A comprehensive analysis method for lightning disaster-causing factors on high-speed railways

Abstract

The present invention discloses a comprehensive analysis method for the hazard factors of lightning disasters on high-speed railways. The present invention introduces a lightning current intensity grading strategy, comprehensively considers multiple key dimensions such as the lightning frequency, lightning current wave head steepness, adjacent lightning return stroke time interval, and the precise position of lightning relative to the transmission line T line and the feeder line F line under each level of lightning current intensity, performs comprehensive calculations, and uses fuzzy operation technology to fuse these multi-dimensional data to generate vector results with evaluation significance, thereby achieving accurate quantification of the numerical values ​​of the hazard factors. The present invention significantly improves the accuracy of the analysis of the hazard factors of lightning disasters on high-speed railways, effectively avoids the problem of large errors in the calculation of hazard factors in traditional methods, and achieves in-depth optimization of the analysis process. The present invention provides a more scientific and effective guidance scheme for the formulation of high-speed railway lightning disaster defense strategies, and effectively enhances the lightning protection capability and operational safety of high-speed railway systems.

Description

Technical Field

[0001] The present invention belongs to the technical field of meteorological disaster prevention, and in particular relates to a comprehensive analysis method of disaster-causing factors of lightning disasters on high-speed railways. Background Art

[0002] According to the scientific theory of meteorological disaster risk assessment, the formation of lightning disasters on high-speed railways is mainly affected by three core factors: disaster-causing factors, disaster-prone environments, and carriers. Disaster-causing factors specifically refer to lightning weather indicators. In the past, when calculating disaster-causing factors, the main focus was on the cumulative probability of lightning frequency and lightning current amplitude, and simply weighted the average lightning current intensity and the frequency of ground flashes. However, this method has two significant problems:

[0003] There is a lack of detailed analysis of the intensity of lightning current for direct lightning strikes on high-speed railways. Compared with bypass strikes, the impact of lightning on high-speed railways focuses more on direct lightning strikes. The intensity of lightning current directly determines the severity of lightning damage. Strong lightning currents may directly hit the wires and pillars of the contact network, causing insulators to burst, and strong electromagnetic pulses may even instantly destroy sensitive electronic components in signal equipment. In contrast, although the frequency of small current lightning may be high, the probability of it causing direct lightning strikes is relatively small. Studies have shown that the intensity of lightning current has a significant impact on the probability of direct lightning strikes on high-speed railways. Specifically, the greater the lightning current intensity, the greater the probability of direct lightning damage. For example, the probability of lightning exceeding 50kA causing an impact on the contact network of a high-speed railway is much greater than that of lightning of 10kA.

[0004] The short-term impulse performance of lightning has not been fully considered. If multiple lightning impulses occur continuously in a short period of time, the arrester may accelerate aging and damage due to frequent actions. In some cases, although the contact network will automatically reclose to restore power supply after tripping, multiple lightning impulses in a short period of time may make the fault situation more complicated, thereby reducing the success rate of reclosing. At the same time, multiple lightning impulses in a short period of time may also cause the contact network insulators to frequently withstand overvoltage, increase the risk of flashover, and thus reduce the reliability and availability of the high-speed rail system. In addition, when the rate of rise of the lightning impulse voltage is fast, the lightning wave will cause the equipment voltage to rise rapidly in a very short period of time, which may cause the contact network insulation to be broken down.

[0005] Therefore, when deeply analyzing the causative factors of lightning disasters on high-speed railways, it is particularly important to accurately evaluate the impact of lightning current intensity and comprehensively consider the damage that short-term lightning impulses may cause to the contact network. This is also the core problem that the present invention is committed to solving. Accurate analysis of lightning causative factors can provide a solid scientific basis for the risk assessment of lightning disasters on high-speed railway equipment and systems, and lay a solid foundation for the formulation of targeted lightning protection design strategies, thereby comprehensively improving the safety and reliability of high-speed railway operations. Summary of the invention

[0006] Purpose of the invention: In view of the above-mentioned existing problems and shortcomings, the purpose of the present invention is to provide a comprehensive analysis method for the hazard factors of lightning disasters on high-speed railways, which comprehensively considers the influence of lightning current intensity level and short-term lightning impulse on the high-speed railway contact network, significantly improves the accuracy of the analysis of hazard factors of lightning disasters on high-speed railways, effectively avoids the problem of large errors in the calculation of hazard factors in traditional methods, and realizes the deep optimization of the analysis process.

