CN117094915B - Grid GIS graph correction method based on orthographic image of unmanned aerial vehicle - Google Patents
Grid GIS graph correction method based on orthographic image of unmanned aerial vehicle Download PDFInfo
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Abstract
The invention discloses a grid GIS graph correction method based on an orthographic image of an unmanned aerial vehicle, which comprises the following steps: step 1, carrying out area edge layout extraction and analysis on GIS graphic data of a power grid by taking a line as a unit; step 2, automatically processing the data, carrying out data analysis, equipment arrangement and format conversion on the extracted data of the station area, and forming contrast analysis with the orthographic image of the unmanned aerial vehicle; and step 3, distributing the converted data to corresponding services through a data distribution module to finish GIS graphic data deviation correction. According to the method, correction of the graph and topology information of the power grid equipment in the GIS system is realized through the information such as the orthographic images and the tower attributes collected in the unmanned aerial vehicle inspection process, so that the problems of insufficient accuracy, low maintenance efficiency and the like in the traditional data maintenance mode are solved.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicle inspection of an electric power system, in particular to a grid GIS graph correction method based on an orthographic image of an unmanned aerial vehicle.
Background
With the gradual penetration of informatization construction in China, more and more areas adopt unmanned aerial vehicle technology to replace the traditional manual mode for line inspection, a large amount of image attribute data is accumulated in the process, and high-precision effective utilization cannot be obtained.
Meanwhile, under the background of the current technology development, in the lean management work of service scenes such as electric power fault research and judgment, rush repair visualization and the like, the requirements on the precision of power grid equipment in a GIS are higher and higher.
The power grid data in the GIS system is manually maintained in the traditional mode, and the following defects mainly exist: (1) The maintenance process has more human intervention, and the image attribute data is observed manually, so that data deviation is easy to occur; and (2) the data is required to be positioned and input device by device, so that the efficiency is low.
Therefore, how to solve the problem of correcting the grid GIS graph by the orthographic image of the unmanned aerial vehicle, avoid the grid data deviation, improve the data maintenance efficiency and become the technical problem to be solved urgently by the personnel in the field.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a grid GIS graph deviation rectifying method based on an orthographic image of an unmanned aerial vehicle.
A power grid GIS graph deviation rectifying method based on an orthographic image of an unmanned aerial vehicle comprises the following steps:
step 1, carrying out distribution area edge layout extraction and analysis on GIS graphic data of a power grid by taking a line as a unit, wherein the distribution area edge layout extraction and analysis specifically comprises distribution transformers, CF boxes, access points, attributes, positions and connection relations of metering box equipment;
step 2, automatically processing the data, carrying out data analysis, equipment arrangement and format conversion on the extracted data of the station area, and forming contrast analysis with the orthographic image of the unmanned aerial vehicle;
and 3, releasing the GIS graph, namely releasing the converted data to corresponding services through a data release module, and finishing deviation correction of the GIS graph data.
Preferably, in the GIS graphic data extraction and analysis of the step 1, the method specifically comprises the following sub-steps:
step 1.1, a data extraction preparation stage;
step 1.1.1, unmanned aerial vehicle image information collection, namely completing unmanned aerial vehicle orthographic image data related data collection by taking a line as a unit, wherein the collection content comprises nameplates, sequence numbers and equipment coordinates of equipment such as regional orthographic image data, station houses, towers and the like;
step 1.1.2, collecting GIS system data information, and extracting power grid equipment under a line in a GIS system by taking the line as a unit, wherein the extracted content comprises attribute, coordinate and topological relation information of equipment such as line outgoing points, operation towers, physical towers, wires, cables, station rooms and the like;
step 1.2, data analysis stage:
step 1.2.1, unmanned aerial vehicle data information analysis is carried out, unmanned aerial vehicle image information is analyzed, equipment running numbers are obtained according to equipment nameplates, line topological relations are obtained according to sequence numbers, and an equipment information table containing unique corresponding relations of equipment is obtained by combining equipment coordinate information;
step 1.2.2, GIS data information analysis is carried out by taking a line as a unit, and the name of the line is judged through a line outlet point; obtaining a line topology relation through the attribute analysis of the terminal numbers of the operation towers, the physical towers, the wires, the cables and the station building equipment; and obtaining the equipment operation number through the equipment operation number attribute, and generating an equipment information table containing the unique corresponding relation of the equipment.
