CN117668765A - Intelligent fusion processing method based on survey big data - Google Patents

Abstract

The invention discloses an intelligent fusion processing method based on survey big data, which comprises the following steps: dividing a survey fusion level into survey sub-levels; respectively acquiring survey monitoring information data corresponding to each survey sub-level; respectively evaluating a plurality of survey schemes corresponding to each survey sub-level according to the survey monitoring information data, and sequencing the plurality of survey schemes corresponding to each survey sub-level; and generating a survey site selection engineering technical economic scheme according to the sequencing result. The invention achieves the effect of improving the technical and economic evaluation accuracy of the survey site selection multi-level data fusion processing through three-layer fusion of the survey data, and solves the problem that the technical and economic evaluation accuracy of the survey site selection multi-level data fusion processing is difficult to improve in the prior art.

Description

Intelligent fusion processing method based on survey big data

Technical field

The present invention relates to the technical field of survey data fusion, and in particular to an intelligent fusion processing method based on survey big data.

Background technique

With the development of science and technology and the progress of society, a large amount of data has been generated in the field of surveying, which includes various types of information such as topography, geological structure, and environmental changes. The processing and analysis of these data are of great significance to the development of the survey field. However, traditional data processing methods can no longer meet the processing needs of large-scale and complex data. Therefore, the integration of big data and artificial intelligence technology provides new technical means and solutions for the field of surveying.

The existing intelligent fusion processing method based on survey big data combines big data technology with artificial intelligence technology to efficiently and intelligently process and analyze the massive data generated in the survey field, taking advantage of the storage, processing and analysis of big data. capabilities, as well as artificial intelligence machine learning, deep learning and other algorithms, to realize the mining, analysis and prediction of complex data.

For example, the invention patent with the publication number: CN116862170A discloses a geological survey and sampling method for power transmission and transformation engineering, including: pre-planned route characteristic data extraction, geological survey sampling point layout, geological survey sampling point information parameter extraction and analysis, data comprehensive processing, Target erection route selection determination and target erection route basic data sharing.

For example, the invention patent with announcement number: CN116912070B announces a security early warning method and system that integrates GIS and multi-source data, including: retrieving a GIS model generated based on field survey data of the monitored area; Divide it into multiple grid areas; obtain the precipitation information, water level information and meteorological forecast of each grid area respectively; calculate the safe drainage volume, water storage volume and water seepage volume of each grid area based on the GIS model and water level information; based on the safe drainage volume, Water storage volume, water seepage volume, precipitation information and meteorological forecasts are combined with GIS models to predict the probability of flood disasters and landslide disasters in each grid area.

Among the above existing technologies, due to the rich sources of basic geographical information data, power grid tower data and site selection project data, it is difficult to achieve centralized management of data, and there is a problem that it is difficult to improve the accuracy of the technical and economic assessment of multi-level data fusion processing for survey and site selection.

Contents of the invention

By providing an intelligent fusion processing method based on survey big data, the embodiment of the present application solves the problem in the existing technology that it is difficult to improve the accuracy of technical and economic assessment of multi-level data fusion processing for survey site selection, and achieves the goal of improving the accuracy of survey site selection. The effect of technical and economic evaluation accuracy of multi-level data fusion processing.

The embodiment of the present application provides an intelligent fusion processing method based on survey big data, including: dividing the survey fusion level into each survey sub-level; obtaining the survey monitoring information data corresponding to each survey sub-level respectively; and according to the survey monitoring information The data evaluates several survey plans corresponding to each survey sub-level, and obtains the evaluation coefficients corresponding to the several survey plans at each survey sub-level. The evaluation coefficients corresponding to the several survey plans at each survey sub-level are arranged in descending order to determine The first survey plan evaluation coefficient of each survey sub-level is obtained; according to the first survey plan evaluation coefficient of each survey sub-level, the first survey monitoring plan corresponding to each survey sub-level is obtained; and the technical and economic plan of the survey site selection project is generated based on the sorting results.