[0007] Technical solution: To achieve the above invention purpose, the present invention adopts the following technical solution: A comprehensive analysis method of the hazard factors of lightning disasters on high-speed railways, comprising the following steps:

[0008] S1, collect lightning records occurring along the high-speed railway, and sort them into 5 lightning current intensity levels according to the lightning current intensity;

[0009] S2, dividing the high-speed railway into several grids of 1km*1km, obtaining the short-time lightning impulse index of each grid by statistics, and sorting the short-time lightning impulse index by size and subdividing them into 5 levels;

[0010] The short-term lightning impulse indicators include lightning frequency, lightning current wave head steepness, adjacent lightning return stroke interval, lightning relative to the transmission line precise position, lightning relative to the feeder precise position;

[0011] S3, establish a short-time lightning impulse index membership matrix: under the lightning current intensity level j, according to the five short-time lightning impulse index levels, calculate the short-time lightning impulse index membership value matrix of all grids respectively;

[0012] S4, based on the entropy method and the historical short-time lightning impulse index data of the grid along the high-speed railway, the weight vector W corresponding to the short-time lightning impulse index is calculated, and the comprehensive membership vector L of the short-time lightning impulse index under the lightning current intensity level j is obtained through the fuzzy transformation algorithm j , ;

[0013] Then, the comprehensive membership vector of the short-time lightning impulse index of each grid under other lightning current intensity levels is completed, so as to obtain the comprehensive membership vector L of the short-time lightning impulse index under different lightning current intensities;

[0014] S5, the comprehensive evaluation result D of 5 different short-time lightning impulse indicators under the jth lightning current intensity level is calculated by weighted average method j ; Finally, based on the comprehensive evaluation results D j , and construct a comprehensive evaluation model for disaster-causing factors.

[0015] Furthermore, after the lightning current intensities described in step S1 are sorted, they are divided into five levels according to the 30th percentile, 50th percentile, 70th percentile, and 90th percentile of the ranking.

[0016] Furthermore, the five-level classification method of the short-term lightning impulse index in step S2 is as follows:

[0017] (1) First, count and calculate the lightning frequency value in each grid and sort them by size;

[0018] (2) Select the percentile as k, , and the kth percentile classification threshold P is calculated by the following formula k ,

[0019] ,

[0020] In the formula, N represents the number of lightning frequencies, and q represents the number of integer digits; P q Indicates q The value of lightning frequency corresponding to the percentile; P q-1 Indicates q-1 The value of lightning frequency corresponding to the percentile; P k represents the grading threshold of the kth percentile, corresponding to P 30 , P 50 , P 70 , P 90 ;

[0021] (3) Press (0, P 30 ],(P 30 , P 50 ],(P 50 , P 70 ],(P 70 , P 90 ],(P 90 , 100] divide the lightning frequency into corresponding levels i, i = 1, 2, 3, 4, 5;

[0022] (4) Referring to steps (1) to (3), the remaining four short-duration lightning impulse indicators are divided into five levels.

[0023] Furthermore, the calculation of the short-time lightning impulse index membership value matrix in step S3 includes the following steps:

[0024] (1) Select the median of the five levels of short-term lightning impulse index as the reference point v, , are the median values ​​of each short-time lightning impulse index at level i, i=1, 2, 3, 4, 5;

[0025] (2) For different short-term lightning impulse indicators, the respective membership degrees are calculated according to the following function: ,

[0026] The membership degree of lightning frequency and lightning current wave head steepness is calculated using the following formula:

[0027] When the level of short-time lightning impulse index i=1,

[0028] ,

[0029] When the level of short-time lightning impulse index is i=2,3,4,

[0030] ,

[0031] When the level of short-time lightning impulse index i=5,

[0032] ,

[0033] The membership of the time interval between adjacent lightning return strokes, the precise position of lightning relative to the transmission line, and the precise position of lightning relative to the feeder is calculated using the following formula:

[0034] When the level of short-time lightning impulse index i=5,

[0035] ,

[0036] When the level of short-time lightning impulse index is i=2,3,4,

[0037] ,

[0038] When the level of short-time lightning impulse index i=1,

[0039] ,

[0040] In the formula, is the actual value of the short-time lightning impulse index, is the membership of the short-time lightning impulse index level i with the lightning current intensity level j. After the above calculation, the membership vectors of the five short-time lightning impulse indicators are obtained, and the membership matrix μ of the five indicators is constructed.

