Multi-source heterogeneous underground pipeline data checking method and system for scientific research community

Abstract

The application discloses a scientific research institute-oriented multi-source heterogeneous underground pipeline data checking method and system, relates to the technical field of underground pipeline surveying and mapping data processing, and comprises the following steps: positioning a map pipeline area needing to be updated through a map space index, and uploading multi-source heterogeneous data; performing verification and screening based on basic attributes to obtain effective heterogeneous data; performing standardized conversion under a pipeline facility attribute architecture, determining multi-channel data, performing threshold cascade verification and alignment fusion, and obtaining pipeline checking data; and updating the pipeline checking data to the map pipeline area and performing terminal interface display. The application solves the technical problems of single checking level, large topological space error and inability to perform hierarchical visual display of achievements of existing institute multi-source pipeline data, achieves hierarchical multi-level automatic checking and fusion of scientific research institute multi-source underground pipeline data, and improves the technical effects of data topological and spatial precision and visual display.

Description

Technical Field

[0001] This invention relates to the field of underground pipeline mapping data processing technology, specifically to a method and system for verifying multi-source heterogeneous underground pipeline data for research institutes. Background Technology

[0002] Currently, underground pipelines in research institute areas include various types such as water supply and drainage, electricity, gas, and communications. Pipeline data sources are scattered and collection standards are not uniform, resulting in a large amount of multi-source heterogeneous data. Existing pipeline verification methods mostly adopt a single attribute verification mode, lacking hierarchical cascade verification logic. This makes it impossible to simultaneously check the basic attributes of pipelines, the topological reference relationships of pipeline points, and 3D spatial collision issues. Defects such as data topological misalignment and insufficient spatial clearance are difficult to fully identify. Furthermore, various types of pipeline data are stored in a mixed manner, and the verification results cannot be presented in a hierarchical and visual manner. The workload of manual review is large and the data correction efficiency is low, making it difficult to meet the data usage needs of high-precision pipeline operation and maintenance and planning design in research institute areas.

[0003] The existing campus has technical problems such as a single verification level for multi-source pipeline data, large topological spatial errors, and the inability to display results in a layered and visual manner. Summary of the Invention

[0004] This application provides a method and system for verifying multi-source heterogeneous underground pipeline data in research institutes, which addresses the technical problems of existing multi-source pipeline data verification in research institutes, such as single-level verification, large topological spatial errors, and inability to display results in a hierarchical and visual manner.

[0005] In view of the above problems, this application provides a method and system for verifying multi-source heterogeneous underground pipeline data in research institutes.

[0006] The first aspect of this application provides a method for verifying multi-source heterogeneous underground pipeline data in research institute areas, the method comprising:

[0007] Using the map sheet spatial index, the map sheet pipeline area requiring updating is located. Multi-source heterogeneous data is uploaded, combining pipeline attribute information and pipeline connection relationships. The multi-source heterogeneous data undergoes verification and filtering based on basic attributes using a data validator with a first verification threshold to obtain valid heterogeneous data. The data validator, composed of a knowledge rule base and a forward inference mechanism, derives threshold dynamic rules through self-combination and extension of basic verification rules. Standardization transformation under the pipeline facility attribute architecture is performed on the valid heterogeneous data to determine multi-channel data. Threshold cascade verification and alignment fusion are then performed based on the second, third, and fourth verification thresholds configured with dynamic rules to obtain pipeline verification data. The multi-channel data corresponds one-to-one with the valid heterogeneous data. The pipeline verification data is then updated to the map sheet pipeline area and displayed on the terminal interface.

[0008] A second aspect of this application provides a data verification system for multi-source heterogeneous underground pipelines in research institute areas, the system comprising:

[0009] The multi-source heterogeneous data upload module is used to locate the map sheet pipeline area that needs to be updated through map sheet spatial indexing, and upload multi-source heterogeneous data by combining pipeline attribute information and pipeline connection relationship; the heterogeneous data acquisition module is used to perform verification and filtering based on basic attributes on the multi-source heterogeneous data through the first verification threshold of the data validator to obtain valid heterogeneous data, wherein the data validator is composed of a knowledge rule base and a forward inference mechanism, and obtains threshold dynamic rules by executing the self-combination and extension derivation of basic verification rules; the pipeline verification data acquisition module is used to perform standardized transformation under the pipeline facility attribute architecture on the valid heterogeneous data, determine multi-channel data, and perform threshold cascade verification and alignment fusion based on the second, third and fourth verification thresholds configured by dynamic rules to obtain pipeline verification data, wherein the multi-channel data corresponds one-to-one with the valid heterogeneous data; the terminal interface display module is used to update the pipeline verification data to the map sheet pipeline area and display it on the terminal interface.

