Distribution network GIS data total analysis system based on search tree

Abstract

The invention relates to the technical field of computer science, and particularly discloses a distribution network GIS data total analysis system based on a search tree, which comprises a central controller, a data acquisition module, a data preprocessing module, a search tree construction module, a traversal and recursive execution module, a data analysis and extraction module, a power supply module and a data reduction and secondary processing module, the modules and the sub-modules of the system work together, the data acquisition module accurately and efficiently acquires original data and avoids errors caused by manual acquisition, the data preprocessing module processes the acquired data and solves the problem of data dispersion and confusion, and the search tree construction module constructs an efficient structure and improves the data processing efficiency. The traversal and recursive execution module can accurately obtain data according to needs, the data analysis and extraction module deeply mines data values, the data reduction and secondary processing module meets different scene requirements, and the data visualization module visually displays the data and helps planners to understand the data.

Description

Technical Field

[0001] The present invention relates to the field of computer science and technology, and in particular to a distribution network GIS data full-volume parsing system based on a search tree. Background Art

[0002] At present, in the current power grid planning scope, there are many very significant technical shortcomings in the processing and management of distribution network GIS data. In power grid planning, key tasks such as the drawing of current / prospective grid diagrams, the association of construction projects, and the integration of various planning data have always been extremely lacking in efficient information-based auxiliary tools. From a traditional perspective, the drawing of current and prospective maps is usually done manually with the help of CAD, which not only consumes a lot of time and manpower costs, but also easily leads to errors and inconsistencies. At the same time, the relevant data is stored and managed through tables and documents, which makes the data scattered and messy, making it difficult to achieve effective integration and correlation analysis.

[0003] In the planning process, due to the lack of visualization means, it is difficult for planners to intuitively and clearly understand and control the overall architecture and development trend of the power grid, which in turn has an adverse impact on the scientificity and rationality of the planning. The management procedures are complicated and trivial, involving a large amount of manual operations and data verification work, which is extremely inefficient and prone to errors. In addition, the existing data processing model cannot fully tap the potential value contained in the data and it is difficult to achieve in-depth application of the data. As for standardized and structured data such as XML models, they cannot be effectively combined with planning table data, which greatly limits the depth and accuracy of daily planning. Moreover, the interconnection between various system interfaces faces many difficulties, which has caused a lot of debugging work. The restrictions and reviews on network security have further increased the difficulty of system integration and data sharing. The existing software tools are not satisfactory in terms of versatility and scalability, and it is difficult to meet the actual needs of different regions and scenarios, and it is impossible to respond to changes quickly and carry out flexible development. Summary of the invention

[0004] The purpose of the present invention is to provide a distribution network GIS data full-volume parsing system based on a search tree to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above-mentioned purpose, the present invention provides a distribution network GIS data full-quantity analysis system based on a search tree, comprising a central controller, a data acquisition module, a data preprocessing module, a search tree construction module, a traversal and recursive execution module, a data analysis and extraction module, a power supply module, a data restoration and secondary processing module, a data visualization module and a data storage module, wherein the power supply module is used to supply power to the central controller, the power supply module is electrically connected to the central controller, and the data acquisition module, the data preprocessing module, the search tree construction module, the traversal and recursive execution module, the data analysis and extraction module, the data restoration and secondary processing module, the data visualization module and the data storage module are all electrically connected to the central controller.

[0006] Furthermore, the data acquisition module includes a device driver submodule, a data sampling submodule, and a data buffer submodule. The data buffer submodule is signal-connected to the data sampling submodule, and the data buffer submodule is electrically connected to the data driver submodule.

[0007] Furthermore, the data acquisition module also includes a data format conversion submodule and a data transmission submodule, the data format conversion submodule is electrically connected to the data sampling submodule and the device driver submodule, the data buffer submodule is connected to the data sampling submodule signal through the data transmission module, and the device driver submodule is used to drive the hardware devices of the data sampling submodule, the data buffer submodule and the data format conversion submodule to communicate and operate to obtain raw data.

[0008] Furthermore, the data preprocessing module includes a data cleaning submodule, a data screening submodule, a data integration submodule, a data standardization submodule and a feature engineering submodule. The data cleaning submodule, data screening submodule, data integration submodule and feature engineering submodule are connected through data transmission submodule, data standardization submodule and data acquisition module signals. The data cleaning submodule, data screening submodule, data integration submodule and feature engineering submodule are electrically connected to the central controller. The data standardization submodule is used to standardize the data to a specific range.

