Geological risk early warning method, computer readable storage medium and program product

Abstract

The invention provides a geological risk early warning method, a computer readable storage medium and a program product, and the method comprises the steps: obtaining the geological disaster risk grade of a region where a high-voltage transmission tower is located, and obtaining the geological disaster risk grade through comprehensive evaluation according to the geological risk influence factors of the region; generating meteorological early warning indexes according to the geological disaster risk levels, wherein the meteorological early warning indexes comprise judgment thresholds corresponding to different early warning levels; collecting one or more kinds of meteorological effective data of the area, wherein the meteorological effective data is obtained through calculation according to the meteorological real-time data and the meteorological prediction data; comparing the meteorological effective data with a judgment threshold value to determine a corresponding early warning level; and outputting early warning information according to the determined early warning level. The early warning level obtained by the scheme reflects the risk condition of the high-voltage transmission line tower area, so that the early warning level is more accurate, the early warning measures can be taken in a targeted manner, and the safety and the reliability are improved.

Description

Technical Field

[0001] The invention relates to geographic data processing, and in particular to a geological risk early warning method, a computer-readable storage medium and a program product. Background Art

[0002] Power corridors are becoming increasingly crowded. High-voltage transmission lines, especially ultra-high voltage transmission lines, are long overall, with a large number of poles and towers. They pass through areas with complex terrain. The spatial distribution of regional meteorological elements varies significantly, and there is often a risk of geological disasters at the locations of the poles and towers.

[0003] Electricity users have higher and higher requirements for power reliability, especially power supply continuity. The safety and reliability of high-voltage transmission networks face many risk factors. In addition to their own vulnerability, there are many natural factors that pose severe challenges to their safety. According to statistics, natural disasters have become the second largest factor affecting the safety of high-voltage transmission networks after equipment failures, and geological risks, such as landslides, floods, mudslides, rock collapses, etc., are natural disasters that have a greater impact on high-voltage transmission networks. Therefore, geological risk warnings in the area of ​​high-voltage transmission towers are very necessary to improve the safety and reliability of high-voltage transmission networks.

[0004] The existing geological risk warning for high-voltage transmission lines mainly focuses on a single type of geological disaster by monitoring and controlling the factors affecting the disaster, and then analyzing and calculating the data to achieve the purpose of disaster prediction and warning. The indicators of each type of warning are provided by water conservancy, meteorology, geology and other professions to provide warning classification methods, and the warning rating is carried out according to the corresponding observation data, so that different warning measures can be taken according to the warning level.

[0005] However, the above method does not take into account the geological characteristics of the location of the high-voltage transmission line tower. Although the construction location has been surveyed and meets the construction specifications in the early stage of construction planning, the risk resistance capacity varies greatly under different environmental conditions. The existing warning level determination method may not truly reflect the risk situation of the transmission line tower, which is easy to cause false alarms and missed alarms. Summary of the invention

[0006] An object of the present invention is to be able to accurately assess the geological risk warning level of the high voltage transmission line tower area.

[0007] In particular, according to one aspect of the present invention, the present invention provides a geological risk early warning method for a high-voltage transmission line tower area, comprising:

[0008] Obtain the geological disaster risk level of the area where the high-voltage transmission tower is located. The geological disaster risk level is obtained through comprehensive evaluation based on the geological hazard influencing factors of the area;

[0009] Generate meteorological warning indicators according to the geological disaster risk level, including the judgment thresholds corresponding to different warning levels;

[0010] Collect one or more effective meteorological data of the area, which are calculated based on real-time meteorological data and meteorological forecast data;

[0011] Compare the effective meteorological data with the judgment threshold to determine the corresponding warning level;

[0012] Output warning information according to the determined warning level.

[0013] Optionally, after the step of determining the corresponding warning level, the method further includes:

[0014] When the warning level is higher than the preset level threshold, determine the geological hazard influencing factors affected by the effective meteorological data;

[0015] Re-collect the geological hazard influencing factors affected by the effective meteorological data to obtain updated factor data;

[0016] Re-evaluate the geological hazard risk level based on the updated factor data to update the geological hazard risk level;

[0017] A hazard visual interface is generated based on the map of the high-voltage transmission line tower area according to the updated geological hazard risk level.

[0018] Optionally, the meteorological valid data includes precipitation valid data; and

[0019] The steps to collect effective precipitation data for a region include:

[0020] Obtain historical precipitation observation data of precipitation observation stations in the area where the high-voltage transmission tower is located and the surrounding preset area;

[0021] Calculate the actual effective precipitation in the area where the high-voltage transmission tower is located based on historical precipitation observation data;

[0022] Obtain precipitation forecast information in the area where the high-voltage transmission tower is located;

[0023] Calculate the expected effective precipitation based on the precipitation forecast information and the actual effective precipitation.

[0024] Optionally, the step of calculating the actual effective precipitation in the area where the high-voltage transmission tower is located according to the historical precipitation observation data includes:

[0025] Determine the number of precipitation observing stations;

[0026] When there are multiple precipitation observation stations, respectively obtain the distances from the multiple precipitation observation stations to the high-voltage transmission line towers;

[0027] Calculate the precipitation observation evaluation data of the area where the high-voltage transmission tower is located in each historical period according to the distance and the historical precipitation observation data of each precipitation observation station;

[0028] Determine the actual influencing factors of precipitation observation evaluation data according to the length of time from the corresponding historical period to the current time point;

[0029] The actual effective precipitation is calculated based on the precipitation observation evaluation data for each historical period and its actual influencing factors.

[0030] Optionally, the step of calculating the expected effective precipitation according to the precipitation forecast information and the actual effective precipitation includes:

[0031] Configure the first expected impact factor according to the time from the expected time point to the current time point, and use the first expected impact factor to make an expected correction to the actual effective precipitation;

[0032] Determine the expected precipitation in a plurality of expected time periods from the expected time point to the current time point from the precipitation forecast information;

[0033] According to the duration from the end point of each expected time period to the expected time point, the respective second expected impact factors are configured;

[0034] Use the second expected impact factor of each expected period to make an expected correction to the corresponding expected precipitation;

[0035] The expected effective precipitation is calculated based on the actual effective precipitation after the expected correction and the expected precipitation after the expected correction.