[0010] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0011] By using the map sheet spatial index, the pipeline area requiring updating is located. Multi-source heterogeneous data is uploaded, combining pipeline attribute information and pipeline connection relationships. The multi-source heterogeneous data is then subjected to a first verification threshold by a data validator, performing verification and filtering based on fundamental attributes to obtain valid heterogeneous data. Standardization transformation under the pipeline facility attribute architecture is performed on the valid heterogeneous data to determine multi-channel data. Threshold cascade verification and alignment fusion are then performed based on a second, third, and fourth verification threshold configured with dynamic rules to obtain pipeline verification data. This pipeline verification data is then updated to the map sheet pipeline area and displayed on the terminal interface. This achieves the technical effect of hierarchical, multi-level automatic verification and fusion of multi-source underground pipeline data in research institute areas, improving data topology and spatial accuracy, and providing visual display. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 A schematic diagram of the data verification method for multi-source heterogeneous underground pipelines in research institutes provided in this application embodiment;

[0014] Figure 2 This is a schematic diagram of the structure of a multi-source heterogeneous underground pipeline data verification system for research institutes, provided in an embodiment of this application.

[0015] Figure labeling: 10 for multi-source heterogeneous data upload module, 20 for heterogeneous data acquisition module, 30 for pipeline verification data acquisition module, and 40 for terminal interface display module. Detailed Implementation

[0016] This application provides a method and system for verifying multi-source heterogeneous underground pipeline data in research institutes, which addresses the technical problems of existing multi-source pipeline data verification in research institutes, such as single-level verification, large topological spatial errors, and inability to display results in a hierarchical and visual manner.

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0018] Example 1, as Figure 1 As shown, this application provides a method for verifying multi-source heterogeneous underground pipeline data in research institute areas, the method comprising:

[0019] Step S100: Locate the map sheet pipeline area that needs to be updated using the map sheet spatial index, and upload multi-source heterogeneous data by combining pipeline attribute information and pipeline connection relationship.

[0020] Specifically, the spatial index retrieval mechanism is invoked to traverse the pipeline drawing sheets across the entire campus. Based on the coordinates of the pipeline update range, the corresponding sheet number is matched to accurately locate the pipeline area of ​​the sheet that needs to be updated. Complete pipeline attribute information such as pipeline type, diameter, and burial depth within this area is retrieved, along with pipeline connectivity and endpoint binding relationships between pipe points. Multi-source heterogeneous pipeline data, including pipeline vectors, text attributes, and 3D points collected from different channels such as surveying, construction, and maintenance, are bound to the located target sheet pipeline area, along with the associated pipeline attributes and pipe point connection relationships, and uploaded synchronously to the system backend. This provides complete original heterogeneous pipeline data with spatial association information for subsequent multi-level threshold verification.

[0021] Step S200: The multi-source heterogeneous data is subjected to the first verification threshold of the data validator, and verification and filtering based on basic attributes are performed to obtain valid heterogeneous data. The data validator is composed of a knowledge rule base and a forward reasoning mechanism, and the threshold dynamic rules are obtained by executing the self-combination and extension of the basic verification rules.

[0022] Specifically, standardized verification rules corresponding to various basic pipeline attributes such as pipeline material, burial depth, pipe diameter, and pipe point type are pre-entered into the knowledge rule base. The forward inference engine relies on the basic verification rules stored in the base to complete the autonomous combination and expansion of rules, generating a first verification threshold dynamic rule adapted to the current data scenario. Unlike the traditional hard-coded fixed verification process that cannot customize rules and lacks intelligent reasoning capabilities, this step relies on the forward inference mechanism to realize the dynamic generation of verification rules. Then, the dynamic rules of the first verification threshold are called to verify all basic attribute fields of pipelines and pipe points in the multi-source heterogeneous data one by one. Invalid data entries with missing attributes, out-of-bounds values, non-standard field formats, and parameters that do not conform to the hospital's pipeline design standards are eliminated. Pipeline data with complete attributes and compliant parameters are retained as valid heterogeneous data, completing the initial cleaning of the original multi-source heterogeneous data.

[0023] Step S300: Perform standardized transformation under the pipeline facility attribute architecture on the effective heterogeneous data to determine multi-channel data. Based on the second, third, and fourth verification thresholds configured by dynamic rules, perform threshold cascade verification and alignment fusion to obtain pipeline verification data. The multi-channel data corresponds one-to-one with the effective heterogeneous data.

