Underground pipeline big data visualization system and method

Abstract

The embodiment of the invention provides an underground pipeline big data visualization system, and the system comprises an underground pipeline data collection module which is used for collecting original data needed for forming an underground pipeline digital map; the data processing module is used for storing the data and performing spatial conversion processing on the original data to obtain available data with consistent spatial geolocation reference and unified data logic; the underground pipeline digital map modeling module is used for carrying out grid division on a geographic area; carrying out partition modeling based on available data in each grid, and generating a subregional underground pipeline digital map; the big data visualization module is used for receiving the underground pipeline digital maps of the sub-regions and combining the underground pipeline digital maps to form a complete underground pipeline digital map; and the data is displayed at the visualization terminal, so that the visualization of the underground pipeline is realized. The underground pipeline data can be displayed more visually, a user can obtain information more simply and conveniently, and user experience is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of big data visualization technology, and in particular to an underground pipeline big data visualization system and method. Background Art

[0002] Big data is a resource-driven development that contributes to the better development of people's lives in the information age. Underground pipelines, as essential fluid and information transport media, are crucial to every aspect of urban production and life. Existing traditional underground pipeline management relies heavily on traditional surveying and mapping data and engineering drawings. This is compounded by the lack of standardized data formats used for geological surveys, pipeline design, pipeline installation, and big data monitoring and management, making unified management of underground pipelines difficult. Furthermore, traditional underground pipeline displays often utilize two-dimensional drawings, which place high demands on users when searching for information, making detailed information difficult to obtain. Summary of the Invention

[0003] The embodiments of the present disclosure provide an underground pipeline big data visualization system and method to solve the problems of inconsistent data formats and difficulty for users to obtain information.

[0004] Based on the above problems, in the first aspect, a big data visualization system for underground pipelines is provided, comprising:

[0005] Underground pipeline data acquisition module, used to collect the original data required to form the underground pipeline digital map;

[0006] A data processing module is used to store data and perform spatial conversion processing on the original data to obtain usable data with consistent spatial geographic positioning benchmarks and unified data logic;

[0007] An underground pipeline digital map modeling module is used to divide the geographical area into grids; and based on the available data in each grid, a partition model is generated to generate a regional underground pipeline digital map;

[0008] The big data visualization module is used to receive the digital maps of underground pipelines in the sub-regions and combine them to form a complete digital map of underground pipelines; and display it on a visualization terminal to realize the visualization of underground pipelines.

[0009] In combination with the first aspect, in a possible implementation, the data processing module is used to store the raw data in a database, and perform spatial conversion processing on the raw data through the database; the database includes: a structured database and an unstructured database; wherein the structured database is used to store geographic location coordinates representing geological conditions, underground pipeline locations, and monitoring device locations; the unstructured database is used to store physical quantities monitored by the monitoring device.

[0010] In combination with the first aspect, in a possible implementation, the underground pipeline digital map modeling module is used to: generate a three-layer model of a ground remote sensing image model, a point cloud model, and an oblique image model based on the available data; and fuse the three-layer model to form a composite model; based on the geographic location coordinates of the underground pipeline and the monitoring device in the available data, embed the underground pipeline and the monitoring device into the composite model to generate a regional digital map of the underground pipeline.

[0011] In combination with the first aspect, in one possible implementation, the big data visualization module is used to: visualize the digital map of the underground pipeline and the physical quantities monitored by the monitoring device at the coordinates retrieved according to the geographic location coordinates on the visualization terminal; and / or allow reversible addition and / or removal of data.

[0012] In combination with the first aspect, in a possible implementation, the data transceiver module is used to receive a data transmission request issued by a mobile terminal, and encrypt the data according to the data transmission request and send it to the mobile terminal, so that the mobile terminal decrypts, restores and displays the encrypted data to achieve visualization.

[0013] In combination with the first aspect, in a possible implementation, the data transceiver module is used to: determine the geographic coordinate system E of the geographic area divided by the grid, determine the reference plane passing through the origin of the coordinate system and the smooth surface whose projection on the reference plane completely covers the reference plane in the digital map of the underground pipeline in the sub-region, and divide the smooth surface into multiple regions; wherein the reference plane is the XOY plane in the geographic coordinate system E with the origin as O or other planes parallel to the XOY plane; the smooth surface is the reference plane or other planes parallel to the XOY plane; based on the geographic coordinate system E, determine the geographic location coordinates of the data transmission request; based on the data transmission request, use the geographic location coordinates and the request time τ as parameters to generate an encryption matrix in the multiple regions using a multi-parameter dynamic random number generation algorithm; use the encryption matrix to encrypt the digital map of the underground pipeline in the sub-region to generate first-level encrypted data, and generate an offset matrix; use the offset matrix to perform second-level encryption on the first-level encrypted data and generate a second-level encrypted map to transmit to the mobile terminal.

[0014] In a second aspect, a method for generating an underground pipeline big data visualization system is provided, comprising: collecting raw data required to form a digital map of underground pipelines; storing the data and performing spatial conversion processing on the raw data to obtain usable data with consistent spatial geographic positioning benchmarks and unified data logic; gridding the geographical area; and generating regional digital maps of underground pipelines based on partition modeling of the usable data within each grid; combining the regional digital maps of underground pipelines to form a complete digital map of underground pipelines; and displaying the map on a visualization terminal to achieve visualization of underground pipelines.

[0015] In combination with the second aspect, in one possible implementation, collecting the raw data required to form a digital map of underground pipelines includes: storing the raw data in a database, and performing spatial conversion processing on the raw data through the database; the database includes: a structured database and an unstructured database; wherein the structured database is used to store geographic location coordinates representing geological conditions, underground pipeline locations, and monitoring device locations; and the unstructured database is used to store physical quantities monitored by the monitoring device.

[0016] In combination with the second aspect, in a possible implementation, the partition modeling based on the available data in each grid includes: generating a three-layer model of a ground remote sensing image model, a point cloud model, and an oblique image model based on the available data; and fusing the three-layer model to form a composite model; based on the geographic location coordinates of the underground pipelines and monitoring devices in the available data, embedding the underground pipelines and monitoring devices into the composite model to generate a regional digital map of the underground pipelines.