[0009] Furthermore, the search tree construction module includes a node generation submodule, an edge generation submodule, a balance adjustment submodule, a tree structure optimization submodule and an index establishment submodule. The node generation submodule, the edge generation submodule, the balance adjustment submodule, the tree structure optimization submodule and the index establishment submodule are all electrically connected to the central controller. The node generation submodule is used to create nodes of the search tree, the edge generation submodule is used to establish connecting edges between nodes, the balance adjustment submodule is used to ensure the balance of the search tree, the tree structure optimization submodule is used to optimize the structure of the tree and reduce storage space, and the index establishment submodule establishes an index for the search tree to accelerate data search.

[0010] Furthermore, the traversal and recursive execution module includes a depth-first traversal submodule, a breadth-first traversal submodule, a random traversal submodule, a recursive call control submodule and a traversal result processing submodule. The depth-first traversal submodule, breadth-first traversal submodule, random traversal submodule, recursive call control submodule and traversal result processing submodule are all electrically connected to the central controller. The depth-first traversal submodule, breadth-first traversal submodule, random traversal submodule, recursive call control submodule and traversal result processing submodule can select the corresponding traversal submodule for operation according to needs. The recursive call control submodule ensures the security of the recursion. The traversal result is processed by the traversal result processing submodule and passed to the data analysis and extraction module.

[0011] Furthermore, the data analysis and extraction module includes a data statistics submodule, a pattern recognition submodule, an association analysis submodule, a classification and prediction submodule and an anomaly detection submodule. The data statistics submodule, the pattern recognition submodule, the association analysis submodule, the classification and prediction submodule and the anomaly detection submodule are electrically connected to the central controller. The data analysis and extraction module is used to receive the results of the traversal and recursive execution modules. The data statistics submodule calculates statistics. The pattern recognition submodule, the association analysis submodule, the classification and prediction submodule and the anomaly detection submodule perform corresponding analysis and extraction operations respectively, and pass the results to subsequent modules.

[0012] Furthermore, the data restoration and secondary processing module includes an original data recovery module, a data enhancement submodule, a data aggregation submodule, a data fusion submodule and a data smoothing submodule. The original data recovery module, the data enhancement submodule, the data aggregation submodule, the data fusion submodule and the data smoothing submodule are electrically connected to the central controller. The data restoration and secondary processing module is used to receive the results of the data analysis and extraction module. The original data recovery module restores the original data as needed. The data enhancement submodule, the data aggregation submodule, the data fusion submodule and the data smoothing submodule perform corresponding processing on the data, and the processed data is passed to the data visualization module.

[0013] Furthermore, the data visualization module includes a graphics drawing submodule, a color mapping submodule, a coordinate axis configuration submodule, a label adding submodule and an interactive response submodule. The graphics drawing submodule, color mapping submodule, coordinate axis configuration submodule, label adding submodule and interactive response submodule are all electrically connected to the central controller. The data visualization module is used to receive data from the data restoration and secondary processing module. The graphics drawing submodule draws graphics, the color mapping submodule performs color configuration, the coordinate axis configuration submodule sets the coordinate axis, the label adding submodule adds labels, and the interactive response submodule processes user interactions, so as to jointly display intuitive visualization effects to users.

[0014] Furthermore, the data storage module includes a database management submodule, a data writing submodule, an index updating submodule, a data backup submodule and a data recovery submodule. The database management submodule, the data writing submodule, the index updating submodule, the data backup submodule and the data recovery submodule are electrically connected to the central controller. The data storage module is used to receive data from other modules. The database management submodule manages the database, the data writing submodule writes data to the storage medium, the index updating submodule updates the index, the data backup submodule performs backup operations, and the data recovery submodule restores data when needed.

[0015] Compared with the prior art, the beneficial effects of the present invention are: the modules and sub-modules of the system work together, the data acquisition module accurately and efficiently obtains original data to avoid errors in manual collection, the data preprocessing module processes the collected data to solve the problem of scattered and chaotic data, the search tree construction module constructs an efficient structure to improve data processing efficiency, the traversal and recursive execution module can accurately obtain data on demand, the data analysis and extraction module deeply mines the value of data, the data restoration and secondary processing module meets the needs of different scenarios, the data visualization module intuitively displays data to help planners understand, and the data storage module ensures the safe storage, query, backup and recovery of data. In short, the modules work closely together to significantly improve the efficiency and scientificity of power grid planning and overcome the technical defects of traditional methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a structural diagram of the overall system of the present invention;

[0017] Figure 2 It is a structural diagram of the constituent submodules in the data acquisition module of the present invention;

[0018] Figure 3 It is a structural diagram of the constituent submodules in the data preprocessing module of the present invention;

[0019] Figure 4 A structural diagram of the constituent submodules in the search tree construction module of the present invention;

[0020] Figure 5 It is a structural diagram of the constituent submodules in the traversal and recursive execution module of the present invention;

[0021] Figure 6 It is a structural diagram of the constituent submodules in the data analysis and extraction module of the present invention;

[0022] Figure 7 It is a structural diagram of the submodules in the data restoration and secondary processing module of the present invention;

[0023] Figure 8 It is a structural diagram of the constituent submodules in the data visualization module of the present invention;

[0024] Fig. 9 It is a structural diagram of the constituent submodules in the data storage module of the present invention.

