High building area lightning density analysis method and device

Abstract

The invention relates to the technical field of lightning detection, and particularly discloses a high building area lightning density analysis method and device, and the method comprises the steps: obtaining the lightning positioning historical data of a high building area; performing ground-to-ground lightning distribution characteristic analysis on the lightning positioning historical data to obtain an observation lightning density distribution expression; simplifying the observation lightning density distribution expression to obtain a convolution expression of the observation lightning density; and adopting a Richardson-Lucy algorithm to carry out iterative operation on the convolution expression of the observed lightning density to obtain an optimal estimated value of the real lightning density. The high building area lightning positioning record density distribution is subjected to refined analysis, the convolution expression of the observed lightning density is subjected to iterative operation, the problem of the influence of lightning positioning errors is solved, the lightning density value of the surrounding area of the high building can be false increased by directly applying the small-lattice-distance grid method, and the positioning accuracy is improved. And the lightning density value at the central position is far less than the true value.

Description

Technical Field

[0001] The invention relates to the technical field of lightning detection, and in particular to a method and device for analyzing lightning density in a high-rise building area. Background Art

[0002] With the development of lightning detection technology, a large-area lightning location system composed of multiple lightning detection substations can monitor lightning activities in real time and over a large area, and detect the time, location, peak value of lightning current, polarity and other parameters of cloud-to-ground discharge (ground lightning). At present, the ground lightning location system has become the most important lightning monitoring technology, and the detection efficiency has reached more than 90%, but there are still positioning errors of hundreds of meters. At present, there are more and more high-rise buildings in cities, and the height of buildings is getting higher and higher. Researchers are more concerned about using lightning location detection data to conduct statistical analysis on the lightning distribution characteristics in the area of ​​high-rise buildings in cities.

[0003] The grid method is currently the most commonly used method for analyzing the two-dimensional geographic spatial distribution characteristics of lightning. It divides the analyzed area into equally spaced grids, and then assigns the lightning location data to a certain grid based on its geographic location parameters, and then further counts the lightning data within each grid. In order to analyze the difference characteristics of lightning distribution in detail, the grid spacing needs to be as small as 100m, which is smaller than the average positioning error of most current operational ground-to-ground lightning location systems. Therefore, the direct application of the grid method is likely to lead to misjudgment of the lightning attribution grid.

[0004] For areas with tall buildings, most ground-to-ground flashes occur above the tall buildings, while areas near the tall buildings have very few actual lightning strikes due to the shielding effect of the tall buildings. Therefore, in areas with tall buildings, the horizontal gradient variation of ground-to-ground flash distribution is actually very large. However, if the grid method is directly applied (even if the grid spacing is 100 meters or less), it is often difficult to analyze this feature. For example, there is an extremely tall building in the center of a flat area, and all ground-to-ground flashes in the area occur on the top of the building. However, due to the positioning error of LLS, the positioning points must be scattered around the building, which will cause the lightning density values ​​of the surrounding grid points to appear falsely increased, while the lightning density of the grid where the extremely tall building is located to appear falsely decreased.

[0005] Sima Wenxia et al. (2012) and Shi Xiangbo et al. (2015) have tried to improve the grid method, that is, for a subdivided grid (the grid spacing can be less than 1 km), the statistics of lightning parameter values ​​(such as lightning density) are not limited to the grid, but all lightning data in a large range (generally a radius of several kilometers) artificially set around the grid. It should be pointed out that this method is essentially a smoothing method and still cannot obtain detailed difference information on lightning distribution in high-rise building areas.

[0006] In order to solve the statistical errors of lightning density gridding in high-building areas caused by random errors in lightning location results, the inventors studied an improved analysis method. Using this method, an optimization analysis of ground lightning return stroke density with a grid spacing of 100 meters in high-building areas in Guangzhou was carried out, and the analysis results before and after optimization were compared.

