CN111582597B - Method and equipment for predicting landslide hazard of power transmission line - Google Patents
Method and equipment for predicting landslide hazard of power transmission line Download PDFInfo
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Abstract
The invention discloses a landslide hazard prediction method for a power transmission line, which is based on collection and preparation of various sources and various types of data, and comprises the steps of extracting, quantifying and analyzing relevant disaster factor data of a power transmission line region by utilizing spatial data digital rasterization, and establishing a geographic spatial information model by utilizing a GIS superposition analysis method to predict the landslide hazard of the power transmission line region. And integrating topography, landform, geology, vegetation, hydrology, meteorological factors and engineering induction factors, calculating the index weights of all parameters by adopting a analytic hierarchy process, and finally establishing and solving a model through data standardization and reclassification to determine the landslide hazard risk level of the power transmission line region. According to the invention, the risk grade classification is carried out on landslide disasters of the power transmission line area by adopting an analytic hierarchy process and a geospatial information model, so that a reliable basis is provided for the safety control of the power transmission line.
Description
Technical Field
The invention relates to the field of natural disaster prediction, in particular to a method and equipment for predicting landslide hazard of a power transmission line.
Background
Landslide refers to the natural phenomenon that a large amount of mountain substances suddenly slide downwards along a sliding surface inside the mountain substances under the action of gravity, and the landslide is stimulated by various external factors, such as earthquake, volcanic, river scouring, snow melting, rainfall, human activities and the like. Especially the destructive power of other secondary disasters caused by large landslides is far more than its direct destructive power.
The types and development rules of the geological disasters in different sections are different, but the development distribution of the geological disasters still has obvious space-time rules, namely GIS (Geographic Information System), has unique visual effect and advanced and complete image drawing function, and fully applies the GIS to one of the hot directions of the current geological disaster research in various disaster relief works. Therefore, there is an urgent need to design a method for predicting landslide risk of a power transmission line to solve such problems.
Disclosure of Invention
The invention aims to provide a method for predicting landslide hazard of a power transmission line,
in order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
the invention comprises the following steps:
a, performing ground object interpretation and digitization through remote sensing images and visual interpretation, extracting lithology, fracture and road indexes, obtaining DEM data of a target section area of a power transmission line, and inputting parameter information obtained by performing surface analysis on the DEM data into a corresponding spatial database;
b, constructing an information quantity risk prediction model in the spatial database: grading the influence factors, counting the information quantity of landslide disasters of the power transmission line, and representing the degree of risk predictability by using the information quantity of the quantized data;
reclassifying all quantized data of the target area, judging the effectiveness of the model according to the distribution condition of the existing power transmission line partitions, if the model is effective, continuing to execute, otherwise, returning, and evaluating again after checking the quality of the influence factor data or updating the influence factor;
determining a key priority processing candidate line area through a judging result of the effectiveness of the model, determining power transmission lines to be processed preferentially in the subareas according to the risk prediction grade, creating a power transmission network data set according to an actual power transmission network, screening out the power transmission lines (demand points) to be processed preferentially, and marking the power transmission lines in the corresponding space coordinate area;
e, outputting the final evaluation grade: and determining landslide hazard grades of the power transmission lines according to the hazard prediction grades, overlapping and analyzing the digitized hazard prediction partition map layers and the power transmission line map layers, selecting the power transmission lines positioned in the areas with high or extremely high hazard prediction, and determining the safety hazard grades of the evaluated power transmission line section areas.
Further, the data of the remote sensing image is derived from a global public high-resolution image or an airborne high-resolution remote sensing image acquired by an unmanned aerial vehicle (helicopter), the DEM is generated by processing airborne three-dimensional laser Lidar data point clouds of the helicopter, and the derived data comprises a gradient index, a slope index, a curvature index, a vegetation index and a river.
Further, reclassifying the information quantity of all grids in the target area, and judging the effectiveness of the model according to the distribution condition of the power transmission line subareas.
Further, determining and grading the influence factors, visually representing the degree of closeness between the influence factors and the research object through the information quantity value of the information quantity model, and selecting the dangerous prediction influence factors by combining the actual conditions of the target area.