[0025] In the figure: 1. Central controller; 2. Data acquisition module; 21. Device driver submodule; 22. Data sampling submodule; 23. Data buffer submodule; 24. Data format conversion submodule; 25. Data transmission submodule; 3. Data preprocessing module; 31. Data cleaning submodule; 32. Data screening submodule; 33. Data integration submodule; 34. Data standardization submodule; 35. Feature engineering submodule; 4. Search tree construction module; 41. Node generation submodule; 42. Edge generation submodule; 43. Balance adjustment submodule; 44. Tree structure optimization submodule; 45. Index establishment submodule; 5. Traversal and recursive execution module; 51. Depth-first traversal submodule; 52. Breadth-first traversal submodule; 53. Random traversal submodule; 54. Recursive call control submodule; 55. Traversal result processing submodule Module; 6. Data analysis and extraction module; 61. Data statistics submodule; 62. Pattern recognition submodule; 63. Association analysis submodule; 64. Classification and prediction submodule; 65. Anomaly detection submodule; 7. Data restoration and secondary processing module; 71. Original data recovery module; 72. Data enhancement submodule; 73. Data aggregation submodule; 74. Data fusion submodule; 75. Data smoothing submodule; 8. Data visualization module; 81. Graphics drawing submodule; 82. Color mapping submodule; 83. Coordinate axis configuration submodule; 84. Annotation adding submodule; 85. Interactive response submodule; 9. Data storage module; 91. Database management submodule; 92. Data writing submodule; 93. Index update submodule; 94. Data backup submodule; 95. Data recovery submodule; 10. Power supply module. DETAILED DESCRIPTION

[0026] Example

[0027] See also Figure 1-Figure 9 , exemplarily, the connection relationship between the sub-modules in each module in the embodiment of the present invention is one example, and the connection relationship between other sub-modules can also be determined according to the signal transmission direction between the sub-modules. The connection relationship between the sub-modules in each module is not limited here.

[0028] In an embodiment of the present invention, a distribution network GIS data full-volume parsing system based on a search tree includes a central controller 1, a data acquisition module 2, a data preprocessing module 3, a search tree construction module 4, a traversal and recursive execution module 5, a data analysis and extraction module 6, a power supply module 10, a data restoration and secondary processing module 7, a data visualization module 8 and a data storage module 9. The power supply module 10 is used to supply power to the central controller 1. The power supply module 10 is electrically connected to the central controller 1. The data acquisition module 2, the data preprocessing module 3, the search tree construction module 4, the traversal and recursive execution module 5, the data analysis and extraction module 6, the data restoration and secondary processing module 7, the data visualization module 8 and the data storage module 9 are all electrically connected to the central controller 1. The central controller 1 coordinates and manages the various modules in a unified manner, thereby ensuring The system operates efficiently and stably. The data acquisition module 2 can obtain data comprehensively and accurately, providing rich original information for subsequent processing. The data preprocessing module 3 performs preliminary optimization on the data to improve the data quality. The search tree construction module 4 and the traversal and recursive execution module 5 cooperate with each other to effectively improve the efficiency of data search and processing. The data analysis and extraction module 6 deeply mines the value of data and provides strong support for decision-making. The data restoration and secondary processing module 7 meets different needs and enhances the availability of data. The data visualization module 8 displays complex data intuitively for easy understanding and analysis. The data storage module 9 ensures the safe storage and convenient call of data. In short, the modules work together to enable the entire system to have powerful data processing and analysis capabilities, providing an efficient, accurate and comprehensive solution for the full analysis of distribution network GIS data.

[0029] See also Figure 2The data acquisition module 2 includes a device driver submodule 21, a data sampling submodule 22, and a data buffer submodule 23. The data buffer submodule 23 is connected to the data sampling submodule 22 by signal, and the data buffer submodule 23 is electrically connected to the data driver submodule. The data acquisition module 2 also includes a data format conversion submodule 24 and a data transmission submodule 25. The data format conversion submodule 24 is electrically connected to the data sampling submodule 22 and the device driver submodule 21. The data buffer submodule 23 is connected to the data sampling submodule 22 by signal through the data transmission module. The device driver submodule 21 is used to drive the hardware devices of the data sampling submodule 22, the data buffer submodule 23 and the data format conversion submodule 24 to communicate and operate to obtain raw data. The data acquisition submodule 21 provides drivers for the hardware device communication operation of other submodules, ensuring the basic support for data acquisition. The data buffer submodule 23 can temporarily store data, smooth data transmission, and avoid data loss or congestion. The data sampling submodule 22 collects data according to the set rules to ensure the accuracy and validity of the data. The data format conversion submodule 24 converts the original data of different formats to facilitate subsequent processing. The data transmission submodule 25 ensures the efficient transmission of data between various submodules. The submodules cooperate and work closely with each other to realize the complete process from hardware equipment to data acquisition, buffering, conversion and transmission, which greatly improves the efficiency and quality of data acquisition and provides a reliable and high-quality data source for the stable operation of the entire system and subsequent data processing.