Preferably, the data automatic processing in step 2 specifically includes the following two types:
A. performing device quantity difference processing; the unmanned aerial vehicle data information and GIS data information table uses the equipment running number as the unique corresponding field, when the unmanned aerial vehicle data information is more than GIS data information data, a row is inserted into the GIS data information data table, the mark is newly added, and the attribute field comprises the running number, the line, the equipment coordinates and the topological relation; when the unmanned aerial vehicle data information is less than the GIS data information data, deleting the line in the GIS data information data mark, and automatically updating the topological relation of the upper and lower equipment;
B. performing device position difference processing; the unmanned aerial vehicle data information and the GIS data information table take the equipment running number as a unique corresponding field, the coordinate position of the corresponding equipment in the unmanned aerial vehicle data information is overlapped in the GIS, whether the equipment has a gland water system, a building and the like or not is judged through buffer analysis, and if the equipment does not have the gland water system, the building and the like, the coordinate position of the corresponding equipment in the unmanned aerial vehicle data information is updated to the GIS data information table; if the coordinate position exists, the coordinate position is shifted to the position of the previous topological equipment until no gland is generated, and the secondary coordinate is updated to the GIS data information table.
Preferably, the step 1.2 data analysis stage further comprises:
step 1.2.3, data difference analysis is performed, and equipment running numbers of unmanned aerial vehicle data information and GIS data information are analyzed; if the two are different, carrying out the quantity difference processing of the equipment A in the step 2; and if the two information are consistent, starting the verification and analysis of the equipment position information, and when the equipment coordinate positions in the unmanned aerial vehicle data information and the GIS data information exceed the tolerance value x, performing the B equipment position difference processing in the step 2.
Preferably, the issuing of the GIS graph in the step 3 specifically comprises the following sub-steps:
step 3.1, data reading operation; reading the stylized file data;
step 3.2, data recovery operation; the equipment is restored in the GIS graph layer by layer according to the layering mode of the outlet point, the operation tower, the physical tower, the wire, the cable and the station room by analyzing the read data, and finally needed equipment relation information is obtained by restoring the data of each layer;
step 3.3, data release operation; and releasing the formed data restoration file into the GIS through a storage server interface in the GIS.
Preferably, in step 1.1.2, equipment layering is required for the power grid equipment for which a connection relationship is established, and power grid data is reversely traced through a topological relationship, so that the extraction of the power grid data is realized, and the specific extraction method is as follows:
a1, setting an outlet switch as a source, judging whether an on-off state exists or not, and judging the number of on-off devices;
a2, reversely tracing the power grid equipment with connection relation in the next level, judging whether an on-off state exists or not, and judging the number of the on-off equipment;
a3, judging the equipment type (the breaking equipment or the non-breaking equipment) through the opening and closing state of the power grid equipment, classifying the equipment type into the breaking equipment if the attribute information shows the opening and closing state, and extracting the corresponding equipment attribute information; if the attribute information does not have an open-close state, classifying the attribute information into non-open-close equipment;
a4, extracting attribute information of the two types of equipment, and identifying the type of the power grid equipment according to the extracted attribute information to carry out induction;
and (5) continuously and reversely tracing the power grid equipment with the connection relation in the next hierarchy for the beginning class equipment while extracting the attribute information, and repeating the steps A2, A3 and A4 until the beginning class equipment is reversely traced to the non-breaking class equipment.
Preferably, in step 1.1.2, the specific step of extracting the device attribute information includes:
b1, extracting characteristic values of power grid equipment, wherein the characteristic values comprise: the method comprises the steps of a station area ID, a distribution transformer name, an asset number, a distribution transformer longitude, a distribution transformer latitude, a line type, a station room type, a line outlet point, a disconnecting link switch state, a superior connection relation type, a superior connection relation name, a connection relation type and a connection relation name;
b2, judging the type of the equipment and the connection relation between the equipment through the extracted equipment characteristic values;
and B3, tracing the upper-level equipment through the equipment connection relation until the substation room equipment, determining a station room and a line to which the equipment belongs according to the tracing result, and classifying and extracting the tracing result.