A risk detection apparatus for detecting a power transmission line, the risk detection apparatus comprising:
the data receiving device is used for performing ground object interpretation and digitization through remote sensing images and visual interpretation, extracting lithology, fracture and road indexes and acquiring DEM data of a target section area of the power transmission line;
the data storage device is used for storing the DEM data and the DEM data information of the target segment area and analysis comparison information, and inputting the parameter information obtained by carrying out surface analysis on the DEM data into a corresponding spatial database;
model construction means for constructing an information amount risk prediction model in the spatial database: grading the influence factors, counting the information quantity of landslide disasters of the power transmission line, and representing the degree of risk predictability by using the information quantity of the quantized data;
the data classification device reclassifies all quantized data of the target area, judges the validity of the model according to the distribution condition of the existing power transmission line partitions, if the model is valid, continues to execute, otherwise returns, and re-evaluates the data after checking the quality of the influence factors or updating the influence factors;
the data judging device is used for determining a key priority processing candidate line area according to a judging result of the effectiveness of the model, determining power transmission lines needing priority processing in the subareas according to the risk prediction grade, creating a power transmission network data set according to an actual power transmission network, screening out the power transmission lines (demand points) needing priority processing and marking the power transmission lines in the corresponding space coordinate areas;
and the evaluation output device determines landslide disaster grade of the power transmission line according to the risk prediction grade, stacks and analyzes the digitized risk prediction partition layer and the power transmission line layer, selects the power transmission line positioned in the area with high or extremely high risk prediction, and determines the safety risk grade of the evaluated power transmission line section area.
Further, the data classifying device can be used for reclassifying the information quantity of all grids of the target area, and judging the effectiveness of the model according to the distribution condition of the power transmission line partitions.
Further, the data classification device can be used for determining and classifying the influence factors, the information quantity model intuitively shows the degree of tightness between the influence factors and the study objects through the information quantity value, and according to the actual situation of a target area, factor indexes such as gradient, slope direction, height, vegetation, river, lithology, fracture zone, precipitation and the like are selected for predicting the influence factors, the influence factors are classified, and the number of occurrence of the power transmission line disasters in each factor classification area is counted by using an area counting tool.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements a transmission line landslide risk prediction method when executing the computer program.
A computer-readable storage medium storing a computer program for executing a transmission line landslide hazard prediction method.
Compared with the prior art, the invention has the following beneficial effects:
according to the invention, the risk classification is carried out on the power transmission line research area based on the geospatial information model by adopting an analytic hierarchy process, a safety stability evaluation basis is provided for the power transmission line, the safety of the whole line is evaluated by comparing and calculating the quantized data of the line, and a more powerful technical support is provided for the safety control design and construction of the power transmission line channel.
Drawings
Fig. 1 is a schematic diagram of an evaluation technical route of a landslide hazard prediction method of a power transmission line;
FIG. 2 is a schematic diagram of the index of the evaluation system;
fig. 3 is a schematic diagram of DEM data of line a according to the invention;
fig. 4 is a schematic diagram of DEM data of line B according to the invention;
fig. 5 is a schematic diagram of DEM data of line C according to the invention.
Detailed Description
The invention will be further illustrated by the following description and examples, which include but are not limited to the following examples.
As shown in fig. 1 and 2, the present invention includes the steps of:
a, acquiring parameter information of a target area;
b, performing ground object interpretation and digitization through remote sensing images and visual interpretation, extracting lithology, fracture and road indexes, obtaining DEM data of a target section area of the power transmission line, and inputting parameter information obtained by performing surface analysis on the DEM data into a corresponding spatial database;
c, constructing an information quantity risk prediction model: grading the influence factors and counting the information quantity of landslide disasters of the power transmission line, and then superposing the information quantity of all factors, wherein the information quantity of the quantized data represents the degree of risk predictability:
reclassifying all quantized data of the target area, judging the effectiveness of the model according to the distribution condition of the existing power transmission line partitions, if the model is effective, continuing to execute, otherwise, returning, and evaluating again after checking the quality of the influence factor data or updating the influence factor;
e, determining a key priority processing candidate line area according to a judging result of the effectiveness of the model, determining the power transmission lines to be processed preferentially in the subareas according to the risk prediction grade, creating a power transmission network data set according to an actual power transmission network, screening out the power transmission lines (demand points) to be processed preferentially, and marking the power transmission lines in the corresponding space coordinate area;
f, outputting the final evaluation grade: and determining landslide disaster grades of the power transmission lines according to the risk prediction grades, overlapping and analyzing the digitized risk prediction partition map layers and the power transmission line map layers, selecting the power transmission lines positioned in the areas with high or extremely high risk prediction, and primarily determining the safety risk grades of the evaluated power transmission line section areas.