[0030] See also Figure 3The data preprocessing module 3 includes a data cleaning submodule 31, a data screening submodule 32, a data integration submodule 33, a data standardization submodule 34 and a feature engineering submodule 35. The data cleaning submodule 31, the data screening submodule 32, the data integration submodule 33 and the feature engineering submodule 35 are connected to the data acquisition module 2 through the data transmission submodule 25, the data standardization submodule 34 and the data acquisition module 2 signal. The data cleaning submodule 31, the data screening submodule 32, the data integration submodule 33 and the feature engineering submodule 35 are electrically connected to the central controller 1. The data standardization submodule 34 is used to standardize the data to a specific range. The data cleaning submodule 31 can effectively remove noise, errors and duplicate data to improve the purity of the data. The data screening submodule 32 can accurately filter out useful data according to specific conditions to improve the pertinence and value of the data. For example, the original data can be directly filtered, and the data output by the data cleaning submodule can also be filtered. The data integration submodule 33 can Integrate data from multiple sources to break down data silos and form a comprehensive data set. Similarly, the data integration submodule can integrate the original data, or the data output by the data cleaning submodule or the data screening submodule. The feature engineering submodule 35 is responsible for extracting and constructing meaningful features to provide strong support for subsequent analysis and processing. The data standardization submodule 34 standardizes the data to a specific range, enhancing the comparability and versatility of the data. Through the connection of the data transmission submodule 25, each submodule and the data acquisition module 2 achieve efficient communication and work together under the unified scheduling of the central controller 1 to pre-process the collected data in a comprehensive, in-depth and orderly manner, providing high-quality, standardized and easy-to-process data for subsequent modules, thereby significantly improving the performance of the entire system and the accuracy of the analysis results. In addition, any submodule in the data preprocessing module 3 can obtain data output by any other module or any other submodule connected to any signal through the central controller 1.

[0031] See also Figure 4The search tree construction module 4 includes a node generation submodule 41, an edge generation submodule 42, a balance adjustment submodule 43, a tree structure optimization submodule 44 and an index establishment submodule 45. The node generation submodule 41, the edge generation submodule 42, the balance adjustment submodule 43, the tree structure optimization submodule 44 and the index establishment submodule 45 are all electrically connected to the central controller 1. The node generation submodule 41 is used to create nodes of the search tree, the edge generation submodule 42 is used to establish connecting edges between nodes, the balance adjustment submodule 43 is used to ensure the balance of the search tree, the tree structure optimization submodule 44 is used to optimize the structure of the tree and reduce storage space, and the index establishment submodule 45 is used to establish an index for the search tree to accelerate data search. The node generation submodule 41 creates nodes of the search tree and lays a foundation for building the search tree. 2 establishes connecting edges between nodes so that the nodes are interconnected to form a complete tree structure; the balance adjustment submodule 43 ensures the balance of the search tree to avoid excessive tilting that affects the search efficiency; the tree structure optimization submodule 44 optimizes the structure of the tree to reduce the storage space occupied and improve the resource utilization efficiency; the index establishment submodule 45 establishes an index for the search tree, which greatly accelerates the data search speed. Under the unified control of the central controller 1, these submodules cooperate with each other and work closely together to jointly build an efficient, balanced, optimized and easy-to-find data search tree structure, which provides strong support for the data processing and analysis of the entire system and significantly improves the performance and operation efficiency of the system; wherein, any submodule in the search tree construction module 4 obtains the preprocessed data output by the data preprocessing module 3 and creates a search tree according to the preprocessed data.