[0036] Optionally, the geological hazard influencing factors affected by the effective precipitation data include hydrological conditions and vegetation coverage, and before the step of re-evaluating the geological disaster risk level according to the updated factor data, the following steps are further included:

[0037] Determine whether the weights of hydrological conditions and vegetation coverage need to be increased based on the warning level;

[0038] If so, modify the factor weights of hydrological conditions and vegetation coverage according to the available precipitation data.

[0039] Optionally, the effective meteorological data also includes effective wind speed; and

[0040] The steps to collect the effective wind speed for an area include:

[0041] Obtain wind speed measurement data detected by a wind speed detection device in the area where the high-voltage transmission tower is located;

[0042] Acquire temperature and humidity data detected by temperature and humidity sensors in the area where the high-voltage transmission tower is located;

[0043] The wind speed measurement data is corrected using the temperature and humidity data to obtain the effective wind speed.

[0044] Optionally, the step of generating a meteorological warning indicator according to the geological disaster risk level includes:

[0045] Obtain correction coefficients corresponding to the geological disaster risk levels;

[0046] The preset initial meteorological warning indicators are corrected using correction coefficients to obtain the judgment thresholds corresponding to different warning levels, and the judgment thresholds decrease accordingly as the geological disaster risk level increases.

[0047] According to another aspect of the present invention, there is also provided a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of any of the above-mentioned geological risk early warning methods for high-voltage transmission line tower areas.

[0048] According to another aspect of the present invention, a computer program is also provided, which, when executed by a processor, implements the steps of any of the above-mentioned geological risk early warning methods for high-voltage transmission line tower areas.

[0049] The geological risk early warning method for the high-voltage transmission line tower area of ​​the present invention generates a meteorological early warning index according to the geological disaster risk level. The geological disaster risk level is obtained through comprehensive evaluation based on the geological hazardous influencing factors of the region. The generated meteorological early warning index is consistent with the geological conditions of the high-voltage transmission line tower area, ensuring that the early warning level obtained by using the meteorological early warning index reflects the risk situation of the high-voltage transmission line tower area, making the early warning level more accurate, facilitating targeted early warning measures, avoiding misreporting and omissions of early warnings, improving the risk handling efficiency of power grid operation units, and effectively ensuring the safe and stable operation of the high-voltage transmission network.

[0050] Furthermore, the geological risk early warning method for the high-voltage transmission line tower area of ​​the present invention, when the early warning level is higher than the preset level threshold, re-collects the geological hazard influencing factors affected by the effective meteorological data, re-evaluates the geological disaster risk level, and timely updates the geological environment of the high-voltage transmission line tower area, which is conducive to timely reinforcement and maintenance. The geological conditions of the high-voltage transmission line tower area are intuitively displayed using a dangerous visual interface, which reduces the analysis workload of maintenance personnel and facilitates management.

[0051] Furthermore, the geological risk early warning method for the high-voltage transmission line tower area of ​​the present invention conducts targeted analysis and processing of the collected data such as precipitation and wind speed according to their impact on geological risks, thereby ensuring the accuracy of meteorological early warning indicators.

[0052] Based on the following detailed description of specific embodiments of the present invention in conjunction with the accompanying drawings, those skilled in the art will become more aware of the above and other objects, advantages and features of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Hereinafter, some specific embodiments of the present invention will be described in detail in an exemplary and non-limiting manner with reference to the accompanying drawings. The same reference numerals in the accompanying drawings indicate the same or similar components or parts. It should be understood by those skilled in the art that these drawings are not necessarily drawn to scale. In the accompanying drawings:

[0054] Figure 1 is a schematic diagram of a geological risk early warning method for a high-voltage transmission line tower area according to an embodiment of the present invention;

[0055] Figure 2 is a schematic diagram of determining the geological disaster risk level in a geological risk early warning method for a high-voltage transmission line tower area according to an embodiment of the present invention;

[0056] Figure 3 It is a hierarchical structure diagram of dangerous influencing factors and geological data thereof in a geological risk early warning method for a high-voltage transmission line tower area according to an embodiment of the present invention;

[0057] Figure 4 It is a flow chart for collecting effective precipitation data in a geological risk early warning method for a high-voltage transmission line tower area according to an embodiment of the present invention;

[0058] Figure 5 is a flow chart of calculating effective precipitation in a geological risk early warning method for a high-voltage transmission line tower area according to an embodiment of the present invention;

[0059] Figure 6 is a flow chart of calculating expected effective precipitation in a geological risk early warning method for a high-voltage transmission line tower area according to an embodiment of the present invention;

[0060] Figure 7 It is a flow chart of collecting effective wind speed in an area in a geological risk early warning method for a high-voltage transmission line tower area according to an embodiment of the present invention;

[0061] Figure 8 is a schematic diagram of a computer-readable storage medium according to an embodiment of the present invention; and

[0062] Fig. 9is a schematic diagram of a computer program product according to an embodiment of the present invention. DETAILED DESCRIPTION

[0063] It should be understood by those skilled in the art that the embodiments described below are only some embodiments of the present invention, rather than all embodiments of the present invention, and these embodiments are intended to explain the technical principles of the present invention, rather than to limit the protection scope of the present invention. Based on the embodiments provided by the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should still fall within the protection scope of the present invention.

[0064] Figure 1 1 is a schematic diagram of a geological risk early warning method for a high-voltage transmission line tower region according to an embodiment of the present invention. The geological risk early warning method for a high-voltage transmission line tower region generally may include:

[0065] Step S101, obtaining the geological disaster risk level of the area where the high-voltage transmission tower is located, and the geological disaster risk level is obtained through comprehensive evaluation based on the geological hazard influencing factors of the area.

[0066] Step S102, generating meteorological warning indicators according to the geological disaster risk level, the meteorological warning indicators include judgment thresholds corresponding to different warning levels. Meteorological warning indicators can be configured according to different types of meteorological data. In some embodiments, meteorological warning indicators may include precipitation warning indicators and wind warning indicators. In addition, meteorological warning indicators may also be set according to the environmental characteristics of the high-voltage transmission tower, and additional temperature and humidity indicators (for ice-prone areas, extremely cold areas), effective vegetation coverage, etc. are set. Each meteorological warning indicator includes multiple numerical ranges, each numerical range corresponds to a warning level, and the upper and lower limits of the numerical range are respectively used as judgment thresholds for comparison with the meteorological valid data collected and calculated.