[0024] Specifically, the effective heterogeneous data is first standardized and transformed according to a unified pipeline facility attribute architecture. Data from different sources are allocated to corresponding channels in a multi-channel network and uniformly transformed to the same spatial coordinate system. A heterogeneous graph structure is built with pipe points as nodes and pipelines as edges. Nodes are entered with pipe point type, burial depth, elevation, and material attributes, while edges are entered with pipe diameter, flow direction, and connection method attributes. Each channel extracts the topological feature subspace corresponding to the heterogeneous graph, and a cross-channel attention mechanism is used to complete the multi-channel feature association, generating multi-channel data that corresponds one-to-one with the effective heterogeneous data. Subsequently, for each channel's data, dynamic rules are generated based on a knowledge rule base and a forward inference engine to initialize the parameters of the second, third, and fourth verification thresholds. The initialization process involves three levels of threshold serial verification. The second verification threshold is loaded with the point-to-line reference consistency rule, generating a corresponding threshold based on the matching conditions between pipelines and pipeline references. The third verification threshold is loaded with the topology connectivity rule, generating a corresponding threshold based on connectivity conditions such as no isolated pipelines and no return loops in the network. The fourth verification threshold is loaded with the three-dimensional cross-collision rule, generating a corresponding threshold based on the pipeline safety elevation clearance requirements. These three levels of threshold serial verification are performed on the multi-channel data in sequence. The pass rate and anomaly distribution of each channel are statistically analyzed simultaneously. Based on the verification performance, each channel is assigned a corresponding weight. The verified data of each channel is then aligned and weighted according to the channel weights to integrate and eliminate topological, spatial, and attribute conflicts between multi-source data, ultimately forming unified, standardized, and logically conflict-free pipeline verification data.

[0025] Step S400: Update the pipeline verification data to the pipeline area of ​​the map sheet and display it on the terminal interface.

[0026] Specifically, the corresponding pipeline layer on the map sheet is retrieved, and the pipeline verification data is overwritten into the original pipeline layer under that map sheet. According to the rule of independent layered storage and management of single pipeline elements and their supporting attributes, dedicated layers are generated for each type of pipeline and pipe point element to complete the layer update. After the update is completed, all pipeline layers are loaded in the layer overlay display mode on the terminal interface. The terminal can control the visibility of different pipeline layers such as water supply and drainage, power, and communication, and synchronously display the complete attribute information corresponding to each pipeline and pipe point. It intuitively presents the complete spatial distribution of the underground pipeline network in the hospital area after multi-level verification and correction, which makes it convenient for staff to intuitively check the spatial location, topological relationship and attribute parameters of pipelines, and complete the visualization output of the results after the pipeline data verification process.

[0027] In one possible implementation, step S200 further includes:

[0028] Step S210: Divide the inspection rules into priority levels according to logical dependencies and deploy cascading verification thresholds.

[0029] Step S220: Call the basic verification rules and store them in the knowledge rule base. Use the combination of adaptive rules and rule extensions under the basic verification rule matching under the verification threshold adaptation as the reasoning mechanism, and deploy the forward inference engine.

[0030] Step S230: Based on the cascaded verification threshold as the basic architecture, dynamically generate verification rules using the knowledge rule base and the forward inference engine, and deploy the data verifier.

[0031] Specifically, the logic of pipeline data verification is analyzed. Basic attribute verification is a prerequisite for all topology and spatial verifications. Therefore, the rules related to basic pipeline attributes are assigned the highest priority, and the first verification threshold is deployed accordingly. Pipeline point-line reference relationship verification needs to be carried out after attribute compliance, and is set as the second priority, with the second verification threshold deployed. Pipeline network topology connectivity verification depends on the correctness of point-line reference relationships, and is set as the third priority, with the third verification threshold deployed. 3D pipeline cross-collision spatial verification relies on a complete connected topology network, and is set as the lowest priority, with the fourth verification threshold deployed. The four thresholds are arranged in a hierarchical order from basic attributes to point-line references, then to topology connectivity, and finally to 3D spatial collisions, forming a cascaded architecture that is progressive and does not proceed to the next level of verification if the previous verification fails. This completes the deployment and construction of the entire hierarchical cascaded verification threshold system.

[0032] Standardized basic verification rules corresponding to pipeline basic attributes, point-line references, topological connectivity, and 3D spatial collisions are collected, uniformly entered, and persistently stored in the knowledge rule base to complete the rule resource accumulation. The core logic of forward inference is designed, driven by the adaptation requirements of the current verification thresholds at all levels, automatically retrieves matching basic verification rules from the knowledge rule base for free combination, and at the same time, based on the characteristics of the hospital pipeline scene, the parameters of the existing basic rules are expanded and conditions are derived to generate new dynamic verification rules. This set of logic that relies on threshold adaptive matching to realize rule combination and derivation is encapsulated into the inference kernel, equipped with input and output interfaces, rule call scheduling module, and threshold adaptive adjustment module to build a complete forward inference engine. A real-time data interaction channel is established with the knowledge rule base, so that the inference engine can read and call the basic rules in the base at any time and dynamically generate verification rules adapted to each level of thresholds, completing the overall deployment of the forward inference engine, the core component of the data verifier.