[0032] See also Figure 5The traversal and recursive execution module 5 includes a depth-first traversal submodule 51, a breadth-first traversal submodule 52, a random traversal submodule 53, a recursive call control submodule 54 and a traversal result processing submodule 55. The depth-first traversal submodule 51, the breadth-first traversal submodule 52, the random traversal submodule 53, the recursive call control submodule 54 and the traversal result processing submodule 55 are all electrically connected to the central controller 1. The depth-first traversal submodule 51, the breadth-first traversal submodule 52, the random traversal submodule 53, the recursive call control submodule 54 and the traversal result processing submodule 55 can select the corresponding traversal submodule for operation according to the needs. The recursive call control submodule 54 ensures the security of the recursion. The traversal result is processed by the traversal result processing submodule 55 and passed to the data analysis and extraction module. The depth-first traversal submodule 51, the breadth-first traversal submodule 52 and the random traversal submodule 53 provide a variety of traversal methods, which can be flexibly selected according to different data characteristics and requirements to achieve the most efficient data access. The recursive call control submodule 54 strictly ensures the security of the recursive operation to prevent problems such as system crashes caused by excessive recursion. The traversal result processing submodule 55 is responsible for professional processing of the acquired traversal results so that they can be passed to the data analysis and extraction module in a more standardized and useful form. Under the coordination of the central controller 1, these submodules work together to not only ensure the stability and reliability of the traversal and recursive execution process, but also efficiently obtain valuable information, providing a solid foundation for subsequent data analysis and processing, and greatly improving the operating efficiency and processing capabilities of the entire system.

[0033] See also Figure 6The data analysis and extraction module 6 includes a data statistics submodule 61, a pattern recognition submodule 62, an association analysis submodule 63, a classification and prediction submodule 64 and an anomaly detection submodule 65. The data statistics submodule 61, the pattern recognition submodule 62, the association analysis submodule 63, the classification and prediction submodule 64 and the anomaly detection submodule 65 are electrically connected to the central controller 1. The data analysis and extraction module 6 is used to receive the results of the traversal and recursive execution modules. The data statistics submodule 61 calculates the statistics, the pattern recognition submodule 62, the association analysis submodule 63, the classification and prediction submodule 64 and the anomaly detection submodule 65 perform corresponding analysis and extraction operations respectively, and pass the results to the subsequent modules. By receiving the traversal and recursive execution modules, the data statistics submodule 61 calculates the statistics, the pattern recognition submodule 62, the association analysis submodule 63, the classification and prediction submodule 64 and the anomaly detection submodule 65 perform corresponding analysis and extraction operations respectively, and pass the results to the subsequent modules. According to the results of the execution module, the data statistics submodule 61 can accurately calculate various statistics and provide basic data support for subsequent analysis. The pattern recognition submodule 62 can keenly discover the patterns and laws in the data. The association analysis submodule 63 is good at finding the correlation between the data. The classification and prediction submodule 64 can accurately classify and effectively predict the data. The anomaly detection submodule 65 can timely identify the abnormal values ​​and abnormal patterns in the data. Each submodule performs its own duties and cooperates with each other to perform corresponding analysis and extraction operations, and pass the valuable results to the subsequent modules, thereby realizing in-depth mining and effective use of data, and providing key and accurate information basis for decision-making and optimization of the entire system.

[0034] See also Figure 7The data restoration and secondary processing module includes an original data recovery module 71, a data enhancement submodule 72, a data aggregation submodule 73, a data fusion submodule 74 and a data smoothing submodule 75. The original data recovery module 71, the data enhancement submodule 72, the data aggregation submodule 73, the data fusion submodule 74 and the data smoothing submodule 75 are electrically connected to the central controller 1. The data restoration and secondary processing module is used to receive the results of the data analysis and extraction module. The original data recovery module 71 restores the original data as needed, and the data enhancement submodule 72, the data aggregation submodule 73, the data fusion submodule 74 and the data smoothing submodule 75 perform corresponding processing on the data. The processed data is transmitted to the data visualization module. During use, the data analysis and extraction module receives the results of the data analysis and extraction module. After the results of the block are obtained, the original data recovery module 71 can flexibly restore the original data according to specific needs, providing more possibilities for subsequent processing. The data enhancement submodule 72 enhances the data by adding noise and other methods, enriching the diversity of the data. The data aggregation submodule 73 aggregates and summarizes the data to achieve data simplification and generalization. The data fusion submodule 74 fuses multi-source data for comprehensive processing to mine more comprehensive information. The data smoothing submodule 75 smoothes the data, removes burrs, and improves the quality of the data. The submodules work together to process the data comprehensively and finely, and finally pass the processed data to the data visualization module, which is fully prepared for the intuitive display and in-depth understanding of the data, effectively improving the data processing efficiency and application value of the entire system.