According to some embodiments of the present application, generating a technical and economic plan for a survey site selection project based on the sorting results includes: jointly generating several top survey monitoring plans corresponding to each survey sub-level according to several predefined inter-level data associations. Survey fusion level survey monitoring scheme; respectively evaluate the several survey fusion level survey monitoring schemes, and generate several survey fusion level survey monitoring scheme evaluation coefficients; arrange the evaluation coefficients of the several survey fusion level survey monitoring schemes in descending order, and get the first place The evaluation coefficient of the survey fusion level survey and monitoring plan; the survey fusion level survey and monitoring plan corresponding to the evaluation coefficient of the first survey fusion level survey and monitoring plan is recorded as the technical and economic plan of the survey and site selection project.

According to some embodiments of the present application, the survey and monitoring information data include: meteorological conditions, number and height of tower points, distance between adjacent towers, tower electrical grade, tower structural grade, number of substations, tower foundation pile positions, ground angle bolts Offset, insulator string rating, and ground conductor rating data.

According to some embodiments of the present application, each of the survey sub-levels includes a first survey sub-level, a second survey sub-level and a third survey sub-level, and several survey plans corresponding to the first survey sub-level are evaluated according to the survey monitoring information data, Obtain the evaluation coefficients corresponding to several survey plans at the first survey sub-level, including: based on the number and height of the tower points, the distance between adjacent towers and the number of substations, obtain the corresponding impact value of the total earthwork clearance; based on the meteorological conditions As well as the predefined construction period days in several survey monitoring plans corresponding to the first survey sub-level, the meteorological condition impact value is calculated; according to the meteorological condition impact value, the number and height of tower points, the distance between adjacent towers, the number of substations and The impact value of the total earthwork clearance is used to evaluate several survey monitoring plans at the first survey sub-level, and the corresponding evaluation coefficients of several survey plans at the first survey sub-level are obtained.

According to some embodiments of the present application, evaluating several survey plans corresponding to the second survey sub-level based on survey monitoring information data, and obtaining evaluation coefficients corresponding to several survey plans at the second survey sub-level includes: according to the second survey sub-level Corresponding to the predefined tower foundation pile positions in several survey monitoring plans, determine the tower foundation pile position influence value data; according to the tower electrical grade, tower structural grade and the tower foundation pile position influence value data, the second survey sub-level Several corresponding survey plans are evaluated, and the evaluation coefficients corresponding to several survey plans at the second survey sub-level are obtained.

According to some embodiments of the present application, evaluating several survey plans corresponding to the third survey sub-level based on survey monitoring information data, and obtaining evaluation coefficients corresponding to several survey plans at the third survey sub-level includes: according to the second survey sub-level Several survey and monitoring plans corresponding to the level are used to obtain the ground angle bolt offset, insulator string level and ground wire level; the third survey fusion sub-level is based on the ground angle bolt offset, insulator string level and ground wire level. Several corresponding survey plans are evaluated, and the evaluation coefficients corresponding to several survey plans at the third survey sub-level are obtained.

One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

1. Divide the survey fusion level into the first survey fusion sub-level, the second survey fusion sub-level and the third survey fusion sub-level; evaluate the first survey fusion sub-level and the second survey fusion sub-level respectively based on the survey monitoring information data And the survey and monitoring plans corresponding to the third survey fusion sub-level, and the corresponding level survey and monitoring plans are respectively sorted, so as to generate the technical and economic plan of the survey and site selection project based on the evaluation and sorting results, thereby achieving the improvement of multi-level data for survey and site selection. The effect of the accuracy of technical and economic evaluation of fusion processing solves the problem in the existing technology that it is difficult to improve the accuracy of technical and economic evaluation of multi-level data fusion processing of survey and site selection.

2. Use the survey monitoring information data to evaluate the survey monitoring plans corresponding to the first survey fusion sub-level, the second survey fusion sub-level, and the third survey fusion sub-level respectively, and sort the corresponding level survey monitoring plans respectively, thereby selecting Finding the optimal survey and monitoring plan at each level can greatly improve the efficiency of the method in obtaining the optimal plan, thereby enhancing the operability of the method.

3. By obtaining the survey and monitoring plan for the first survey fusion sub-level, the survey and monitoring plan for the second survey fusion sub-level, and the survey and monitoring plan for the third survey fusion sub-level, according to several predefined data correlation relationships between levels, Several survey fusion level survey and monitoring plans are jointly generated, so that the first survey fusion level survey and monitoring plan is recorded as the survey site selection engineering technical and economic plan, thereby improving the practicality of the intelligent fusion processing results based on survey big data.