[0017] In conjunction with the second aspect, in a possible implementation, the method for generating an underground pipeline big data visualization system further includes:

[0018] Receive a data transmission request from a mobile terminal, encrypt the data according to the data transmission request and send it to the mobile terminal, so that the mobile terminal decrypts, restores and displays the encrypted data to achieve visualization.

[0019] A third aspect provides an underground pipeline big data visualization system, characterized by comprising: at least one server and a visualization terminal;

[0020] The at least one server is configured to collect raw data required to form a digital map of underground pipelines; store the data and perform spatial conversion processing on the raw data to obtain usable data with consistent spatial geographic positioning references and unified data logic; divide the geographical area into grids; and generate a digital map of underground pipelines for each region based on the partition modeling of the usable data within each grid, and transmit the generated digital map to the visualization terminal;

[0021] The visualization terminal is used to combine the digital maps of underground pipelines in the sub-regions to form a complete digital map of underground pipelines and display it, thereby realizing visualization of underground pipelines.

[0022] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method for generating an underground pipeline big data visualization system as described in the second aspect are executed.

[0023] The beneficial effects of the embodiments of the present disclosure include:

[0024] The present disclosure provides an underground pipeline big data visualization system, including: an underground pipeline data acquisition module, which is used to collect the original data required to form an underground pipeline digital map; a data processing module, which is used to store data and perform spatial conversion processing on the original data to obtain usable data with consistent spatial geographic positioning benchmarks and unified data logic; an underground pipeline digital map modeling module, which is used to grid the geographical area; and based on the available data in each grid, partition modeling is performed to generate a digital map of underground pipelines in each region; a big data visualization module is used to receive the digital maps of underground pipelines in each region and combine them to form a complete digital map of underground pipelines; and display them on a visualization terminal to realize the visualization of underground pipelines. The underground pipeline big data visualization system provided by the embodiment of the present disclosure uses big data technology to adopt a grid processing method to perform partition modeling, and displays the established model on a visualization terminal to realize the visualization of underground pipelines, so that users can understand the arrangement and status of underground pipelines more intuitively and clearly, thereby improving user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A schematic diagram of an underground pipeline big data visualization system provided by an embodiment of the present disclosure;

[0026] Figure 2 A hierarchical schematic diagram of an underground pipeline big data visualization system provided by an embodiment of the present disclosure;

[0027] Figure 3 A schematic diagram of the storage and transmission of data within the system provided by the embodiment of the present disclosure;

[0028] Figure 4 A flowchart for establishing a database provided in an embodiment of the present disclosure;

[0029] Figure 5 A schematic diagram of composite model fusion provided in an embodiment of the present disclosure;

[0030] Figure 6 A schematic diagram of a method for visualizing underground pipeline big data provided by an embodiment of the present disclosure;

[0031] Figure 7 A schematic diagram of the overall layout of the data gridding and server, data transceiver module, and underground pipeline digital map modeling module provided in the embodiment of the present disclosure;

[0032] Figure 8 A pipeline fusion digital schematic map that only retains the remote sensing image layer provided in an embodiment of the present disclosure;

[0033] Figure 9 The encryption effect diagram provided by the embodiment of the present disclosure adopts the encryption matrix size (512*630) on the smooth surface of the Beijing geographical range;

[0034] Figure 10a The command k provided in the embodiment of the present disclosure D =1801: Part of the encrypted matrix diagram;

[0035] Figure 10b A partial (128*128) top view of an encrypted matrix diagram in Matlab provided in an embodiment of the present disclosure;

[0036] Figure 10c The encrypted matrix diagram (128*128) from a top view at the same location and time on the second day provided by the embodiment of the present disclosure;

[0037] Figure 11 The first and second level encryption provided by the embodiment of the present disclosure and the use of the additional code A=0.6 to obtain the final encrypted composite model M f process maps;

[0038] Figure 12a One of the details of the partial comparison between the encrypted data and the original data provided in the embodiment of the present disclosure;

[0039] Figure 12b This is the second detail of the partial comparison between the encrypted data and the original data provided in the embodiment of the present disclosure. DETAILED DESCRIPTION

[0040] The present disclosure provides an underground pipeline big data visualization system. Preferred embodiments of the present disclosure are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are intended only to illustrate and explain the present disclosure and are not intended to limit the present disclosure. Furthermore, the embodiments and features within the embodiments of the present disclosure may be combined with one another unless there is a conflict.

[0041] The present disclosure provides an underground pipeline big data visualization system. Figure 1 Shown, including:

[0042] The underground pipeline data acquisition module 101 is used to acquire the raw data required to form the underground pipeline digital map;

[0043] The data processing module 102 is used to store data and perform spatial conversion processing on the original data obtained in 101 to obtain usable data with consistent spatial geographic positioning benchmarks and unified data logic;

[0044] The underground pipeline digital map modeling module 103 is used to divide the geographical area into grids; and based on the available data obtained in 102 in each grid, the zoning modeling is performed to generate a digital map of the underground pipelines in each region;

[0045] The big data visualization module 104 is used to receive the regional underground pipeline digital maps obtained in 103 and combine them to form a complete underground pipeline digital map; and display it on the visualization terminal to realize the visualization of the underground pipeline.