The remote sensing image data are derived from global public high-resolution images or aerial vehicle (helicopter) acquired aviation onboard high-resolution remote sensing images, the DEM is generated by processing helicopter onboard three-dimensional laser Lidar data point clouds, and the data further derive the indexes including gradient indexes, slope indexes, curvature indexes, vegetation indexes, rivers and the like.
Reclassifying the information quantity of all grids in the target area, and judging the effectiveness of the model according to the distribution condition of the existing power transmission line subareas.
And determining and grading the influence factors, visually representing the degree of tightness between the influence factors and the research object by the information quantity model through the information quantity value, selecting dangerous prediction influence factors, such as factor indexes of gradient, slope direction, elevation, vegetation, river, lithology, fracture zone, precipitation and the like, grading the influence factors according to the actual conditions of the target area, and counting the occurrence quantity of the power transmission line disasters in each factor classification area by using an area counting tool.
The distribution of landslide has close relation with water system and valley topography, and the effects of weathering and unloading are remarkable on two sides of a deep river valley in a mountain-extremely high mountain area, so that the landslide becomes a disaster area of collapse, landslide and debris flow. The landform is expressed as a deep canyon and a steep mountain, landslide often occurs simultaneously with collapse and debris flow, has mass-sending characteristics, and has serious threat to highways and resident facilities because geological disasters are densely distributed in a strip shape in part of areas.
The landslide hazard has obvious seasonality and is often synchronous with the rainstorm and flood in the rainy season. The promotion effect of rainfall on geological disasters is mainly represented by rainfall saturated rock-soil mass and volume weight increase; the humidity of the rock soil is increased and the intensity is reduced; the rain seeps downwards, the ground water level rises and flows, and hydrostatic pressure and lifting pressure are generated, so that the anti-skid resistance near a potential sliding surface is reduced; the rainfall makes river water swell and fall, especially the mountain flood is very easy to wash the surface layer deposit of the bank slope and wash the slope feet, resulting in deformation and damage of the bank slope.
The extent of geological disaster development is closely related to stratum lithology, and the type and the nature of a rock-soil body are fundamental factors influencing the stability of a slope. The distribution of landslide disasters is obviously controlled by geological structures, and the types, scales and occurrence frequencies of the geological disasters are consistent with the regional structures, so that obvious zoning and zoning characteristics are shown. The field investigation shows that most of slopes passing through regional large breaks, fold shaft parts, extrusion broken belts, joint dense belts and the like are poor in stability, and are high-probability parts of landslides.
Seismic and ergonomic activities are important factors in inducing geologic hazards. The strong earthquake not only can form a large-scale ground surface fracture zone, but also can obviously reduce the strength of a rock-soil body and destroy the stability of a natural slope, thereby forming a large-scale mountain geological disaster. Collapse, landslide and debris flow disasters caused by earthquakes far exceed those directly caused by earthquakes themselves in certain areas. Human engineering activities are important factors for inducing geological disasters, and due to the fact that in recent years, human beings destroy surface vegetation and the construction of partial engineering buildings excavate slopes, ecological environments are destroyed, water and soil loss is caused, natural stable states of the slopes are destroyed, and collapse and landslide caused are continuously caused; a large amount of soil and stones stripped by cutting slopes are discarded into the channels, so that a rich source of solid substances is provided for the formation of debris flow.
Examples
The line A is positioned on a south Jing fracture zone, the fracture zone is a regional trunk fracture structural zone with certain cutting depth, scale and division, and the line A is a north Fuan pool first town, minqing, germany and south Jing line, extends to about 30 degrees in North east, and has a length of more than 400km in province, a south Guangdong, a north Zhejiang and a aviation sheet, and has clear linear images.
Line B is seen in the area of the vast horizontal formation zone between the north edge of the royal fold and the southwest extending tail of the eastern parallel ridge Gu Ou, and in the northwest of the eastern Yanshan volcanic fracture zone of the Min, in the southeast coastal volcanic zone. The Chuan Dong region is in the Hua-Zhang mountain fracture zone and the Hua-Ying mountain fracture zone south section, which are approximately parallel and distributed in a feathered form. The Yingshan fracture zone is a rule-based fracture zone in the eastern part of the Sichuan basin, the total length of which exceeds 300 km, passes through Dazhou, guangan, chongqing, luzhou, neijiang, yonggong and Yibin seven markets and extends into Yunnan. The activity is not obvious since the north (Dazhou-Hechuan) metric element, the seismic record is not destructive, and the south (Hechuan-Yibin) is a susceptible area of medium-intensity seismic.