Description of drawings

Figure 1 is a flow chart of an intelligent fusion processing method based on survey big data provided by an embodiment of the present application.

Detailed ways

By providing an intelligent fusion processing method based on survey big data, the embodiment of the present application solves the problem in the existing technology that it is difficult to improve the accuracy of technical and economic assessment of multi-level data fusion processing for survey site selection. The survey selection is generated by evaluating the sorting results. The technical and economic plan of the site project has achieved the effect of improving the accuracy of the technical and economic assessment of multi-level data fusion processing for survey and site selection.

The technical solution in the embodiment of this application is to solve the above-mentioned problem that it is difficult to improve the accuracy of technical and economic assessment of multi-level data fusion processing for survey and site selection. The overall method is as follows:

By dividing the survey fusion level into the first survey fusion sub-level, the second survey fusion sub-level and the third survey fusion sub-level, the three-layer fusion of survey data achieves the goal of improving the accuracy of the technical and economic evaluation of multi-level data fusion processing for survey site selection. The efficiency effect solves the problem in the existing technology that it is difficult to improve the accuracy of the technical and economic assessment of multi-level data fusion processing for survey and site selection.

In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation modes.

As shown in Figure 1, it is a flow chart of the intelligent fusion processing method based on survey big data provided by the embodiment of the present application. The method includes the following steps:

Divide the survey fusion level into each survey sub-level; obtain survey monitoring information data corresponding to each survey sub-level respectively; evaluate several survey plans corresponding to each survey sub-level according to the survey monitoring information data, and obtain each survey plan respectively. Evaluation coefficients corresponding to several survey plans at the survey sub-level; Arrange the evaluation coefficients corresponding to the several survey plans at each survey sub-level in descending order to determine the evaluation coefficient of the first survey plan at each survey sub-level; According to each survey sub-level The top survey plan evaluation coefficient is used to obtain the top survey monitoring plan corresponding to each survey sub-level; the technical and economic plan for the survey site selection project is generated based on the sorting results.

In this embodiment, the survey fusion level is divided into a first survey fusion sub-level, a second survey fusion sub-level, and a third survey fusion sub-level. The first survey fusion sub-level, the second survey fusion sub-level, and the third survey fusion sub-level The sub-levels respectively contain corresponding survey and monitoring information data; the survey and monitoring solutions corresponding to the first survey fusion sub-level, the second survey fusion sub-level and the third survey fusion sub-level are respectively evaluated according to the survey and monitoring information data, where, the survey and monitoring scheme Including several survey and monitoring schemes at the first survey fusion sub-level, several survey and monitoring schemes at the second survey fusion sub-level and several survey and monitoring schemes at the third survey fusion sub-level, and the corresponding level survey and monitoring schemes are respectively sorted; according to the evaluation The sorting results generate technical and economic plans for survey and site selection projects.

In this embodiment, the survey fusion level is divided into a first survey fusion sub-level, a second survey fusion sub-level, and a third survey fusion sub-level. The first survey fusion sub-level mainly corresponds to survey data fusion at the survey line level. The second survey fusion sub-level mainly corresponds to the survey data fusion of specific tower attribute data, and the third survey fusion sub-level mainly corresponds to the survey data fusion of specific tower attribute data at the component level of survey towers.

According to the survey monitoring information data, several survey plans corresponding to each survey sub-level are evaluated respectively, and several survey plans corresponding to each survey sub-level are sorted, specifically as follows:

Several survey monitoring plans at the first survey fusion sub-level are evaluated to obtain several first survey plan evaluation coefficients. Several survey monitoring plans at the first survey fusion sub-level correspond to several first survey plan evaluation coefficients one by one, and the Several first survey plan evaluation coefficients are arranged in descending order, and the first first survey plan evaluation coefficient and the corresponding first survey fusion sub-level survey monitoring plan are obtained, which are recorded as the first first survey fusion sub-level survey monitoring plan;

Several survey monitoring plans at the second survey fusion sub-level are evaluated to obtain several second survey plan evaluation coefficients. Several survey monitoring plans at the second survey fusion sub-level correspond to several second survey plan evaluation coefficients one by one, and the Several second survey plan evaluation coefficients are arranged in descending order, and the first second survey plan evaluation coefficient and the corresponding second survey fusion sub-level survey monitoring plan are obtained, which are recorded as the first second survey fusion sub-level survey monitoring plan;

Several survey monitoring plans at the third survey fusion sub-level are evaluated, and several third survey plan evaluation coefficients are obtained. Several survey monitoring plans at the third survey fusion sub-level correspond to several third survey plan evaluation coefficients one by one, and the Several third survey plan evaluation coefficients are arranged in descending order, and the first third survey plan evaluation coefficient and the corresponding third survey fusion sub-level survey and monitoring plan are obtained, which are recorded as the first third survey fusion sub-level survey and monitoring plan.

