MHz; The Nyquist sampling theorem is used to set the sampling rate of the ADC sampling module to more than twice the highest frequency in the high-frequency sequence square wave excitation.

8. A cable fault diagnosis system with sequential square wave excitation according to claim 6, characterized in that: include: The high-frequency current sensor uses a high-frequency Rogowski coil with ultra-high bandwidth, and uses a high-frequency operational amplifier integration circuit to convert the response current signal into a voltage signal, and uses the operational amplifier to compensate the phase difference to 0 before entering the ADC sampling module.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the method according to any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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