[0067] Step S103, collect one or more effective meteorological data of the area, the effective meteorological data is calculated based on the real-time meteorological data and the meteorological forecast data. In some embodiments, the effective meteorological data may include: effective precipitation data, effective wind speed, etc. In addition, effective temperature, effective humidity, effective vegetation coverage, etc. may be further set.

[0068] Step S104, compare the effective meteorological data with the determination threshold to determine the corresponding warning level. That is, the effective meteorological data is matched with the numerical range of the corresponding meteorological warning index. If the effective meteorological data falls within a certain numerical range, the warning level corresponding to the numerical range is used as the determined warning level.

[0069] Step S105: output warning information according to the determined warning level. In addition to the warning level, the warning information may also include the corresponding response measures of the warning level. Different warning levels may send warning information to different ranges, and the output methods of the warning information may be different.

[0070] The above-mentioned step of generating meteorological warning indicators according to the geological disaster risk level includes: obtaining a correction coefficient corresponding to the geological disaster risk level; using the correction coefficient to correct the preset initial meteorological warning indicator to obtain the judgment threshold corresponding to different warning levels, and the judgment threshold decreases accordingly with the increase of the geological disaster risk level. For example, in the initial state, the judgment threshold intervals of the four warning levels of level one (dangerous level), level two (relatively dangerous level), level three (low dangerous level), and level four (safety level) are respectively set to (T11, T12), (T21, T22), (T31, T32), and (T41, T42). For the geological disaster risk level of the risk-free area, it is still judged according to the judgment threshold of the above-mentioned preset initial meteorological warning indicator. Accordingly, the geological disaster risk level in the low-risk area is set with a correction coefficient q1, the geological disaster risk level in the medium-risk area is set with a correction coefficient q2, the geological disaster risk level in the higher-risk area is set with a correction coefficient q3, and the geological disaster risk level in the high-risk area is set with a correction coefficient q4. For the geological disaster risk level in high-risk areas, the judgment threshold intervals of the four warning levels can be set to (q4*T11, q4*T12), (q4*T21, q4*T22), (q4*T31, q4*T32), (q4*T41, q4*T42). By configuring the values ​​of q1 to q4, the judgment threshold can be lowered, so that for higher geological disaster risk levels, the severity of the warning is correspondingly increased, ensuring that the warning level can accurately indicate the risk.

[0071] The geological risk early warning method for the high-voltage transmission line tower area of ​​the above-mentioned embodiment generates a meteorological early warning index according to the geological disaster risk level. The geological disaster risk level is obtained through comprehensive evaluation based on the geological hazardous influencing factors of the region. The generated meteorological early warning index is consistent with the geological conditions of the high-voltage transmission line tower area, ensuring that the early warning level obtained using the meteorological early warning index reflects the risk situation of the high-voltage transmission line tower area, making the early warning level more accurate, which is conducive to targeted early warning measures, avoiding false alarms and omissions in early warnings, improving the risk handling efficiency of the power grid operation unit, and effectively ensuring the safe and stable operation of the high-voltage transmission network.

[0072] Figure 2Schematic diagram of determining the geological disaster risk level in a geological risk early warning method for a high-voltage transmission line tower area according to an embodiment of the present invention. The geological disaster risk level can be obtained by comprehensive evaluation using geological hazard influencing factors of the area before and after the construction of the high-voltage transmission line tower. The process of determining the geological disaster risk level in some embodiments may include:

[0073] Step S201, obtaining geological data of the high-voltage transmission line tower area.

[0074] The high-voltage transmission line tower area can be an area obtained by expanding to both sides with the line connecting the high-voltage transmission line towers as the center line. For example, a line connecting the high-voltage transmission line towers is established, and the line is used as the center to expand a certain distance (2 kilometers) outward to obtain the high-voltage transmission line tower area. Geological data is classified according to the dangerous influencing factors. The method of this embodiment requires the use of multi-source data, including but not limited to high-precision multi-spectral satellite remote sensing image data, elevation data, water system data, earthquake and geological structure data, etc.

[0075] Step S202: Calculate the geological data according to the preset factor weight corresponding to each dangerous influencing factor to obtain the evaluation index score of each dangerous influencing factor. The factor weight can be configured according to the influence of the geological data type on the dangerous influencing factor.

[0076] An optional execution process of step S202 may be: obtaining a pre-constructed element weight vector for a hazardous impact factor. The element weight vector uses the weight value of each type of geological data in the hazardous impact factor as an element; the geological data score values ​​of the hazardous impact factor are combined into a data vector in the order of the corresponding weight values ​​in the element weight vector; the element weight vector is multiplied with the data vector to obtain the evaluation index score of the hazardous impact factor. By performing a vector dot product calculation, the calculation efficiency can be improved and the assessment process can be accelerated. For example, for a hazardous impact factor, it contains n types of geological data, the corresponding scores are a1, a2, a3...an, and the corresponding weights are p1, p2, p3...pn: the data vector can be a=[a1, a2, a3,...an], and the element weight vector is p=[p1, p2, p3,...pn] T The final evaluation index score of the risk impact factor is

[0077] The construction process of the element weight vector may include: randomly selecting two geological data from the risk influencing factors for importance evaluation; forming a judgment matrix based on the results of the importance evaluation; and performing a consistency check on the judgment matrix. The judgment matrix with a qualified consistency test result is normalized to obtain an element weight vector. One execution process of the step of performing a consistency check on the judgment matrix may include: calculating the maximum eigenvector of the judgment matrix; calculating the inconsistency index based on the maximum eigenvector; calculating the ratio of the inconsistency index to the preset random consistency index, and if the ratio is less than the preset threshold, the consistency test result is determined to be qualified. The judgment matrix is ​​generated by comparing two types of geological data. For example, for the risk influencing factor C and its corresponding geological data factor P, the importance of the factors can be determined by comparing and analyzing the degree of risk impact using a pairwise comparison method.

