A lightning overvoltage waveform evaluation method and device

Abstract

The present invention discloses a method and device for evaluating a lightning overvoltage waveform. The method comprises: obtaining lightning impulse test waveform data containing oscillations or overshoots, and lightning overvoltage waveform data to be measured containing oscillations or overshoots; constructing a nonlinear system of equations and an algebraic equation based on the lightning impulse test waveform data; calculating a first vector based on the nonlinear system of equations and the algebraic equation in combination with a least squares method; constructing a double exponential model based on the highest component of the first vector and the characteristic root data corresponding to the highest component; inputting the lightning overvoltage waveform data to be measured containing oscillations or overshoots into the double exponential model to obtain an evaluated lightning overvoltage waveform reference curve. The present invention, through a lightning overvoltage waveform evaluation method, effectively determines the parameters of a non-standard lightning overvoltage test wave while avoiding errors in the manual parameter determination process.

Description

Technical Field

[0001] The present invention relates to the technical field of high voltage testing, and in particular to a method and device for evaluating a lightning overvoltage waveform. Background Art

[0002] Lightning overvoltage, also known as atmospheric overvoltage, is a natural phenomenon that is uncontrolled, high in amplitude, and short in duration. It poses a significant threat to the stable operation and insulation performance of power equipment. In addition to direct lightning overvoltages on outdoor equipment, lightning overvoltages can also generate induced overvoltages. Furthermore, indoor equipment or other in-station equipment can also experience overvoltages due to lightning waves intruding from lightning strikes on transmission lines. Power generation, transmission, transformation, and distribution equipment in the power system can all be affected by lightning overvoltages, potentially causing power outages or equipment damage. To ensure that the insulation capacity of power equipment meets the requirements for withstanding lightning surges, lightning surge testing is required before equipment leaves the factory or is put into operation.

[0003] Natural lightning waves are non-periodic pulses with statistical parameters. To simulate natural lightning impulses, relevant standards such as the International Electrotechnical Commission (IEC) and national standards (GBs) specify standard lightning overvoltage waveforms. Key parameters are the wavefront time Tf, the half-peak time Tt, and the amplitude Um. The value of Um is related to the voltage level of the equipment under test. For standard lightning impulse test voltage waves, the wavefront time Tf is 1.2μs ± 30%, and the half-peak time Tt is 50μs ± 20%.

[0004] Standard lightning overvoltages are primarily generated using impulse voltage generators. In actual testing and production, the lightning overvoltage wavefront may exhibit overshoot near its peak or oscillation within the wavefront, often exhibiting waveforms that differ from the standard. International and national standards require that the recorded waveform be converted into a test voltage waveform, from which a reference curve is determined. The wavefront time Tf, half-peak time Tt, and amplitude Um parameters are manually determined from this reference curve. This reference curve can be obtained graphically by the high-voltage test operator, but this method is subject to human influence, cannot accurately and impartially measure parameters, and is difficult to digitize. Alternatively, signal processing techniques from digitally recorded data can be used to mathematically determine the parameters.

[0005] Therefore, in order to ensure that the insulation capacity of power equipment meets the requirements of withstanding lightning impulses and to solve the technical problem that the existing methods are affected by human factors and cannot accurately and impartially measure parameters, it is urgent to construct an evaluation method for lightning overvoltage waveforms. Summary of the Invention

[0006] The present invention provides a method and device for evaluating a lightning overvoltage waveform, which solves the technical problem that the existing methods are affected by human factors and cannot accurately and impartially measure parameters.

[0007] In a first aspect, the present invention provides a method for evaluating a lightning overvoltage waveform, comprising:

[0008] Acquire lightning impulse test waveform data containing oscillation or overshoot, and lightning overvoltage waveform data to be tested containing oscillation or overshoot;

[0009] Constructing a set of nonlinear equations and algebraic equations based on the lightning impulse test waveform data;

[0010] According to the nonlinear equation group and the algebraic equation, combined with the least squares method, a first vector is calculated;

[0011] constructing a double exponential model based on the highest component of the first vector and the eigenvalue data corresponding to the highest component;

[0012] The lightning overvoltage waveform data containing oscillation or overshoot to be measured is input into the double exponential model to obtain an estimated lightning overvoltage waveform reference curve.