Preferably, the data recovery operation of step 3.2 further comprises the following sub-steps:
c1, extracting geographic elements in GIS (geographic information system) such as buildings, rivers, greenbelts, lakes and the like according to the number of station rooms and the data preprocessing result, and converting the geographic elements into point, line or surface elements; judging the actual distance between different transformers according to the longitude and latitude information of the transformers, converting the actual distance into a canvas through a scale, and determining the position point of the canvas in the canvas;
s2 grid point matrix with connection relation in definition canvasWhere ln×n denotes the distance between grid points;
setting upThen matrix w= =>；
S3, calculating the quantity xj of connection lines of the arrangement equipment and the transformer circuit, and forming according to xj；
Wherein i represents a transformer, j represents arrangement equipment;
by calculation ofKeep->An arrangement scheme with smaller numerical values;
s4, assuming that all grid points in canvas have correlation, the average value of the number of connecting lines in the arrangement scheme reserved in S3 isThereby forming variable a; wherein n represents->The number of arrangement schemes reserved in the process;
s5, calculating a parameter value B through the acquired variable A;
wherein, the smaller the B value is, the more accords with the arrangement requirement; therefore, selecting an arrangement scheme with the minimum B value, and determining the position of arrangement equipment in the canvas;
c6, connecting the transformer i with the arrangement equipment j, recording grids through which the connecting wires pass, and checking the grids; taking an obstacle table, inquiring whether a grid through which a connecting line passes has a condition of crossing the obstacle or not from the table, if so, avoiding the obstacle between points i and j under the condition of considering the minimum error, and forming a (data recovery file) primary platform area model diagram;
and C7, performing operations such as node correction, primary graph optimization, investigation of independent equipment and the like on the primary platform region model diagram to obtain a data recovery file, namely a secondary platform region model diagram.
The invention has the advantages and technical effects that:
the invention provides a grid GIS (geographic information system) graph deviation correcting method based on an orthographic image of an unmanned aerial vehicle, and provides an unmanned aerial vehicle data information and GIS data information analysis method, which can form a uniform comparison method for scattered unmanned aerial vehicle data information and GIS data information and visually compare the data differences.
The invention also provides a processing method of unmanned aerial vehicle data information and GIS data information difference, which can rectify the missing or offset power grid equipment in the GIS, effectively reduces human intervention in the data input process, releases human power and simultaneously effectively reduces errors possibly generated in the human participation process.
Drawings
FIG. 1 is a table of unmanned aerial vehicle image information and GIS data information generated in the invention;
FIG. 2 is a logic relationship diagram of GIS data information extraction process in the present invention;
FIG. 3 is a logic diagram illustrating a data deskewing process according to the present invention;
fig. 4 is a table of unmanned aerial vehicle image information and GIS data information generated in an embodiment of the present invention;
fig. 5 is a table of unmanned aerial vehicle image information and GIS data information formed after the difference analysis in the embodiment of the present invention;
fig. 6 is a schematic diagram of a data recovery rule according to the present invention.
Detailed Description
For a further understanding of the nature, features, and efficacy of the present invention, the following examples are set forth to illustrate, but are not limited to, the invention. The present embodiments are to be considered as illustrative and not restrictive, and the scope of the invention is not to be limited thereto.
The invention provides a grid GIS graph correction method based on an unmanned aerial vehicle orthographic image, which realizes correction of grid equipment graph and topology information in a GIS system through information such as the orthographic image, the tower attribute and the like collected in the unmanned aerial vehicle inspection process. Therefore, the problems of insufficient accuracy, low maintenance efficiency and the like in the traditional data maintenance mode are solved.
The invention relates to a grid GIS graph correction method based on an orthographic image of an unmanned aerial vehicle, which at least comprises the following steps:
1. the method comprises the steps of extracting and analyzing a distribution transformer, a CF box, an access point and a metering box device according to a distribution diagram of a region of geographic information system GIS graphic data of a power grid by taking a line as a unit.
2. And (3) automatically processing the data, and comparing and analyzing the extracted data of the area with the unmanned aerial vehicle orthographic image through data analysis, equipment arrangement and format conversion.
3. And publishing the GIS graph, namely publishing the converted data to corresponding services through a data publishing module to finish GIS graph data deviation correction.
The extraction, analysis, processing and release of GIS graphic data comprise the following stages:
1. data preparation phase
(1) Unmanned aerial vehicle image information collection
And (3) completing the data collection related to the orthographic image data of the unmanned aerial vehicle by taking the line as a unit, wherein the collection content comprises nameplates, sequence numbers and equipment coordinates of equipment such as regional orthographic image data, station houses (power transmission and distribution), towers (power transmission and distribution) and the like.