[0041] Furthermore, the specific process of calculating the comprehensive membership vector L in step S4 is as follows:

[0042] Firstly, according to the short-time lightning impulse index data collected from the grids along the high-speed railway, the weight vector W of each short-time lightning impulse index is calculated by the entropy method;

[0043] Then, through fuzzy change synthesis operation, the weight vector W of each short-time lightning impulse index under different lightning current intensity level j is combined with the corresponding membership matrix μ to obtain the comprehensive membership vector L of each short-time lightning impulse index under different lightning current intensity level j. j , L j =μ*W, , They respectively represent the comprehensive membership of the short-time lightning impulse index under the lightning current intensity level j in the five levels.

[0044] Furthermore, the comprehensive evaluation result D in step S5 j It is calculated by the following formula:

[0045] ,

[0046] Next, the comprehensive evaluation model of disaster factors is constructed according to the following formula:

[0047] ,

[0048] In the formula, R represents the disaster factor value; j represents the lightning current intensity level; D j It is the comprehensive evaluation result of short-time lightning impulse index under lightning current intensity level j;

[0049] Finally, the disaster factor values ​​in all grids along the high-speed railway are calculated to form the disaster factor grid data of the entire line.

[0050] Furthermore, the lightning records collected in step S1 that occur along the high-speed railway are within a range of 0.5 km on both sides of the high-speed railway.

[0051] Beneficial effects: Compared with the prior art, the present invention has the following advantages: (1) The present invention innovatively proposes a refined analysis method for the hazard factors of lightning disasters on high-speed railways. This method comprehensively considers the lightning current intensity level and the impact of short-term lightning impulses on the contact network, significantly improving the accuracy of the analysis of the hazard factors of lightning disasters on high-speed railways, effectively avoiding the problem of large errors in the calculation of hazard factors in traditional methods, and achieving in-depth optimization of the analysis process.

[0052] (2) The method provided by the present invention comprehensively and deeply considers the complex impacts that lightning current intensity and short-term lightning impulses may have on the high-speed railway system. By accurately capturing and analyzing the patterns of lightning activities along the high-speed railway and its potential impacts, it provides a more scientific and effective guidance for the formulation of lightning defense strategies for high-speed railways, and effectively enhances the lightning protection capability and operational safety of the high-speed railway system. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1The present invention is a logic flow chart of the comprehensive analysis method of the hazard factors of high-speed railway lightning disasters. DETAILED DESCRIPTION

[0054] The present invention is further explained below in conjunction with the accompanying drawings and specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention. After reading the present invention, various equivalent forms of modifications to the present invention by those skilled in the art all fall within the scope defined by the claims attached to this application.

[0055] like Figure 1 As shown, the present invention innovatively proposes a calculation method for accurately quantifying the impact of lightning on the contact network of high-speed railways. This method introduces a lightning current intensity grading strategy, comprehensively considers multiple key dimensions such as the lightning frequency, lightning current wave head steepness, adjacent lightning return stroke time interval, and the precise position of lightning relative to the transmission line (T line) and feeder (F line) under each level of lightning current intensity, and performs a comprehensive calculation. Then, fuzzy operation technology is used to fuse these multi-dimensional data to generate vector results with evaluation significance, thereby achieving accurate quantification of the numerical value of the disaster-causing factor. The specific steps for implementing this method mainly include: S1 lightning current intensity level division; S2 short-term lightning impulse index calculation; S3 construction of a comprehensive evaluation model for disaster-causing factors.

[0056] S1, lightning current intensity level classification

[0057] (1) Data collection and collation: lightning records occurring within a range of 0.5 km on both sides of the high-speed railway are collected, and lightning records with lightning current intensity ≤ 5 kA or lightning current intensity ≥ 200 kA are eliminated to form a data set;

[0058] (2) Count the lightning current intensity values ​​in the statistics and sort them by size;

[0059] (3) Select the percentile as k, , and the kth percentile classification threshold P is calculated by the following formula k ,

[0060] ,

[0061] In the formula, N represents the number of lightning records, q represents the number of integer digits, and k represents the selected percentile. ;P k represents the grading threshold of the kth percentile, corresponding to P 30 , P 50 , P 70 , P 90 ;

[0062] (4) Press (0, P 30 ],(P30 , P 50 ],(P 50 , P 70 ],(P 70 , P 90 ],(P 90 , 100] divide the lightning records into corresponding levels j, j = 1, 2, 3, 4, 5, as shown in Table 1.