[0046] The underground pipeline big data visualization system provided by the embodiments of the present disclosure can use big data technology to generate a visualized digital map of underground pipelines. The system can more intuitively display the distribution of underground pipelines and the physical quantities monitored by monitoring devices within the pipelines. During implementation, a variety of data needs to be collected, including:

[0047] The underground pipeline big data visualization system in this embodiment adopts a layered design, such as Figure 2 As shown, it is divided into 7 layers, the specific contents are as follows:

[0048] Infrastructure layer: mainly includes basic hardware facilities such as servers, storage devices, network switches, hardware firewalls, monitoring facilities, etc., which play a physical support role;

[0049] Operating environment: Based on the infrastructure, one Windows host and three Linux hosts are built as the operating environment for the visualization system and applications;

[0050] Data layer: mainly includes: Storage Area Network (SAN) storage for storing shared files, such as PDF, doc / docx, and other documents; spatial databases (storing basic geographic data, professional geographic data, metadata information for image files / terrain files, etc.); non-spatial databases (storing user information, permission information, data dictionary, logs, and other attribute information); and other libraries (storing system runtime cache), providing data storage capabilities for the service layer;

[0051] Support layer: mainly includes identity authentication, permission management, data conversion, log management, cache, load balancing, Geographic Information System (GIS) engine, etc., providing software support for various applications during the operation of the entire visualization system;

[0052] Service layer: mainly includes World Wide Web (Web) feature service (WFS), Web map service including warehouse management system (WMS) service, Web map tile service (WMTS), tile map service), terrain service (publishing MPT data service, publishing 3D Tiles elevation service), 3D model service (publishing 3DML data service, publishing 3D Tiles model data service), provides data service registration and audit functions, and provides business support capabilities for the application layer;

[0053] Application layer: mainly includes seven parts of the overall system design, including data management, data quality inspection, data exchange, service management, comprehensive display, field survey and mapping app and operation and maintenance management, providing application capabilities for the user layer;

[0054] User layer: Professionals in surveying, exploration, geotechnical engineering, civil engineering, etc. access the system through browsers, clients, and mobile apps.

[0055] In the underground pipeline big data visualization system provided by the embodiment of the present disclosure, the data processing module 102 is used to store the original data in a database and perform spatial conversion processing on the original data through the database; the database includes: a structured database and an unstructured database;

[0056] In this embodiment, Figure 3 As shown, the storage and transmission of data within the system needs to go through data demand analysis, data collection, data quality inspection and storage, results library, release library and provide data services for users.

[0057] In this embodiment, the establishment method of each database is as follows Figure 4 Shown, including:

[0058] S401, data demand analysis;

[0059] S402 designs database tables and data storage organization structures based on the analysis results, and collects various source data examples;

[0060] S403: The collected data undergoes data quality inspection, data exchange, and data storage to form a data results database, including a basic database, a project database, a system management database, and metadata;

[0061] Based on the data results library, S404 derives image cache tile database, digital line map cache tile database, topographic map cache tile database, and three-dimensional data cache tile database; by assembling and configuring the raster data, vector data, three-dimensional data, metadata, spatial business data, monitoring device data, and non-spatial business data of the results library, a publishing library is formed to provide external services, including map base map data, map business layers, statistical charts, combined aggregation sets, data packages, data interfaces, etc.

[0062] In this embodiment, the problem of inconsistent data formats is solved by the data processing module 102, which is reflected in the data layer. The data layer of the visualization system is a structured database and an unstructured database. The structured database is mainly used to store spatial data such as the geographic location coordinates that represent geological conditions, underground pipeline locations, and monitoring device locations, non-spatial data such as the correspondence between the geographic location coordinates of the monitoring device and the physical quantities monitored by the monitoring device, cache data, etc.; the unstructured database is used to store basic data files such as the physical quantities monitored by the monitoring device, business data files such as data transmission history records, and document files and other file type data. Among them, the structured database can perform spatial conversion and other processing on spatial data to generate geographic location coordinates with consistent spatial geographic positioning benchmarks and unified data logic.

[0063] In this embodiment, the structured database design uses PostGIS as the data carrier, and the unstructured database uses PostgreSQL for storage.

[0064] Unstructured databases include a data information library and a data file library. The data information library stores a list of data files and related descriptive information, such as the physical quantities monitored by detection devices and their geographic coordinates. The data file library stores files by type, time, and other information, providing fast retrieval of the data information library and downloading of some files to facilitate data sharing. Different permissions can be set for different users to add, browse, and download data.

[0065] In the underground pipeline big data visualization system provided by the embodiment of the present disclosure, the underground pipeline digital map modeling module 103 is used to: generate a three-layer model of a ground remote sensing image model, a point cloud model, and an oblique image model based on available data; and fuse the three-layer model to form a composite model; and embed the underground pipeline and the monitoring device into the composite model based on the geographic location coordinates of the underground pipeline and the monitoring device in the available data to generate a regional digital map of the underground pipeline.

[0066] In this embodiment, remote sensing image technology is used in combination with the data in the partition in the available data to generate a remote sensing image model of the partition; point cloud technology is used in combination with the data in the partition in the available data to generate a point cloud model of the partition; oblique image technology is used in combination with the data in the partition in the available data to generate an oblique image model of the partition; the three-layer model is adapted to the actual geographical situation. Figure 5 As shown, the coordinate systems of the three-layer models of the remote sensing image model, the point cloud model and the oblique image model are aligned so that the origin of the coordinate system of each of the three-layer models coincides with the X-axis or the Y-axis, completing the fusion of the three-layer models to form a composite model.

[0067] In the embodiment of the present disclosure, the big data visualization module 104 is used to: visualize the digital map of the underground pipeline and the physical quantities monitored by the monitoring device at the coordinates retrieved according to the geographic location coordinates on the visualization terminal; and / or allow reversible addition and / or removal of data.

[0068] In this embodiment, the underground pipeline digital map modeling module 103 in the local underground pipeline big data visualization system can embed the detection devices arranged in the underground pipeline into the model based on their geographic coordinates, allowing the locations of various detection devices to be visualized on the underground pipeline digital map. This visualization also allows the location of the monitoring device in the pipeline to be located using its geographic coordinates, and allows for real-time reverse query of the physical quantities monitored by the monitoring device.

[0069] The underground pipeline big data visualization system provided in the embodiment of the present disclosure also includes: a data transceiver module, which is used to receive a data transmission request issued by a mobile terminal, and encrypt the data according to the data transmission request and send it to the mobile terminal, so that the mobile terminal decrypts, restores and displays the encrypted data to achieve visualization.