[0033] The data validator uses a cascaded verification threshold system, with priority levels defined and sequentially connected from the first to the fourth level, as its overall operational framework. This system establishes a data interaction link between the knowledge rule base and the forward inference engine, enabling the forward inference engine to read various basic verification rules stored in the knowledge rule base in real time. Based on the verification scenario requirements corresponding to each level of threshold, the system performs self-combination and extension of basic rules, dynamically generating exclusive verification rules adapted to each level of threshold. The four-level cascaded verification thresholds, the knowledge rule base, and the forward inference engine with rule-based intelligent reasoning capabilities are integrated and packaged into a unified whole. This system is equipped with a data input interface, a hierarchical verification scheduling module, and an abnormal data output branch, forming a complete data validator. It can sequentially call dynamically generated verification rules to complete hierarchical verification of input pipeline data, unlike the traditional hard-coded fixed verification process, achieving intelligent and scenario-based dynamic adaptation of verification rules.

[0034] In one possible implementation, step S210 further includes:

[0035] Step S211: The cascaded verification threshold includes a first verification threshold based on basic attributes, a second verification threshold based on point-line reference relationships, a third verification threshold based on topological connectivity, and a fourth verification threshold based on three-dimensional cross collision.

[0036] Specifically, four independent verification thresholds are set according to the verification logic sequence. The first verification threshold is specifically for compliance verification of basic attribute fields such as pipeline material, pipe diameter, burial depth, and elevation. The second verification threshold focuses on the consistency verification of the point-line reference correspondence between pipelines and pipe points. The third verification threshold is used to check the overall topological connectivity of the pipeline network and identify topological defects such as isolated pipe points, suspended pipelines, and elevation backflow loops. The fourth verification threshold is responsible for the three-dimensional spatial detection of pipelines to determine whether there are spatial intersections and collisions between pipelines and between pipelines and structures that have not reached the safe clearance. The four thresholds are connected sequentially from the initial basic data verification to the deep spatial topology verification, forming a complete progressive cascade verification system.

[0037] In one possible implementation, step S300 further includes:

[0038] Step S310: Standardize and transform the effective heterogeneous data according to the pipeline facility attribute architecture to obtain multi-channel data.

[0039] Step S320: The standardization conversion method includes:

[0040] The effective heterogeneous data are input into the corresponding channels in the multi-channel network. A unified spatial coordinate system is used to construct a heterogeneous graph structure with pipe points as nodes and pipelines as edges. The node attributes include pipe point type, burial depth, elevation and material information, and the edge attributes include pipe diameter, flow direction and connection method.

[0041] Each channel extracts the topological feature subspaces of the heterogeneous graph structure that are of the same origin, and associates them through a cross-channel attention mechanism to obtain multi-channel data.

[0042] Specifically, valid heterogeneous data from different sources are imported into the corresponding independent channels within a multi-channel network and uniformly converted to the same spatial coordinate system. The collected pipe points are used as nodes in the graph structure and the pipelines are used as edges to build a heterogeneous graph. The nodes carry pipe point attributes such as pipe type, burial depth, elevation, and material, while the edges carry pipeline attributes such as pipe diameter, flow direction, and connection method. Each channel extracts its own topological feature subspace corresponding to its heterogeneous graph, and then the cross-channel attention mechanism is used to complete the association and fusion of topological features between multiple channels. Finally, standardized multi-channel data that matches each set of valid heterogeneous data is output.

[0043] During the standardization transformation, effective heterogeneous data is classified and input into a multi-channel network matching channel, and uniformly transformed to a global standard spatial coordinate system. Various pipe points collected on-site are used as nodes of the heterogeneous map, and each pipeline segment is used as the edge of the heterogeneous map to build the overall pipeline heterogeneous map structure. The nodes are bound to all attribute information such as pipe point type, burial depth, elevation, and material, and the pipeline edges are bound to pipeline attributes such as pipe diameter, fluid flow direction, and pipe point connection method, thus completing the unified structured modeling of multi-source data.

[0044] Each channel separately analyzes its own pipeline heterogeneity map and extracts a common topological feature subspace containing the number of pipe connection points, pipeline connectivity, elevation distribution, and pipe connection structure. An independent topological feature matrix is ​​constructed for each channel. Then, feature association calculation is carried out through a cross-channel attention mechanism. First, the inner product operation is performed on the topological feature matrices of any two channels to obtain the feature similarity score. After normalization, attention weight coefficients between channels are generated. Based on the weight coefficients, the common topological features of different channels are weighted, matched, and cross-associated to eliminate the differences in topological expression of multi-source data. The standardized features after all channels are associated are integrated, and finally, multi-channel data corresponding one-to-one with the effective heterogeneous data is output.