[0078] The above importance assignment can be obtained by analyzing the previous data, or it can be scored by experts in related fields. After the judgment matrix is ​​constructed, a consistency test is required. After the judgment matrix is ​​constructed, a consistency test is required. Let λmax(A) be the maximum eigenvector in matrix A, then the inconsistency index CI can be set as: The meaning of CI is CI=0, A is completely consistent; the larger the CI, the more serious the inconsistency of A. The random consistency index RI is set to a preset value. The ratio of the inconsistency index to the preset random consistency index is calculated as CR=CI / RI. When CR<0.1, the judgment matrix is ​​judged to meet the consistency (the consistency test result is qualified); if not, the judgment matrix can be modified, and the importance of factors xi and xj can be re-set until the judgment matrix meets the consistency. The above preset ratio threshold of 0.1 can be adjusted according to the evaluation requirements.

[0079] After obtaining a judgment matrix with a qualified consistency test result, the judgment matrix is ​​normalized to obtain the final element weight vector. The normalization process can be: first normalize the column vector of the matrix, that is, the sum of the values ​​of the elements in each column is 1 (the proportional relationship of each element remains unchanged), then sum each row and normalize again, that is, add up the elements of each row separately, take the accumulated sum as the value of each row, and then normalize so that the sum of the values ​​of each row is 1 (the proportional relationship of the elements in each row remains unchanged). The final element weight vector is obtained.

[0080] Step S203, a comprehensive evaluation is performed based on the evaluation index scores of all risk influencing factors to obtain a geological disaster risk assessment value for the high-voltage transmission line tower area. The comprehensive evaluation can also be completed by weight calculation or other calculation methods. For example, a weight is assigned to each risk influencing factor according to the degree of influence of the risk influencing factor on the risk of geological disasters, and then a geological disaster risk assessment value is obtained by weighted calculation.

[0081] The execution process of a comprehensive evaluation may include: obtaining a pre-constructed comprehensive weight vector, the comprehensive weight vector uses the weight value of each hazardous influencing factor as an element; combining the evaluation index scores into an index vector in the order of the corresponding weight values ​​in the comprehensive weight vector; performing a dot multiplication calculation on the comprehensive weight vector and the index vector to obtain a geological hazard assessment value. Thus, the weight calculation is performed again using a calculation method similar to step S102. For example, for m hazardous influencing factors, the corresponding evaluation index scores are C1, C2, C3...Cm, and the corresponding weights are P1, P2, P3...Pm, respectively. Then the index vector can be C=[C1, C2, C3,...Cm], and the comprehensive weight vector is P=[P1, P2, P3,...Pm]. T The final evaluation index score of the risk impact factor is

[0082] The comprehensive weight vector can also be constructed in a similar way to the construction of the element weight vector. First, by comparing the impact of each hazard influencing factor on the geological hazard of the high-voltage transmission line tower area, a judgment matrix is ​​constructed, and after a consistency test, normalization is performed to obtain a comprehensive weight vector. Since the construction process of the comprehensive weight vector is similar to the construction process of the element weight vector, those skilled in the art can realize the construction of the comprehensive weight vector according to the construction method of the element weight vector.

[0083] The obtained geological hazard risk assessment value can be used to generate a risk visual interface based on a map of the high-voltage transmission line tower area. The resulting risk visual interface can intuitively show the geological risk of the high-voltage transmission line tower area.

[0084] Figure 3 It is a hierarchical structure diagram of dangerous influencing factors and their geological data in a geological risk early warning method for a high-voltage transmission line tower area according to an embodiment of the present invention. The geological disaster risk assessment value A is obtained by comprehensive evaluation based on the evaluation index scores of all dangerous influencing factors, wherein the dangerous influencing factors include: engineering lithology C1, topography C2, hydrological conditions C3, surface cover C4, and geological structure C5.

[0085] The geological data belonging to engineering lithology include lithology type P1, which is determined based on the surface exposed lithology and the interlayer lithology related to the occurrence of disasters. Lithology P1 is determined based on the surface exposed lithology and the interlayer related to the occurrence of disasters, and is divided into five categories: loess soft rock and severely weathered granite, soft and hard rock interlayers, hard rock with developed joints, hard sedimentary rock, and hard igneous rock. An example of an optional different lithology score is shown in Table 1, and the higher the score, the higher the danger.

[0086] Table 1

[0087]

[0088] The lithology scores shown in Table 1 are optional example values ​​that can be summarized based on research data on different lithologies.

[0089] The geological data belonging to the topography C2 include: slope height P2, slope gradient P3, slope aspect P4, slope shape P5, and slope structure P6.

[0090] Slope height P2 refers to the height difference from the foot of the slope to the top of the slope, which is extracted using the DEM (Digital Elevation Model) data of the study area through the spatial analysis function of GIS (Geographic Information System). An example of an optional slope height score is shown in Table 2, where a higher score represents a higher risk.

[0091] Table 2

[0092] Rock slope height (m) >300 300-100 100-30 30-15 <15 score 5 4 3 2 1 Soil slope height (m) >300 300-100 100-15 15-10 <10 Rating value 5 4 3 2 1

[0093] The slope height score shown in Table 2 is an optional example value, which can be summarized based on the hazard risk research data of different slope heights.

[0094] The slope P3 can also be extracted based on DEM data. An example of an optional slope score is shown in Table 3. The higher the score, the higher the danger.

[0095] Table 3

[0096] Slope(°) 0-5 5-8 8-15 15-25 25-35 35-90 Rating value 1 3 3 5 2 2

[0097] The slope scores shown in Table 3 are optional example values ​​that can be summarized based on hazard risk research data for different slopes.

[0098] Slope aspect P4 can be extracted based on DEM data and can be divided into 8 categories: NNE (0-45°), NE (45-90°), SE (90-135°), SSE (135-180°), SSW (180-225°), SW (225-270°), NW (270-315°), NW (315-360°). An example of an optional slope aspect score is shown in Table 4, where a higher score indicates a higher risk.

[0099] Table 4

[0100] Slope aspect (°) 0-45 45-90 90-135 135-180 180-225 225-270 270-315 315-360 Rating value 2 3 3 2 1 4 5 3

[0101] The slope aspect scores shown in Table 4 are optional example values ​​that can be summarized based on hazard risk research data for different slope aspects.