[0070] In this embodiment, when data anomalies occur, maintenance personnel can be dispatched to the designated area to troubleshoot. After entering the pipeline, the maintenance personnel, wearing a mobile terminal, sends a data transmission request to the visualization terminal. The visualization terminal encrypts the data and sends it to the mobile terminal, which decrypts it. This allows the maintenance personnel to more intuitively understand their location and the fault location using the visualization provided by the mobile terminal, improving maintenance efficiency.

[0071] In the embodiment of the present disclosure, the data transceiver module is used to:

[0072] P1 determines a geographic coordinate system E of a geographic area divided into a grid, determines a reference plane passing through the origin of the coordinate system and a smooth surface whose projection on the reference plane completely covers the reference plane in the digital map of the underground pipelines in the sub-region, and divides the smooth surface into a plurality of regions; wherein the reference plane is the XOY plane in the geographic coordinate system E with the origin being O, or another plane parallel to the XOY plane; and the smooth surface is the reference plane or another plane parallel to the XOY plane.

[0073] P2 determines the geographical location coordinates of the data transmission request based on the geographical coordinate system E;

[0074] P3 generates encryption matrices in the multiple regions using a multi-parameter dynamic random number generation algorithm based on the data transmission request and the geographic location coordinates and the request time τ as parameters;

[0075] P4 uses the encryption matrix to encrypt the digital map of the underground pipelines in the sub-region to generate first-level encrypted data and an offset matrix; uses the offset matrix to perform second-level encryption on the first-level encrypted data and generates a second-level encrypted map to transmit to the mobile terminal.

[0076] In this embodiment, P2 specifically includes: P2-1 assumes W(τ) = r(τ)·w(τ), multi-parameter dynamic random number generation algorithm rand[x(τ), y(τ), W(τ)] = rand[x(τ), y(τ), r(τ)·w(τ)]∈(-1, 1), where x(τ), y(τ) are the geographic location coordinates of the projection of the raster data layer on the smooth surface under E when requested at time τ, w(τ) is a preset parameter, for a given time τ, a given w(τ) value, and x(τ), y(τ), the generated random value is the same, r(τ) is a random number generation function that changes with time τ, and r(τ)∈(-1, 1), τ is expressed as a decimal in the form of Y.MRHMS, where Y is the year, M is the month expressed in two digits, R is the day expressed in two digits, and HMS are the two-digit hours, minutes, and seconds of the day, respectively. For example, at 0:0:01 on January 1, 2021, τ is expressed as 2021.0101000001.

[0077] Preferably, the w(τ) includes the encrypted geographic data range area R(τ), the encryption matrix width Wid(τ) and height H(τ) corresponding to the location of the requester (visual terminal or mobile terminal), the additional ID code, and the allowed offset s x (τ),s y (τ), the average length of each region projected on the reference plane Average width and a linear and / or nonlinear combination of at least one parameter in each of the two sets of parameters of the preset coordinates X0(τ) and Y0(τ) in the projection They represent linear, nonlinear, and linear and nonlinear mixed combinations, abbreviated as C1(τ), C2(τ), and C3(τ), respectively. st is a state indicator, indicating that it is empty when the parameter exists, and st=0 indicates that the parameter does not exist. x (τ),s y (τ) satisfies r is the spatial resolution of the raster data layer, k is negatively correlated with the number of regional divisions k = NC [num (τ)], num (τ) is the number of divided regions, k ∈ [1, K], K>>1, and when the number of divided regions is 1, k = K, and the number of divisions makes the average area of ​​each region projected on the reference plane qr 2 , when q∈(1,2], k=1.

[0078] It is understood that the area R(τ) of the encrypted geographic data range is determined by the size of the raster data layer at the time of the request. It can be the entire raster data layer or at least one grid portion thereof. The region where the encrypted matrix corresponds to the requested location covers at least one of the divided grids, with its range customized by the requester and belonging to the region of interest (ROI) within the encrypted geographic data range. The actual coordinate location at the time of the request can be in the region where the encrypted matrix is ​​located (e.g., near the requester) or not. The average area is the projected area of ​​the smooth surface on the reference plane divided by the number of divided regions.

[0079] After obtaining w(τ), it is stipulated that the average value of the derivative of each point on each boundary of each region in multiple regions is calculated as

[0080]

[0081] where x j (τ)→x(τ) and y j (τ)→y(τ) is defined as the distance between each point x on the boundary j (τ),y j (τ) moves in both directions of the X and Y axes to reach a pixel point adjacent to x(τ) and y(τ).

[0082] Among them, the derivative calculation of the points on the boundary of the geographical area corresponding to the projection of the multiple areas on the reference plane is calculated based on the existing X and Y direction derivatives. For example, if the geographical area is a mountainous area, and the boundary of the mountainous area is the side of a rectangle, then when the divided area is a sub-rectangle located at the corner of the rectangle, there are two boundaries at the vertex of the corresponding corner, and the derivatives at the vertex of the corner are calculated based on the existing X and Y direction derivatives. When the corner of the mountainous area boundary is a non-rectangular corner, the midpoint of the boundary length is used as the boundary to divide it into two boundaries and calculate the existing X and Y direction derivatives. At this time, the corner sub-area is still at most eight at time τ. and parameter.

[0083] At time τ, P2-2 selects C g (τ) and NC, constantly changing s x (τ),s y (τ), X o (τ), Y o (τ), get the k value k D =NC[num D (τ)] so that on the boundary b among the plurality of regions

[0084]

[0085]

[0086] Both exist, and |s x (τ)+k D rand[x(τ),y(τ),W(τ)]| [x(τ),y(τ)]∈R |∈(2|r|,2k D |r|],|s y (τ)+k D rand[x(τ),y(τ),W(τ)]| [x(τ),y(τ)]∈R |∈(2|r|,2k D |r|], thus obtaining the intermediate value W proc (τ), and then calculate the average value of the derivatives of p points on each boundary of each region in multiple regions b j is a point on the boundary b, and W proc (τ)=r(τ)·w proc (τ)=r(τ)·C g proc (τ);

[0087] P2-3 calculations x 、sy 、 Xo, Yo, τ, the requester's location coordinates x ap (τ) and y ap (τ), and all partitioned regions and combination of Form an encryption matrix JM(τ)=k D rand[x(τ),y(τ),w D ],in Also for linear and / or nonlinear combinations, G = 11, 22, 33 represent linear, nonlinear, and linear and nonlinear mixed combinations, respectively, abbreviated as and and

[0088] Preferably, r(τ)=rand[x(τ),y(τ),w(τ)], then Therefore, the value of W(τ) at different times is also changing.

