A calculation method for superposition of algorithms for power equipment crossing fire risk forest areas

Abstract

The present invention discloses a calculation method for algorithm superposition of power equipment crossing fire risk forest areas, which relates to the field of forest fire prevention technology, including: obtaining the risk level of the fire risk forest area; obtaining the regional location information of the fire risk forest area; obtaining the trigger probability of the fire cause corresponding to the risk level of the fire risk forest area; obtaining the fire risk forest area with the lowest risk level as the characteristic fire risk forest area; forming a characteristic risk function for the power equipment in the characteristic fire risk forest area; forming a risk function for the fire risk forest areas with different risk levels; forming a superposition function based on at least one actual fire risk forest area crossed by the power equipment. By forming a characteristic risk function for the power equipment in the characteristic fire risk forest area and forming a risk function for the fire risk forest areas with different risk levels, the risk of each area is evaluated in a targeted manner to avoid excessive judgment errors that affect the accuracy of prediction and prevention.

Description

Technical Field

[0001] The present invention relates to the technical field of forest fire prevention, and in particular to a calculation method for algorithm superposition of electric power equipment crossing a forest area with fire risks. Background Art

[0002] Forest fire is one of the natural disasters that pose the greatest threat to forest resources. Once a forest fire occurs, it will not only cause serious losses to forestry resources, but also lead to the destruction of the regional forestry ecological environment, causing problems such as the degradation of the forest ecosystem, and will also pose a great threat to the safety of life and property of people in the forest area. Therefore, protecting forest resources and preventing forest fires is one of the core tasks of forestry work.

[0003] The laying of power equipment such as transmission lines will inevitably pass through forests. Therefore, preventing forest fires can effectively protect power equipment.

[0004] However, the existing prediction algorithms are unified for different areas of the forest. However, the forest covers a large area and the fire risks in different areas vary greatly. Using the same parameters for judgment is likely to lead to large judgment errors, affecting the accuracy of prediction and prevention. Summary of the invention

[0005] In order to solve the above technical problems, a calculation method for algorithm superposition of power equipment across fire risk forest areas is provided. This technical solution solves the problem that the existing prediction algorithm proposed in the above background technology unifies different areas of the forest, but the forest coverage area is large, and the fire risks in different areas vary greatly. Using the same parameters for judgment is likely to lead to large judgment errors, affecting the accuracy of prediction and prevention.

[0006] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0007] A calculation method for superimposing algorithms for power equipment crossing fire risk forest areas, comprising:

[0008] Based on historical data, at least one fire risk forest area is obtained, the fire risk forest area is graded, and the risk level of the fire risk forest area is obtained;

[0009] Acquire regional location information of the fire risk forest area, wherein the regional location information includes the coverage of the fire risk forest area;

[0010] At least one fire trigger that triggers the occurrence of fire in the fire risk forest area;

[0011] Obtain the triggering probability of the fire cause corresponding to the risk level of the fire risk forest area;

[0012] Obtain the fire risk forest area with the lowest risk level as the characteristic fire risk forest area;

[0013] Form a characteristic risk function for power equipment in forest areas with characteristic fire risks;

[0014] Based on the characteristic fire risk forest areas, a risk function of fire risk forest areas with different risk levels is formed;

[0015] Forming a superposition factor for the fire risk forest area, determining the risk level of at least one actual fire risk forest area crossed by the power equipment according to the location information, and forming a superposition function based on at least one actual fire risk forest area crossed by the power equipment;

[0016] When the result of the data input superposition function of the actual fire risk forest area is greater than the preset value, there is a fire risk for the power equipment in the actual fire risk forest area.

[0017] Preferably, the step of classifying the fire risk forest areas to obtain the risk levels of the fire risk forest areas comprises the following steps:

[0018] Based on historical data, the frequency of fires in fire-risk forest areas is counted to obtain at least one probability of fire occurrence;

[0019] Based on at least one fire occurrence probability, a fire occurrence probability range is obtained;

[0020] Divide the fire occurrence probability range into at least one probability interval;

[0021] The risk level is assigned to the probability interval according to the value of the center of the probability interval. The larger the value of the center of the probability interval, the greater the risk level.

[0022] When the probability of fire occurrence in a fire risk forest area falls within a probability interval, the risk level of the probability interval is matched to the fire risk forest area.