(2) GIS system data information collection
And extracting equipment of the power grid under the line in the GIS by taking the line as a unit, wherein the extraction content comprises equipment attribute, coordinate and topological relation information such as line outlet points, operation towers (power transmission and distribution), physical towers, wires (power transmission and distribution), cables (power transmission and distribution), station rooms (power transmission and distribution) and the like.
a, extracting equipment range:
and layering the equipment aiming at the power grid equipment establishing the connection relationship, and reversely tracing the power grid data through the topological relationship to realize the extraction of the power grid data.
A1, setting an outlet switch as a source, judging whether an on-off state exists or not, and judging the number of on-off devices.
A2, reversely tracing the power grid equipment with connection relation in the next level, judging whether an on-off state exists or not, and judging the number of the on-off equipment.
A3, judging the equipment type (the breaking equipment or the non-breaking equipment) through the opening and closing state of the power grid equipment, classifying the equipment type into the breaking equipment if the attribute information shows the opening and closing state, and extracting the corresponding equipment attribute information; and if the attribute information does not have an open-close state, classifying the equipment into a non-open-close type equipment.
And A4, extracting attribute information of the two types of equipment, and identifying the type of the power grid equipment through the extracted attribute information to carry out induction.
And (5) continuously and reversely tracing the power grid equipment with the connection relation in the next hierarchy for the beginning class equipment while extracting the attribute information, and repeating the steps A2, A3 and A4 until the beginning class equipment is reversely traced to the non-breaking class equipment.
b, extracting attribute information:
b1, extracting characteristic values of power grid equipment, wherein the characteristic values comprise: the method comprises the steps of a station area ID, a distribution transformer name, an asset number, a distribution transformer longitude, a distribution transformer latitude, a line type, a station room type, a line outlet point, a disconnecting link switch state, a superior connection relation type, a superior connection relation name, a connection relation type, a connection relation name and the like.
And B2, judging the type of the equipment and the connection relation between the equipment through the extracted equipment characteristic values.
And B3, tracing the upper-level equipment through the equipment connection relation until the substation room equipment, determining a station room and a line to which the equipment belongs according to the tracing result, and classifying and extracting the tracing result.
2. Data analysis stage
(1) Unmanned aerial vehicle data information analysis
Analyzing the image information of the unmanned aerial vehicle, obtaining an equipment operation number according to an equipment nameplate, obtaining a line topological relation according to the sequence number, and obtaining an equipment information table containing the unique corresponding relation of the equipment by combining the equipment coordinate information.
(2) GIS data information analysis
Carrying out GIS data information analysis by taking a line as a unit, judging a line name through a line outlet point, obtaining a line topological relation through analyzing terminal number attributes of equipment of an operation tower (power transmission and distribution), a physical tower, a wire (power transmission and distribution), a cable (power transmission and distribution) and a station room (power transmission and distribution), obtaining an equipment operation number through equipment operation number attributes, and generating an equipment information table containing unique corresponding relation of equipment.
(3) Data diversity analysis
Firstly analyzing running numbers of equipment of unmanned aerial vehicle data information and GIS data information, carrying out (1) equipment quantity difference processing in a data processing stage under the condition that difference exists, if the two pieces of equipment quantity difference processing are consistent, starting equipment position information verification analysis, and carrying out (2) equipment position difference processing in the data processing stage under the condition that the equipment coordinate positions in the unmanned aerial vehicle data information and the GIS data information exceed an tolerance value x.
3. Data processing stage
(1) Device number difference processing
The unmanned aerial vehicle data information and GIS data information table uses the equipment running number as the unique corresponding field, when the unmanned aerial vehicle data information is more than GIS data information data, a row is inserted into the GIS data information data table, the mark is newly added, and the attribute field comprises the running number, the line, the equipment coordinates and the topological relation; when the unmanned aerial vehicle data information is less than the GIS data information data, deleting the line in the GIS data information data mark, and automatically updating the topological relation of the upper and lower equipment.