[0013] Optionally, based on the lightning impulse test waveform data, a nonlinear equation group and an algebraic equation are constructed, including:

[0014] Measuring and sampling the lightning impulse test waveform data to obtain a sampling sample;

[0015] Based on the sampling samples, the nonlinear equation group and the algebraic equation are constructed.

[0016] Optionally, calculating the first vector according to the nonlinear equation group and the algebraic equation in combination with a least squares method includes:

[0017] Transforming the nonlinear system of equations to obtain a linear system of equations;

[0018] Calculating characteristic root data based on the linear equations and the algebraic equation using a least squares method;

[0019] The characteristic root data is input into the nonlinear equation group to obtain a first vector.

[0020] Optionally, calculating characteristic root data based on the linear equations and the algebraic equation using the least squares method includes:

[0021] Calculating based on the linear equations using a least squares method to obtain a second vector;

[0022] The second vector is input into an algebraic equation to obtain characteristic root data.

[0023] Optionally, constructing a double exponential model based on the highest component of the first vector and the eigenvalue data corresponding to the highest component includes:

[0024] determining the first vector of the highest components as the coefficients of the double exponential model;

[0025] Calculating an attenuation coefficient and an angular frequency based on the first vector of the highest component and the characteristic root data corresponding to the first vector of the highest component;

[0026] The bi-exponential model is constructed based on the first vector of the highest component, the attenuation coefficient, and the angular frequency.

[0027] In a second aspect, the present invention provides a lightning overvoltage waveform evaluation device, comprising:

[0028] An acquisition module is used to acquire lightning impulse test waveform data containing oscillation or overshoot, and lightning overvoltage waveform data to be tested containing oscillation or overshoot;

[0029] A construction module, for constructing a nonlinear equation group and an algebraic equation based on the lightning impulse test waveform data;

[0030] A calculation module, configured to calculate a first vector based on the nonlinear equation group and the algebraic equation in combination with a least squares method;

[0031] a modeling module, configured to construct a double exponential model based on a highest component of the first vector and eigenvalue data corresponding to the highest component;

[0032] The evaluation module is used to input the lightning overvoltage waveform data containing oscillation or overshoot to be measured into the double exponential model to obtain an evaluated lightning overvoltage waveform reference curve.

[0033] Optionally, the building blocks include:

[0034] A sampling submodule is used to measure and sample the lightning impulse test waveform data to obtain a sampling sample;

[0035] A construction submodule is used to construct the nonlinear equation group and the algebraic equation based on the sampling samples.

[0036] Optionally, the calculation module includes:

[0037] A transformation submodule, configured to transform the nonlinear equations to obtain a linear equations system;

[0038] A calculation submodule, configured to calculate characteristic root data based on the linear equations and the algebraic equation using a least squares method;

[0039] The input submodule is used to input the characteristic root data into the nonlinear equation group to obtain a first vector.

[0040] Optionally, the calculation submodule includes:

[0041] a calculation unit, configured to calculate based on the linear equations using a least squares method to obtain a second vector;

[0042] The input unit is used to input the second vector into the algebraic equation to obtain characteristic root data.

[0043] Optionally, the modeling module includes:

[0044] a determination submodule, configured to determine a first vector of the highest component as a coefficient of the double exponential model;

[0045] a frequency submodule, configured to calculate an attenuation coefficient and an angular frequency based on the first vector of the highest component and characteristic root data corresponding to the first vector of the highest component;

[0046] A modeling submodule is used to construct the double exponential model based on the first vector of the highest component, the attenuation coefficient and the angular frequency.