[0045] In one possible implementation, step S300 further includes:

[0046] Step S330: For the multi-channel data, perform threshold rule generation and rule initialization on a channel-by-channel basis to configure the verification threshold parameters, and obtain the initialized second verification threshold, third verification threshold and fourth verification threshold.

[0047] Step S340: Based on the second verification threshold, the third verification threshold and the fourth verification threshold, perform multi-source heterogeneous feature alignment and fusion under threshold cascade verification on the multi-channel data to obtain pipeline verification data.

[0048] Specifically, it iterates through the multi-channel data of each channel, calls the forward inference engine to retrieve the corresponding level rules from the knowledge rule base, and uses a dedicated calculation formula to solve the threshold problem. For the second verification threshold point-line reference consistency check, a threshold calculation formula is set. ,in This represents the total number of pipelines connected to a single pipe point. The compliance threshold is the number of times this pipe point is referenced by the pipeline endpoint. If the calculation result is greater than 0, the point-line reference is determined to be abnormal; for the third verification threshold topology connectivity verification, a topology anomaly quantification formula is used. , The number of isolated pipe points, This refers to the number of suspended pipelines. The number of elevation return loops, compliance threshold. A value greater than 0 indicates a topology defect; for the fourth check threshold 3D cross-collision check, a spatial safety determination formula is used. , , The elevations of the two intersecting pipelines To standardize the minimum safe clearance, The actual spatial distance of the pipeline, compliance conditions are as follows: and The corresponding pipeline topology and three-dimensional spatial data are substituted into each channel to calculate the three types of threshold values. The calculated threshold values ​​are then assigned to the corresponding level thresholds to complete parameter initialization. The above rule retrieval, formula calculation, and threshold assignment process is executed cyclically for all channels to finally obtain the second, third, and fourth verification thresholds for each channel to independently complete parameter initialization.

[0049] Following the cascading order of point-line referencing, topological connectivity, and 3D spatial collision, the second verification threshold formula is first applied. Validate the reference relationships between pipe points and pipelines in multi-channel data channel by channel, and filter... Points and lines ≠0 refer to abnormal data; data that passes the second threshold check is sent to the third check threshold, and then processed by the formula. Identify isolated pipe points, suspended pipes, and return loops in the topology network, and remove data with abnormal topology connectivity; then input the topology-compliant data into the fourth verification threshold, and apply the elevation difference formula. , clear distance formula To verify the issue of cross-collision between 3D pipelines, only compliant verification data that meets the safety spacing requirements in 3D space is retained. The pass rate and anomaly distribution of data for each channel are statistically analyzed. The pass rate percentage is used as the basis for channel weight allocation. The topology, attributes, and spatial features corresponding to the compliant data after verification of each channel are uniformly mapped to the same spatial coordinate system to complete cross-channel feature alignment. Then, the corresponding channel weights are used to perform weighted fusion calculations on the features after multi-channel alignment to eliminate attribute deviations, topological conflicts, and spatial misalignments of pipeline data from different data sources. After integration and unification, standardized pipeline verification data without logical conflicts is generated.

[0050] In one possible implementation, step S340 further includes:

[0051] Step S341: Initialize the threshold parameter set with the point-line reference consistency rule corresponding to the second verification threshold. The first threshold is dynamically generated based on the topological reference relationship between pipeline points and pipelines. The basic threshold condition for the first threshold is that the same pipeline endpoint must reference one and only one pipeline point, and the number of times a pipeline point is referenced is equal to the number of pipelines it is connected to.

[0052] Step S342: Generate a second threshold based on the topological connectivity rules corresponding to the third verification threshold. The basic threshold conditions for the second threshold are: the pipeline network is fully connected, there are no isolated pipe points or suspended pipelines, the flow direction is along the direction of decreasing elevation, and there are no backtracking loops.

[0053] Step S343: Generate the third threshold based on the three-dimensional cross-collision rules corresponding to the fourth verification threshold, wherein the basic threshold condition for the third threshold is that the elevation difference between intersecting pipelines in space is greater than the safe distance and the pipelines maintain a net distance from the outer wall of the structure.