[0035] See also Figure 8The data visualization module 8 includes a graphics drawing submodule 81, a color mapping submodule 82, a coordinate axis configuration submodule 83, a label adding submodule 84 and an interactive response submodule 85. The graphics drawing submodule 81, the color mapping submodule 82, the coordinate axis configuration submodule 83, the label adding submodule 84 and the interactive response submodule 85 are all electrically connected to the central controller 1. The data visualization module 8 is used to receive data from the data restoration and secondary processing module. The graphics drawing submodule 81 draws graphics, the color mapping submodule 82 performs color configuration, the coordinate axis configuration submodule 83 sets the coordinate axis, the label adding submodule 84 adds labels, and the interactive response submodule 85 processes user interactions, and together display intuitive visualization effects for users. After receiving data After restoring and processing the data of the secondary processing module, the graphics drawing submodule 81 can accurately draw various graphics and clearly present the shape of the data. The color mapping submodule 82 highlights the characteristics and differences of the data through clever color configuration. The coordinate axis configuration submodule 83 reasonably sets the coordinate axis to ensure that the display of the data has accurate measurement and proportion. The annotation adding submodule 84 adds clear and concise annotations to the graphics to enhance the readability of the data. The interactive response submodule 85 can promptly handle the user's interactive operations, such as zooming and panning, so that users can explore the data in depth from different angles. These submodules cooperate with each other to create intuitive, vivid, easy-to-understand and easy-to-operate visualization effects for users, greatly enhancing the user's perception and analysis capabilities of data.

[0036] See also Fig. 9The data storage module 9 includes a database management submodule 91, a data writing submodule 92, an index updating submodule 93, a data backup submodule 94 and a data recovery submodule 95. The database management submodule 91, the data writing submodule 92, the index updating submodule 93, the data backup submodule 94 and the data recovery submodule 95 are electrically connected to the central controller 1. The data storage module 9 is used to receive data from other modules. The database management submodule 91 manages the database, the data writing submodule 92 writes data to the storage medium, the index updating submodule 93 updates the index, the data backup submodule 94 performs a backup operation, and the data recovery submodule 95 restores data when needed. The data storage module is electrically connected to the central controller 1, ensuring uniformity and Effective control can receive data from other modules and realize centralized management of data. The database management submodule 91 manages the database comprehensively to ensure stable operation and efficient performance of the database. The data writing submodule 92 writes data accurately to the storage medium to ensure data storage security. The index updating submodule 93 updates the index in time to improve the efficiency of data query. The data backup submodule 94 performs backup operations regularly to effectively prevent data loss. The data recovery submodule 95 can quickly restore data when needed to ensure business continuity and data availability. The submodules work together to build a reliable, efficient and well-recoverable data storage system, which provides a solid foundation for data preservation and utilization of the entire system.

[0037] The algorithm for recursively calculating the Fibonacci sequence is: Fn=F(n-1)+Fn-2, where F0=0, F1=1; the data visualization module 8 adopts a map projection algorithm, such as Mercator projection, and the specific calculation formula is: x=λ-λ0, y=ln(tan(φ / 2)+sec(φ) / 2), where λ is longitude, λ0 is the central meridian longitude, and φ is latitude. The present invention does not limit the specific algorithms used in each module, for example, it does not limit the data cleaning method, data screening method or data integration method used in the data preprocessing module.

[0038] The working principle of the present invention is: in power grid planning, the data acquisition module 2 can accurately and efficiently obtain the original data through the coordinated work of the device driver submodule 21, the data sampling submodule 22, etc., avoiding the errors and inconsistencies of manual collection. The data cleaning, screening, integration and other submodules in the data preprocessing module 3 can effectively process the collected data, remove invalid and erroneous data, integrate multi-source data, extract meaningful features and standardize them, and solve the problem that the data is scattered and chaotic and difficult to integrate and analyze. The search tree construction module 4 and its submodules jointly construct an efficient search tree structure, which improves the efficiency of data search and processing. The different traversal modes and control submodules of the traversal and recursive execution module 5 can comprehensively and accurately obtain data information according to needs. The data analysis and extraction module 6 can obtain the data information through the data analysis and extraction module 6. Through the collaboration of various sub-modules, the value of data is deeply excavated, the in-depth application of data is realized, and strong support is provided for planning. The data restoration and secondary processing module can restore, enhance, aggregate and process the data according to the needs to meet the needs of different scenarios. The data visualization module 8 displays complex data to planners in an intuitive and clear manner through sub-modules such as graphics drawing and color mapping, so that they can intuitively understand and grasp the overall architecture and development trend of the power grid. Finally, the data storage module ensures the safe storage, efficient query, reliable backup and recovery of data through sub-modules such as database management and data writing. In summary, the system has significantly improved the efficiency and scientificity of power grid planning through the close cooperation and collaborative work of various modules and their sub-modules, and solved many technical defects in traditional methods.