[0007] Based on this technical background, the present invention proposes a method and device for analyzing lightning density in a high-rise building area. Summary of the invention

[0008] In view of the shortcomings of the prior art, the present invention provides a method and device for analyzing lightning density in a high-rise building area. The method performs a refined analysis on the density distribution of lightning location records in the high-rise building area, and uses the Richardson-Lucy algorithm to iteratively calculate the convolution expression of the observed lightning density. The method solves the problem that due to the influence of lightning location errors, the direct application of the small-grid method may lead to a false increase in the lightning density value in the area around the high-rise building, while the lightning density value at the center of the high-rise building is far less than the true value. The method achieves the optimal estimation of the true lightning density, which is more in line with the actual situation.

[0009] In order to achieve the above object, a first aspect of the present invention provides a method for analyzing lightning density in a high-rise building area, comprising:

[0010] Obtain historical data on lightning locations in areas with tall buildings;

[0011] Analyzing the ground-to-ground lightning distribution characteristics on the lightning location historical data to obtain an expression for the observed lightning density distribution;

[0012] Simplifying the observed lightning density distribution expression to obtain a convolution expression of the observed lightning density;

[0013] The Richardson-Lucy algorithm is used to iteratively calculate the convolution expression of the observed lightning density to obtain the optimal estimate of the true lightning density.

[0014] A second aspect of the present invention provides a high-building area lightning density analysis device, comprising:

[0015] An acquisition module is used to obtain historical data of lightning location in high-building areas;

[0016] A feature analysis module, used to analyze the ground-to-ground lightning distribution characteristics of the lightning location historical data to obtain an expression for the observed lightning density distribution;

[0017] A simplification module, used for simplifying the observed lightning density distribution expression to obtain a convolution expression of the observed lightning density;

[0018] The iteration module is used to iteratively calculate the convolution expression of the observed lightning density using the Richardson-Lucy algorithm to obtain the optimal estimated value of the real lightning density.

[0019] A third aspect of the present invention provides an electronic device, the electronic device comprising:

[0020] A memory storing executable instructions;

[0021] A processor, wherein the processor runs the executable instructions in the memory to implement the lightning density analysis method in a high-building area described in the first aspect.

[0022] A fourth aspect of the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method for analyzing lightning density in a high-building area described in the first aspect.

[0023] The beneficial effects of the present invention include:

[0024] The lightning density analysis method for high-rise building areas proposed in the present invention performs a refined analysis on the density distribution of lightning location records in high-rise building areas, and uses the Richardson-Lucy algorithm to iteratively calculate the convolution expression of the observed lightning density. This solves the problem that due to the influence of lightning location errors, the direct application of the small-grid method may lead to a false increase in the lightning density value in the area around the high-rise building, while the lightning density value at the center of the high-rise building is far less than the true value. This achieves the optimal estimation of the true lightning density, which is more in line with the actual situation.

[0025] Other features and advantages of the present invention will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The above and other objects, features and advantages of the present invention will become more apparent through a more detailed description of exemplary embodiments of the present invention with reference to the accompanying drawings.

[0027] Figure 1 This is a schematic flow chart of the lightning density analysis method for high-building areas proposed in the present invention.

[0028] Figure 2 This is a schematic diagram of direct statistical results of lightning return stroke frequency distribution in a high-rise building area in a specific implementation of the high-rise building area lightning density analysis method proposed in the present invention.

[0029] Figure 3 This is a schematic diagram of the analysis results of lightning return stroke frequency distribution in a high-building area after optimization in a specific implementation of the high-building area lightning density analysis method proposed in the present invention.

[0030] Figure 4 This is a schematic diagram comparing the differences before and after optimization in a specific implementation of the method for analyzing lightning density in a high-building area proposed in the present invention. DETAILED DESCRIPTION

[0031] The preferred embodiments of the present invention will be described in more detail below. Although the preferred embodiments of the present invention are described below, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0032] The present invention provides a method for analyzing lightning density in a high-rise building area. Figure 1 As shown, including:

[0033] Obtain historical data on lightning locations in areas with tall buildings;

[0034] The lightning location historical data are analyzed for ground-to-ground lightning distribution characteristics, and the expression for observed lightning density distribution is obtained.