[0054] Specifically, the process iterates through all pipeline endpoints and pipe point records in the current multi-channel data, counting the reference numbers of the pipe points bound to both ends of each pipeline segment and the total number of pipelines connected to a single pipe point. A threshold calculation formula is constructed based on the fundamental criteria that each endpoint of a single pipeline can be associated with exactly one pipe point, and that the total number of times a pipe point is referenced by pipeline endpoints is exactly equal to the actual number of pipelines connected to that pipe point. ,in The number of pipe points referenced at the pipeline endpoints. The compliance baseline threshold is set to the total number of pipelines connected to the pipeline points. The threshold, judgment conditions, and field matching logic are uniformly entered into the parameter set of the second verification threshold to complete the initialization of the entire set of parameters of the second verification threshold, providing a quantitative judgment standard for verifying the point-line reference relationship of multi-channel data.

[0055] Traverse all nodes and edges of the current heterogeneous pipeline graph and count the number of isolated pipeline points. Number of suspended pipelines without supporting pipelines The number of return loops formed along the elevation increase Constructing a topological defect quantification formula The compliance benchmark threshold is set based on the following fundamental threshold constraints: overall interconnectedness of the pipeline network, absence of isolated pipeline points, absence of suspended pipelines, and pipeline flow strictly extending along the direction of elevation decrease without any elevation backtracking loops. If the result of the formula is greater than 0, it means that there is a topological connectivity anomaly. The calculation formula, judgment constraints, and benchmark threshold are uniformly entered into the third verification threshold to complete the threshold configuration, providing a quantitative judgment basis for the cascade verification of multi-channel data topological connectivity.

[0056] Extract the three-dimensional spatial coordinates and elevation parameters of all pipelines and structures from the multi-channel data, and construct a spatial determination calculation formula. , ,in , The elevation values ​​are for two intersecting pipelines in space. This refers to the actual spatial distance between the pipeline and the outer wall of the structure. To standardize the minimum safe clearance, the basic threshold criteria are set as follows: the elevation difference between intersecting pipelines must be greater than the safe pipeline spacing, and the actual clearance between all pipelines and the outer wall of the structure must be greater than the standard minimum clearance. The compliance benchmark threshold is set as follows: and The system traverses all three-dimensional intersecting pipelines and structures to complete batch threshold calculations. The calculation formulas, safety distance standards, and compliance judgment conditions are uniformly entered into the fourth verification threshold to form the third threshold parameter set, providing a quantitative judgment standard for multi-channel data to carry out three-dimensional spatial cross-collision cascade verification.

[0057] In one possible implementation, step S320 further includes:

[0058] Step S321: For the multi-channel data, determine the N verification data and N channel weights of the N channel data pairs in sequence, and obtain the pipeline verification data through data alignment and weighted fusion, where N is the number of heterogeneous data sources, and the N verification data correspond one-to-one with the multi-channel data.

[0059] Specifically, let N be the total number of heterogeneous data sources. Each channel in the multi-channel network corresponds to multi-channel data collected from one type of data source. After each channel independently completes threshold cascade verification, it generates corresponding single-channel verification data. Combining the verification pass rate, spatial and attribute anomaly distribution results obtained by each channel during the verification process, the single-channel comprehensive score is calculated and normalized to obtain the channel weight. The sum of all channel weights is 1. Then, the standard spatial coordinate system is uniformly used to complete the topology and attribute alignment of pipeline nodes and pipeline edges of each channel. The features of each channel's verification data, such as nodes, pipe diameter, burial depth, and three-dimensional elevation, are weighted and calculated and merged according to the corresponding channel weights. This eliminates attribute deviations, spatial misalignments, and topological conflicts caused by inconsistent collection standards of different data sources. Finally, unified pipeline verification data without abnormal conflicts is generated.

[0060] In one possible implementation, step S321 further includes:

[0061] The first channel data undergoes cascaded verification of the verification threshold to obtain the first verification data. The first verification data is identified by the verification pass rate and anomaly distribution. Each anomaly node in the anomaly distribution is identified by its spatial coordinates and attribute deviation. The first channel data is any channel data in the multi-channel data.

[0062] The weight of the first channel is determined based on the pass rate and anomaly distribution.

[0063] Specifically, any one channel within the multi-channel data is selected as the first channel data. The second, third, and fourth verification thresholds are sequentially cascaded to verify the data in this channel, generating the first verification data. At the same time, a unique verification identifier is configured for the first verification data. The identifier includes the overall data verification pass rate and complete anomaly distribution information for this channel. For each identified abnormal pipe point or pipeline node within the anomaly distribution, the corresponding three-dimensional spatial coordinate parameters and attribute deviation values ​​that do not match the standard pipeline architecture are simultaneously bound. The single-channel verification results, anomaly location, and anomaly cause data are completely retained.