[0047] As can be seen from the above technical solution, the present invention has the following advantages: the present invention provides a method for evaluating a lightning overvoltage waveform, by obtaining lightning impulse test waveform data containing oscillations or overshoots, and lightning overvoltage waveform data containing oscillations or overshoots to be measured, and constructing a nonlinear equation system and an algebraic equation based on the lightning impulse test waveform data. According to the nonlinear equation system and the algebraic equation, combined with the least squares method, a first vector is calculated. Based on the highest component of the first vector and the characteristic root data corresponding to the highest component, a double exponential model is constructed. The lightning overvoltage waveform data containing oscillations or overshoots to be measured is input into the double exponential model to obtain an evaluated lightning overvoltage waveform reference curve. Through this lightning overvoltage waveform evaluation method, the technical problem that existing methods are affected by human factors and cannot accurately and impartially measure parameters is solved, the parameters of non-standard lightning overvoltage test waves are effectively determined, and errors in the manual parameter determination process are avoided. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0049] Figure 1 This is a flowchart of a first embodiment of a method for evaluating a lightning overvoltage waveform according to the present invention;

[0050] Figure 2 This is a flowchart of a second embodiment of a method for evaluating a lightning overvoltage waveform according to the present invention;

[0051] Figure 3 Schematic diagram of a curve of a lightning overvoltage waveform before and after signal processing in a method for evaluating a lightning overvoltage waveform of the present invention;

[0052] Figure 4 The figure is a structural block diagram of an embodiment of a lightning overvoltage waveform evaluation device of the present invention. DETAILED DESCRIPTION

[0053] The embodiments of the present invention provide a method and device for evaluating a lightning overvoltage waveform, which are used to solve the technical problem that existing methods are affected by human factors and cannot accurately and impartially measure parameters.

[0054] In order to make the purpose, features, and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0055] For example 1, please refer to Figure 1 , Figure 1 This is a flowchart of a first embodiment of a method for evaluating a lightning overvoltage waveform according to the present invention, comprising:

[0056] Step S101, obtaining lightning impulse test waveform data containing oscillation or overshoot, and lightning overvoltage waveform data to be tested containing oscillation or overshoot;

[0057] Step S102, constructing a nonlinear equation group and an algebraic equation based on the lightning impulse test waveform data;

[0058] Step S103, calculating a first vector based on the nonlinear equation group and the algebraic equation in combination with the least squares method;

[0059] Step S104: constructing a double exponential model based on the highest component of the first vector and the eigenvalue data corresponding to the highest component;

[0060] Step S105 : inputting the lightning overvoltage waveform data containing oscillation or overshoot to be measured into the double exponential model to obtain an estimated lightning overvoltage waveform reference curve.

[0061] A lightning overvoltage waveform evaluation method provided in an embodiment of the present invention obtains lightning impulse test waveform data containing oscillations or overshoots, as well as lightning overvoltage waveform data to be measured containing oscillations or overshoots. Based on the lightning impulse test waveform data, a nonlinear system of equations and an algebraic equation are constructed. A first vector is calculated using the nonlinear system of equations and the algebraic equation in combination with the least squares method. A double exponential model is constructed based on the highest component of the first vector and the eigenvalue data corresponding to the highest component. The lightning overvoltage waveform data to be measured containing oscillations or overshoots is input into the double exponential model to obtain an evaluated lightning overvoltage waveform reference curve. This lightning overvoltage waveform evaluation method solves the technical problem that existing methods are affected by human factors and cannot accurately and impartially measure parameters. The parameters of non-standard lightning overvoltage test waves are effectively determined, while avoiding errors in the manual parameter determination process.

[0062] For example 2, please refer to Figure 2 , Figure 2 The present invention is a flowchart of a method for evaluating a lightning overvoltage waveform, comprising:

[0063] Step S201, obtaining lightning impulse test waveform data containing oscillation or overshoot, and lightning overvoltage waveform data to be tested containing oscillation or overshoot;

[0064] In the embodiment of the present invention, lightning impulse test waveform data containing oscillation or overshoot and lightning overvoltage waveform data to be tested containing oscillation or overshoot are obtained.

[0065] In a specific implementation, lightning impulse test waveform data containing oscillation or overshoot and lightning overvoltage waveform data to be measured containing oscillation or overshoot are obtained, and their expressions are constructed as an exponential component model.