[0023] Preferably, the obtaining of the regional location information of the fire risk forest area comprises the following steps:

[0024] Obtain the edge of the fire risk forest area, evenly set at least one sampling point inside the fire risk forest area, and obtain the location coordinates of the sampling point based on GPS;

[0025] The minimum value of the distance from the sampling point to the edge of the fire risk forest area is taken as the characteristic distance;

[0026] The minimum value of at least one characteristic distance is set to a preset distance.

[0027] Preferably, forming at least one fire trigger that triggers the occurrence of fire in the fire risk forest area comprises the following steps:

[0028] Extract environmental characteristics of fire risk forest areas when no fire occurs, and obtain at least one unnecessary trigger;

[0029] Extract environmental characteristics of fires in fire-risk forest areas and obtain at least one suspected trigger;

[0030] obtaining, as a preliminary fire cause, a suspected trigger among at least one suspected trigger that is different from at least one unnecessary trigger;

[0031] The conditional probability of triggering a fire is calculated when the initial fire trigger occurs. When the conditional probability of triggering a fire is greater than a preset value, the initial fire trigger is used as the fire trigger.

[0032] Preferably, obtaining the trigger probability of the fire cause corresponding to the risk level of the fire risk forest area includes the following steps:

[0033] Calculate the average values ​​of temperature, humidity, precipitation, moisture content of fuels and continuous drought time in fire risk forest areas of the same risk level;

[0034] When the temperature, humidity, precipitation, moisture content of combustibles and continuous drought time are taken as extreme values, the probability of fire occurrence is respectively taken as the contribution weights of temperature, humidity, precipitation, moisture content of combustibles and continuous drought time to the fire trigger;

[0035] The average values ​​of temperature, humidity, precipitation, moisture content of combustibles and continuous drought time in the fire risk forest area of ​​the risk level are multiplied by their contribution weights to the fire triggers and added up to obtain the triggering probability of the fire triggers.

[0036] Preferably, forming a characteristic risk function for the power equipment in the characteristic fire risk forest area comprises the following steps:

[0037] The critical values ​​of temperature, humidity, precipitation, moisture content of fuels and continuous drought time when fire occurs in characteristic fire risk forest areas are calculated;

[0038] The weighted averages of the contributions of temperature, humidity, precipitation, moisture content of combustibles and continuous drought time to at least one fire trigger were calculated respectively;

[0039] Statistical characteristics: actual values ​​of temperature, humidity, precipitation, moisture content of fuels and continuous drought time in fire risk forest areas;

[0040] The characteristic risk function is as follows: ;

[0041] in, is the actual value of the temperature, is the critical value of temperature, is the weighted mean of the contribution of temperature to at least one fire cause, is the actual value of humidity, is the critical value of humidity, is the weighted mean of the contribution of humidity to at least one fire cause, is the actual value of precipitation, is the critical value of precipitation, is the weighted mean of the contribution of precipitation to at least one fire cause, is the actual value of the moisture content of the combustible material, is the critical value of moisture content in combustibles, is the weighted average of the contribution of the moisture content of combustibles to at least one fire cause, is the actual value of continuous drought time, is the critical value of continuous drought time, is the weighted average of the contribution of continuous drought time to at least one fire trigger;

[0042] Preferably, the forming of risk functions of fire risk forest areas of different risk levels based on characteristic fire risk forest areas comprises the following steps:

[0043] The trigger probability of at least one fire trigger corresponding to the risk level of the fire risk forest area is averaged to obtain the risk coefficient;

[0044] The trigger probability of at least one fire trigger corresponding to the risk level of the characteristic fire risk forest area is averaged to obtain the basic coefficient;

[0045] The risk coefficient is compared with the basic coefficient and multiplied by the characteristic risk function to obtain the risk function of the fire risk forest area.

[0046] Preferably, forming a superposition factor for the fire risk forest area comprises the following steps:

[0047] The superposition factor is a conditional function, and the superposition factor takes a value of 0 or 1. The superposition factor is paired with the fire risk forest area;

[0048] When the risk level of the actual fire risk forest area crossed by the power equipment is consistent with the risk level of the fire risk forest area corresponding to the superposition factor, the superposition factor of the fire risk forest area is 1; otherwise, the superposition factor of the fire risk forest area is 0.