Claims

1. A distribution network GIS data full-volume analysis system based on a search tree, characterized in that: The system comprises a central controller (1), a data acquisition module (2), a data preprocessing module (3), a search tree construction module (4), a traversal and recursive execution module (5), a data analysis and extraction module (6), a power supply module (10), a data restoration and secondary processing module (7), a data visualization module (8) and a data storage module (9), wherein the power supply module (10) is used to supply power to the central controller (1), the power supply module (10) and the central controller (1) are electrically connected, and the data acquisition module (2), the data preprocessing module (3), the search tree construction module (4), the traversal and recursive execution module (5), the data analysis and extraction module (6), the data restoration and secondary processing module (7), the data visualization module (8) and the data storage module (9) are all electrically connected to the central controller (1); The central controller (1) is used to manage other modules, the data acquisition module (2) is used to obtain raw data, the data preprocessing module (3) is used to perform preprocessing operations on the raw data, the search tree construction module (4) is used to construct a search tree based on the data after the preprocessing operation, the traversal and recursive execution module (5) is used to perform data search on the search tree according to the search requirements to obtain data search results, the data analysis and extraction module (6) is used to perform data analysis and data extraction on the data search results, the data restoration and secondary processing module (7) is used to restore and / or secondary processing operations on the data analysis results and the data extraction results, the data visualization module (8) is used to perform visual display operations based on the data restoration results and / or the data secondary processing results, and the data storage module (9) is used to store the output data results of other modules, and the other modules include at least one of the following: a data acquisition module (2), a data preprocessing module (3), a search tree construction module (4), a traversal and recursive execution module (5), a data analysis and extraction module (6), a data restoration and secondary processing module (7) and a data visualization module (8).

2. A distribution network GIS data full-volume analysis system based on a search tree according to claim 1, characterized in that: The data acquisition module (2) comprises a device driving submodule (21), a data sampling submodule (22), and a data buffering submodule (23); the data buffering submodule (23) is signal-connected to the data sampling submodule (22), and the data buffering submodule (23) is electrically connected to the data driving submodule (21); The device driver submodule (21) is used to provide a driver for the hardware device communication operation of other submodules in the data acquisition module (2), the data sampling submodule (22) is used to collect raw data according to set rules, and the data buffer submodule (23) is used to temporarily store raw data.

3. A distribution network GIS data full-volume parsing system based on a search tree according to claim 2, characterized in that: The data acquisition module (2) further comprises a data format conversion submodule (24) and a data transmission submodule (25), wherein the data format conversion submodule (24) is electrically connected to the data sampling submodule (22) and the device driving submodule (21), and the data buffer submodule (23) is signal-connected to the data sampling submodule (22) via the data transmission submodule (25); The device driver submodule (21) is used to drive the hardware devices of the data sampling submodule (22), the data buffer submodule (23) and the data format conversion submodule (24) to communicate and operate to obtain original data; the format conversion submodule (24) is used to perform a unified conversion operation on original data of different formats, and the data transmission submodule (25) is used for data transmission operations between the submodules.

4. A distribution network GIS data full-volume analysis system based on a search tree according to claim 3, characterized in that: The data preprocessing module (3) comprises a data cleaning submodule (31), a data screening submodule (32), a data integration submodule (33), a data standardization submodule (34) and a feature engineering submodule (35); the data cleaning submodule (31), the data screening submodule (32), the data integration submodule (33) and the feature engineering submodule (35) are connected by signals through the data transmission submodule (25), the data standardization submodule (34) and the data acquisition module (2); the data cleaning submodule (31), the data screening submodule (32), the data integration submodule (33) and the feature engineering submodule (35) are electrically connected to the central controller (1); The data cleaning submodule (31) is used to remove noise, errors and duplicate data from the original data collected by the data collection module (2); the data screening submodule (32) is used to screen out valid data according to specific conditions; the data integration submodule (33) is used to integrate the data; the data standardization submodule (34) is used to standardize the data to a specific range; and the feature engineering submodule (35) is used to extract and construct effective features.

5. A distribution network GIS data full-volume analysis system based on a search tree according to claim 4, characterized in that: The search tree construction module (4) comprises a node generation submodule (41), an edge generation submodule (42), a balance adjustment submodule (43), a tree structure optimization submodule (44) and an index establishment submodule (45), and the node generation submodule (41), the edge generation submodule (42), the balance adjustment submodule (43), the tree structure optimization submodule (44) and the index establishment submodule (45) are all electrically connected to the central controller (1); The node generation submodule (41) is used to create nodes of the search tree, the edge generation submodule (42) is used to establish connecting edges between nodes, the balance adjustment submodule (43) is used to adjust the balance of the search tree, the tree structure optimization submodule (44) is used to optimize the structure of the search tree, and the index establishment submodule (45) is used to establish an index for the search tree.