[0066] The exponential component model constructed is specifically as follows:

[0067]

[0068] Among them, x(k) is the kth sampling sample, the value range of k is 0 to N-1, N is the number of sampling points, the corresponding sampling result is x(k), there are N sampling points in total, B is the n-dimensional coefficient vector, where

[0069] Step S202, measuring and sampling the lightning impulse test waveform data to obtain a sample;

[0070] In the embodiment of the present invention, the lightning impulse test waveform data is measured and sampled through a voltage divider to obtain sampled samples, and the number of samples is N.

[0071] Step S203, constructing a nonlinear equation system and an algebraic equation based on the sampled samples;

[0072] In an embodiment of the present invention, based on the sampling sample, a system of equations including N equations about the first vector B and the characteristic root z is written, and the characteristic root z satisfies the algebraic equation containing the second vector A.

[0073] In a specific implementation, the nonlinear equations are specifically:

[0074]

[0075] The algebraic equation is specifically:

[0076] a1z n +a2z n-1 +…+a n z = 0;

[0077] Among them, B is the n-dimensional coefficient vector, a1~a n is the intermediate coefficient.

[0078] Step S204, transforming the nonlinear equation system to obtain a linear equation system;

[0079] In an embodiment of the present invention, the nonlinear system of equations is transformed into a linear system of equations.

[0080] In a specific implementation, the linear equations are specifically:

[0081] x k =a1x(k-1)+a2x(k-2)+...+a n x(kn);

[0082] Among them, x k is the kth sample, a1~a n is the intermediate coefficient, the value range of k is 0 to N-1, and N is the number of sampling points.

[0083] Repeat the transformation of the nonlinear equation group Nn times, k = n ~ N-1, to form an Nn-variable linear equation group.

[0084] Step S205, using the least squares method, based on the linear equations and the algebraic equation, calculate the characteristic root data;

[0085] In an optional embodiment, the least squares method is used to calculate the characteristic root data based on the linear equation system and the algebraic equation, including:

[0086] Calculating based on the linear equations using a least squares method to obtain a second vector;

[0087] The second vector is input into an algebraic equation to obtain characteristic root data.

[0088] In an embodiment of the present invention, a least squares method is used to perform calculations based on the linear equations to obtain a second vector, and the second vector is input into an algebraic equation to obtain characteristic root data.

[0089] In the specific implementation, the linear equations of the above steps can be obtained by the least square method to obtain a1~a n The solution is the second vector A of order n.

[0090] Substitute the solved second vector A into a1z n +a2z n-1 +…+a n When z=0, we can solve the characteristic roots z1~z n .

[0091] Step S206, inputting the characteristic root data into the nonlinear equation system to obtain a first vector;

[0092] In an embodiment of the present invention, the characteristic root data is input into the nonlinear equation group to obtain a first vector.

[0093] In the specific implementation, the characteristic roots z1~z n . Substitute the nonlinear equations obtained in the previous step and solve the n-order first vector B as B1~B n .

[0094] Step S207, determining the first vector with the highest component as the coefficient of the double exponential model;

[0095] In the embodiment of the present invention, the highest component of the first vector B is taken as the coefficient of the double exponential model.

[0096] Step S208, calculating an attenuation coefficient and an angular frequency based on the first vector of the highest component and the characteristic root data corresponding to the first vector of the highest component;

[0097] In the embodiment of the present invention, the attenuation coefficient and the angular frequency are obtained by calculating the first vector B of the highest component and its corresponding characteristic root z.

[0098] Step S209, constructing the double exponential model based on the first vector of the highest component, the attenuation coefficient and the angular frequency;

[0099] In an embodiment of the present invention, a double exponential model is constructed according to the first vector based on the highest component, the attenuation coefficient and the angular frequency.

[0100] In a specific implementation, the first vector B1 and the first vector B2, as well as the corresponding characteristic roots z1 and z2, are taken to construct a double exponential model.

[0101] The double exponential model is obtained as follows:

[0102]

[0103] Among them, x k is the kth sample, a1~a n is the intermediate coefficient, k ranges from 0 to N-1, N is the number of sampling points, B is the n-dimensional coefficient vector, λ i =log(z i / Δt)=α i ±jω i .