In this embodiment, the corresponding survey and monitoring solutions for the three levels can be obtained in the following ways: Layer management: The mapping data in the designed line corridor are managed in layers, and each type of surface object belongs to one layer. Unified naming and attribute settings are carried out, the adjustment layers are managed according to vectorized data, and the layer style supports customization. Interactive drawing: Use data to collect points on the three-dimensional earth to construct point, line, surface and other ground object objects. At the end of the drawing of each object, an attribute table will pop up and fill in the name and type of the ground object identification; Coordinate entry: By importing the specified format coordinate file or input the coordinate value information of each point to construct point, line, surface and other surface objects; CAD data import: supports parsing fixed-format dwg files, and imports graphic data of specified categories in the dwg file by setting matching classification information to the designated layer; Attribute maintenance: By managing the attribute information corresponding to each graphic object, including the classification, feature name, label symbol, extended attribute information, etc.; Graphic editing: Supports editing of feature mapping data within the designed route corridor Operations include moving points, lines, and surfaces, node editing, style settings, attribute additions, deletions, and other operations. It supports modifying the boundary range of entered graphic objects and adjusting the appearance of graphics; attachment maintenance: manages attachments associated with objects, and supports Operations such as adding, deleting, and exporting; plot export: supports plotting data to be exported to dwg files in layers according to their classification information. Control point achievement management realizes the control point management function in the early stage of transmission line engineering. Control point attributes include coordinate system, coordinates, collection time, collector, etc. Supports functions such as parsing and output of xls, txt and other files, and can calculate coordinate transformation parameters based on selected control points, and perform coordinate transformation work on server data. The three-dimensional display of digital design results realizes the loading of engineering three-dimensional models and terrain, as well as basic functions such as three-dimensional scene browsing and measurement. Distance measurement: Data types include: point cloud, tilt, vector, dom, dem and efficient loading; Solution management: Solution retrieval based on the solution name, solution number, solution type, voltage level and other information combinations to quickly locate the solution you need to find. Add a plan: The new plan is used to create a new project plan. The user creates a plan based on the plan name and plan stage. When adding a plan, the information of the new plan can be entered, such as adding information such as voltage level, construction unit, construction unit, design unit, supervision unit, etc.; During the process of creating a new plan, you can consider setting the plan coordinate system synchronously. Modify the plan: By selecting the plan name and plan stage, the user can edit the information of the existing plan according to the actual situation. The editing content includes the plan name, construction unit, construction unit, design unit, supervision unit and other information; Delete plan: User selection After deleting the plan, delete the node of the project plan in the project management data list, and delete the data, materials and design phase directories of each stage of the project. Survey results management: Mainly realizes the storage, maintenance and management of relevant data and materials in the three majors of surveying, geology and hydrometeorology in the area involved in the plan.

In this embodiment, the specific process of generating the technical and economic plan for the survey site selection project based on the evaluation ranking results is: obtaining the survey and monitoring plan at the first and first survey fusion sub-level, the survey and monitoring plan at the first and second survey fusion sub-level, and the survey and monitoring plan at the first and second survey fusion sub-level. The survey and monitoring plan of the three survey fusion sub-levels is based on a number of predefined inter-level data relationships. The several pre-defined inter-level data relationships include: first, the survey and monitoring plan of the first survey fusion sub-level and the second survey fusion sub-level. The corresponding predefined data association relationship of the survey and monitoring scheme and the predefined data association relationship of the survey and monitoring scheme corresponding to the first and second survey fusion sub-level and the survey and monitoring scheme corresponding to the third survey and fusion sub-level jointly generate several survey and fusion level survey and monitoring schemes; The evaluation of several survey fusion-level survey and monitoring programs generates several survey fusion-level survey and monitoring program evaluation coefficients. Several survey fusion-level survey and monitoring programs have one-to-one correspondence with the evaluation coefficients of several survey fusion-level survey and monitoring programs. For several survey fusion-level survey and monitoring programs, the evaluation coefficients are generated The evaluation coefficients are arranged in descending order, and the evaluation coefficient of the first survey fusion level survey and monitoring plan and the corresponding survey fusion level survey and monitoring plan are obtained, which are recorded as the technical and economic plan of the survey and site selection project.