(2) Device location differential processing
The unmanned aerial vehicle data information and the GIS data information table take the equipment running number as a unique corresponding field, the coordinate position of the corresponding equipment in the unmanned aerial vehicle data information is overlapped in the GIS, whether the equipment has a gland water system, a building and the like or not is judged through buffer analysis, and if the equipment does not have the gland water system, the building and the like, the coordinate position of the corresponding equipment in the unmanned aerial vehicle data information is updated to the GIS data information table; if the coordinate position exists, the coordinate position is shifted to the position of the previous topological equipment until no gland is generated, and the secondary coordinate is updated to the GIS data information table.
4. Data distribution stage
(1) Data read operation
And reading the formatted file data.
(2) Data recovery operation
The equipment is restored in the GIS graph layer by layer according to the layering modes of an outlet point, an operation tower (power transmission and distribution), a physical tower, wires (power transmission and distribution), cables (power transmission and distribution), station rooms (power transmission and distribution) and the like through analysis of the read data, and finally needed equipment relation information such as equipment connection relation restoration, position restoration and the like is obtained through restoration of the data of each graph layer.
C1, extracting geographic elements in GIS (geographic information system) such as buildings, rivers, greenbelts, lakes and the like according to the number of station rooms and the data preprocessing result, and converting the geographic elements into point, line or surface elements; judging the actual distance between different transformers according to the longitude and latitude information of the transformers, converting the actual distance into a canvas through a scale, and determining the position point of the canvas in the canvas;
s2 grid point matrix with connection relation in definition canvasWhere ln×n denotes the distance between grid points;
setting upThen matrix w= =>。
S3, calculating the quantity xj of connection lines of the arrangement equipment and the transformer circuit, and forming according to xj；
Wherein i represents a transformer, j represents arrangement equipment;
by calculation ofKeep->An arrangement scheme with smaller numerical values;
s4, assuming that all grid points in canvas have correlation, the average value of the number of connecting lines in the arrangement scheme reserved in S3 isThereby forming variable a. Wherein n represents->The number of arrangement schemes reserved in the process;
s5, calculating a parameter value B through the acquired variable A;
wherein, the smaller the B value is, the more accords with the arrangement requirement. Therefore, selecting an arrangement scheme with the minimum B value, and determining the position of arrangement equipment in the canvas;
and C6, connecting the transformer i with the arrangement equipment j, recording grids through which the connecting wires pass, and checking the grids. Taking an obstacle table, inquiring whether a grid through which a connecting line passes has a condition of crossing the obstacle or not from the table, if so, avoiding the obstacle between points i and j under the condition of considering the minimum error, and forming a (data recovery file) primary platform area model diagram;
c7, performing operations such as node correction, preliminary graph optimization, investigation of independent equipment and the like on the primary platform region model diagram to obtain a secondary platform region model diagram (of a data recovery file);
(3) data publishing operation
And releasing the formed data restoration file into the GIS through a storage server interface in the GIS.
In order to more clearly describe the specific embodiments of the present invention, an example is provided below:
the sample adopts a 21-line of a transformer substation in a civilian road to rectify and analyze line data, and the partial parameters and coordinates of the sample data are desensitized due to the sensitivity of map coordinate data.
And collecting 21-line unmanned aerial vehicle orthographic image data, wherein the content comprises regional orthographic image data, a power distribution pole tower running number, a power distribution pole tower sequence number, a power distribution pole tower nameplate and power distribution pole tower coordinates.
Extracting relevant data information in a GIS, taking a switch of a transformer substation in a civilian tract as a starting point, judging that the switch of the transformer substation in the civilian tract is in a closed state, tracing power grid equipment downwards to be a power distribution pole tower side 2100001, and repeating the previous step until the fuse in the drop-out type on the pole is in the closed state, and continuing tracing to the side 2100004;
analyzing the image information of the unmanned aerial vehicle, judging that the running number information of equipment under a line is (2100001, 2100005) through an equipment nameplate, and obtaining the equipment connection relation of the tower through an image AI intelligent recognition technology by combining the orthophoto data and the tower coordinate data, and describing through a structured language (see fig. 4);
forming the extracted GIS data information into structured data (see FIG. 4);
carrying out data difference analysis, wherein the difference of the number of the devices exists;
through quantity difference analysis, the unmanned aerial vehicle has more image information data, and after comparison, the new operation of 'utilizing 2100005' number towers is carried out on a GIS number information table, and the equipment connection relation fields of 'utilizing 2100004', 'utilizing 2100005' and other two-base towers are synchronously updated;
returning to the quantity difference analysis, and carrying out the equipment position difference analysis after judging that the quantity difference analysis does not exist;
through analysis, the tower coordinates of No. 2100004 have larger difference, and the equipment coordinate fields in the GIS number information table are updated to 117.413467, 38.434463 according to constraint conditions "
Performing equipment position reduction processing on the updated coordinates, and displaying that the coordinates do not have a gland and the coordinate values are effective;
returning to data difference analysis, the two tables of data are identical (FIG. 5);
reading data in a GIS data information table;
12. data processing is performed, and the related variable data "li 2100004", "li 2100003, li 2100005", "117.413438, 38.434464", "li 2100005", "li 2100004", "117.413467, 38.434463" are distributed into the GIS system.