[0063] Table 1 Lightning current intensity levels

[0064]

[0065] S2, short-time lightning impulse index calculation:

[0066] (1) Determine the short-term lightning impulse indicators and levels: Divide the high-speed railway line into 1km*1km grid areas, and count the short-term lightning impulse indicators at each lightning current intensity level for each grid, including: lightning frequency, lightning current wave head steepness, time interval between adjacent lightning return strokes, precise position of lightning relative to the transmission line (T line), precise position of lightning relative to the feeder line (F line). Each short-term lightning impulse indicator of all grids along the railway is subdivided into five levels according to percentiles (P30, P50, P70, P90). The grading method is the same as the lightning current intensity grading method.

[0067] (2) Establishing the membership matrix of short-time lightning impulse index: For different lightning current intensity levels, the membership values ​​of various short-time lightning impulse indexes are calculated according to a 1km*1km grid. In the calculation process, the present invention adopts different types of membership functions to adapt to the characteristics of different indicators. Specifically, the lightning frequency membership and the lightning current wave head steepness membership are calculated based on extremely small membership functions, because these indicators are usually expected to have values ​​as small as possible. The membership of the time interval between adjacent lightning return strokes, the membership of the precise position of lightning relative to the T line, and the membership of the precise position of lightning relative to the F line are calculated based on extremely large membership functions, because these indicators are usually expected to have values ​​as large as possible.

[0068] In order to quantify these memberships more accurately, the present invention selects the median of the five level intervals of the short-term lightning impulse index as the reference point v, , They are the median values ​​of each short-time lightning impulse index at level i, i=1, 2, 3, 4, 5. For extremely small membership indexes, the following calculation function is used to determine its membership value:

[0069] When the value of the short-time lightning impulse index is at the lowest level (i=1):

[0070] ,

[0071] When the short-term lightning impulse index is at the intermediate level (i=2,3,4):

[0072] ,

[0073] When the short-duration lightning impulse index is at the highest level (i=5):

[0074] ,

[0075] For extremely large membership indices, the following calculation function is used to determine its membership value:

[0076] When the value of the short-time lightning impulse index is at the highest level (i=5):

[0077] ,

[0078] When the value of the short-time lightning impulse index is at the intermediate level (i=2,3,4):

[0079] ,

[0080] When the value of the short-time lightning impulse index is at the lowest level (i=1):

[0081] ,

[0082] In the formula, is the actual value of the short-time lightning impulse index, is the membership of the short-time lightning impulse index level i with the lightning current intensity level j. After the above calculation, the membership vectors of the five short-time lightning impulse indicators are obtained, and the membership matrix μ of the five indicators is constructed.

[0083] (3) Calculate the comprehensive membership vector of short-term lightning impulse indicators: Following the principle of the entropy method, relying on the grid lightning indicators (lightning frequency, lightning current wave head steepness, time interval between adjacent lightning return strokes, precise position of lightning relative to the T line, precise position of lightning relative to the F line) data collected along the high-speed railway, calculate the weight vector W corresponding to each short-term lightning impulse indicator. The entropy method calculation method is as follows:

[0084] First, the samples of various short-term lightning impulse indicators are standardized, among which: lightning frequency and lightning current wave head steepness are positive indicators, and the time interval between adjacent lightning return strokes, the precise position of lightning relative to the T line, and the precise position of lightning relative to the F line are negative indicators. The normalization formula for positive indicator data is:

[0085] ,

[0086] The standardized formula for the negative indicator is:

[0087] ,

[0088] In the formula, m is the number of samples, x is the sample value, and y is the standardized result;

[0089] Next, the entropy value of each indicator is calculated according to the following formula:

[0090] ,

[0091] Based on this, the index difference coefficient is calculated according to the formula g=1-e; finally, the weight of the short-time lightning impulse index is calculated according to the following formula:

[0092] ,

[0093] And form a weight vector W={W z}, where z = 1, 2, 3, 4, 5. Finally, the weight vector W is combined with the membership matrix μ of the five lightning indicators using the synthetic operation formula of fuzzy transformation: , the comprehensive membership vector L of the short-time lightning impulse index is obtained, where μ is the membership matrix of the short-time lightning impulse index, and W is the weight vector of the short-time lightning impulse index.