[0102] Slope shape P5 Slope shape refers to the cross-sectional shape of the slope, which is divided into three types: straight, concave and convex. It can be extracted using GIS spatial analysis tools. The three types of slopes, straight, concave and convex, are set with corresponding evaluation scores, and the evaluation peak value is summarized based on the risk research data of different slope shapes.

[0103] Slope structure P6 Slope structure refers to the relationship between the strata and the slope, which can be determined based on field geological surveys and is divided into steeply inclined slopes, moderately reversed slopes, gently inclined slopes, flat slopes, oblique slopes, and transverse slopes. An example of an optional slope aspect score is shown in Table 5. The higher the score, the higher the danger.

[0104] Table 5

[0105]

[0106] The slope structure score shown in Table 5 is an optional example value, which can be summarized based on the geological hazard risk research data of different slope structures.

[0107] The geological data belonging to hydrological condition C3 include: surface humidity P8 and distance to the river P7. The surface humidity P8 can be obtained by interpreting remote sensing images, extracting humidity index I (Relative Moisture Index 1, referred to as RMI 1), relative humidity II (Relative Moisture Index 2, referred to as RMI2), normalized moisture index (Normalized Moisture Index, referred to as NDMI) and normalized water index (Modified Normalized Difference Water Index, referred to as MNDWI) from the image, and then using principal component analysis (Principal Component Analysis, referred to as PCA) and SPSS (Statistical Package for the Social Sciences) software to determine the index representing humidity. For example, if the humidity finally obtained is λi, the assigned score can be calculated based on λi.

[0108] The distance P7 from the river is obtained through the water system data and the GIS buffer analysis function. Generally, the study area is divided into five levels: 0-300m, 300-600m, 600-900m, 900-1200m, and >1200m. An example of the score of the distance P7 from the water system is shown in Table 6. The higher the score, the higher the danger.

[0109] Table 6

[0110] Distance to water system (m) 0-300 300-600 600-900 900-1200 >1200 Rating value 5 4 3 2 1

[0111] The scoring value for the distance to the water system shown in Table 6 is an optional example value, which can be summarized based on the research data on the geological hazard risk of the distance to the water system.

[0112] The geological data belonging to surface cover C4 include vegetation coverage P9. Vegetation coverage P9 can be extracted using remote sensing satellite data. Four indexes, Normalized Difference Vegetation Index (NDVI), Simple Ratio Vegetation Index (SRI), Enhanced Vegetation Index (EVI), and Atmospheric Resistance Vegetation Index (ARVI), are extracted from satellite images. Then, the principal component analysis (PCA) method is used to use SPSS software to determine the index that best represents the surface cover. The final calculated surface cover is divided into five categories: <5%, 5%-10%, 10%-15%, 15%-20%, and >20%.

[0113] Similarly, principal component analysis (PCA) was used with SPSS software to determine the index that best represents vegetation coverage, and the assigned score could be set based on the obtained surface coverage.

[0114] Geological data belonging to geological structure C5 may include: distance to geological fault P10 and earthquake intensity impact P1 1. Geological tectonic activities related to high-voltage transmission line towers include faults that are still active in neotectonic movements. Tectonic factors may not be considered when there is no neotectonic movement. According to the distance to the fault, it is divided into five categories, namely 0-300m, 300-500m, 500-100m, 100-1500m and >1500m. An example of scoring of the distance to geological fault P10 is shown in Table 7. The higher the score, the higher the danger.

[0115] Table 7

[0116] Distance from fracture (m) 0-300 300-500 500-1000 1000-1500 >1500 Rating value 5 4 3 2 1

[0117] The score of the distance to geological fault P10 shown in Table 7 is an optional example value, which can be summarized based on the geological hazard risk research data of the distance to geological fault.

[0118] The impact of earthquake intensity impact P11 on the corresponding project is divided into 12 levels of intensity, which are divided into 4 levels, namely >9, 9-7, 6-4, and ≤3. An example of the score of earthquake intensity impact P11 is shown in Table 8. The higher the score, the higher the risk.

[0119] Table 8

[0120] Earthquake intensity (level) ≥9 7-9 6-4 ≤3 Rating value 5 4 3 1

[0121] The scores of earthquake intensity impact shown in Table 8 are optional example values ​​that can be summarized based on the geological hazard risk research data of earthquake intensity impact.

[0122] The pre-set scoring value for each type of geological data reflects the impact of the same type of geological data on the hazard. After obtaining the geological data of each sampling area, the corresponding scoring value can be obtained through the scoring method introduced above.

[0123] The above geological data are classified according to the dangerous influence factors to which they belong, and the geological data of each type of dangerous influence factor are calculated according to the corresponding weight to obtain the evaluation index score of the dangerous influence factor of this type, and then the evaluation index scores of multiple types of dangerous influence factors are comprehensively evaluated to obtain the geological disaster risk assessment value of the high-voltage transmission line tower area. The above geological disaster risk assessment value can be used to generate a dangerous visual interface based on the map of the high-voltage transmission line tower area, so as to intuitively reflect the geological conditions of the high-voltage transmission line tower area.

[0124] In some embodiments, the natural breakpoint method can be used to divide the geological hazard risk assessment value into a set number of numerical intervals, and each numerical interval corresponds to a geological hazard risk level. For example, the geological hazard risk level can be divided into high-risk areas, relatively high-risk areas, medium-risk areas, low-risk areas, and no-risk areas; for example, the geological hazard risk level can be graded from low risk to high risk and set to 1 to 9 levels in sequence. The specific number of geological hazard risk levels can be set according to specific management and early warning processing specifications.

[0125] The above comprehensive evaluation process to obtain the geological hazard risk level provides a method for quickly evaluating the geological hazard risk of each tower location of the high-voltage transmission line. The evaluation is faster and more efficient, and the results are intuitive, providing a data basis for the safety of high-voltage transmission lines, so as to provide targeted early warning forecasts and take protective measures in advance.

[0126] In the geological risk warning method for the high-voltage transmission line tower area of ​​an embodiment of the present invention, the geological disaster risk level is further used to generate meteorological warning indicators, so that the meteorological warning indicators correspond to the geological conditions of the high-voltage transmission line tower area, thereby accurately warning of risks.