The line C is mainly broken in thirty in Hubei province, and mainly breaks in two groups of NE (NNE) and NW (NNW) according to trend, and the SN breaks in the direction of the adjacent EW. The latest activity age of most breaks is the early and middle updating ages, and the late updating ages are distributed in the Massa Medicata Fermentata and Rota of the northwest of the jaw, the former is represented by the break of the bamboo mountain-bamboo stream and the break of the Qingfeng, and the latter is represented by the break of the mountain-Rota. The fracture movement in the new construction movement period is mostly represented as positive fault property, the vertical difference dislocation of the two discs is large, the horizontal displacement is not obvious, and the fracture movement strength of different regions is different. Recent studies have shown that the fracture of the golden house shed has a certain sign of activity at late renewal and has the property of reverse-flushing activity.
TABLE 1 Risk evaluation determination matrix
In this embodiment, as shown in fig. 3, 4 and 5, table 1 is a risk evaluation determination matrix of the factor index. The distribution of geological disasters has close relation with water systems and valley landforms, and landslide has the characteristics of mass-developing and centralized induction. Some landslide has huge scale and complex cause; some complex slope bodies are often misjudged as huge landslide bodies due to landslide features. The development rule of landslide is mainly characterized in that (1) landslide intensively develops in deep canyons and tributary valleys thereof, and is closely related to the landform characteristics and structures, lithology and vegetation conditions. (2) Landslide mostly develops in slate, schist, and sand shale areas. (3) In the same lithology area, landslide develops along fracture structural bands and joint dense bands. (4) The lithology is the same, the steeper the valley slope is, the more favorable the landslide and collapse development is. Risk assessment is carried out on three power transmission line research areas of a route A, a route B and a route C, and risk classification is carried out on the research areas by adopting a hierarchical analysis method through high-precision DEM and DOM data, so that a stability basis is provided for the power transmission lines. Meanwhile, a principle method is provided for line selection and stability prediction of transmission lines, railways, highways and the like, and the method has important reference value.
Stability analysis is carried out on the slope bodies of the three power transmission lines, so that stability coefficients of the three power transmission lines under two working conditions are obtained. Through comparison, the stability coefficient under the natural working condition is larger, the landslide body is in a stable state, and the stability coefficient of the landslide body is sharply reduced under the heavy rain working condition but is still in a more stable state. By comparing the cloud pictures, compared with the displacement, stress and strain under the natural working condition, the three calculated result values under the obvious heavy rain working condition are obviously increased, and the landslide body is in a dangerous state.
The three-dimensional geological model established in the numerical simulation process is expanded from a typical section, and can approximately reflect the condition of a landslide body. And the section of the two dangerous section shapes is selected for calculation, the average value of the stability coefficients is taken to evaluate the safety of the whole line, and the judgment result can be used as a reference to provide more powerful technical support for the design and construction of the power transmission line channel.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical aspects of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the above embodiments, it should be understood by those of ordinary skill in the art that: modifications and equivalents may be made to the specific embodiments of the invention without departing from the spirit and scope of the invention, which is intended to be covered by the claims.
Claims (7)
1. The method for predicting the landslide hazard of the power transmission line is characterized by comprising the following steps of:
a, performing ground object interpretation and digitization through remote sensing images and visual interpretation, extracting lithology, fracture and road indexes, obtaining DEM data of a target section area of a power transmission line, and inputting parameter information obtained by performing surface analysis on the DEM data into a corresponding spatial database;
b, constructing an information quantity risk prediction model in the spatial database: grading the influence factors, counting the information quantity of landslide disasters of the power transmission line, and representing the degree of risk predictability by using the information quantity of the quantized data;
reclassifying the information quantity of grids corresponding to all quantized data in the target area, judging the effectiveness of the model according to the distribution condition of the existing power transmission line partitions, if the model is effective, continuing to execute, otherwise, returning, and re-evaluating after checking the quality of the data of the influence factors or updating the influence factors;
determining a key priority processing candidate line area according to a judging result of the effectiveness of the model, determining power transmission lines needing priority processing in the subareas according to the risk prediction grade, creating a power transmission network data set according to an actual power transmission network, screening out the power transmission lines needing priority processing and marking the power transmission lines in a corresponding space coordinate area;
e, outputting the final evaluation grade: and determining landslide hazard grades of the power transmission lines according to the hazard prediction grades, overlapping and analyzing the digitized hazard prediction partition map layers and the power transmission line map layers, selecting the power transmission lines positioned in the areas with high or extremely high hazard prediction, and determining the safety hazard grades of the evaluated power transmission line section areas.