[0049] Preferably, determining the risk level of at least one actual fire risk forest area crossed by the power equipment according to the location information comprises the following steps:

[0050] At least one test point is evenly selected on the edge of the actual fire risk forest area, and the location coordinates of the test point are obtained based on GPS;

[0051] For at least one test point, if the distance between the sampling point and the test point in the fire risk forest area does not exceed the preset distance, the area of ​​the actual fire risk forest area is located in the fire risk forest area;

[0052] When an area of ​​an actual fire risk forest area is located within a fire risk forest area, the risk level of the fire risk forest area is assigned to the actual fire risk forest area.

[0053] Preferably, forming a superposition function based on at least one actual fire risk forest area spanned by the power equipment comprises the following steps:

[0054] Generate a regional reserved position, multiply and superimpose the regional reserved position with the risk function and superposition factor of at least one fire risk forest area, and obtain a superposition function;

[0055] When using the Overlay function, the actual fire risk forest area is substituted into the regional reserve position.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] By obtaining the trigger probability of fire triggers corresponding to the risk level of fire risk forest areas, forming characteristic risk functions for power equipment in characteristic fire risk forest areas, and forming risk functions for fire risk forest areas with different risk levels, different areas of the forest can be divided to ensure that the fire risks in the divided areas are relatively consistent. The characteristic risk function is selected as a benchmark, and the benchmark is used to superimpose different areas to obtain the risk function in each area. In this way, the risk of each area can be evaluated in a targeted manner, so that the evaluation results are more consistent with the actual situation in each area, avoiding excessive judgment errors that affect the accuracy of prediction and prevention. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 A flow chart of a calculation method for superimposing algorithms for electric power equipment crossing a forest area with fire risks according to the present invention;

[0059] Figure 2 A schematic diagram of a process for classifying fire risk forest areas and obtaining risk levels of fire risk forest areas according to the present invention;

[0060] Figure 3 A schematic diagram of a process for obtaining regional location information of a fire risk forest area according to the present invention;

[0061] Figure 4 A schematic diagram of a process for forming at least one fire trigger for triggering a fire in a fire risk forest area according to the present invention;

[0062] Figure 5A schematic diagram of a flow chart of obtaining the triggering probability of a fire cause corresponding to the risk level of a fire risk forest area according to the present invention;

[0063] Figure 6 It is a schematic diagram of a flow chart of forming a characteristic risk function for electric power equipment in a characteristic fire risk forest area according to the present invention;

[0064] Figure 7 It is a flow chart of forming a risk function of fire risk forest areas of different risk levels based on characteristic fire risk forest areas of the present invention;

[0065] Figure 8 It is a schematic diagram of the process of forming a superposition factor for a fire risk forest area according to the present invention;

[0066] Fig. 9 A schematic diagram of a flow chart of determining the risk level of at least one actual fire risk forest area crossed by an electric power device according to location information of the present invention;

[0067] Fig.10 A schematic diagram of a flow chart of forming a superposition function based on at least one actual fire risk forest area spanned by an electric power device according to the present invention. DETAILED DESCRIPTION

[0068] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0069] Reference Figure 1 As shown, a calculation method for superimposing algorithms for power equipment across fire risk forest areas includes:

[0070] Based on historical data, at least one fire risk forest area is obtained, the fire risk forest area is graded, and the risk level of the fire risk forest area is obtained;

[0071] Acquire regional location information of the fire risk forest area, wherein the regional location information includes the coverage of the fire risk forest area;

[0072] At least one fire trigger that triggers the occurrence of fire in the fire risk forest area;

[0073] Obtain the triggering probability of the fire cause corresponding to the risk level of the fire risk forest area;

[0074] Obtain the fire risk forest area with the lowest risk level as the characteristic fire risk forest area;

[0075] Form a characteristic risk function for power equipment in forest areas with characteristic fire risks;

[0076] Based on the characteristic fire risk forest areas, a risk function of fire risk forest areas with different risk levels is formed;

[0077] Forming a superposition factor for the fire risk forest area, determining the risk level of at least one actual fire risk forest area crossed by the power equipment according to the location information, and forming a superposition function based on at least one actual fire risk forest area crossed by the power equipment;

[0078] When the result of the data input superposition function of the actual fire risk forest area is greater than the preset value, there is a fire risk for the power equipment in the actual fire risk forest area.