[0089] It should be understood that the coordinates x(τ) and y(τ) used in the calculation of the limit or limit sum above refer to the coordinates of the point on the partition boundary b, and not necessarily the location at the time of the request. The coordinates x and y in the encryption matrix, as defined by the multi-parameter dynamic random number generation algorithm, represent the user's location at the time of the request. There are actually eight times as many parameters as the partition area involved in the combination. In order to make the writing concise, no additional subscripts are used here to indicate the average values ​​of the derivatives of different partition areas.

[0090] It can be understood that, on the one hand, the parameter w(τ) is different, including smooth surface, s x ,s y ,X o ,Y o ,C1,C2,C3, p, The changes in these parameters cause different w(τ), and also include the w generated by user requests at different locations at the same time. D Different, the same location user at different request time τ, these factors will cause w(τ) to change; on the other hand, under the conditions of offset constraint, boundary constraint and R domain constraint, for any request time τ, due to Therefore, these two factors cause the encryption matrix JM(τ) to change with w(τ) and k, which increases the difficulty of cracking the dynamic change of the encryption matrix JM(τ). The change of k also means that s x (τ),sy The range of (τ) is changed accordingly. Among them, the negative correlation function NC is the independent variable, and X o (τ), Y o (τ) is the independent variable, the encryption matrix width Wid(τ) and height H(τ) are the request variables, the rectangular area R of the mountain area is the amount preset by the requester, p∈[1,+∞) is the independent variable, and and As p changes, the selected smooth surface is also an independent variable. When the function form of rand[x(τ), y(τ), W(τ)] itself is different, the calculation results are also different. Therefore, rand[x(τ), y(τ), W(τ)] itself is an independent variable, and the combination w(τ)=C g (τ), g = 1, 2, 3 and There are three independent variables, τ, the requester's location coordinates x ap (τ) and y ap (τ) is also an independent variable.

[0091] Therefore, for a given R(τ), Wid(τ), H(τ) and ID code, the set of independent variables in the method is There are actually 19 independent variables, the set of variables required to decrypt the code There are 23 variables, and considering and The construction of the encryption matrix requires all the parameter sets There are 23+8mun parameters. The encryption matrix generation depends on a maximum of 23+8mun parameters. Adjusting any parameter will cause the random encryption value of the encryption matrix to change. The encryption matrix has a very high resistance to decryption.

[0092] The encryption matrix can be adjusted through parameters to control the detail changes of the encryption matrix, ensuring that the encryption matrix has quite rich detail changes. The finer the area is divided, the less important it is to meet the requirements of internal smoothness. Because on the one hand, the finer the division, the closer the internal size is to the resolution, the less visually perceptible the distortion; on the other hand, the finer the division, the more boundaries there are, and the more the distortion depends on whether the boundaries are smooth. Moreover, at this time, since k is close to 1 and the absolute value of rand[x(τ), y(τ), W(τ)] is less than 1, the internal offset is always guaranteed to be below the resolution, so the smoothness is not greatly affected. If the number of divisions decreases, the internal offset may be larger, but at this time, due to the large area of ​​the region, the offset and distortion may still be reasonable visually. However, if it is considered unreasonable visually at this time, you can also choose a suitable s in the second-level encryption process. x (τ),s y (τ) to adjust the offset.

[0093] When the division is coarser, since the internal area itself is smoothed by the smooth surface, even if the k times rand[x(τ), y(τ), W(τ)] offset is generated after the first level encryption and the second level encryption is generated after the second level encryption, the internal area is smoothed. Due to the negative correlation, although k is large and the absolute value of rand[x(τ), y(τ), W(τ)] is less than 1, the encryption matrix may also be large, but a small offset can still be selected in the secondary encryption (i.e., according to s x (τ),s y (τ) selection) thus ensuring that the overall smoothness is not greatly affected, and at this time as long as the boundary is smooth, the encrypted matrix can be considered smooth.

[0094] Therefore, in summary, the present invention only chooses to calculate the directional derivatives of X and Y on the important boundaries. If they exist, they are considered smooth or the appropriate s is selected in the second level encryption process. x (τ),s y (τ) is used to adjust the offset to obtain a satisfactory smoothness, which greatly reduces the amount of calculation.

[0095] It should be emphasized that if the random number of rand[x(τ), y(τ), W(τ)] is very small (of course, its probability is also small), the smoothness of the region is even less affected. Although this may make the first-level encryption offset smaller than the resolution, or the encryption matrix may still be relatively large, it is still possible to choose a suitable s in the second-level encryption process. x (τ),s y (τ) ensures that the digital image can produce appropriate offset and distortion.

[0096] P3 specifically includes:

[0097] P3-1 is the coordinate of the raster data layer (for the sake of simplicity, it is uniformly described as [X1(τ), Y1(τ)]) and the location coordinate of the requester [x ap (τ),y ap (τ)] is encrypted by projection on the reference plane or smooth surface

[0098] P3-2 will and Superimpose to obtain first-level encrypted data Then the offset matrix And now the coordinate system E becomes E (1) ;

[0099] It should be understood that at this time, the smooth surface is also encrypted to form a first-level encrypted smooth surface.

[0100] P3-3 translates the composite model before encryption together with the coordinate system E so that E and E (1) The data on the smooth surface are overlapped and deleted to form a first-level encrypted composite model M1.