2. The method for predicting landslide hazard of a power transmission line according to claim 1, wherein the data of the remote sensing image is derived from a global public high-resolution image or an airborne high-resolution remote sensing image acquired by an unmanned aerial vehicle and/or a helicopter, the DEM is generated by processing a helicopter airborne three-dimensional laser Lidar data point cloud, and the derived data comprises a gradient index, a slope index, a curvature index, a vegetation index and a river.
3. The method for predicting landslide risk of power transmission line according to claim 1, wherein the influence factors are determined and classified, the information quantity model visually represents the degree of closeness between the influence factors and the study object through the information quantity value, and the risk prediction influence factors are selected in combination with the actual conditions of the target area.
4. A risk detection apparatus for detecting a power transmission line, the risk detection apparatus comprising:
the data receiving device is used for performing ground object interpretation and digitization through remote sensing images and visual interpretation, extracting lithology, fracture and road indexes and acquiring DEM data of a target section area of the power transmission line;
the data storage device is used for storing the DEM data and the DEM data information of the target segment area and analysis comparison information, and inputting parameter information obtained by carrying out surface analysis on the DEM data into a corresponding spatial database;
model construction means for constructing an information amount risk prediction model in the spatial database: grading the influence factors, counting the information quantity of landslide disasters of the power transmission line, and representing the degree of risk predictability by using the information quantity of the quantized data;
the data classification device reclassifies the information quantity of grids corresponding to all quantized data in the target area, judges the validity of the model according to the distribution condition of the existing power transmission line partitions, if the model is valid, continues to execute, otherwise returns, and re-evaluates after checking the quality of the influence factor data or updating the influence factor;
the data judging device is used for determining a key priority processing candidate line area according to a judging result of the effectiveness of the model, determining power transmission lines needing priority processing in the subarea according to the risk prediction grade, creating a power transmission network data set according to an actual power transmission network, and screening and marking the power transmission lines needing priority processing in the corresponding space coordinate area;
and the evaluation output device determines landslide disaster grade of the power transmission line according to the risk prediction grade, stacks and analyzes the digitized risk prediction partition layer and the power transmission line layer, selects the power transmission line positioned in the area with high or extremely high risk prediction, and determines the safety risk grade of the evaluated power transmission line section area.
5. The apparatus for detecting the risk of a power transmission line according to claim 4, wherein the data classifying means is adapted to determine and classify the influence factors, the information quantity model intuitively represents the degree of closeness between the influence factors and the study object by the information quantity value, and selects the risk prediction influence factors, such as factor indexes of gradient, slope direction, height, vegetation, river, lithology, fracture zone, precipitation, etc., in combination with the actual condition of the target area, classify the influence factors, and uses the area statistics tool to count the occurrence number of the power transmission line disaster in each factor classification area.
6. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the power transmission line landslide risk prediction method of any one of claims 1 to 3 when executing the computer program.
7. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program for executing the transmission line landslide hazard prediction method of any one of claims 1 to 3.
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| CN112465247A (en) * | 2020-12-04 | 2021-03-09 | 上海电力大学 | Power transmission line path selection method considering geological disasters |
| CN112946240B (en) * | 2021-02-01 | 2022-08-02 | 北京科技大学 | Landslide geological disaster gene identification and prediction system |
| CN113888031A (en) * | 2021-10-27 | 2022-01-04 | 北京中地华安环境工程有限公司 | Landslide hazard risk evaluation method, landslide hazard risk evaluation device, electronic device, and medium |
| CN116362631B (en) * | 2023-06-02 | 2023-08-11 | 国网安徽省电力有限公司经济技术研究院 | DC power distribution network operation safety evaluation system based on big data |
| CN116796651B (en) * | 2023-08-24 | 2023-12-26 | 国网浙江省电力有限公司宁波供电公司 | Power cable aging fault analysis method, electronic equipment and storage medium |
| CN117668040A (en) * | 2024-01-30 | 2024-03-08 | 北京江河惠远科技有限公司 | Geological data processing method for high-voltage transmission line pole tower area and related products |
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