CN117668765A - Intelligent fusion processing method based on survey big data - Google Patents
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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
Technical Field
The invention relates to the technical field of survey data fusion, in particular to an intelligent fusion processing method based on survey big data.
Background
With the development of technology and the advancement of society, the field of surveying has generated a large amount of data including various types of information such as topography, geologic structures, environmental changes, and the like. The processing and analysis of these data is of great importance for the development of the survey field. However, conventional data processing methods have failed to meet the processing requirements of large-scale, complex data. Therefore, the fusion 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 the survey big data is used for efficiently and intelligently processing and analyzing mass data generated in the survey field by combining the big data technology with the artificial intelligence technology, and the complex data is mined, analyzed and predicted by utilizing the storage, processing and analysis capabilities of the big data, the machine learning, the deep learning and other algorithms of the artificial intelligence.
For example, publication No.: the invention patent of CN116862170A discloses a geological survey sampling method for power transmission and transformation engineering, which comprises the following steps: extracting pre-planned route characteristic data, distributing geological survey sampling points, extracting and analyzing information parameters of the geological survey sampling points, comprehensively processing data, selecting and judging a target erection route, and sharing basic data of the target erection route.
For example, bulletin numbers: the invention discloses a safety pre-alarm method and a system for fusing GIS and multi-source data of CN116912070B, wherein the method comprises the following steps: retrieving a GIS model generated based on the monitored area field survey data; dividing the monitored area into a plurality of grid areas in the GIS model; respectively acquiring precipitation information, water level information and weather forecast of each grid area; calculating the safe drainage, water storage and water seepage of each grid area according to the GIS model and the water level information; and predicting the probability of flood disasters and landslide disasters in each grid area according to the safe drainage, the water storage, the water seepage, the rainfall information and the weather forecast and by combining with the GIS model.
In the prior art, the basic geographic information data, the power grid tower data and the site selection engineering data are rich in sources, so that centralized management of the data is difficult to realize, and the problem that the technical and economic evaluation accuracy of the survey site selection multi-level data fusion processing is difficult to improve is solved.
Disclosure of Invention
According to the embodiment of the application, by providing the intelligent fusion processing method based on the survey big data, 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 is solved, and the effect of improving the technical and economic evaluation accuracy of the survey site selection multi-level data fusion processing is achieved.
The embodiment of the application provides 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 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.
According to some embodiments of the present application, the generating a survey site-selection engineering economic plan from the ranking results includes: 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.
According to some embodiments of the present application, 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.
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 the evaluating the plurality of survey schemes corresponding to the first survey sub-level according to the survey monitoring information data, to obtain evaluating coefficients corresponding to the plurality of survey schemes of the first survey sub-level includes: 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 the meteorological conditions and predefined construction period days in a plurality of survey monitoring schemes corresponding to the 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.
According to some embodiments of the present application, evaluating a number of survey solutions corresponding to the second survey sub-level from the survey monitoring information data, resulting in evaluation coefficients corresponding to the number 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.
According to some embodiments of the present application, wherein evaluating the number of survey solutions corresponding to the third survey sub-level based on the survey monitoring information data, obtaining 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.
One or more technical solutions provided in the embodiments of the present application at least have the following technical effects or advantages:
1. dividing the survey fusion level into a first survey fusion sub-level, a second survey fusion sub-level, and a third survey fusion sub-level; according to the method, 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 monitoring information data, the corresponding survey monitoring schemes of the levels are respectively sequenced, so that a survey site selection engineering technical economic scheme is generated according to an evaluation sequencing result, the effect of improving the technical economic evaluation accuracy of the survey site selection multi-level data fusion processing is further achieved, and the problem that in the prior art, the technical economic evaluation accuracy of the survey site selection multi-level data fusion processing is difficult to improve is solved.
2. And respectively evaluating the corresponding survey monitoring schemes of the first survey fusion sub-level, the second survey fusion sub-level and the third survey fusion sub-level through the survey monitoring information data, and respectively sequencing the corresponding survey monitoring schemes of the levels, so that the optimal survey monitoring scheme of each level is selected, the efficiency of acquiring the optimal scheme by the method can be greatly improved, and the operability of the enhancement method is further realized.