[0064] First, set the basic scoring calculation formula. In the formula, P is the pass rate of the channel verification. This represents the total number of abnormal nodes in this channel that contain records of spatial coordinate and attribute deviations. The original score for the channel is calculated by substituting the pass rate value obtained from the first channel's verification, the number of abnormal nodes, and the total number of nodes into the total number of all pipeline nodes in the channel. The total score is obtained by summing the original scores of all channels. Then, through the normalization formula The normalized weight of the first channel is calculated, and the sum of the weights of all channels is always equal to 1. The higher the pass rate of channel verification and the lower the proportion of abnormal nodes, the higher the original score and the larger the corresponding channel weight value. This completes the quantitative determination of the first channel weight based on the verification quality.

[0065] In one possible implementation, step S400 further includes:

[0066] Step S410: Write the pipeline verification data into the pipeline layer of the map area, and display the pipeline network in a layer overlay manner on the terminal interface.

[0067] In this approach, a pipeline element and its corresponding attribute information are stored and managed as a single layer.

[0068] Specifically, the system locates the geographic boundary area of ​​the target map sheet to be updated, clears outdated data from the existing pipeline layers in that area, and, according to the hierarchical structure of water supply and drainage, power, communication, and gas pipelines, writes the pipe points, 3D coordinates of the pipelines, and various attribute parameters from the pipeline verification data into the corresponding pipeline layers to complete the layer overlay update. Simultaneously, it stores the verification anomaly markers associated with each element. The terminal interface loads the base map layer and various layered pipeline layers, adopting an interactive layer overlay rendering mode. It supports individually enabling or disabling the display status of any type of pipeline layer. For abnormal pipeline elements with attribute deviations, spatial collisions, or topological defects, differentiated highlighting color schemes are used for annotation. When a pipeline or pipe point is selected with the mouse, a pop-up window displays complete attribute information such as burial depth, material, pipe diameter, and verification anomaly records. Layered overlays present the complete spatial distribution network of pipelines after multi-level verification and correction, enabling visualized verification and interactive browsing of the verification results.

[0069] When storing and managing pipeline layers, pipeline elements of a single category, such as water supply pipes, drainage pipes, gas pipes, power lines, and communication lines, are divided into separate layers. All pipe points and pipeline segment geometric data of the same type of pipeline, along with a complete set of attribute information specific to that pipeline, such as burial depth, elevation, pipe diameter, material, and verification anomaly markers, are integrated into an independent layer partition for storage. Each pipeline layer is independent of the others and can perform data writing, modification, hiding, and loading operations independently. This not only achieves data isolation and control of different pipeline elements, but also provides standardized layer data support for layered overlay visualization on the terminal interface.

[0070] Using the No. 3 power room of a comprehensive research institute as the actual test scenario, synchronous verification tests were conducted by integrating three types of multi-source pipeline data: as-built CAD, inspection GPS, and utility tunnel BIM. The verification results are shown in Table 1.

[0071] Original pipeline point summary record 1268 1268 The first threshold removes invalid data. 187 articles 192 articles The second threshold line is misused. 36 places 112 places Third threshold topology connectivity anomaly 14 places 57 places Fourth threshold 3D collision anomaly 8 places 43 places Average deviation of 3D coordinates after fusion 0.86m 0.12m Manual review time for a single map sheet 142min 36min

[0072] It is evident that the four-level cascaded threshold of this invention can detect multiple types of defects, including attributes, point-line references, topological connectivity, and three-dimensional space, layer by layer. After data fusion, the spatial accuracy is significantly improved, and the layered visualization function greatly reduces the workload of manual review. This fully demonstrates the technical effect of this method in automatically verifying and fusing layered multi-level data, improving pipeline topology and spatial accuracy, and displaying the data in a layered and visualized manner.

[0073] Example 2, based on the same inventive concept as the multi-source heterogeneous underground pipeline data verification method for research institutes in the aforementioned examples, such as... Figure 2 As shown, this application provides a data verification system for multi-source heterogeneous underground pipelines in research institutes. The system and method embodiments in this application are based on the same inventive concept. The system includes:

[0074] The multi-source heterogeneous data upload module 10 is used to locate the map sheet pipeline area that needs to be updated through the map sheet spatial index, and upload multi-source heterogeneous data by combining pipeline attribute information and pipeline connection relationship.

[0075] The heterogeneous data acquisition module 20 is used to perform verification and filtering based on basic attributes on the multi-source heterogeneous data through the first verification threshold of the data validator to obtain valid heterogeneous data. The data validator is composed of a knowledge rule base and a forward reasoning mechanism, and obtains threshold dynamic rules by executing the self-combination and extension of basic verification rules.

[0076] The pipeline verification data acquisition module 30 is used to perform standardized transformation under the pipeline facility attribute architecture on the effective heterogeneous data, determine multi-channel data, and perform threshold cascade verification and alignment fusion based on the second, third and fourth verification thresholds configured by dynamic rules to obtain pipeline verification data, wherein the multi-channel data corresponds one-to-one with the effective heterogeneous data.