[0127] In some embodiments, after the step of determining the corresponding warning level, it may also include: when the warning level is higher than the preset level threshold, determining the geological hazard influencing factors affected by the effective meteorological data; re-collecting the geological hazard influencing factors affected by the effective meteorological data to obtain updated factor data; re-evaluating the geological disaster risk level according to the updated factor data to update the geological disaster risk level; generating a dangerous visual interface based on the map of the high-voltage transmission line tower area according to the updated geological disaster risk level. For example, the warning levels determined according to the effective precipitation data include level one (dangerous level), level two (relatively dangerous level), level three (low dangerous level), and level four (safety level), and the level colors can be represented by red, orange, yellow, and green in turn. If it is determined that the warning level reaches level two or above, the geological hazard risk level needs to be re-evaluated.

[0128] The above-mentioned recollection of geological hazard risk influencing factors and reassessment of geological disaster risk level can still be performed using the above-mentioned process from step S201 to step S203. The above-mentioned geological hazard influencing factors affected by effective meteorological data are selected from all geological hazard influencing factors according to the geological impacts generated by the corresponding meteorological data. For example, precipitation (rainfall, snowfall, etc.) has a greater impact on hydrological conditions, surface cover, and slope structure; for another example, wind force has an impact on factors such as surface cover, slope structure, and lithology.

[0129] Figure 4 The present invention is a flowchart of collecting effective precipitation data in a geological risk early warning method for a high-voltage transmission line tower area according to an embodiment of the present invention. The steps of collecting effective precipitation data in the area include:

[0130] Step S401, obtaining historical precipitation observation data of precipitation observation stations in the area where the high-voltage transmission tower is located and the surrounding preset area;

[0131] Step S402, calculating the actual effective precipitation in the area where the high-voltage transmission tower is located based on the historical precipitation observation data;

[0132] Step S403, obtaining precipitation forecast information of the area where the high-voltage transmission tower is located;

[0133] Step S404, calculating the expected effective precipitation according to the precipitation forecast information and the actual effective precipitation.

[0134] Precipitation, especially heavy rain, is the main factor inducing geological disasters, especially landslides. The impact of precipitation on geological disasters is mainly related to parameters such as rainfall, rainfall time, and rainfall intensity. Under different geological conditions, the impact of precipitation is also different. The method of this embodiment sets corresponding precipitation warning indicators for different geological disaster risk levels, such as setting 4 levels of level one (danger level), level two (relatively dangerous level), level three (low dangerous level), and level four (safety level), and each level is set with a judgment threshold, that is, a numerical range.

[0135] The above process of collecting effective precipitation data takes into account both historical precipitation observation data and expected effective precipitation, thereby achieving the effect of effective warning before danger occurs.

[0136] Figure 5 The present invention is a flowchart of calculating effective precipitation in a geological risk early warning method for a high-voltage transmission line tower area according to an embodiment of the present invention. The process of calculating the actual effective precipitation in the area where the high-voltage transmission tower is located based on historical precipitation observation data may include:

[0137] Step S501, determining the number of precipitation observation stations.

[0138] In the calculation process, the high-voltage transmission tower to be calculated is called the target tower. The actual effective precipitation in the area where the target tower is located is calculated by the measured values ​​of the surrounding precipitation observation stations. The precipitation observation station is generally deployed by the meteorological department and generally does not coincide with the geographical location of the tower. Therefore, this embodiment needs to convert the observation data of the precipitation observation station adjacent to the target tower to obtain the actual effective precipitation.

[0139] When selecting a precipitation observation station, if the precipitation observation station meets the set geographical conditions, the precipitation observation historical data of the single precipitation observation station can be used alone. The above geographical conditions can be that the distance between the precipitation observation station and the target tower is short (for example, within 1 km) and there are no obvious obstacles between the two (for example, there are no mountains, tall buildings, or rivers in between). If there is no precipitation observation station that meets the above geographical conditions, multiple nearby precipitation observation stations are selected.

[0140] In some embodiments, the nearest precipitation observation station can be first selected as the first precipitation observation station Y1, and the line from Y1 to the target tower can be used as the baseline. Then, one or more precipitation observation stations can be selected on both sides of the baseline in a set direction (for example, clockwise or counterclockwise) to minimize the influence of terrain on precipitation calculations.

[0141] Step S502: When there are multiple precipitation observation stations, respectively obtain the distances from the multiple precipitation observation stations to the high-voltage transmission line towers.

[0142] Step S503, calculate the precipitation observation evaluation data of the area where the high-voltage transmission tower is located in each historical period according to the distance and the historical precipitation observation data of each precipitation observation station. Take three precipitation observation stations Y1, Y2, and Y3 as an example, the distances from the target towers are L1, L2, and L3 respectively, and the precipitation observation values ​​in a certain period are P1, P2, and P3 respectively. Then the formula for calculating the precipitation observation evaluation data P in the area where the high-voltage transmission tower is located in the period can be:

[0143] P=((L2+L3)*P1+(L1+L3)*P2+(L1+L2)*P3)) / (2*(L1+L2+L3)).

[0144] Step S504, determine the actual impact factor of the precipitation observation and evaluation data according to the duration from the corresponding historical period to the current time point. For example, in the case of determining precipitation hour by hour, the precipitation observation and evaluation data calculated within 1 hour before the current moment is PA0, the precipitation observation and evaluation data calculated for the previous two hours is PA1, the precipitation observation and evaluation data calculated for the previous three hours is PA2, and so on, then the precipitation observation and evaluation data calculated for the previous hour 24 hours ago is PA23, because the longer the time from the current moment, the water storage capacity, groundwater permeability, and surface water will be gradually attenuated, so the precipitation observation and evaluation data configuration coefficients (i.e., actual impact factors) for different durations can be configured according to the duration and the specific attenuation effect, for example, the coefficient k1 is set for PA1, the coefficient k2 is set for PA2, ..., and the coefficient k23 is set for PA23. k1, k2, ..., k23 can gradually decrease.