[0035] The expression of observed lightning density distribution is simplified to obtain the convolution expression of observed lightning density.

[0036] The Richardson-Lucy algorithm is used to iteratively calculate the convolution expression of the observed lightning density to obtain the optimal estimate of the true lightning density.

[0037] In the present invention, a refined analysis is performed on the density distribution of lightning location records in the high-rise building area, and the Richardson-Lucy algorithm is used to iteratively calculate the convolution expression of the observed lightning density. This solves the problem that due to the influence of lightning location errors, the direct application of the small-grid method may lead to a false increase in the lightning density value in the area around the high-rise building, while the lightning density value at the center of the high-rise building is much smaller than the true value. This achieves the optimal estimation of the true lightning density, which is more in line with the actual situation.

[0038] According to the present invention, analyzing the distribution characteristics of ground-to-ground lightning on historical lightning location data includes:

[0039] Set the grid size for lightning location historical data analysis;

[0040] Eliminate the positive polarity cloud flash records in the historical data of lightning location;

[0041] Keep the negative polarity cloud flash records in the lightning location history data;

[0042] All positioning records are corrected for a systematic deviation to the east.

[0043] According to the present invention, the conditions for the expression of observed lightning density distribution are:

[0044] The statistical time of lightning location historical data meets the length required for ground-to-ground lightning distribution characteristics analysis:

[0045] The lightning location system has stable detection performance.

[0046] According to the present invention, the observed lightning density distribution expression is:

[0047] g(x,y)=H·f(x,y)+n(x,y);

[0048] Among them, g(x,y) is the lightning density distribution observed by the lightning location system, f(x,y) is the real lightning density distribution, H is the operator that causes "blurring" or "distortion", and n(x,y) is the noise;

[0049] The blurred or distorted operator is produced by the distortion of the real lightning density distribution due to the positioning error of the lightning location system.

[0050] According to the present invention, the condition for simplifying the expression of observed lightning density distribution is:

[0051] In the entire high-building area, the random error distribution of each lightning location result follows the same distribution function.

[0052] Preferably, the convolution expression of the observed lightning density is:

[0053]

[0054] Among them, p(x,y) is the distribution function, is the convolution operator.

[0055] According to the present invention, the expression of the distribution function is:

[0056]

[0057] Where σ is the variance, and x and y are two-dimensional normally distributed variables.

[0058] The present invention will be described in more detail below by way of examples.

[0059] Embodiment 1:

[0060] This embodiment provides a method for analyzing lightning density in a high-rise building area, including:

[0061] 1) Lightning location information description:

[0062] The Guangdong-Hong Kong-Macao Lightning Location System was jointly built by the meteorological departments of Guangdong Province, Hong Kong and Macao since 2005. By 2007, a total of 6 detection substations (using IMPACT probes) had been built. In 2012, 11 new detection substations were added to the Guangdong-Hong Kong-Macao Lightning Location System. The newly built detection stations used Vaisala's LS-700X series probes, which can detect ground flashes and cloud flashes at the same time (the theoretical detection efficiency of cloud flashes is about 40-50%), thereby improving the detection capability of lightning activities in the Pearl River Delta region. In 2018, the Guangdong-Hong Kong-Macao Lightning Location System replaced all the original IMPACT probes with LS-700X series probes, and added two substations. The Guangdong-Hong Kong-Macao Lightning Location System adopts the time difference-direction integrated positioning method, and the detection parameters include GPS time, longitude and latitude, intensity, cloud flash / ground flash identification and polarity of lightning discharge.