3. The first survey fusion sub-level survey monitoring scheme, the first second survey fusion sub-level survey monitoring scheme and the first third survey fusion sub-level survey monitoring scheme are obtained, and a plurality of survey fusion level survey monitoring schemes are jointly generated according to a plurality of predefined inter-level data association relations, so that the first survey fusion level survey monitoring scheme is recorded as a survey site selection engineering technical economic scheme, and further practicability of an intelligent fusion processing result based on survey big data is improved.
Drawings
Fig. 1 is a flowchart of an intelligent fusion processing method based on survey big data according to an embodiment of the present application.
Detailed Description
According to the embodiment of the application, the intelligent fusion processing method based on the survey big data is provided, the problem that in the prior art, the technical economy evaluation accuracy of the survey site selection multi-level data fusion processing is difficult to improve is solved, the technical economy scheme of the survey site selection engineering is generated through the evaluation sequencing result, and the effect of improving the technical economy evaluation accuracy of the survey site selection multi-level data fusion processing is achieved.
The technical solution in the embodiment of the present application is to solve the above problem that it is difficult to improve the accuracy of technical and economic evaluation of survey site selection multi-level data fusion processing, and the overall method is as follows:
by dividing the survey fusion hierarchy into a first survey fusion sub-hierarchy, a second survey fusion sub-hierarchy and a third survey fusion sub-hierarchy, the effect of improving the technical and economic evaluation accuracy of the survey site selection multi-level data fusion processing is achieved, and 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 is solved.
In order to better understand the above technical solutions, the following detailed description will refer to the accompanying drawings and specific embodiments.
As shown in fig. 1, a flowchart of an intelligent fusion processing method based on survey big data according to an embodiment of the present application is provided, and the method includes 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 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.
In this embodiment, the survey fusion hierarchy is divided into a first survey fusion sub-hierarchy, a second survey fusion sub-hierarchy, and a third survey fusion sub-hierarchy, where the first survey fusion sub-hierarchy, the second survey fusion sub-hierarchy, and the third survey fusion sub-hierarchy respectively include corresponding survey monitoring information data; respectively evaluating the corresponding survey monitoring schemes of the first survey fusion sub-level, the second survey fusion sub-level and the third survey fusion sub-level according to the survey monitoring information data, wherein the survey monitoring schemes comprise a plurality of survey monitoring schemes of the first survey fusion sub-level, a plurality of survey monitoring schemes of the second survey fusion sub-level and a plurality of survey monitoring schemes of the third survey fusion sub-level, and respectively sequencing the corresponding level survey monitoring schemes; and generating a survey site selection engineering technical economic scheme according to the evaluation sequencing result.
In this embodiment, the survey fusion hierarchy is divided into a first survey fusion sub-hierarchy, a second survey fusion sub-hierarchy and a third survey fusion sub-hierarchy, where the first survey fusion sub-hierarchy mainly corresponds to the survey data fusion of the survey cable arrangement level, the second survey fusion sub-hierarchy mainly corresponds to the survey data fusion of the survey specific tower attribute data, and the third survey fusion sub-hierarchy mainly corresponds to the survey data fusion specific tower attribute data fusion of the survey tower component level.
And 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, wherein the method specifically comprises the following steps:
evaluating a plurality of survey monitoring schemes of the first survey fusion sub-level to obtain a plurality of first survey scheme evaluation coefficients, wherein the plurality of survey monitoring schemes of the first survey fusion sub-level are in one-to-one correspondence with the plurality of first survey scheme evaluation coefficients, and the plurality of first survey scheme evaluation coefficients are arranged in a descending order to obtain a first survey scheme evaluation coefficient and a corresponding first survey fusion sub-level survey monitoring scheme, and the first survey fusion sub-level survey monitoring scheme is recorded as the first survey fusion sub-level survey monitoring scheme;
evaluating a plurality of survey monitoring schemes of the second survey fusion sub-level to obtain a plurality of second survey scheme evaluation coefficients, wherein the plurality of survey monitoring schemes of the second survey fusion sub-level are in one-to-one correspondence with the plurality of second survey scheme evaluation coefficients, and the plurality of second survey scheme evaluation coefficients are arranged in a descending order to obtain a first second survey scheme evaluation coefficient and a corresponding second survey fusion sub-level survey monitoring scheme, and the first second survey scheme evaluation coefficient and the corresponding second survey fusion sub-level survey monitoring scheme are recorded as the first second survey fusion sub-level survey monitoring scheme;
and evaluating the plurality of survey monitoring schemes of the third survey fusion sub-level to obtain a plurality of third survey scheme evaluation coefficients, wherein the plurality of survey monitoring schemes of the third survey fusion sub-level are in one-to-one correspondence with the plurality of third survey scheme evaluation coefficients, and the plurality of third survey scheme evaluation coefficients are arranged in a descending order to obtain a first third survey scheme evaluation coefficient and a corresponding survey monitoring scheme of the third survey fusion sub-level, and the first third survey scheme evaluation coefficient and the corresponding survey monitoring scheme of the third survey fusion sub-level are recorded as the first third survey fusion sub-level survey monitoring scheme.