Finally, the invention adopts the mature products and the mature technical means in the prior art.
It will be understood that modifications and variations will be apparent to those skilled in the art from the foregoing description, and it is intended that all such modifications and variations be included within the scope of the following claims.
Claims (3)
1. The utility model provides a grid GIS figure deviation correcting method based on unmanned aerial vehicle orthographic image, which is characterized by comprising the following steps:
step 1, carrying out distribution area edge layout extraction and analysis on GIS graphic data of a power grid by taking a line as a unit, wherein the distribution area edge layout extraction and analysis specifically comprises distribution transformers, CF boxes, access points, attributes, positions and connection relations of metering box equipment;
step 2, automatically processing the data, carrying out data analysis, equipment arrangement and format conversion on the extracted data of the station area, and forming contrast analysis with the orthographic image of the unmanned aerial vehicle;
step 3, GIS graph release, namely releasing the converted data to corresponding services through a data release module to finish GIS graph data deviation correction;
the GIS graphic data extraction and analysis in the step 1 specifically comprises the following sub-steps:
step 1.1, a data extraction preparation stage;
step 1.1.1, unmanned aerial vehicle image information collection, namely completing unmanned aerial vehicle orthographic image data related data collection by taking a line as a unit, wherein the collection content comprises regional orthographic image data, nameplates, sequence numbers and equipment coordinates of equipment in a station house and a tower;
step 1.1.2, collecting GIS system data information, and extracting power grid equipment under a line in a GIS system by taking the line as a unit, wherein the extracted content comprises attribute, coordinate and topological relation information of line outgoing points, operation towers, physical towers, wires, cables and equipment in a station room;
step 1.2, data analysis stage:
step 1.2.1, unmanned aerial vehicle data information analysis is carried out, unmanned aerial vehicle image information is analyzed, equipment running numbers are obtained according to equipment nameplates, line topological relations are obtained according to sequence numbers, and an equipment information table containing unique corresponding relations of equipment is obtained by combining equipment coordinate information;
step 1.2.2, GIS data information analysis is carried out by taking a line as a unit, and the name of the line is judged through a line outlet point; obtaining a line topology relation through the attribute analysis of the terminal numbers of the operation towers, the physical towers, the wires, the cables and the station building equipment; obtaining an equipment operation number through the equipment operation number attribute, and generating an equipment information table containing the unique corresponding relation of the equipment;
the automatic data processing in the step 2 specifically comprises the following two types:
A. performing device quantity difference processing; the unmanned aerial vehicle data information and GIS data information table uses the equipment running number as the unique corresponding field, when the unmanned aerial vehicle data information is more than GIS data information data, a row is inserted into the GIS data information data table, the mark is newly added, and the attribute field comprises the running number, the line, the equipment coordinates and the topological relation; when the unmanned aerial vehicle data information is less than the GIS data information data, deleting the line in the GIS data information data mark, and automatically updating the topological relation of the upper and lower equipment;
B. performing device position difference processing; the unmanned aerial vehicle data information and the GIS data information table take the equipment running number as a unique corresponding field, the coordinate position of the corresponding equipment in the unmanned aerial vehicle data information is overlapped in the GIS, whether the equipment has a gland water system or a building condition is judged through buffer analysis, and if the equipment does not have the gland water system or the building condition, the coordinate is updated to the GIS data information table; if the coordinate position exists, the coordinate position is shifted to the position of the previous topological equipment until no gland is generated, and the secondary coordinate is updated to the GIS data information table;
the step 1.2 data analysis stage further comprises:
step 1.2.3, data difference analysis is performed, and equipment running numbers of unmanned aerial vehicle data information and GIS data information are analyzed; if the two are different, carrying out the quantity difference processing of the equipment A in the step 2; if the two information are consistent, starting equipment position information verification analysis, and when the equipment coordinate positions in the unmanned aerial vehicle data information and the GIS data information exceed the tolerance value x, performing B equipment position difference processing in the step 2;
the GIS graph publishing in the step 3 specifically comprises the following sub-steps:
step 3.1, data reading operation; reading the stylized file data;