[0101] P4 specifically includes:

[0102] P4-1 uses the offset matrix M s The first-level encrypted data J1 is encrypted at the second level to generate the second-level encrypted data And now the coordinate system E becomes E (2) ;

[0103] It should be understood that the smooth surface of the first level encryption is also encrypted at the second level, forming a second level encryption smooth surface. When the first level encryption produces an undesirable offset, it can still be adjusted in the second level encryption process. x (τ),s y (τ) (and thus JM(τ) also changes) to ensure that the digital image can produce appropriate offset and distortion.

[0104] P4-2 The first-level encrypted composite model M1 together with the coordinate system E (1) Translate together so that the coordinate system E (1) With E (2) Overlap and delete the data on the first-level encrypted smooth surface to form a second-level encrypted composite model M2;

[0105] P4-3 preset additional code A∈(0,1), calculate E (2) With E (1) The length of the line segment between the coordinate origins under E is L, and the secondary encrypted composite model M2 is connected with the coordinate system E on the line segment. (2) Translate together by distance AL so that E (2) The coordinate origin is close to E (1) The coordinate origin of the final encrypted composite model M f ;

[0106] P4-4 If M1, M2, M f 、M f If the offset in the encrypted matrix area corresponding to the position of the requester is within the preset range, at least one of them is transmitted to the requester. If all of them are not within the preset range, the encryption step is repeated until the obtained M1, M2, M f 、M f At least one offset of the encryption matrix area corresponding to the position of the requester satisfies a preset range, and then at least one of the at least one is selected and transmitted to the requester.

[0107] After introducing the additional code A∈(0), the set of independent variables in the method becomes There are actually 20 independent variables, and the set of variables required to decrypt the code becomes There are 24 variables, and considering and Then the set of all parameters needed to construct the encryption matrix becomes There are 24+8mun parameters.

[0108] It is understandable that the additional code is another way to adjust the offset.

[0109] In this embodiment, a data encryption and transmission method based on a multi-parameter dynamic adjustment encryption matrix of a data transmission request is adopted, which improves the resistance of data to reverse decryption during transmission with more variable parameters, making the data transmission of the local pipeline big data visualization system more secure and reliable.

[0110] The present disclosure provides a method for generating an underground pipeline big data visualization system. Figure 6 Shown, including:

[0111] S601, collecting raw data required to form a digital map of underground pipelines;

[0112] S602, storing the data and performing spatial conversion processing on the original data to obtain usable data with consistent spatial geographic positioning reference and unified data logic;

[0113] S603, dividing the geographical area into grids; and generating a digital map of underground pipelines in each region by partitioning modeling based on the available data in each grid;

[0114] S604: Combine the digital maps of underground pipelines in the sub-regions to form a complete digital map of underground pipelines; and display the map on a visualization terminal to achieve visualization of underground pipelines.

[0115] In the embodiment of the present disclosure, collecting the raw data required to form a digital map of underground pipelines includes: storing the raw data in a database and performing spatial conversion processing on the raw data through the database; the database includes: a structured database and an unstructured database; wherein the structured database is used to store geographic location coordinates representing geological conditions, underground pipeline locations and monitoring device locations; and the unstructured database is used to store physical quantities monitored by the monitoring device.

[0116] In the embodiment of the present disclosure, the partition modeling based on the available data in each grid includes: generating a three-layer model of a ground remote sensing image model, a point cloud model, and an oblique image model based on the available data; and fusing the three-layer model to form a composite model; based on the geographic location coordinates of the underground pipelines and monitoring devices in the available data, embedding the underground pipelines and monitoring devices into the composite model to generate a regional digital map of the underground pipelines.

[0117] The underground pipeline big data visualization system generation method provided in the embodiment of the present disclosure also includes: receiving a data transmission request issued by a mobile terminal, and encrypting the data according to the data transmission request and sending it to the mobile terminal, so that the mobile terminal decrypts, restores and displays the encrypted data to achieve visualization.

[0118] The embodiment of the present disclosure provides an underground pipeline big data visualization system, characterized by comprising: at least one server and a visualization terminal;

[0119] The at least one server is configured to collect raw data required to form a digital map of underground pipelines; store the data and perform spatial conversion processing on the raw data to obtain usable data with consistent spatial geographic positioning references and unified data logic; divide the geographical area into grids; and generate a digital map of underground pipelines for each region based on the partition modeling of the usable data within each grid, and transmit the generated digital map to the visualization terminal;

[0120] The visualization terminal is used to combine the digital maps of underground pipelines in the sub-regions to form a complete digital map of underground pipelines and display it, thereby realizing visualization of underground pipelines.

[0121] An embodiment of the present disclosure provides a computer-readable storage medium having a computer program stored thereon. When executed by a processor, the computer program executes the steps of the method for generating an underground pipeline big data visualization system provided in any embodiment of the present disclosure. The storage medium may be a volatile or non-volatile computer-readable storage medium.

[0122] In a preferred embodiment, Figure 6 As shown, a pipeline is gridded to form six grids A1 to A6. The visualization system includes: an underground pipeline data acquisition module 101, a data processing module 102, an underground pipeline digital map modeling module 103, a big data visualization module 104 and a data transceiver module.

[0123] At least one server receives the encrypted monitoring device data transmitted by the sensor end, loads the modeling data of the grid on the server end, and transmits it to the visualization terminal. It can be used to monitor and analyze the underground pipeline data in the grid, receive the encrypted data transmitted by the data transceiver module and decrypt the data, so that the visualization terminal can realize data and information communication.

[0124] The underground pipeline digital map modeling module 103 is used to form the data partitioning and modeling processing required for pipeline visualization, specifically including tile partitioning and modeling of pipeline basic data, pipeline engineering project data, monitoring device data and other data.

[0125] The data transceiver module, whose encryption unit corresponds to the modeling unit in each grid, Figure 7 The multiple data tile encryption unit in the grid A1-A6 is given as an example, which can be used to perform multiple data encryption on various types of pipeline data in the grid A1-A6 to form encrypted data, and transmit the encrypted data to the visualization terminal.

[0126] The multiple data tiles include a set of all pipeline data in multiple grids, and the set includes data for each grid, wherein each type of pipeline data includes basic data, engineering project data, etc.