The data source of technical and economic indicators in this embodiment is shown in Table 1 below.

Table 1

Further, the first survey plan evaluation coefficient, the second survey plan evaluation coefficient, the third survey plan evaluation coefficient and the survey fusion level survey monitoring plan evaluation coefficient, the specific acquisition processes are respectively: the first survey plan evaluation coefficient represents the influence of meteorological conditions The data obtained from the evaluation and analysis of the survey monitoring plan at the first survey fusion sub-level using value data, tower point number data, tower height data, adjacent tower distance data, substation number data and total earthwork clearance impact value data; the second survey The plan evaluation coefficient represents the data obtained through the evaluation and analysis of the survey and monitoring plan at the second survey fusion sub-level through tower electrical grade data, tower structural grade data and tower foundation pile position influence value data; the third survey plan evaluation coefficient represents the data obtained through the ground angle bolts The offset data, insulator string grade data and ground conductor grade data are the data obtained from the evaluation and analysis of the survey and monitoring plan at the third survey fusion sub-level.

Further, the acquisition and analysis process of survey monitoring information data corresponding to the evaluation coefficient of the first survey plan is: direct data extraction based on the survey monitoring plan corresponding to the first survey fusion sub-level to obtain tower point number data, tower height data, and adjacent tower distances data and substation quantity data; based on the tower point number data, tower height data, adjacent tower distance data and substation number data processing, the corresponding total earthwork clearance impact value data is obtained; according to the delay of the first survey fusion sub-level corresponding to the impact of meteorological conditions The meteorological condition impact value data is obtained by comparing and calculating the predefined construction period days in the survey monitoring plan; from this, the evaluation coefficients corresponding to several survey plans at the first survey sub-level are calculated.

Further, the acquisition and analysis process of survey monitoring information data corresponding to the evaluation coefficient of the second survey plan is: based on the predefined data association relationship between the survey monitoring plan corresponding to the first survey fusion sub-level and the survey monitoring plan corresponding to the second survey fusion sub-level. Select the survey and monitoring plan corresponding to the second survey fusion sub-level; directly extract data based on the survey and monitoring plan corresponding to the second survey fusion sub-level to obtain the tower electrical grade data and tower structural grade data; obtain the survey and monitoring corresponding to the second survey fusion sub-level The predefined tower foundation pile positions in the plan and the different project costs corresponding to different tower foundation pile positions are compared and calculated to obtain the tower foundation pile position impact value data; from this, the corresponding evaluations of several survey plans at the second survey sub-level are calculated. coefficient.

Further, the acquisition and analysis process of survey monitoring information data corresponding to the evaluation coefficient of the third survey plan is: based on the predefined data association relationship between the survey monitoring plan corresponding to the first second survey fusion sub-level and the survey monitoring plan corresponding to the third survey fusion sub-level. Select the survey and monitoring plan corresponding to the third survey fusion sub-level; directly extract data based on the survey and monitoring plan corresponding to the second survey fusion sub-level to obtain ground angle bolt offset data, insulator string grade data and ground wire grade data; thus Calculate the evaluation coefficients corresponding to several survey plans at the third survey sub-level.

In this embodiment, in addition to data extraction, the above data can also be obtained through a fast calculation model. The data correlation relationship includes the survey monitoring plan corresponding to the second survey fusion sub-level and the survey monitoring corresponding to the third survey fusion sub-level. The plan predefines the data association relationship. For example, after obtaining the survey and monitoring plan of the first survey fusion sub-level, although there are several survey and monitoring plans of the second survey fusion sub-level, there cannot be any data that is not included in the current plan database. For example, the insulator voltage rating refers to the maximum voltage value that the insulator can withstand, and is usually used for high-voltage equipment in power systems. The eight common insulator voltage levels include: 1kV, 3kV, 6kV, 10kV, 20kV, 35kV, 66kV and 110kV. Insulators of different voltage levels are suitable for different power systems and equipment. For example, 1kV and 3kV insulators are suitable for low-voltage distribution systems, while 66kV and 110kV insulators are suitable for high-voltage transmission systems. In the power system, the selection and use of insulators play a vital role in the safe operation of power equipment and the stable operation of the power grid. Once the voltage level of the UHV tower is determined, the corresponding tower voltage level will be determined accordingly. Unsuitable solutions will be eliminated directly.