[0063] 2) Lightning density optimization:

[0064] Assume that the detection performance of the lightning location system is stable over a sufficiently long statistical period, the real distribution of lightning density in a certain area is f(x, y), the operator that causes the real lightning density distribution to be "blurred" or "distorted" due to the positioning error of the lightning location system is H, the lightning density distribution observed by the lightning location system is g(x, y), and n(x, y) is noise, then:

[0065] g(x,y)=H·f(x,y)+n(x,y)……………………(1);

[0066] Consider the following simplified case: Assume that in the entire high-rise building area, the random error distribution of each lightning location result follows the same distribution function p(x, y); then equation (1) is transformed into:

[0067]

[0068] In the formula is the convolution operator;

[0069] According to the evaluation results of Chen Lvwen et al. (2020), after the system deviation is corrected, the arithmetic mean (median) of the positioning errors of the first lightning strike, subsequent lightning strike, and upward lightning strike of the Guangzhou Tower are approximately 563 (192) m, 185 (89) m, and 225 (106) m. For simplicity, in this example, it is assumed that Where σ = 100m, which means that the location errors of all lightning location records in the high-rise building area are assumed to obey a two-dimensional normal distribution with a mean square error of 100m;

[0070] The essence of the lightning density optimization method is to obtain the optimal estimate of the real lightning density f(x,y) based on the lightning density g(x,y) obtained by using lightning location data. As can be seen from formula (2), this is very similar to the deconvolution problem of fuzzy image restoration, and the existing mature image restoration algorithm can be used for reference. Since the degradation function p(x,y) has been set, the Richardson-Lucy algorithm can be directly used to iteratively calculate f(x,y).

[0071] 3) Detailed analysis of lightning density in high-rise building areas in Guangzhou:

[0072] The area with the most high-rise buildings in Guangzhou is mainly located along the north-south central axis of Guangzhou from Canton Tower to CITIC Plaza. The distribution of the main high-rise buildings in this area is as follows: Figure 2 ( Figure 2 The frequency distribution of regional strikes against high-rise buildings in Guangzhou from 2014 to 2018 is shown in the figure. Letters A to E represent five high-rise buildings with a height of more than 350 meters, including Guangzhou Tower (600 meters, built in 2009), Guangzhou Chow Tai Fook Finance Center (530 meters, built in 2014), Guangzhou International Finance Center (440 meters, built in 2009), CITIC Plaza (390 meters, built in 1996) and Guangsheng International Building (360 meters, built in 2011). The solid triangle, hollow triangle and cross mark represent high-rise buildings with heights ranging from 300 to 349 meters, 250 to 299 meters and 200 to 249 meters respectively.

[0073] The distribution characteristics of ground-to-ground flashes in high-rise building areas in Guangzhou were analyzed using the historical lightning location data of Guangdong, Hong Kong and Macao in the past five years (2014-2018), and the grid size was set to 0.001°×0.001°. First, the positive cloud-to-ground flash records of the data were eliminated. Considering that the positive ground-to-ground flash location records with an intensity of 0-10kA are likely to be obtained by the lightning location system misjudging cloud flashes as positive ground-to-ground flashes, they are also eliminated. Negative ground-to-ground flashes with a grounding point height of ≥200m are easily misjudged as cloud flashes, so negative cloud-to-ground flash records are retained in the location data. In addition, all location records in the area were corrected for a systematic deviation of 0.001° to the east.

[0074] Figure 2Direct statistical results of the distribution of lightning strike frequency in the high-rise building area of ​​Guangzhou from 2014 to 2018 are given, among which the maximum value of the grid point at the strike density center near the Guangzhou Tower (A) is 264 times; according to the statistical results of Lv Weitao et al. (2020), the number of lightning strikes observed at the Guangzhou Tower by TOLOG (Guangzhou High-rise Building Lightning Observation Station) alone during 2014-2018 reached 172 times, and the actual number should be more (the number of upward strikes without strikes is to be counted); according to the statistics of Chen Luwen et al. (2020), the number of ground lightning strikes within a radius of 200m from the center of the lightning strike density of the Guangzhou Tower during 2014-2018 was 655 times, while the number of strikes within a radius of 200-500m was 143 times; it can be inferred that the actual number of ground lightning strikes that occurred at the Guangzhou Tower during 2014-2018 should be more than 600 times; the maximum value obtained by directly using the grid method is only 264 times, which is much smaller than the actual situation;