[0127] In a preferred embodiment, a data encryption method based on a grid-based multi-parameter dynamic adjustment encryption matrix includes the following steps, taking grid A6 as an example:

[0128] S1. Determine the geographic coordinate system E of the mountain area divided by the grid (e.g. Figure 8 As shown), a fusion model is constructed using a modeling system, wherein a smooth surface having a reference plane with an origin of a coordinate system as determined by the raster data layer is divided into a plurality of regions;

[0129] S2. According to the data transmission request, a multi-parameter dynamic random number generation algorithm is set based on the geographic location coordinates and the request time τ, and encryption matrices are generated in the multiple regions based on the algorithm, so that the boundary of the encryption matrix in each region is continuous and smooth at time τ;

[0130] S3. Encrypting the grid data layer and the projection of the requester's location coordinates on the reference plane or smooth surface using an encryption matrix according to the request to form primary encrypted data, and forming an offset matrix;

[0131] S4. Performing secondary encryption on the primary encrypted data using an offset matrix to generate a secondary encrypted map, which is then transmitted to the sub-server.

[0132] Among them, S2 specifically includes the following steps:

[0133] S2-1 Assume W(τ) = r(τ)·w(τ), and the multi-parameter dynamic random number generation algorithm rand[x(τ), y(τ), W(τ)] = rand[x(τ), y(τ), r(τ)·w(τ)]∈(-1,1), where x(τ), y(τ) are the geographic location coordinates of the projection of the raster data layer on the smooth surface under E when the user requests at time τ, w(τ) is a preset parameter, and the random number is related to x(τ), y(τ), and w(τ). For a given time τ, a given w(τ) value, and x(τ), y(τ), the generated random number value is the same, r(τ) is a random number generation function that changes with time τ, and r(τ)∈(-1,1), and try to express τ as 2021.0226152600. The time parameter 2021.0226152600 is omitted in the following formulas to make the writing concise, and what is actually represented is the expression of τ=2021.0226152600 at a given time.

[0134] The area of ​​grid A6 is set to R. The location of the data transmission request corresponds to the actual width W and height H as the encryption matrix width W and height H. The allowed offset s x ,s y are all 2m. If the average length and average width of each area projected on the smooth surface are also 120m, and the preset coordinates Xo and Yo in the projection are the geometric center of each area offset to the north direction of X by one or more distances with a resolution of 2m, the additional ID code is 000000001. The w is the arithmetic sum of the above 10 data, where s x ,s y satisfy When k=180, To obtain w(τ), it is stipulated that the average value of the derivatives of three points (end points and midpoints) on each boundary of each region in multiple regions is calculated as

[0135] S2-2 Select arithmetic and combination methods and Constantly changing x (τ),s y (τ), X o (τ), Y o (τ), and obtain the k value mun D According to R and The number of divided regions ( [] represents rounding) so that on the boundary b in the plurality of regions exist, and Thus we get the middle W proc (τ) value, and then calculate the average value of the derivatives of three points (the two endpoints and the midpoint of the boundary) on each boundary of each region in multiple regions,

[0136]

[0137]

[0138] S2-3 calculations x (τ),s y (τ), X o (τ), Y o (τ), τ, the requester's location coordinates x ap (τ) and y ap (τ), and all partitioned regions and The linear combination of Forming an encryption matrix

[0139] The above algorithm obtains Figure 10a Select the area R in the mountain area A and create a three-dimensional encrypted matrix in Matlab (let k D =1801), where α is the reference plane, i.e., a region segment of the selected smooth surface. Figure 10b This is a diagram of an encrypted matrix (128*128) viewed from above in Matlab. Figure 10c This is a top-down view of the encrypted matrix (128*128) at the same location and time on the second day. It can be seen that the two encrypted matrices are completely different due to the change in time.

[0140] S3 specifically includes:

[0141] S3-1 takes the raster data layer as an example, and locates the coordinates of the raster data layer [X1(τ), Y1(τ)] and the requester's location coordinates The projection on the smooth surface, that is, the base plane itself, is encrypted.

[0142]

[0143] S3-2 will and Superimpose to obtain first-level encrypted data Then the offset matrix And now the coordinate system E becomes E (1) ;

[0144] S3-3 Figure 11Translate the original (indicated by the black box) together with the coordinate system E so that E and E (1) The data on the first-level encrypted smooth surface are overlapped and deleted to form the first-level encrypted composite model M1.

[0145] S4 specifically includes:

[0146] S4-1 uses the offset matrix M s The first-level encrypted data J1 is encrypted at the second level to generate the second-level encrypted data And now the coordinate system E becomes E (2) ;

[0147] S4-2 Figure 11 As shown, the first-level encrypted composite model M1 together with the coordinate system E (1) Translate together so that the coordinate system E (1) With E (2) Overlap and delete the data on the secondary smooth surface to form a secondary encrypted composite model M2;

[0148] S4-3 Figure 11 The preset additional code A=0.6 is shown, and E is calculated. (2) With E (1) The length of the line segment between the coordinate origins under E is L, and the secondary encrypted composite model M2 is connected with the coordinate system E on the line segment. (2) Translate together by a distance of 0.6L so that E (2) The coordinate origin is close to E (1) The coordinate origin of the final encrypted composite model M f ;

[0149] S4-4 Figure 9 This is an encryption effect diagram obtained according to this embodiment using the Beijing geographical scope and an encryption matrix size (512*630). Figure 12a and 12b for Figure 8 The comparison of local encrypted data and original data shows details. It can be seen that the encrypted data and the original data are only offset in position, while the visual distortion of the geometric shape is very small, which meets the offset requirement. f Transmit to the server or system visualization terminal.

[0150] Through the description of the above embodiments, those skilled in the art can clearly understand that the embodiments of the present disclosure can be implemented through hardware or by means of software plus a necessary general hardware platform. Based on this understanding, the technical solutions of the embodiments of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.), including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments of the present disclosure.

[0151] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of a preferred embodiment, and the modules or processes in the accompanying drawings are not necessarily required for implementing the present disclosure.