[0079] Reference Figure 2 As shown in the figure, the fire risk forest areas are classified into different levels, and the risk level of the fire risk forest areas is obtained by the following steps:

[0080] Based on historical data, the frequency of fires in fire-risk forest areas is counted to obtain at least one probability of fire occurrence;

[0081] Based on at least one fire occurrence probability, a fire occurrence probability range is obtained;

[0082] Divide the fire occurrence probability range into at least one probability interval;

[0083] The risk level is assigned to the probability interval according to the value of the center of the probability interval. The larger the value of the center of the probability interval, the greater the risk level.

[0084] When the probability of fire occurrence in a fire risk forest area falls within a probability interval, the risk level of the probability interval is matched to the fire risk forest area.

[0085] By classifying fire risk forest areas, we can obtain the fire risk conditions in different regions, and then conduct different fire situation analyses on the fire risk forest areas according to the different fire risk conditions. Otherwise, if the same method is used to analyze the entire forest, the fire risk forest areas in different locations are quite different, so it is easy to have analysis deviations, resulting in poor prediction results.

[0086] Reference Figure 3 As shown, obtaining the regional location information of the fire risk forest area includes the following steps:

[0087] Obtain the edge of the fire risk forest area, evenly set at least one sampling point inside the fire risk forest area, and obtain the location coordinates of the sampling point based on GPS;

[0088] The minimum value of the distance from the sampling point to the edge of the fire risk forest area is taken as the characteristic distance;

[0089] The minimum value of at least one characteristic distance is set to a preset distance.

[0090] Its location information is represented by the characteristic distance and the coordinates of the sampling points. When identifying the area, it is only necessary to compare with the sampling points, and there is no need to compare the points in the entire fire risk forest area. This can reduce processing time and computing power. When identifying, it is necessary to determine the fire risk forest area that includes the actual fire risk forest area. When the boundaries of the actual fire risk forest area are all included in the fire risk forest area, a test point is taken on the boundary of the actual fire risk forest area. When the distance between the sampling point in the fire risk forest area and the test point does not exceed the preset distance, since the distance from the sampling point to the edge of the fire risk forest area is not less than the preset distance, the test points are all within the fire risk forest area. Therefore, the fire risk forest area that includes the actual fire risk forest area can be determined.

[0091] Reference Figure 4 As shown, forming at least one fire trigger that triggers the occurrence of fire in a fire risk forest area includes the following steps:

[0092] Extract environmental characteristics of fire risk forest areas when no fire occurs, and obtain at least one unnecessary trigger;

[0093] Extract environmental characteristics of fires in fire-risk forest areas and obtain at least one suspected trigger;

[0094] obtaining, as a preliminary fire cause, a suspected trigger among at least one suspected trigger that is different from at least one unnecessary trigger;

[0095] The conditional probability of triggering a fire is calculated when the initial fire trigger occurs. When the conditional probability of triggering a fire is greater than a preset value, the initial fire trigger is used as the fire trigger.

[0096] There are inducements for the formation of fire, but the inducements do not directly lead to the occurrence of fire. It is also necessary to determine the direct factors of the fire as the fire trigger, and its inducements can serve as the triggering probability of the fire trigger.

[0097] Reference Figure 5 As shown, obtaining the trigger probability of the fire cause corresponding to the risk level of the fire risk forest area includes the following steps:

[0098] Calculate the average values ​​of temperature, humidity, precipitation, moisture content of fuels and continuous drought time in fire risk forest areas of the same risk level;

[0099] When the temperature, humidity, precipitation, moisture content of combustibles and continuous drought time are taken as extreme values, the probability of fire occurrence is respectively taken as the contribution weights of temperature, humidity, precipitation, moisture content of combustibles and continuous drought time to the fire trigger;

[0100] The average values ​​of temperature, humidity, precipitation, moisture content of combustibles and continuous drought time in the fire risk forest area of ​​the risk level are multiplied by their contribution weights to the fire triggers and added up to obtain the triggering probability of the fire triggers.

[0101] The actual conditions in each fire risk forest area are different, and therefore the triggering conditions for fire triggers are also different. In order to predict fires, each fire risk forest area needs to make statistics on the triggering probability of fire triggers in advance. The triggering probability of fire triggers is determined by factors such as temperature, humidity, precipitation, moisture content of combustibles, and continuous drought time. Because dryness is a necessary condition for ignition, arson is unpredictable and firefighting can only be carried out based on image recognition when a fire occurs.