[0075] Figure 3 The optimized lightning strike frequency distribution analysis results of the high-rise building area in Guangzhou, where the maximum value of the grid point of the strike density center near the Guangzhou Tower is 558 times; it can be seen that the maximum value obtained after optimization should be more in line with the actual situation; from the perspective of the entire area, after optimization, Figure 2 Several high-value centers of lightning stroke density of tall buildings in the image are not only preserved, but also further enhanced and highlighted; for example, the lightning stroke density centers of the two tall buildings, East Tower (B) and West Tower (C), which are very close (less than 300 meters), are separated more clearly; the lightning stroke density centers of Guangsheng International Building (E) and the Yuexiu Financial Building to its east are also separated more clearly;

[0076] Figure 4 The difference comparison before and after optimization is given; it can be seen that after optimization, the center of the Guangzhou Tower lightning stroke density is significantly enhanced, and at the same time, the lightning distribution in the outer area of ​​the Guangzhou Tower is significantly reduced; it must be pointed out that this optimization method follows the overall conservation principle of the number of lightning strokes, that is, the total number of strokes in the entire high-rise building area remains unchanged before and after optimization; that is to say, the strokes originally distributed in the outer area of ​​the Guangzhou Tower are more concentrated in the center of the Guangzhou Tower lightning density after optimization; Wu Shanshan et al. used TOLOG optical observation data from 2009 to 2014 and found that the Guangzhou Tower's attraction to the downward ground flash in the nearby area resulted in no ground flash being observed within a range of about 1 km nearby; therefore, after optimization, the change characteristics of the lightning distribution in high buildings, "enhancement in the center and weakening around", should be more in line with the actual situation;

[0077] 4) Conclusion and discussion:

[0078] This example performs an optimization analysis of the ground lightning return stroke density with a grid spacing of 100 meters in the high-rise building area in Guangzhou, and compares the analysis results before and after the optimization. The results show that:

[0079] 1) Due to the influence of lightning location error, the direct application of the small-grid method can lead to a false increase in the lightning density value around tall buildings, while the lightning density value at the center of the tall building is much smaller than the true value.

[0080] 2) After applying the optimization method based on the principle of fuzzy image restoration, the lightning distribution map of high buildings obtained by the small-grid method shows the changing characteristics of "enhancement in the center and weakening around", which is more in line with the actual situation.

[0081] The number of lightning strikes on high buildings, the comparison of the number of lightning strikes on buildings of different heights, and the refined characteristics of ground lightning distribution in high-rise building (group) areas are issues of great concern to lightning researchers, and they also have very important application value in the practice of lightning protection engineering. Obviously, compared with methods such as installing lightning counters, the application of lightning location data obviously has an incomparable convenience advantage; however, how to overcome the influence of positioning errors of current business lightning location systems and obtain more refined analysis results is something we need to study hard. The method proposed in this embodiment solves the problem that due to the influence of lightning location errors, the direct application of the small-grid method can lead to a false increase in the lightning density value in the area around the high building, while the lightning density value at the center of the high building is much smaller than the true value, thereby achieving the optimal estimation of the true lightning density, which is more in line with the actual situation.

[0082] Embodiment 2:

[0083] This embodiment provides a method for analyzing lightning density in a high-rise building area. Figure 1 As shown, including:

[0084] Obtain historical data on lightning locations in areas with tall buildings;

[0085] The lightning location historical data are analyzed for ground-to-ground lightning distribution characteristics, and the expression for observed lightning density distribution is obtained.

[0086] The expression of observed lightning density distribution is simplified to obtain the convolution expression of observed lightning density.

[0087] The Richardson-Lucy algorithm is used to iterate the convolution expression of the observed lightning density to obtain the optimal estimate of the real lightning density.