[0104] See also Figure 3 , Figure 3 Schematic diagram of the curve of the lightning overvoltage waveform before and after signal processing in a lightning overvoltage waveform evaluation method of the present invention; wherein the double exponential model is a reference curve expression obtained after processing the lightning impulse test waveform containing oscillation or overshoot, and the wavefront time T of the reference curve f and half-peak time T t , and the amplitude U m It can be used as the parameter of the actual lightning impulse test waveform.

[0105] Step S210, inputting the lightning overvoltage waveform data containing oscillation or overshoot to be measured into the double exponential model to obtain an estimated lightning overvoltage waveform reference curve;

[0106] In an embodiment of the present invention, the lightning impulse test waveform data containing oscillation or overshoot to be measured is input into the double exponential model to obtain a reference curve expression of the processed lightning impulse test waveform containing oscillation or overshoot.

[0107] A lightning overvoltage waveform evaluation method provided in an embodiment of the present invention obtains lightning impulse test waveform data containing oscillations or overshoots, as well as lightning overvoltage waveform data to be measured containing oscillations or overshoots. Based on the lightning impulse test waveform data, a nonlinear system of equations and an algebraic equation are constructed. A first vector is calculated using the nonlinear system of equations and the algebraic equation in combination with the least squares method. A double exponential model is constructed based on the highest component of the first vector and the eigenvalue data corresponding to the highest component. The lightning overvoltage waveform data to be measured containing oscillations or overshoots is input into the double exponential model to obtain an evaluated lightning overvoltage waveform reference curve. This lightning overvoltage waveform evaluation method solves the technical problem that existing methods are affected by human factors and cannot accurately and impartially measure parameters. The parameters of non-standard lightning overvoltage test waves are effectively determined, while avoiding errors in the manual parameter determination process.

[0108] See also Figure 4 , Figure 4 This is a structural block diagram of an embodiment of a lightning overvoltage waveform evaluation device of the present invention, comprising:

[0109] An acquisition module 401 is used to acquire lightning impulse test waveform data containing oscillation or overshoot, and lightning overvoltage waveform data to be tested containing oscillation or overshoot;

[0110] A construction module 402 is used to construct a nonlinear equation group and an algebraic equation based on the lightning impulse test waveform data;

[0111] A calculation module 403 is configured to calculate a first vector based on the nonlinear equation group and the algebraic equation in combination with a least squares method;

[0112] A calculation module 404 is configured to construct a double exponential model based on the highest component of the first vector and the eigenvalue data corresponding to the highest component;

[0113] The evaluation module 405 is configured to input the lightning overvoltage waveform data containing oscillation or overshoot to be measured into the double exponential model to obtain an evaluated lightning overvoltage waveform reference curve.

[0114] In an optional embodiment, the building module 402 includes:

[0115] A sampling submodule is used to measure and sample the lightning impulse test waveform data to obtain a sampling sample;

[0116] A construction submodule is used to construct the nonlinear equation group and the algebraic equation based on the sampling samples.

[0117] In an optional embodiment, the calculation module 403 includes:

[0118] A transformation submodule, configured to transform the nonlinear equations to obtain a linear equations system;

[0119] A calculation submodule, configured to calculate characteristic root data based on the linear equations and the algebraic equation using a least squares method;

[0120] The input submodule is used to input the characteristic root data into the nonlinear equation group to obtain a first vector.

[0121] In an optional embodiment, the calculation submodule includes:

[0122] a calculation unit, configured to calculate based on the linear equations using a least squares method to obtain a second vector;

[0123] The input unit is used to input the second vector into the algebraic equation to obtain characteristic root data.

[0124] In an optional embodiment, the modeling module 404 includes:

[0125] a determination submodule, configured to determine a first vector of the highest component as a coefficient of the double exponential model;

[0126] a frequency submodule, configured to calculate an attenuation coefficient and an angular frequency based on the first vector of the highest component and characteristic root data corresponding to the first vector of the highest component;

[0127] A modeling submodule is used to construct the double exponential model based on the first vector of the highest component, the attenuation coefficient and the angular frequency.