Among them, the specific calculation formula for the evaluation coefficients corresponding to several survey plans at the first survey sub-level is:

;

In the formula, Indicates the evaluation coefficients corresponding to several survey plans at the first survey sub-level,/> Indicates the impact value data of the total earthwork clearance volume,/> Indicates the impact value data of meteorological conditions,/> Represents the number data of pole tower points,/> Indicates tower height data,/> Indicates the distance data between adjacent towers,/> Represents the number data of substations,/> Indicates the weighting factor corresponding to the number of tower points corresponding to the evaluation coefficient of the first survey plan,/> Indicates the weight factor of the tower height corresponding to the evaluation coefficient of the first survey plan,/> The weighting factor indicating the distance between adjacent towers corresponding to the evaluation coefficient of the first survey plan.

In this embodiment, the distance data between adjacent poles and towers is generally a determined value after the plan is determined. The same is true for the data on the number of poles and tower points. The impact value data of the total earthwork removal volume generally only counts the earthwork clearance volume of the tower poles and their bases. The impact value data of meteorological conditions indicates that due to climate reasons, the project is delayed by several days compared to the specified progress. The number of days delayed is the specific number of days data. The impact value data of the total earthwork removal volume indicates that compared with the total earthwork clearance volume of the standard project, the actual The ratio of the total earthwork clearance volume of the project to the total earthwork clearance volume of the standard project minus 1 is the impact value data of the total earthwork clearance volume.

Among them, the specific calculation formula for the evaluation coefficients corresponding to several survey plans at the second survey sub-level is:

;

In the formula, Indicates the evaluation coefficients corresponding to several survey plans at the second survey sub-level,/> Indicates the electrical grade data of the tower,/> Indicates predefined tower electrical standard grade data,/> Indicates the tower structure grade data,/> Represents predefined tower structure standard grade data,/> Represents the tower foundation pile position influence value data,/> Indicates the weighting factor of the tower electrical grade corresponding to the evaluation coefficient of the second survey plan,/> Indicates the weight factor of the tower structure level corresponding to the evaluation coefficient of the second survey plan,/> Represents the weight factor of the second survey plan evaluation coefficient corresponding to the tower foundation pile position impact value data,/> represents a natural constant.

In this embodiment, the tower foundation pile position impact value data indicates that different tower foundation pile positions have different economic costs. Comparative calculations are performed on standard tower foundation pile positions, and the obtained ratio is the tower foundation pile position impact value data. .

Among them, the specific calculation formula for the evaluation coefficients corresponding to several survey plans at the third survey sub-level is:

;

In the formula, Indicates the evaluation coefficients corresponding to several survey plans at the third survey sub-level,/> Indicates the ground angle bolt offset data,/> Indicates insulator string grade data,/> Indicates ground conductor grade data,/> Indicates predefined insulator string standard grade data,/> Indicates predefined ground wire standard grade data,/> Indicates the weighting factor of the third survey plan evaluation coefficient corresponding to the insulator string grade data,/> Indicates the weighting factor of the third survey plan evaluation coefficient corresponding to the ground conductor grade data,/> Indicates the weighting factor of the third survey plan evaluation coefficient corresponding to the ground angle bolt offset data.

In this embodiment, different solutions correspond to different ground angle bolt offset data, insulator string grade data, and ground wire grade data.

The specific calculation formula for obtaining the evaluation coefficient of the first survey fusion level survey monitoring plan is:

,

In the formula, Indicates the evaluation coefficient of the first survey fusion level survey monitoring plan.