[0088] In this embodiment, analyzing the distribution characteristics of ground-to-ground lightning on historical lightning location data includes:

[0089] Set the grid size for lightning location historical data analysis;

[0090] Eliminate the positive polarity cloud flash records in the historical data of lightning location;

[0091] Keep the negative polarity cloud flash records in the lightning location history data;

[0092] In this embodiment, the conditions for the expression of observed lightning density distribution to be established are:

[0093] The statistical time of lightning location historical data meets the length required for ground-to-ground lightning distribution characteristics analysis:

[0094] The lightning location system has stable detection performance;

[0095] In this embodiment, the observed lightning density distribution expression is:

[0096] g(x,y)=H·f(x,y)+n(x,y);

[0097] Among them, g(x,y) is the lightning density distribution observed by the lightning location system, f(x,y) is the real lightning density distribution, H is the operator that causes "blurring" or "distortion", and n(x,y) is the noise;

[0098] The blurred or distorted operator is generated by the distortion of the real lightning density distribution due to the positioning error of the lightning location system;

[0099] In this embodiment, the condition for simplifying the expression of observed lightning density distribution is:

[0100] In the entire high-building area, the random error distribution of each lightning location result follows the same distribution function;

[0101] In this embodiment, the convolution expression of the observed lightning density is:

[0102]

[0103] Among them, p(x,y) is the distribution function, is the convolution operator;

[0104] In this embodiment, the expression of the distribution function is:

[0105]

[0106] Where σ is the variance, and x and y are two-dimensional normally distributed variables.

[0107] Embodiment three:

[0108] This embodiment provides a lightning density analysis device for a high-rise building area, comprising:

[0109] An acquisition module is used to obtain historical data of lightning location in high-building areas;

[0110] The feature analysis module is used to analyze the distribution characteristics of ground-to-ground lightning based on the historical data of lightning location and obtain the distribution expression of observed lightning density;

[0111] A simplification module is used to simplify the observed lightning density distribution expression to obtain the convolution expression of the observed lightning density;

[0112] An iteration module, used to iteratively calculate the convolution expression of the observed lightning density using the Richardson-Lucy algorithm to obtain the optimal estimation value of the real lightning density;

[0113] In this embodiment, analyzing the distribution characteristics of ground-to-ground lightning on historical lightning location data includes:

[0114] Set the grid size for lightning location historical data analysis;

[0115] Eliminate the positive polarity cloud flash records in the historical data of lightning location;

[0116] Keep the negative polarity cloud flash records in the lightning location history data

[0117] All positioning records are corrected for systematic deviations to the east;

[0118] In this embodiment, the conditions for the expression of observed lightning density distribution to be established are:

[0119] The statistical time of lightning location historical data meets the length required for ground-to-ground lightning distribution characteristics analysis:

[0120] The lightning location system has stable detection performance;

[0121] In this embodiment, the observed lightning density distribution expression is:

[0122] g(x,y)=H·f(x,y)+n(x,y);

[0123] Among them, g(x,y) is the lightning density distribution observed by the lightning location system, f(x,y) is the real lightning density distribution, H is the operator that causes "blurring" or "distortion", and n(x,y) is the noise;

[0124] The blurred or distorted operator is generated by the distortion of the real lightning density distribution due to the positioning error of the lightning location system;

[0125] In this embodiment, the condition for simplifying the expression of observed lightning density distribution is:

[0126] In the entire high-building area, the random error distribution of each lightning location result follows the same distribution function;

[0127] In this embodiment, the convolution expression of the observed lightning density is:

[0128]

[0129] Among them, p(x,y) is the distribution function, is the convolution operator;

[0130] In this embodiment, the expression of the distribution function is:

[0131]

[0132] Where σ is the mean square error, and x and y are two-dimensional normally distributed variables.

[0133] Embodiment 4:

[0134] An embodiment of the present invention provides an electronic device including a memory and a processor, including:

[0135] A memory storing executable instructions;

[0136] The processor runs the executable instructions in the memory to implement the lightning density analysis method for high-building area.

[0137] The memory is used to store non-temporary computer-readable instructions. Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, etc.

[0138] The processor may be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In one embodiment of the present invention, the processor is used to run the computer-readable instructions stored in the memory.

[0139] Those skilled in the art should be able to understand that in order to solve the technical problem of how to obtain a good user experience, the present embodiment may also include well-known structures such as a communication bus and an interface, and these well-known structures should also be included in the protection scope of the present invention.