In this embodiment, the corresponding survey monitoring schemes for the three tiers may be obtained by: layer management: and carrying out layer management on the transfer drawing data in the designed line corridor, wherein each type of ground feature belongs to one layer, carrying out unified naming and attribute setting, managing the transfer drawing layer according to the vectorization data, and supporting self definition of the layer style. And (3) interactive drawing: constructing ground object objects such as points, lines, planes and the like on the three-dimensional earth through data, popping up an attribute table when drawing of each object is finished, and filling the names and types of the ground object identifiers; coordinate input: constructing ground object objects such as points, lines, planes and the like by importing coordinate files in a specified format or inputting coordinate value information of each point; CAD data importing: supporting analysis of the dwg file in a fixed format, and importing graphic data of a specified category in the dwg file into a specified layer by setting matched classification information; and (3) attribute maintenance: the attribute information corresponding to each graphic object is managed to comprise the contents of belonging classification, feature names, label signs, extended attribute information and the like; editing a graph: editing operations of feature transfer data in a designed line corridor are supported, including operations of moving of point-line-plane features, node editing, style setting, attribute adding and deleting and the like, modification of the boundary range of an input graphic object is supported, and graphic appearance is adjusted; and (3) accessory maintenance: managing accessories associated with the formulated object, and supporting operations such as adding, deleting, exporting and the like; plotting and deriving: support the hierarchical derivation of the plot data into dwg files according to the belonging classification information. And the control point achievement management realizes the control point management function in the earlier stage of the power transmission line engineering, and the control point attribute comprises a coordinate system, coordinates, acquisition time, acquisition people and the like. The system supports the functions of analysis, output and the like of xls, txt and other files, and can calculate coordinate conversion parameters according to the selected control points, and coordinate conversion of server data is achieved. The digital design result three-dimensional display realizes the basic functions of engineering three-dimensional model, loading of topography, browsing and measuring of three-dimensional scene, and the like. Distance measurement: the data types include: the point cloud, the inclination, the vector, the dom and the dem are loaded efficiently; scheme management: and carrying out scheme retrieval according to the information combinations of scheme names, scheme numbers, scheme types, voltage levels and the like, and rapidly positioning the scheme to be searched. The adding scheme is as follows: the new construction scheme is used for creating a new engineering scheme, and a user can input information of the new engineering scheme, such as information of an added voltage level, a construction unit, a design unit, a supervision unit and the like, when adding the scheme according to the scheme name and the scheme stage; in the process of creating the scheme, a scheme coordinate system can be synchronously set. The modification scheme is as follows: through selecting the scheme name and the scheme stage, a user can edit the information of the existing scheme according to the actual situation, wherein the editing content comprises the information of the scheme name, the construction unit, the design unit, the supervision unit and the like; the deletion scheme is as follows: after the user selects the deletion scheme, deleting the nodes of the engineering scheme in the engineering management data list, and deleting the data, the data and the design stage catalogue of each stage of the engineering. And (5) managing survey results: the scheme mainly relates to the warehousing, maintenance and management of three specialized related data and data of regional measurement, geology and hydrometeorology.