[0102] Reference Figure 6 As shown, forming a characteristic risk function for power equipment in characteristic fire risk forest areas includes the following steps:

[0103] The critical values ​​of temperature, humidity, precipitation, moisture content of fuels and continuous drought time when fire occurs in characteristic fire risk forest areas are calculated;

[0104] The weighted averages of the contributions of temperature, humidity, precipitation, moisture content of combustibles and continuous drought time to at least one fire trigger were calculated respectively;

[0105] Statistical characteristics: actual values ​​of temperature, humidity, precipitation, moisture content of fuels and continuous drought time in fire risk forest areas;

[0106] The characteristic risk function is as follows: ;

[0107] in, is the actual value of the temperature, is the critical value of temperature, is the weighted mean of the contribution of temperature to at least one fire cause, is the actual value of humidity, is the critical value of humidity, is the weighted mean of the contribution of humidity to at least one fire cause, is the actual value of precipitation, is the critical value of precipitation, is the weighted mean of the contribution of precipitation to at least one fire cause, is the actual value of the moisture content of the combustible material, is the critical value of moisture content in combustibles, is the weighted average of the contribution of the moisture content of combustibles to at least one fire cause, is the actual value of continuous drought time, is the critical value of continuous drought time, It is the weighted average of the contribution of continuous drought time to at least one fire trigger.

[0108] The purpose of forming a characteristic risk function for power equipment in characteristic fire risk forest areas is to form an assessment benchmark for fire risk forest areas, because the overall framework of fire situations in different fire risk forest areas is consistent, but the sizes of the influencing factors are different. Therefore, the fire risk forest area with the lowest risk is selected as the benchmark among the fire risk forest areas. The risk functions of the remaining fire risk forest areas can be calculated based on this, so there is no need to recalculate the entire area, which can save time in obtaining the risk function.

[0109] Reference Figure 7 As shown in FIG, based on the characteristic fire risk forest area, forming the risk function of the fire risk forest area with different risk levels includes the following steps:

[0110] The trigger probability of at least one fire trigger corresponding to the risk level of the fire risk forest area is averaged to obtain the risk coefficient;

[0111] The trigger probability of at least one fire trigger corresponding to the risk level of the characteristic fire risk forest area is averaged to obtain the basic coefficient;

[0112] The risk coefficient is compared with the basic coefficient and multiplied by the characteristic risk function to obtain the risk function of the fire risk forest area.

[0113] In fact, the difference between different fire risk forest areas and characteristic fire risk forest areas is in proportional relationship. Therefore, we only need to obtain the proportional coefficient between the two to obtain the risk function of fire risk forest areas with different risk levels through the characteristic risk function. The proportional coefficient is obtained by comparing the mean value of the triggering probability of the fire trigger.

[0114] Reference Figure 8 As shown in Figure 1, forming an overlay factor for fire risk forest areas includes the following steps:

[0115] The superposition factor is a conditional function, and the superposition factor takes a value of 0 or 1. The superposition factor is paired with the fire risk forest area;

[0116] When the risk level of the actual fire risk forest area crossed by the power equipment is consistent with the risk level of the fire risk forest area corresponding to the superposition factor, the superposition factor of the fire risk forest area is 1; otherwise, the superposition factor of the fire risk forest area is 0.

[0117] The purpose of the overlay factor is to determine the risk function of the fire risk forest area that appears in the overlay function. When the actual fire risk forest area is substituted into the overlay function, when the risk level of the actual fire risk forest area is consistent with that of the fire risk forest area, the overlay factor of the risk function of the fire risk forest area takes a value of 1, otherwise the overlay factor takes a value of 0. In this case, only the risk function of the fire risk forest area that is consistent with the risk level of the actual fire risk forest area appears in the overlay function. Therefore, the overlay function can reflect the actual situation of the current area, and its prediction results are relatively accurate.

[0118] Reference Fig. 9 As shown, according to the location information, determining the risk level of at least one actual fire risk forest area crossed by the power equipment includes the following steps:

[0119] At least one test point is evenly selected on the edge of the actual fire risk forest area, and the location coordinates of the test point are obtained based on GPS;

[0120] For at least one test point, if the distance between the sampling point and the test point in the fire risk forest area does not exceed the preset distance, the area of ​​the actual fire risk forest area is located in the fire risk forest area;

[0121] When an area of ​​an actual fire risk forest area is located within a fire risk forest area, the risk level of the fire risk forest area is assigned to the actual fire risk forest area.