[0140] For detailed description of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0141] Embodiment five:

[0142] An embodiment of the present invention provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, a method for analyzing lightning density in a high-building area is implemented.

[0143] The computer-readable storage medium according to the embodiment of the present invention stores non-transitory computer-readable instructions, and when the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the above-mentioned methods of the embodiments of the present invention are executed.

[0144] The above-mentioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or mobile hard disk), media with built-in rewritable non-volatile memory (e.g., memory card) and media with built-in ROM (e.g., ROM box).

[0145] The method for analyzing lightning density in a high-rise building area proposed in an embodiment of the present invention performs a refined analysis on the density distribution of lightning location records in a high-rise building area, and uses the Richardson-Lucy algorithm to iteratively calculate the convolution expression of the observed lightning density. This solves the problem that, due to the influence of lightning location errors, the direct application of a small-grid method may lead to a false increase in lightning density values ​​in areas around high-rise buildings, while the lightning density values ​​at the center of the high-rise buildings are far less than the true values. This achieves the optimal estimation of the true lightning density, which is more in line with the actual situation.

[0146] The embodiments of the present invention have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A method for analyzing lightning density in a high-rise building area, characterized in that: include: Obtain historical data on lightning locations in areas with tall buildings; Analyzing the ground-to-ground lightning distribution characteristics on the lightning location historical data to obtain an expression for the observed lightning density distribution; Simplifying the observed lightning density distribution expression to obtain a convolution expression of the observed lightning density; The Richardson-Lucy algorithm is used to iteratively calculate the convolution expression of the observed lightning density to obtain the optimal estimate of the true lightning density.

2. The method according to claim 1, characterized in that The ground-to-ground lightning distribution characteristics analysis of the lightning location historical data includes: Setting the grid analysis size of the lightning location historical data; Eliminate the positive polarity cloud flash records in the lightning location historical data; Preserve the negative polarity cloud flash records in the lightning location history data; All positioning records are corrected for a systematic deviation to the east.

3. The method according to claim 1, characterized in that The conditions for the expression of observed lightning density distribution to be valid are: The statistical time of the lightning location historical data meets the length required for ground-to-ground lightning distribution characteristics analysis: The lightning location system has stable detection performance.

4. The method according to claim 3, characterized in that The observed lightning density distribution expression is: g(x,y)=H·f(x,y)+n(x,y); Among them, t(x,y) is the lightning density distribution observed by the lightning location system, f(x,y) is the real lightning density distribution, H is the operator that causes "blurring" or "distortion", and n(x,y) is the noise; The blurred or distorted operator is generated by the distortion of the real lightning density distribution due to the positioning error of the lightning positioning system.

5. The method according to claim 4, characterized in that The condition for simplifying the observed lightning density distribution expression is: In the entire high-building area, the random error distribution of each lightning location result follows the same distribution function.

6. The method according to claim 1, characterized in that The convolution expression of the observed lightning density is: Among them, p(x,y) is the distribution function, is the convolution operator.

7. The method according to claim 6, characterized in that The expression of the distribution function is: Where σ is the mean square error, and x and y are two-dimensional normally distributed variables.

8. A lightning density analysis device for a high-rise building area, characterized in that: include: An acquisition module is used to obtain historical data of lightning location in high-building areas; A feature analysis module, used to analyze the ground-to-ground lightning distribution characteristics of the lightning location historical data to obtain an expression for the observed lightning density distribution; A simplification module, used for simplifying the observed lightning density distribution expression to obtain a convolution expression of the observed lightning density; The iteration module is used to iteratively calculate the convolution expression of the observed lightning density using the Richardson-Lucy algorithm to obtain the optimal estimated value of the real lightning density.

9. An electronic device, characterized in that: The electronic device comprises: A memory storing executable instructions; A processor, wherein the processor runs the executable instructions in the memory to implement the lightning density analysis method for a high-building area according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for analyzing lightning density in a high-building area according to any one of claims 1 to 7 is implemented.

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