In this embodiment, the specific process of generating the technical economic scheme of the survey site selection engineering according to the evaluation sequencing result is as follows: obtaining a survey monitoring scheme of a first survey fusion sub-level, a survey monitoring scheme of a first second survey fusion sub-level and a survey monitoring scheme of a first third survey fusion sub-level, according to a plurality of predefined inter-level data association relations, wherein the plurality of predefined inter-level data association relations comprise: the method comprises the steps that a survey monitoring scheme of a first survey fusion sub-level and a survey monitoring scheme corresponding to a second survey fusion sub-level are in predefined data association relation, and a plurality of survey fusion level survey monitoring schemes are generated in a combined mode according to the predefined data association relation of the survey monitoring scheme of the first survey fusion sub-level and the survey monitoring scheme corresponding to a third survey fusion sub-level; and evaluating the survey fusion level survey monitoring schemes to generate a plurality of survey fusion level survey monitoring scheme evaluation coefficients, wherein the plurality of survey fusion level survey monitoring schemes are in one-to-one correspondence with the plurality of survey fusion level survey monitoring scheme evaluation coefficients, and the plurality of survey fusion level survey monitoring scheme evaluation coefficients are arranged in a descending order to obtain a first survey fusion level survey monitoring scheme evaluation coefficient and a corresponding survey fusion level survey monitoring scheme, which are recorded as a survey site selection engineering technical economic scheme.
The sources of the technical and economic index data of this example are 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 are respectively obtained by the following steps: the first survey scheme evaluation coefficient represents data obtained by evaluating and analyzing a survey monitoring scheme of a first survey fusion sub-level through meteorological condition influence value data, tower point position number data, tower height data, adjacent tower distance data, substation number data and total earth clearance influence value data; the second survey plan evaluation coefficients represent data obtained by evaluation and analysis of the survey monitoring plan of the second survey fusion sub-level by the tower electric grade data, the tower structure grade data and the tower foundation pile position influence value data; the third survey plan evaluation coefficients represent data obtained by survey monitoring plan evaluation analysis of the third survey fusion sub-level by the ground angle bolt offset data, the insulator string grade data, and the ground lead grade data.
Further, the survey monitoring information data acquisition and analysis process corresponding to the first survey plan evaluation coefficient is as follows: directly extracting data according to a survey monitoring scheme corresponding to the first survey fusion sub-level to obtain tower point position number data, tower height data, adjacent tower distance data and transformer substation number data; processing according to the pole tower point position number data, the pole tower height data, the adjacent pole tower distance data and the transformer substation number data to obtain corresponding total earth cleaning quantity influence value data; obtaining weather condition influence value data according to comparison calculation of predefined construction period days in a survey monitoring scheme corresponding to a first survey fusion sub-level of weather condition influence delay; from this, evaluation coefficients corresponding to several survey plans of the first survey sub-level are calculated.
Further, the survey monitoring information data acquisition and analysis process corresponding to the second survey plan evaluation coefficients is as follows: selecting a survey monitoring scheme corresponding to the second survey fusion sub-level according to a predefined data association relation of the survey monitoring scheme of the first survey fusion sub-level and the survey monitoring scheme corresponding to the second survey fusion sub-level; directly extracting data according to a survey monitoring scheme corresponding to the second survey fusion sub-level to obtain tower electric grade data and tower structure grade data; the method comprises the steps of obtaining predefined foundation pile positions in a survey monitoring scheme corresponding to a second survey fusion sub-level, obtaining different engineering costs corresponding to different foundation pile positions, and obtaining foundation pile position influence value data through comparison calculation; from this, evaluation coefficients corresponding to several survey plans of the second survey sub-level are calculated.
Further, the survey monitoring information data acquisition and analysis process corresponding to the third survey plan evaluation coefficient is as follows: selecting a survey monitoring scheme corresponding to the third survey fusion sub-level according to a predefined data association relation between the survey monitoring scheme of the first second survey fusion sub-level and the survey monitoring scheme corresponding to the third survey fusion sub-level; directly extracting data according to a survey monitoring scheme corresponding to the second survey fusion sub-level to obtain ground angle bolt offset data, insulator string grade data and ground lead grade data; from this, evaluation coefficients corresponding to several survey plans of the third survey sub-level are calculated.