The embodiment of this application evaluates the survey monitoring solutions corresponding to the first survey fusion sub-level, the second survey fusion sub-level, and the third survey fusion sub-level respectively through the survey monitoring information data, and sorts the corresponding level survey monitoring solutions respectively. Thus, selecting the optimal survey and monitoring plan for each level can greatly improve the efficiency of the method in obtaining the optimal plan, thereby enhancing the operability of the method; the embodiment of this application obtains the first survey and fusion sub-level survey monitoring by plan, the survey and monitoring plan of the first and second survey fusion sub-level and the survey and monitoring plan of the first and third survey fusion sub-level, according to several pre-defined inter-level data correlation relationships, jointly generate several survey and fusion level survey and monitoring plans, so that the first survey and fusion The hierarchical survey and monitoring plan is recorded as the technical and economic plan of the survey site selection project, thereby improving the practicality of the intelligent fusion processing results based on survey big data.

Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the invention 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, etc.) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each process and/or block in the flowchart illustrations and/or block diagrams, and combinations of processes 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 device to produce a machine, such that the instructions executed by the processor of the computer or other programmable data processing device produce a use A device for realizing the functions specified in a process or processes in a flowchart and/or a block or blocks in a block diagram.

These computer program instructions may also be stored in a computer-readable memory that causes a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including the instruction means, the instructions The device implements the functions specified in a process or processes in the flowchart and/or in a block or blocks in the block diagram.

These computer program instructions may also be loaded onto a computer or other programmable data processing device, causing a series of operating steps to be performed on the computer or other programmable device to produce computer-implemented processing, thereby executing on the computer or other programmable device. Instructions provide steps for implementing the functions specified in a process or processes of a flowchart diagram and/or a block or blocks of a block diagram.

Although the preferred embodiments of the present invention have been described, those skilled in the art will be able to make additional changes and modifications to these embodiments once the basic inventive concepts are apparent. Therefore, it is intended that the appended claims be construed to include the preferred embodiments and all changes and modifications that fall within the scope of the invention.

Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the invention. In this way, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims (9)

1. The intelligent fusion processing method based on the survey big data is characterized by comprising the following steps of:

dividing a survey fusion level into survey sub-levels;

respectively acquiring survey monitoring information data corresponding to each survey sub-level;

respectively evaluating a plurality of survey schemes corresponding to each survey sub-level according to the survey monitoring information data to respectively obtain evaluation coefficients corresponding to the plurality of survey schemes of each survey sub-level;

arranging evaluation coefficients corresponding to a plurality of survey schemes of each survey sub-level in a descending order, and determining the evaluation coefficients of the first survey scheme of each survey sub-level;

obtaining a first survey monitoring scheme corresponding to each survey sub-level according to the first survey scheme evaluation coefficient of each survey sub-level;

and generating a survey site selection engineering technical economic scheme according to the sequencing result.

2. The intelligent fusion processing method based on survey big data according to claim 1, wherein the generating a survey site-selection engineering economic scheme according to the ranking result comprises:

combining the first survey monitoring schemes corresponding to the survey sub-levels to generate a plurality of survey fusion level survey monitoring schemes according to a plurality of data association relations among the predefined levels;

respectively evaluating the survey monitoring schemes of the survey fusion levels to generate evaluation coefficients of the survey monitoring schemes of the survey fusion levels;

arranging the survey monitoring scheme evaluation coefficients of the plurality of survey fusion levels in a descending order to obtain first survey fusion level survey monitoring scheme evaluation coefficients;

and recording the survey fusion level survey monitoring scheme corresponding to the evaluation coefficient of the first survey fusion level survey monitoring scheme as a technical and economic scheme of the survey site selection engineering.

3. The survey big data based intelligent fusion processing method of claim 1, wherein the survey monitoring information data comprises:

meteorological conditions, number of pole and tower points, height, distance between adjacent poles and towers, electric grade of poles and towers, structural grade of poles and towers, number of substations, pile positions of towers, deviation amount of ground angle bolts, grade of insulator strings and grade data of ground leads.