[0145] Step S505, calculate the actual effective precipitation according to the precipitation observation evaluation data and its actual influencing factors in each historical period. Still taking the above hourly precipitation determination as an example, the formula for the actual effective precipitation PA finally calculated can be:

[0146] PA=PA0+k1*PA1+k2*PA2+k3*PA3+……+k23*PA23.

[0147] Figure 6 The present invention is a flowchart of calculating the expected effective precipitation in the geological risk early warning method for the high-voltage transmission line tower area according to an embodiment of the present invention. The step of calculating the expected effective precipitation based on the precipitation forecast information and the actual effective precipitation includes:

[0148] Step S601, configure the first expected impact factor according to the time from the expected time point to the current time point, and use the first expected impact factor to make an expected correction to the actual effective precipitation. As the time from the expected time point to the current time point increases, the impact of the current actual effective precipitation on the expected time point may decrease. Therefore, by configuring the first expected impact factor and making an expected correction to the actual effective precipitation, the expected corrected actual effective precipitation can reflect the geological impact of the precipitation at that time on the expected time point.

[0149] The formula for the corrected actual effective precipitation PAf can be:

[0150] PAf=m1*PA, where m1 is the first expected impact factor, which is set according to the length of time from the expected time point to the current time point and the degree to which the geological conditions are affected by precipitation.

[0151] Step S602, determining the expected precipitation in multiple expected time periods from the expected time point to the current time point from the precipitation forecast information. This embodiment can calculate the expected precipitation at multiple expected time points, such as the expected precipitation after 24 hours, the expected precipitation after 36 hours, the expected precipitation after 48 hours, and the expected precipitation after 72 hours. The expected time point to the current time point can be divided into multiple expected time periods according to the forecast period of the precipitation forecast. Taking the precipitation forecast with a period of 12 hours as an example, the expected precipitation after 24 hours includes 2 expected time periods, the expected precipitation after 36 hours includes 3 expected time periods, and so on.

[0152] Step S603, respectively configure the respective second expected impact factors according to the duration from the end point of each expected time period to the expected time point. Still taking the precipitation forecast with a cycle of 12 hours as an example, the expected precipitation after 36 hours includes 3 expected time periods, and the second expected impact factors mf1, mf2, and mf3 can be configured for the expected precipitation Pf1, Pf2, and Pf3 in the 3 expected time periods.

[0153] Step S604, using the second expected impact factor of each expected period to perform expected correction on the corresponding expected precipitation. The expected precipitations Pf1, Pf2, and Pf3 in the three expected periods can be respectively Pf1*mf1, Pf2*mf2, and Pf3*mf3 after expected correction. The calculation formula of the expected corrected expected precipitation Pf can be: Pf=Pf1*mf1+Pf2*mf2+Pf3*mf3.

[0154] Step S605, calculate the expected effective precipitation according to the expected corrected actual effective precipitation and the expected corrected expected precipitation. The expected effective precipitation Pftotal calculated finally = PAf + Pf.

[0155] Through the above calculations, the impact of precipitation on geological disasters in the future can be accurately estimated, thereby further accurately determining the warning level.

[0156] The geological hazard influencing factors affected by the effective precipitation data may include hydrological conditions and vegetation coverage, and before the step of re-evaluating the geological disaster risk level according to the updated factor data, it also includes: judging whether the element weights of hydrological conditions and vegetation coverage need to be increased according to the warning level; if so, modifying the element weights of hydrological conditions and vegetation coverage according to the effective precipitation data. That is, redetermine the element weight vector. The basis for judging whether the element weights of hydrological conditions and vegetation coverage need to be increased according to the warning level can be that if the warning level reaches the set level, for example, reaches a more dangerous level, the element weights of hydrological conditions and vegetation coverage can be automatically increased. In other embodiments, the above-mentioned operation of increasing the weight can be triggered by the management personnel after the warning information is issued.

[0157] Extreme temperature changes, such as freeze-thaw cycles, can cause changes in the physical properties of soil and rock, increasing the risk of geological instability. In cold regions, melting permafrost or retreating glaciers can cause ground subsidence or sliding. Increased air humidity can affect soil water content, especially under conditions of sustained high humidity, increasing soil saturation and thus increasing the likelihood of landslides. Strong winds weaken the stability of the surface, and their effects on geological factors are also affected by extreme temperatures and humidity.

[0158] In some embodiments, the meteorological validity data may also include effective wind speed. Figure 7 This is a flow chart of collecting effective wind speed in a region in a geological risk early warning method for a high-voltage transmission line tower region according to an embodiment of the present invention. The step of collecting effective wind speed in a region may include:

[0159] Step S701, obtaining wind speed measurement data detected by a wind speed detection device in an area where a high-voltage transmission tower is located.

[0160] Step S70, obtaining temperature and humidity data detected by temperature and humidity sensors in the area where the high-voltage transmission tower is located.

[0161] Step S703, using the temperature and humidity data to correct the wind speed measurement data to obtain an effective wind speed. The correction method can be that if the temperature and humidity data reaches a preset extreme value, such as high temperature or extreme cold, the wind speed measurement data is multiplied by a set coefficient, and the effective wind speed obtained is greater than the wind speed measurement data, thereby fully considering the impact of high temperature or extreme cold environment on ice covering, rock weathering, etc.

[0162] The process of wind warning is similar to the above-mentioned precipitation warning process and will not be elaborated here.

[0163] This embodiment also provides a computer-readable storage medium 10 and a computer program product 30 according to an embodiment of the present invention. Figure 8 1 is a schematic diagram of a computer readable storage medium 10 according to an embodiment of the present invention. The computer readable storage medium 10 stores a computer program 11, which, when executed by a processor 20, implements the steps of the geological risk early warning method for a high-voltage transmission line tower area in any of the above embodiments.

[0164] Fig. 9 1 is a schematic diagram of a computer program product 30 according to an embodiment of the present invention. The computer program product 30 includes a computer program 11, which, when executed by a processor 20, implements the steps of the geological risk early warning method for a high-voltage transmission line tower area in any of the above embodiments.

[0165] For the purpose of describing the present embodiment, the computer-readable storage medium 10 can be any device that can contain, store, communicate, propagate or transmit a program for use with an instruction execution system, device or apparatus or in conjunction with such instruction execution system, device or apparatus. More specific examples (non-exhaustive list) of the computer-readable storage medium 10 include the following: an electrical connection portion having one or more wirings (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM).