[0152] Those skilled in the art will appreciate that the modules in the devices of the embodiments may be distributed in the devices of the embodiments as described in the embodiments, or may be located in one or more devices different from the embodiments with corresponding changes. The modules of the above embodiments may be combined into one module or further split into multiple submodules.

[0153] The serial numbers of the above-mentioned embodiments of the present disclosure are for description only and do not represent the advantages or disadvantages of the embodiments.

[0154] Obviously, those skilled in the art may make various changes and modifications to the present disclosure without departing from the spirit and scope of the present disclosure. Thus, if these modifications and variations of the present disclosure fall within the scope of the claims of the present disclosure and their equivalents, the present disclosure is intended to include these modifications and variations.

Claims

1. An underground pipeline big data visualization system, characterized in that: include: Underground pipeline data acquisition module, used to collect the original data required to form the underground pipeline digital map; A data processing module is used to store data and perform spatial conversion processing on the original data to obtain usable data with consistent spatial geographic positioning benchmarks and unified data logic; Underground pipeline digital map modeling module, used to grid the geographical area; Based on the available data in each grid, a zoning model is performed to generate a digital map of underground pipelines in each region; A big data visualization module is used to receive the digital maps of underground pipelines in the sub-regions and combine them to form a complete digital map of underground pipelines; And it is displayed on the visualization terminal to realize the visualization of underground pipelines.

2. The system according to claim 1, wherein The data processing module is used to store the original data in a database and perform spatial conversion processing on the original data through the database; the database includes: a structured database and an unstructured database; The structured database is used to store geographic location coordinates representing geological conditions, underground pipeline locations, and monitoring device locations; Unstructured database, used to store physical quantities monitored by monitoring devices.

3. The system according to claim 1, wherein: The underground pipeline digital map modeling module is used to: Generate a three-layer model of a ground remote sensing image model, a point cloud model, and an oblique image model based on the available data; and fuse the three-layer model to form a composite model; Based on the geographical location coordinates of the underground pipelines and monitoring devices in the available data, the underground pipelines and monitoring devices are embedded in the composite model to generate a regional digital map of the underground pipelines.

4. The system according to claim 1, wherein The big data visualization module is used to: The digital map of the underground pipeline and the physical quantities monitored by the monitoring device at the coordinates retrieved according to the geographical location coordinates are visually displayed on the visualization terminal; and / or reversible addition and / or removal of data is allowed.

5. The system according to claim 1, wherein: Also includes: The data transceiver module is used to receive a data transmission request from a mobile terminal, encrypt the data according to the data transmission request, and send it to the mobile terminal, so that the mobile terminal decrypts, restores and displays the encrypted data to achieve visualization.

6. The system according to claim 5, wherein: The data transceiver module is used for: Determine a geographic coordinate system E of the geographic area divided by the grid, determine a reference plane passing through the origin of the coordinate system and a smooth surface whose projection on the reference plane completely covers the reference plane in the digital map of the underground pipelines in the sub-region, and divide the smooth surface into a plurality of regions; The reference plane is the XOY plane in the geographic coordinate system E with the origin O or other planes parallel to the XOY plane; the smooth surface is the reference plane or other planes parallel to the XOY plane; Determining the geographic location coordinates of the data transmission request based on the geographic coordinate system E; Based on the data transmission request, using the geographic location coordinates and the request time τ as parameters, an encryption matrix is ​​generated in the multiple areas using a multi-parameter dynamic random number generation algorithm; Encrypting the digital map of the underground pipelines in the sub-regions using the encryption matrix to generate first-level encrypted data and an offset matrix; The offset matrix is ​​used to perform secondary encryption on the primary encrypted data and generate a secondary encrypted map which is transmitted to the mobile terminal.

7. A method for generating an underground pipeline big data visualization system, characterized in that: include: Collect the raw data needed to form a digital map of underground pipelines; Storing data and performing spatial conversion processing on the original data to obtain usable data with consistent spatial geographic positioning benchmarks and unified data logic; Divide the geographical area into grids; and generate a digital map of underground pipelines in each region by partitioning the model based on the available data in each grid; Combining the digital maps of underground pipelines in the sub-regions to form a complete digital map of underground pipelines; And it is displayed on the visualization terminal to realize the visualization of underground pipelines.

8. The method according to claim 7, wherein Storing data and performing spatial conversion processing on the original data includes: Storing the original data in a database and performing spatial conversion processing on the original data through the database; the database includes: a structured database and an unstructured database; Among them, the structured database is used to store the geographical location coordinates that characterize geological conditions, underground pipeline locations, and monitoring device locations; the unstructured database is used to store the physical quantities monitored by the monitoring device.

9. The method according to claim 7, wherein Partitioning modeling based on the available data within each grid includes: Generate a three-layer model of a ground remote sensing image model, a point cloud model, and an oblique image model based on the available data; and fuse the three-layer model to form a composite model; Based on the geographical location coordinates of the underground pipelines and monitoring devices in the available data, the underground pipelines and monitoring devices are embedded in the composite model to generate a regional digital map of the underground pipelines.

10. The method according to claim 7, wherein: Also includes: Receive a data transmission request from a mobile terminal, encrypt the data according to the data transmission request and send it to the mobile terminal, so that the mobile terminal decrypts, restores and displays the encrypted data to achieve visualization.

11. An underground pipeline big data visualization system, characterized in that: include: At least one server and visualization terminal; The at least one server is used to collect raw data required to form a digital map of underground pipelines; Storing data and performing spatial conversion processing on the original data to obtain usable data with consistent spatial geographic positioning benchmarks and unified data logic; Divide the geographical area into grids; and generate a digital map of underground pipelines in each region based on the available data partition modeling in each grid, and send the map to the visualization terminal; The visualization terminal is used to combine the digital maps of underground pipelines in the sub-regions to form a complete digital map of underground pipelines and display it, thereby realizing visualization of underground pipelines.

12. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, executes the steps of the method for generating an underground pipeline big data visualization system as described in any one of claims 7 to 10.

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