[0122] Reference Fig.10 As shown, forming a superposition function based on at least one actual fire risk forest area spanned by the power equipment includes the following steps:

[0123] Generate a regional reserved position, multiply and superimpose the regional reserved position with the risk function and superposition factor of at least one fire risk forest area, and obtain a superposition function;

[0124] When using the Overlay function, the actual fire risk forest area is substituted into the regional reserve position.

[0125] The regional reserved position is the position where the actual fire risk forest area is substituted. Its purpose is to compare with the fire risk forest area and then determine the value of the superposition factor. When the value of the superposition factor is determined, the regional reserved position is consistent with the value of the superposition factor multiplied by it.

[0126] Furthermore, the present solution also proposes a storage medium on which a computer-readable program is stored, and when the computer-readable program is called, the above-mentioned calculation method of the algorithm superposition of the power equipment crossing the fire risk forest area is executed.

[0127] It is understandable that the storage medium may be a magnetic medium, such as a floppy disk, a hard disk, or a magnetic tape; an optical medium, such as a DVD; or a semiconductor medium, such as a solid state drive (SSD).

[0128] To sum up, the advantages of the present invention are: by obtaining the trigger probability of the fire cause corresponding to the risk level of the fire risk forest area, forming a characteristic risk function for the power equipment in the characteristic fire risk forest area, and forming a risk function for the fire risk forest area with different risk levels, different areas of the forest can be divided, thereby ensuring that the fire risks in the divided areas are relatively consistent, and selecting the characteristic risk function as a benchmark, and using the benchmark to superimpose different areas to obtain the risk function in each area, thereby enabling a targeted assessment of the risk of each area, so that the assessment result is more consistent with the actual situation in each area, avoiding excessive judgment errors and affecting the accuracy of prediction and prevention.

[0129] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A calculation method for superimposing algorithms for power equipment across fire risk forest areas, It is characterized in that include: Based on historical data, at least one fire risk forest area is obtained, the fire risk forest area is graded, and the risk level of the fire risk forest area is obtained; Acquire regional location information of the fire risk forest area, wherein the regional location information includes the coverage of the fire risk forest area; At least one fire trigger that triggers the occurrence of fire in the fire risk forest area; Obtain the triggering probability of the fire cause corresponding to the risk level of the fire risk forest area; Obtain the fire risk forest area with the lowest risk level as the characteristic fire risk forest area; Form a characteristic risk function for power equipment in forest areas with characteristic fire risks; Based on the characteristic fire risk forest areas, a risk function of fire risk forest areas with different risk levels is formed; Forming a superposition factor for the fire risk forest area, determining the risk level of at least one actual fire risk forest area crossed by the power equipment according to the location information, and forming a superposition function based on at least one actual fire risk forest area crossed by the power equipment; When the result of the superposition function of the data input into the actual fire risk forest area is greater than the preset value, the power equipment has a fire risk in the actual fire risk forest area; The forming of a characteristic risk function for power equipment in a characteristic fire risk forest area comprises the following steps: The critical values ​​of temperature, humidity, precipitation, moisture content of fuels and continuous drought time when fire occurs in characteristic fire risk forest areas are calculated; The weighted averages of the contributions of temperature, humidity, precipitation, moisture content of combustibles and continuous drought time to at least one fire trigger were calculated respectively; Statistical characteristics: actual values ​​of temperature, humidity, precipitation, moisture content of fuels and continuous drought time in fire risk forest areas; The characteristic risk function is as follows: ; in, is the actual value of the temperature, is the critical value of temperature, is the weighted mean of the contribution of temperature to at least one fire cause, is the actual value of humidity, is the critical value of humidity, is the weighted mean of the contribution of humidity to at least one fire cause, is the actual value of precipitation, is the critical value of precipitation, is the weighted mean of the contribution of precipitation to at least one fire cause, is the actual value of the moisture content of the combustible material, is the critical value of moisture content in combustibles, is the weighted average of the contribution of the moisture content of combustibles to at least one fire cause, is the actual value of continuous drought time, is the critical value of continuous drought time, is the weighted average of the contribution of continuous drought time to at least one fire trigger; The risk function of fire risk forest areas of different risk levels is formed based on the characteristic fire risk forest areas, comprising the following steps: The trigger probability of at least one fire trigger corresponding to the risk level of the fire risk forest area is averaged to obtain the risk coefficient; The trigger probability of at least one fire trigger corresponding to the risk level of the characteristic fire risk forest area is averaged to obtain the basic coefficient; The risk coefficient is compared with the basic coefficient and multiplied with the characteristic risk function to obtain the risk function of the fire risk forest area; The forming of superposition factors for fire risk forest areas comprises the following steps: The superposition factor is a conditional function, and the superposition factor takes a value of 0 or 1. The superposition factor is paired with the fire risk forest area; When the risk level of the actual fire risk forest area crossed by the power equipment is consistent with the risk level of the fire risk forest area corresponding to the superposition factor, the superposition factor of the fire risk forest area is 1, otherwise the superposition factor of the fire risk forest area is 0; The forming of the superposition function based on at least one actual fire risk forest area spanned by the power equipment comprises the following steps: Generate a regional reserved position, multiply and superimpose the regional reserved position with the risk function and superposition factor of at least one fire risk forest area, and obtain a superposition function; When using the Overlay function, the actual fire risk forest area is substituted into the regional reserve position.