[0166] The computer program 11 described herein can be downloaded from the computer-readable storage medium 10 to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium 10 in each computing / processing device.

[0167] The computer program 11 for performing the operations of the present invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages.

[0168] The processor 20 that executes the above-mentioned computer program 11 can be any suitable processing device (e.g., processor core, microprocessor, ASIC, FPGA, controller, microcontroller, etc.) and can be one processor 20 or multiple processors 20 that are operably connected.

[0169] It should be understood that each part of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system.

[0170] The flow chart provided by the present embodiment is not intended to indicate that the operation of the method will be performed in any particular order, or that all operations of the method are included in all every case. In addition, the method may include additional operations. Within the scope of the technical ideas provided by the present embodiment method, additional changes may be made to the above method.

[0171] At this point, those skilled in the art should recognize that, although multiple exemplary embodiments of the present invention have been shown and described in detail herein, many other variations or modifications that conform to the principles of the present invention can still be directly determined or derived based on the content disclosed in the present invention without departing from the spirit and scope of the present invention. Therefore, the scope of the present invention should be understood and recognized as covering all these other variations or modifications.

Claims

1. A geological risk early warning method for a high-voltage transmission line tower area, comprising: Obtaining the geological disaster risk level of the area where the high-voltage transmission tower is located, wherein the geological disaster risk level is obtained through comprehensive evaluation based on the geological hazard influencing factors of the area; Generate a meteorological warning index according to the geological disaster risk level, wherein the meteorological warning index includes determination thresholds corresponding to different warning levels; Collecting one or more effective meteorological data of the area, wherein the effective meteorological data is calculated based on real-time meteorological data and meteorological forecast data; Comparing the meteorological effective data with the determination threshold to determine the corresponding warning level; Output warning information according to the determined warning level.

2. The geological risk early warning method for the high-voltage transmission line tower area according to claim 1, wherein: After the step of determining the corresponding warning level, the method further includes: When the warning level is higher than a preset level threshold, determining geological hazard influencing factors affected by the effective meteorological data; Re-collecting geological hazard influencing factors affected by the effective meteorological data to obtain updated factor data; Re-evaluating the geological disaster risk level according to the updated factor data to update the geological disaster risk level; A hazard visual interface is generated based on the map of the high-voltage transmission line tower area according to the updated geological disaster risk level.

3. The geological risk early warning method for high-voltage transmission line tower areas according to claim 2, wherein: The meteorological valid data includes precipitation valid data; and The step of collecting the effective precipitation data of the area comprises: Obtaining historical precipitation observation data of precipitation observation stations in the area where the high-voltage transmission tower is located and in the surrounding preset area; Calculate the actual effective precipitation in the area where the high-voltage transmission tower is located based on the historical precipitation observation data; Obtaining precipitation forecast information for the area where the high-voltage transmission tower is located; The expected effective precipitation is calculated based on the precipitation forecast information and the actual effective precipitation.

4. The geological risk early warning method for high-voltage transmission line tower areas according to claim 3, wherein: The step of calculating the actual effective precipitation in the area where the high-voltage transmission tower is located according to the precipitation observation history data comprises: determining the number of said precipitation observing stations; In the case where there are multiple precipitation observation stations, respectively obtaining the distances from the multiple precipitation observation stations to the high-voltage transmission line tower; Calculate the precipitation observation evaluation data of the area where the high-voltage transmission tower is located in each historical period according to the distance and the precipitation observation historical data of each precipitation observation station; Determine the actual impact factor of the precipitation observation evaluation data according to the time from the corresponding historical period to the current time point; The actual effective precipitation is calculated based on the precipitation observation evaluation data and its actual influencing factors in each historical period.

5. The geological risk early warning method for high-voltage transmission line tower areas according to claim 3, wherein: The step of calculating the expected effective precipitation according to the precipitation forecast information and the actual effective precipitation comprises: Configure a first expected impact factor according to the time from the expected time point to the current time point, and use the first expected impact factor to make an expected correction to the actual effective precipitation; Determine the expected precipitation in a plurality of expected time periods from the expected time point to the current time point from the precipitation forecast information; According to the time from the end point of each expected time period to the expected time point, respectively configure the respective second expected impact factors; Using the second expected impact factor of each expected period to make an expected correction to the corresponding expected precipitation; The expected effective precipitation is calculated based on the actual effective precipitation after the expected correction and the expected precipitation after the expected correction.

6. The geological risk early warning method for a high-voltage transmission line tower area according to any one of claims 3 to 5, wherein: The geological hazard influencing factors affected by the effective precipitation data include hydrological conditions and vegetation coverage, and before the step of re-evaluating the geological disaster risk level according to the updated factor data, the step also includes: Determining whether the weights of the hydrological conditions and the vegetation coverage need to be increased according to the warning level; If so, modify the element weights of the hydrological conditions and the vegetation coverage according to the effective precipitation data.

7. The geological risk early warning method for a high-voltage transmission line tower area according to any one of claims 1 to 6, wherein: The effective meteorological data also includes effective wind speed; and The step of collecting the effective wind speed in the area comprises: Acquire wind speed measurement data detected by a wind speed detection device in the area where the high-voltage transmission tower is located; Acquire temperature and humidity data detected by a temperature and humidity sensor in the area where the high-voltage transmission tower is located; The wind speed measurement data is corrected using the temperature and humidity data to obtain the effective wind speed.

8. The geological risk early warning method for a high-voltage transmission line tower area according to any one of claims 1 to 7, wherein: The step of generating a meteorological warning indicator according to the geological disaster risk level comprises: Obtaining a correction coefficient corresponding to the geological disaster risk level; The preset initial meteorological warning index is corrected using the correction coefficient to obtain the determination thresholds corresponding to the different warning levels, and the determination thresholds decrease accordingly as the geological disaster risk level increases.

9. A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the geological risk early warning method for a high-voltage transmission line tower area according to any one of claims 1 to 8.

10. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the steps of the geological risk early warning method for a high-voltage transmission line tower area according to any one of claims 1 to 8 are implemented.

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