[0094] S3, build a comprehensive evaluation model for disaster factors

[0095] The comprehensive membership vector of short-term lightning impulse indicators under different lightning current intensity levels is: ,in, They represent the membership of the short-time lightning impulse index under the j-th lightning current intensity level in the five evaluation levels ≤P30, (P30, P50], (P50, P70], (P70, P90], and >P90. The weighted average method can be used to obtain the comprehensive evaluation results of the short-time lightning impulse index:

[0096] ,

[0097] Combined with the classification of lightning current intensity, a comprehensive evaluation model of disaster-causing factors can be constructed, as shown in the following formula:

[0098] ,

[0099] Where: R represents the disaster factor value; j represents the lightning current intensity level; D j It is the comprehensive evaluation result of the short-term lightning impulse index under the lightning current intensity level j. The disaster factor value in each grid along the high-speed railway is calculated to form the disaster factor grid data of the entire line. According to the size of the disaster factor value, the natural breakpoint method is used to divide the disaster factor into high risk, medium risk and low risk.

[0100] Example:

[0101] (1) Classification of lightning current intensity levels

[0102] Data collection and collation: lightning records within 0.5 km on both sides of the high-speed railway in Jiangsu Province were collected, and lightning records with lightning current intensity ≤ 5kA or lightning current intensity ≥ 200kA were eliminated to form a data set;

[0103] Calculate percentiles: Calculate the values ​​of the 30th percentile (P30), 50th percentile (P50), 70th percentile (P70), and 90th percentile (P90) of lightning current intensity.

[0104] Classification: Lightning current intensity is classified into 5 levels according to size, as shown in Table 2:

[0105] Table 2 Lightning current intensity levels

[0106]

[0107] (2) Calculation of short-term lightning impulse indicators:

[0108] Determine the short-term lightning impulse indicators and levels: divide the high-speed railway line into 1km*1km grid areas, and count the lightning frequency, lightning current wave head steepness, time interval between adjacent lightning return strokes, lightning position relative to the transmission line (T line), lightning position relative to the feeder (F line) at each lightning current intensity level according to the grids, and subdivide each lightning indicator of all grids along the railway into 5 levels according to percentiles (P30, P50, P70, P90).

[0109] Establish the membership matrix of short-time lightning impulse index: For different lightning current intensity levels, calculate the membership values ​​of the five lightning indicators according to the 1km*1km grid. For example, under the lightning current intensity level of level I, the membership matrix μ of each short-time lightning impulse index in a 1km*1km grid along the high-speed railway is as follows in Table 3:

[0110] Table 3. Membership matrix of short-time lightning impulse index

[0111]

[0112] Calculate the comprehensive membership vector of short-term lightning impulse indicators: Following the principle of the entropy method, relying on the grid short-term lightning impulse indicators (lightning frequency, lightning current wave head steepness, time interval between adjacent lightning return strokes, precise position of lightning relative to the T line, precise position of lightning relative to the F line) data collected along the high-speed railway, calculate the weight vector W corresponding to each short-term lightning impulse indicator: ,

[0113] The weight vector W is combined with the membership matrix μ of the five short-time lightning impulse indicators by using the synthetic operation formula of fuzzy transformation: , and obtain the comprehensive membership vector of the short-term lightning impulse index under the grid level I lightning current intensity level .

[0114] (3) Constructing a comprehensive evaluation model for disaster-causing factors

[0115] Similarly, the comprehensive membership vectors of short-time lightning impulse indicators under the lightning current intensity levels of level II, III, IV, and V of the grid are calculated, respectively: , , , The weighted average method can be used to obtain the comprehensive evaluation results of short-term lightning impulse indicators under five lightning current intensity levels: 3.925, 4.18, 4.04, 4.88, and 4.44. According to the comprehensive evaluation model of disaster factors, the disaster factor value in this grid is calculated to be 4.408.

[0116] The disaster factor value in each grid along the high-speed railway is calculated to form the disaster factor grid data of the entire line. According to the size of the disaster factor value, the natural breakpoint method is used to divide the high-speed railway into high-risk, medium-risk and low-risk areas.