[0128] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0129] In the several embodiments provided in this application, it should be understood that the methods and devices disclosed in the present invention can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection of some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0130] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0131] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0132] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a readable storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned readable storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0133] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments can still be modified, or some of the technical features thereof can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating a lightning overvoltage waveform, characterized in that: include: Acquire lightning impulse test waveform data containing oscillation or overshoot, and lightning overvoltage waveform data to be tested containing oscillation or overshoot; Constructing a set of nonlinear equations and algebraic equations based on the lightning impulse test waveform data; According to the nonlinear equation group and the algebraic equation, combined with the least squares method, a first vector is calculated; constructing a double exponential model based on the highest component of the first vector and the eigenvalue data corresponding to the highest component; Inputting the lightning overvoltage waveform data containing oscillation or overshoot to be measured into the double exponential model to obtain a lightning overvoltage waveform reference curve for evaluation; According to the nonlinear equation group and the algebraic equation, combined with the least squares method, a first vector is calculated, including: Transforming the nonlinear system of equations to obtain a linear system of equations; Calculating characteristic root data based on the linear equations and the algebraic equation using a least squares method; Inputting the characteristic root data into the nonlinear equation group to obtain a first vector; The least squares method is used to calculate characteristic root data based on the linear equations and the algebraic equation, including: Calculating based on the linear equations using a least squares method to obtain a second vector; Inputting the second vector into an algebraic equation to obtain characteristic root data; Constructing a double exponential model based on the highest component of the first vector and the eigenvalue data corresponding to the highest component, including: determining the first vector of the highest components as the coefficients of the double exponential model; Calculating an attenuation coefficient and an angular frequency based on the first vector of the highest component and the characteristic root data corresponding to the first vector of the highest component; The bi-exponential model is constructed based on the first vector of the highest component, the attenuation coefficient, and the angular frequency.

2. The method for evaluating a lightning overvoltage waveform according to claim 1, wherein: Based on the lightning impulse test waveform data, a nonlinear equation group and an algebraic equation are constructed, including: Measuring and sampling the lightning impulse test waveform data to obtain a sampling sample; Based on the sampling samples, the nonlinear equation group and the algebraic equation are constructed.

3. A lightning overvoltage waveform evaluation device, characterized in that: include: An acquisition module is used to acquire lightning impulse test waveform data containing oscillation or overshoot, and lightning overvoltage waveform data to be tested containing oscillation or overshoot; A construction module, for constructing a nonlinear equation group and an algebraic equation based on the lightning impulse test waveform data; A calculation module, configured to calculate a first vector based on the nonlinear equation group and the algebraic equation in combination with a least squares method; a modeling module, configured to construct a double exponential model based on a highest component of the first vector and eigenvalue data corresponding to the highest component; An evaluation module, configured to input the lightning overvoltage waveform data containing oscillation or overshoot to be measured into the double exponential model to obtain an evaluated lightning overvoltage waveform reference curve; The calculation module includes: A transformation submodule, configured to transform the nonlinear equations to obtain a linear equations system; A calculation submodule, configured to calculate characteristic root data based on the linear equations and the algebraic equation using a least squares method; An input submodule, configured to input the characteristic root data into the nonlinear equation group to obtain a first vector; The calculation submodule includes: a calculation unit, configured to calculate based on the linear equations using a least squares method to obtain a second vector; An input unit, configured to input the second vector into an algebraic equation to obtain characteristic root data; The modeling module includes: a determination submodule, configured to determine a first vector of the highest component as a coefficient of the double exponential model; a frequency submodule, configured to calculate an attenuation coefficient and an angular frequency based on the first vector of the highest component and characteristic root data corresponding to the first vector of the highest component; A modeling submodule is used to construct the double exponential model based on the first vector of the highest component, the attenuation coefficient and the angular frequency.

4. The lightning overvoltage waveform evaluation device according to claim 3, characterized in that: The building blocks include: A sampling submodule is used to measure and sample the lightning impulse test waveform data to obtain a sampling sample; A construction submodule is used to construct the nonlinear equation group and the algebraic equation based on the sampling samples.

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