In this embodiment, the above data may be obtained through data extraction, and may also be obtained through a fast price calculation model, where the data association relationship includes a predefined data association relationship between the first survey monitoring scheme of the second survey fusion sub-level and the survey monitoring scheme corresponding to the third survey fusion sub-level, for example, after the first survey monitoring scheme of the first survey fusion sub-level is obtained, although there are several survey monitoring schemes of the second survey fusion sub-level, there cannot be any data currently included in the scheme database, for example, the insulator voltage level refers to the maximum voltage value that the insulator can withstand, and is generally used for high-voltage devices in the power system. Common 8 insulator voltage levels include: 1kV, 3kV, 6kV, 10kV, 20kV, 35kV, 66kV and 110kV. Insulators of different voltage classes are suitable for different power systems and equipment, such as 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 the use of the insulators play a vital role in the safe operation of the power equipment and the stable operation of the power grid, and once the voltage class of the extra-high voltage tower pole is determined, the corresponding tower pole voltage class is directly eliminated along with the determination of other inadaptation schemes.
The specific calculation formula of the evaluation coefficients corresponding to the plurality of survey schemes of the first survey sub-level is as follows:
；
in the method, in the process of the invention,evaluation coefficients corresponding to several survey plans representing a first survey sub-level, +.>Data representing the impact of total earthwork clearance, < +.>Data representing the influence of meteorological conditions, < ->Data representing the number of pole and tower points, < > and->Representing tower height data->Representing adjacent tower distance data, < >>Representing substation quantity data>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.
In this embodiment, the distance data of adjacent towers is generally a determined value after the scheme is determined, the number of tower points is the same, and the total earth cleaning amount influence value data generally only counts the earth cleaning amount of the towers and the bases thereof. The weather condition influence value data indicates that the project is slower than the specified progress by a few days due to weather reasons, the data is the data of specific days after the project is slower by a few days, the total earthwork cleaning amount influence value data indicates that compared with the standard project total earthwork cleaning amount, the ratio of the actual project total earthwork cleaning amount to the standard project total earthwork cleaning amount is reduced by 1, and the total earthwork cleaning amount influence value data is obtained.
The specific calculation formula of the evaluation coefficients corresponding to the plurality of survey schemes of the second survey sub-level is as follows:
；
in the method, in the process of the invention,evaluation coefficients corresponding to several survey plans representing a second survey sub-level, +.>Representing tower electrical grade data, < >>Representing predefined tower electrical standard grade data, +.>Representing tower structure level data, < >>Data representing a predefined tower structure standard class +.>Data representing the impact value of foundation pile position，/>Weight factor representing the tower electrical grade corresponding to the second survey plan evaluation factor, +.>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.
In this embodiment, the tower foundation pile position influence value data represents that the economic costs of different tower foundation pile positions are different, and the comparison calculation is performed on the standard tower foundation pile positions, so that the obtained ratio is the tower foundation pile position influence value data.
The specific calculation formula of the evaluation coefficients corresponding to the plurality of survey schemes of the third survey sub-level is as follows:
；
in the method, in the process of the invention,evaluation coefficients corresponding to several survey plans representing a third survey sub-level, +.>Data representing the displacement of the ground angle bolts, +.>Data representing insulator string grade +.>Representing conductive wire grade data,/>Data representing a standard class of predefined insulator strings, +.>Representing predefined conductive wire standard grade data, +.>Weight factors representing the evaluation coefficients of the third survey plan for the insulator string class data +.>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.
In this embodiment, different schemes correspond to different ground angle bolt offset data, insulator string grade data, and ground lead grade data.
The specific calculation formula for acquiring the evaluation coefficient of the first survey fusion level survey monitoring scheme is as follows:
，
in the method, in the process of the invention,representing the first survey fusion level survey monitoring scheme evaluation coefficients.
According to the embodiment of the application, the first survey fusion sub-level, the second survey fusion sub-level and the third survey fusion sub-level are respectively evaluated through the survey monitoring information data, the corresponding survey monitoring schemes of the corresponding levels are respectively sequenced, so that the optimal survey monitoring scheme of each level is selected, the efficiency of acquiring the optimal scheme by the method can be greatly improved, and the operability of the enhancement method is further realized; according to the embodiment of the application, the first-level survey monitoring scheme, the first-level second-level survey monitoring scheme and the first-level third-level survey monitoring scheme are obtained, and a plurality of survey fusion-level survey monitoring schemes are jointly generated according to a plurality of predefined inter-level data association relations, so that the first-level survey fusion-level survey monitoring scheme is recorded as a survey site selection engineering technical economic scheme, and further practicability of intelligent fusion processing results based on survey big data is improved.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present 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, and the like) 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 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.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
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.
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