[0117] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical solutions and technical concepts of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A comprehensive analysis method for lightning disaster-causing factors of high-speed railways, characterized in that The following steps are involved: S1, collect lightning records occurring along the high-speed railway, and sort them into 5 lightning current intensity levels according to the lightning current intensity; S2, dividing the high-speed railway into several grids of 1km*1km, obtaining the short-time lightning impulse index of each grid by statistics, and sorting the short-time lightning impulse index by size and subdividing them into 5 levels; The short-term lightning impulse indicators include lightning frequency, lightning current wave head steepness, time interval between adjacent lightning return strokes, precise position of lightning relative to the transmission line, and precise position of lightning relative to the feeder; S3, establish a short-time lightning impulse index membership matrix: under the lightning current intensity level j, according to the five short-time lightning impulse index levels, calculate the short-time lightning impulse index membership value matrix of all grids respectively; S4, based on the entropy method and the historical short-time lightning impulse index data of the grid along the high-speed railway, the weight vector W corresponding to the short-time lightning impulse index is calculated, and the comprehensive membership vector L of the short-time lightning impulse index under the lightning current intensity level j is obtained through the fuzzy transformation algorithm j , ; Then, the comprehensive membership vector of the short-time lightning impulse index of each grid under other lightning current intensity levels is completed, so as to obtain the comprehensive membership vector L of the short-time lightning impulse index under different lightning current intensities; S5, the comprehensive evaluation result D of 5 different short-time lightning impulse indicators under the jth lightning current intensity level is calculated by weighted average method j ; Finally, based on the comprehensive evaluation results D j , construct a comprehensive evaluation model for disaster-causing factors; After the lightning current intensities described in step S1 are sorted, they are divided into five levels according to the 30th percentile, 50th percentile, 70th percentile, and 90th percentile of the ranking; The five-level classification method of the short-time lightning impulse index in step S2 is as follows: (1) First, count and calculate the lightning frequency value in each grid and sort them by size; (2) Select the percentile as k, , and the kth percentile classification threshold P is calculated by the following formula k , ， In the formula, N represents the number of lightning frequencies, and q represents the number of integer digits; P q Indicates q The value of lightning frequency corresponding to the percentile; P q-1 Indicates q-1 The value of lightning frequency corresponding to the percentile; P k represents the grading threshold of the kth percentile, corresponding to P 30 , P 50 , P 70 , P 90 ; (3) Press (0, P 30 ],(P 30 , P 50 ],(P 50 , P 70 ],(P 70 , P 90 ],(P 90 , 100] divide the lightning frequency into corresponding levels i, i = 1, 2, 3, 4, 5; (4) Referring to steps (1) to (3), the remaining four short-duration lightning impulse indicators are divided into five levels in turn; The calculation of the short-time lightning impulse index membership value matrix in step S3 includes the following steps: (1) Select the median of the five levels of short-term lightning impulse index as the reference point v, , are the median values ​​of each short-time lightning impulse index at level i, i=1, 2, 3, 4, 5; (2) For different short-term lightning impulse indicators, the respective membership degrees are calculated according to the following function: , The membership degree of lightning frequency and lightning current wave head steepness is calculated using the following formula: When the level of short-time lightning impulse index i=1, ， When the level of short-time lightning impulse index is i=2,3,4, ， When the level of short-time lightning impulse index i=5, ， The membership of the time interval between adjacent lightning return strokes, the precise position of lightning relative to the transmission line, and the precise position of lightning relative to the feeder is calculated using the following formula: When the level of short-time lightning impulse index i=5, ， When the level of short-time lightning impulse index is i=2,3,4, ， When the level of short-time lightning impulse index i=1, ， In the formula, is the actual value of the short-time lightning impulse index, is the membership of the short-time lightning impulse index level i with the lightning current intensity level j. After the above calculation, the membership vectors of the five short-time lightning impulse indicators are obtained, and the membership matrix μ of the five indicators is constructed; The specific process of calculating the comprehensive membership vector L in step S4 is as follows: Firstly, according to the short-time lightning impulse index data collected from the grids along the high-speed railway, the weight vector W of each short-time lightning impulse index is calculated by the entropy method; Then, through fuzzy change synthesis operation, the weight vector W of each short-time lightning impulse index under different lightning current intensity level j is combined with the corresponding membership matrix μ to obtain the comprehensive membership vector L of each short-time lightning impulse index under different lightning current intensity level j. j , L j =μ*W, , They represent the comprehensive membership of the short-time lightning impulse index in the five levels under the lightning current intensity level j; The comprehensive evaluation result D in step S5 j It is calculated by the following formula: ， Next, the comprehensive evaluation model of disaster factors is constructed according to the following formula: ， In the formula, R represents the disaster factor value; j represents the lightning current intensity level; D j It is the comprehensive evaluation result of short-time lightning impulse index under lightning current intensity level j; Finally, the disaster factor values ​​in all grids along the high-speed railway are calculated to form the disaster factor grid data of the entire line.

2. According to claim 1, the comprehensive analysis method of high-speed railway lightning disaster hazard factors is characterized by: The step S1 described in collecting lightning records occurring along the high-speed railway is within a range of 0.5 km on both sides of the high-speed railway.

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