4. A method of intelligent fusion processing based on survey big data according to claim 3, wherein each of the survey sub-levels includes a first survey sub-level, a second survey sub-level, and a third survey sub-level, and wherein evaluating the plurality of survey schemes corresponding to the first survey sub-level based on the survey monitoring information data to obtain the evaluation coefficients corresponding to the plurality of survey schemes of the first survey sub-level comprises:

obtaining a corresponding total earth cleaning quantity influence value according to the number and the height of the pole tower points, the distance between adjacent pole towers and the number of transformer substations;

calculating to obtain a meteorological condition influence value according to meteorological conditions and predefined construction period days in a plurality of survey monitoring schemes corresponding to a first survey sub-level;

and evaluating the plurality of survey monitoring schemes of the first survey sub-level according to the meteorological condition influence value, the number and the height of the pole tower points, the distance between adjacent pole towers, the number of substations and the total earth cleaning amount influence value to obtain evaluation coefficients corresponding to the plurality of survey schemes of the first survey sub-level.

5. The intelligent fusion processing method based on survey big data according to claim 4, wherein evaluating the plurality of survey solutions corresponding to the second survey sub-level based on the survey monitoring information data to obtain the evaluation coefficients corresponding to the plurality of survey solutions of the second survey sub-level comprises:

determining tower foundation pile position influence value data according to predefined tower foundation pile positions in a plurality of survey monitoring schemes corresponding to the second survey sub-level;

and evaluating a plurality of survey schemes corresponding to the second survey sub-level according to the tower electric grade, the tower structure grade and the tower foundation pile position influence value data to obtain evaluation coefficients corresponding to the plurality of survey schemes of the second survey sub-level.

6. The intelligent fusion processing method based on survey big data of claim 5, wherein evaluating the number of survey solutions corresponding to the third survey sub-level based on the survey monitoring information data to obtain the evaluation coefficients corresponding to the number of survey solutions of the third survey sub-level comprises:

obtaining the ground angle bolt offset, the insulator string grade and the ground wire grade according to a plurality of survey monitoring schemes corresponding to the second survey sub-level;

and evaluating a plurality of survey schemes corresponding to the third survey fusion sub-level according to the ground angle bolt offset, the insulator string level and the ground lead level to obtain evaluation coefficients corresponding to the plurality of survey schemes of the third survey sub-level.

7. The intelligent fusion processing method based on survey big data according to claim 4, wherein the calculation formulas of the evaluation coefficients corresponding to the plurality of survey schemes of the first survey sub-level are:

；

in the method, in the process of the invention,evaluation coefficients corresponding to several survey plans representing a first survey sub-level, +.>Indicating the influence value of the total soil clearance, +.>Representing the influence value of meteorological conditions, < >>Representing the number of pole and tower points, < > and->Representing tower height, < >>Representing the distance between adjacent towers->Representing the number of substations>Weight factor representing the number of tower points corresponding to the evaluation coefficient of the first survey plan, +.>Weight factor representing the tower height corresponding to the first survey plan evaluation factor, +.>A weight factor representing the adjacent tower distance corresponds to the first survey plan evaluation factor.

8. The intelligent fusion processing method based on survey big data according to claim 5, wherein the calculation formulas of the evaluation coefficients corresponding to the plurality of survey schemes of the second survey sub-level are:

；

in the method, in the process of the invention,evaluation coefficients corresponding to several survey plans representing a second survey sub-level, +.>Indicating the electrical grade of the tower, < >>Representing a predefined tower electrical grade,/->Representing the structural grade of the tower, < > and->Representing a predefined tower structure level->Data representing the influence value of the pile position of the foundation +.>Indicating that the electric grade of the tower corresponds to the firstWeighting factors for the two survey plan evaluation coefficients, +.>Weight factors representing tower structural levels corresponding to second survey plan evaluation coefficients, +.>Weight factors representing tower foundation pile position influence value data corresponding to second survey plan evaluation coefficients, +.>Representing natural constants.

9. The intelligent fusion processing method based on survey big data according to claim 6, wherein the calculation formulas of the evaluation coefficients corresponding to the plurality of survey schemes of the third survey sub-level are:

；

in the method, in the process of the invention,evaluation coefficients corresponding to several survey plans representing a third survey sub-level, +.>Indicating the ground angle bolt offset,/>Indicating the class of insulator string->Indicating the level of the ground wire,/-, and>representing a predefined insulator string class,/->Representing a predefined conductive line level,/->A weight factor representing the insulator string grade data corresponding to the third survey plan evaluation factor,weight factors representing the conductive line level data corresponding to the third survey plan evaluation coefficients, +.>And weight factors representing the ground angle bolt offset data corresponding to the third survey plan evaluation coefficients.