6. A distribution network GIS data full-volume analysis system based on search tree according to claim 1, characterized in that: The traversal and recursive execution module (5) comprises a depth-first traversal submodule (51), a breadth-first traversal submodule (52), a random traversal submodule (53), a recursive call control submodule (54) and a traversal result processing submodule (55), wherein the depth-first traversal submodule (51), the breadth-first traversal submodule (52), the random traversal submodule (53), the recursive call control submodule (54) and the traversal result processing submodule (55) are all electrically connected to the central controller (1). The depth-first traversal submodule (51) is used to traverse the search tree according to the depth-first traversal requirement, the breadth-first traversal submodule (52) is used to traverse the search tree according to the breadth-first traversal requirement, the random traversal submodule (53) is used to traverse the search tree according to the random traversal requirement, the recursive call control submodule (54) is used to control the depth of recursion, and the traversal result processing submodule (55) is used to process the traversal results output by other submodules and pass the processed traversal results to the data analysis and extraction module (6).

7. A distribution network GIS data full-volume analysis system based on a search tree according to claim 1, characterized in that: The data analysis and extraction module (6) comprises a data statistics submodule (61), a pattern recognition submodule (62), a correlation analysis submodule (63), a classification and prediction submodule (64) and an anomaly detection submodule (65), and the data statistics submodule (61), the pattern recognition submodule (62), the correlation analysis submodule (63), the classification and prediction submodule (64) and the anomaly detection submodule (65) are electrically connected to the central controller (1); The data analysis and extraction module (6) is used to receive the results output by the traversal and recursive execution module (5) to perform data analysis and data extraction, the data statistics submodule (61) is used to calculate statistics based on the traversal results, the pattern recognition submodule (62) is used to determine the data pattern and data regularity based on the traversal results, the association analysis submodule (63) is used to determine the data association relationship based on the traversal results, the classification and prediction submodule (64) is used to determine the data classification and data prediction results based on the traversal results, the anomaly detection submodule (65) is used to determine the abnormal value and abnormal pattern based on the traversal results, and the data analysis and extraction module (6) transmits the data processing results of each submodule to the data restoration and secondary processing module (7).

8. The distribution network GIS data full-volume analysis system based on search tree according to claim 1 is characterized in that: The data restoration and secondary processing module (7) comprises an original data recovery module (71), a data enhancement submodule (72), a data aggregation submodule (73), a data fusion submodule (74) and a data smoothing submodule (75), and the original data recovery module (71), the data enhancement submodule (72), the data aggregation submodule (73), the data fusion submodule (74) and the data smoothing submodule (75) are electrically connected to the central controller (1); The data restoration and secondary processing module (7) is used to receive the data analysis results and data extraction results output by the data analysis and extraction module (6), and to restore and / or perform secondary processing operations on the data analysis results and data extraction results; the original data recovery module (71) is used to restore the original data according to the data analysis results and data extraction results; the data enhancement submodule (72) is used to enhance the data by adding noise; the data aggregation submodule (73) is used to aggregate and summarize the data; the data fusion submodule (74) is used to fuse multi-source data; the data smoothing submodule (75) is used to smooth the data; and the data restoration and secondary processing module (7) transmits the data processing results of each module to the data visualization module (8).

9. A distribution network GIS data full-volume analysis system based on a search tree according to claim 8, characterized in that: The data visualization module (8) comprises a graphics drawing submodule (81), a color mapping submodule (82), a coordinate axis configuration submodule (83), a label adding submodule (84) and an interactive response submodule (85), and the graphics drawing submodule (81), the color mapping submodule (82), the coordinate axis configuration submodule (83), the label adding submodule (84) and the interactive response submodule (85) are all electrically connected to the central controller (1); The data visualization module (8) is used to receive data from the data restoration and secondary processing module (7), the graphics drawing submodule (81) is used to draw graphics, the color mapping submodule (82) is used to perform color configuration, the coordinate axis configuration submodule (83) is used to set the coordinate axis, the annotation adding submodule (84) is used to add annotations, and the interactive response submodule (85) is used to process user interaction information and perform visual display to the user.

10. A distribution network GIS data full-volume analysis system based on a search tree according to claim 9, characterized in that: The data storage module (9) comprises a database management submodule (91), a data writing submodule (92), an index updating submodule (93), a data backup submodule (94) and a data recovery submodule (95); the database management submodule (91), the data writing submodule (92), the index updating submodule (93), the data backup submodule (94) and the data recovery submodule (95) are electrically connected to the central controller (1); The data storage module (9) is used to receive and store data from other modules, and the other modules include at least one of the following modules: a traversal and recursive execution module (5), a data analysis and extraction module (6), a data restoration and secondary processing module (7) and a data visualization module (8); the database management submodule (91) is used to manage the database for data storage; the data writing submodule (92) is used to write the stored data into a storage medium; the index updating submodule (93) is used to update the index; the data backup submodule (94) is used to back up the stored data; and the data recovery submodule (95) is used to recover the data.

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