step 3.2, data recovery operation; the equipment is restored in the GIS graph layer by layer according to the layering mode of the outlet point, the operation tower, the physical tower, the wire, the cable and the station room by analyzing the read data, and finally needed equipment relation information is obtained by restoring the data of each layer;
step 3.3, data release operation; the formed data restoration file is released into the GIS through a storage server interface in the GIS;
in the step 1.1.2, equipment layering is required for the power grid equipment establishing the connection relationship, and the power grid data is reversely traced through the topological relationship, so that the extraction of the power grid data is realized, and the specific extraction method is as follows:
a1, setting an outlet switch as a source, judging whether an on-off state exists or not, and judging the number of on-off devices;
a2, reversely tracing the power grid equipment with connection relation in the next level, judging whether an on-off state exists or not, and judging the number of the on-off equipment;
a3, judging the equipment type (the breaking equipment or the non-breaking equipment) through the opening and closing state of the power grid equipment, classifying the equipment type into the breaking equipment if the attribute information shows the opening and closing state, and extracting the corresponding equipment attribute information; if the attribute information does not have an open-close state, classifying the attribute information into non-open-close equipment;
a4, extracting attribute information of the two types of equipment, and identifying the type of the power grid equipment according to the extracted attribute information to carry out induction;
and (5) continuously and reversely tracing the power grid equipment with the connection relation in the next hierarchy for the beginning class equipment while extracting the attribute information, and repeating the steps A2, A3 and A4 until the beginning class equipment is reversely traced to the non-breaking class equipment.
2. The grid GIS graph correction method based on the orthographic image of the unmanned aerial vehicle according to claim 1, wherein the method is characterized by comprising the following steps of: in the step 1.1.2, the specific step of extracting the equipment attribute information includes:
b1, extracting characteristic values of power grid equipment, wherein the characteristic values comprise: the method comprises the steps of a station area ID, a distribution transformer name, an asset number, a distribution transformer longitude, a distribution transformer latitude, a line type, a station room type, a line outlet point, a disconnecting link switch state, a superior connection relation type, a superior connection relation name, a connection relation type and a connection relation name;
b2, judging the type of the equipment and the connection relation between the equipment through the extracted equipment characteristic values;
and B3, tracing the upper-level equipment through the equipment connection relation until the substation room equipment, determining a station room and a line to which the equipment belongs according to the tracing result, and classifying and extracting the tracing result.
3. The grid GIS graph correction method based on the orthographic image of the unmanned aerial vehicle according to claim 1, wherein the method is characterized by comprising the following steps of: the data recovery operation of step 3.2 further includes the following sub-steps:
c1, extracting geographic elements in GIS (geographic information system), such as buildings, rivers, greenbelts and lakes, according to the number of station rooms and the data preprocessing result, and converting the geographic elements into point, line or surface elements; judging the actual distance between different transformers according to the longitude and latitude information of the transformers, converting the actual distance into a canvas through a scale, and determining the position point of the canvas in the canvas; grid point matrix with connection relation in C2 definition canvasWherein L is n*n Representing the distance between grid points;the method comprises the steps of carrying out a first treatment on the surface of the C3 calculates the number x of connecting wires between the arrangement device and the transformer circuit j According to x j ，/> Wherein i represents a transformer, j represents arrangement equipment;c5, calculating a parameter value B through the obtained variable A; />Wherein, the smaller the B value is, the more accords with the arrangement requirement; therefore, selecting an arrangement scheme with the minimum B value, and determining the position of arrangement equipment in the canvas;
c6, connecting the transformer i with the arrangement equipment j, recording grids through which the connecting wires pass, and checking the grids; taking an obstacle table, inquiring whether a grid through which a connecting line passes has a condition of crossing the obstacle or not from the table, if so, avoiding the obstacle between points i and j under the condition of considering the minimum error, and forming a data recovery file, namely a primary platform area model diagram;
and C7, performing node correction, primary graph optimization and investigation on the primary area model graph to obtain a data restoration file, namely a secondary area model graph.
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