2. According to claim 1, a calculation method for superimposing algorithms for electric power equipment crossing fire risk forest areas, It is characterized in that The classification of the fire risk forest areas to obtain the risk level of the fire risk forest areas includes the following steps: Based on historical data, the frequency of fires in fire-risk forest areas is counted to obtain at least one probability of fire occurrence; Based on at least one fire occurrence probability, a fire occurrence probability range is obtained; Divide the fire occurrence probability range into at least one probability interval; The risk level is assigned to the probability interval according to the value of the center of the probability interval. The larger the value of the center of the probability interval, the greater the risk level. When the probability of fire occurrence in a fire risk forest area falls within a probability interval, the risk level of the probability interval is matched to the fire risk forest area.

3. According to claim 2, a calculation method for superimposing algorithms for electric power equipment crossing fire risk forest areas, It is characterized in that The method of obtaining the regional location information of the fire risk forest area includes the following steps: Obtain the edge of the fire risk forest area, evenly set at least one sampling point inside the fire risk forest area, and obtain the location coordinates of the sampling point based on GPS; The minimum value of the distance from the sampling point to the edge of the fire risk forest area is taken as the characteristic distance; The minimum value of at least one characteristic distance is set to a preset distance.

4. According to claim 3, a calculation method for superimposing algorithms for electric power equipment crossing fire risk forest areas, It is characterized in that The forming of at least one fire trigger that triggers the occurrence of fire in the fire risk forest area comprises the following steps: Extract environmental characteristics of fire risk forest areas when no fire occurs, and obtain at least one unnecessary trigger; Extract environmental characteristics of fires in fire-risk forest areas and obtain at least one suspected trigger; obtaining, as a preliminary fire cause, a suspected trigger among at least one suspected trigger that is different from at least one unnecessary trigger; The conditional probability of triggering a fire is calculated when the initial fire trigger occurs. When the conditional probability of triggering a fire is greater than a preset value, the initial fire trigger is used as the fire trigger.

5. According to claim 4, a calculation method for superimposing algorithms for electric power equipment crossing fire risk forest areas, It is characterized in that The method of obtaining the trigger probability of the fire cause corresponding to the risk level of the fire risk forest area comprises the following steps: Calculate the average values ​​of temperature, humidity, precipitation, moisture content of fuels and continuous drought time in fire risk forest areas of the same risk level; When the temperature, humidity, precipitation, moisture content of combustibles and continuous drought time are taken as extreme values, the probability of fire occurrence is respectively taken as the contribution weights of temperature, humidity, precipitation, moisture content of combustibles and continuous drought time to the fire trigger; The average values ​​of temperature, humidity, precipitation, moisture content of combustibles and continuous drought time in the fire risk forest area of ​​the risk level are multiplied by their contribution weights to the fire triggers and added up to obtain the triggering probability of the fire triggers.

6. According to claim 5, a calculation method for superimposing algorithms for electric power equipment crossing fire risk forest areas, It is characterized in that Determining the risk level of at least one actual fire risk forest area crossed by the power equipment according to the location information comprises the following steps: At least one test point is evenly selected on the edge of the actual fire risk forest area, and the location coordinates of the test point are obtained based on GPS; For at least one test point, if the distance between the sampling point and the test point in the fire risk forest area does not exceed the preset distance, the area of ​​the actual fire risk forest area is located in the fire risk forest area; When an area of ​​an actual fire risk forest area is located within a fire risk forest area, the risk level of the fire risk forest area is assigned to the actual fire risk forest area.

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