[0077] The terminal interface display module 40 is used to update the pipeline verification data to the pipeline area of ​​the map sheet and display it on the terminal interface.

[0078] Furthermore, the system is also used to implement the following functions:

[0079] The inspection rules are divided into priority levels according to logical dependencies, and cascaded verification thresholds are deployed. Basic verification rules are called and stored in the knowledge rule base. An inference mechanism is derived by adaptive rule combination and rule extension under the basic verification rule matching under the adaptive verification threshold, and a forward inference engine is deployed. Based on the cascaded verification thresholds, dynamic verification rules are generated using the knowledge rule base and the forward inference engine, and the data verifier is deployed.

[0080] Furthermore, the system is also used to implement the following functions:

[0081] The cascaded verification thresholds include a first verification threshold based on basic attributes, a second verification threshold based on point-line reference relationships, a third verification threshold based on topological connectivity, and a fourth verification threshold based on three-dimensional cross-collision.

[0082] Furthermore, the system is also used to implement the following functions:

[0083] The effective heterogeneous data is standardized and transformed according to the pipeline facility attribute architecture to obtain multi-channel data. The standardization and transformation method includes: inputting the effective heterogeneous data into the corresponding channels in the multi-channel network, using a unified spatial coordinate system, and constructing a heterogeneous graph structure with pipe points as nodes and pipelines as edges. The node attributes include pipe point type, burial depth, elevation, and material information, and the edge attributes include pipe diameter, flow direction, and connection method. The topological feature subspaces of the same origin in the heterogeneous graph structure are extracted from each channel and associated through a cross-channel attention mechanism to obtain multi-channel data.

[0084] Furthermore, the system is also used to implement the following functions:

[0085] For the multi-channel data, threshold rule generation and rule initialization are performed channel by channel to configure the verification threshold parameters, resulting in the initialized second, third, and fourth verification thresholds. Based on the second, third, and fourth verification thresholds, multi-source heterogeneous feature alignment and fusion under threshold cascade verification are performed on the multi-channel data to obtain pipeline verification data.

[0086] Furthermore, the system is also used to implement the following functions:

[0087] The threshold parameter set is initialized using the point-line reference consistency rule corresponding to the second verification threshold. The first threshold is dynamically generated based on the topological reference relationship between pipeline points and pipelines, with the basic threshold condition being that the same pipeline endpoint must reference exactly one pipeline point, and the number of times a pipeline point is referenced equals the number of pipelines it connects to. The second threshold is generated using the topological connectivity rule corresponding to the third verification threshold, with the basic threshold condition being that the pipeline network is fully connected, there are no isolated pipeline points or suspended pipelines, the flow direction is along the decreasing elevation direction, and there are no backtracking loops. The third threshold is generated using the three-dimensional intersection collision rule corresponding to the fourth verification threshold, with the basic threshold condition being that the elevation difference between spatially intersecting pipelines is greater than the safe distance, and the pipeline maintains a net distance from the outer wall of the structure.

[0088] Furthermore, the system is also used to implement the following functions:

[0089] For the multi-channel data, N verification data and N channel weights are determined sequentially for N channel data pairs. Through data alignment and weighted fusion, the pipeline verification data is obtained, where N is the number of heterogeneous data sources and the N verification data correspond one-to-one with the multi-channel data.

[0090] Furthermore, the system is also used to implement the following functions:

[0091] The first channel data undergoes cascaded verification of the verification threshold to obtain the first verification data. The first verification data is identified by the verification pass rate and anomaly distribution. Each anomaly node in the anomaly distribution is identified by its spatial coordinates and attribute deviation. The first channel data is any channel data in the multi-channel data. The weight of the first channel is determined based on the verification pass rate and anomaly distribution.

[0092] Furthermore, the system is also used to implement the following functions:

[0093] The pipeline verification data is written into the pipeline layer of the map area, and the pipeline network is displayed in the terminal interface in a layer overlay manner; wherein, a pipeline element and its corresponding attribute information are stored and managed as a layer.

[0094] It should be noted that the order of the embodiments described above is for descriptive purposes only and does not represent the superiority or inferiority of the embodiments. Specific embodiments of this specification have been described above. Furthermore, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0095] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0096] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application intends to include such modifications and variations.

Claims

1. A method for verifying multi-source heterogeneous underground pipeline data in research institute areas, characterized in that, The method includes: Using the map sheet spatial index, locate the map sheet pipeline area that needs to be updated, and upload multi-source heterogeneous data by combining pipeline attribute information and pipeline connection relationship; The multi-source heterogeneous data is subjected to a first verification threshold of the data validator, and verification and filtering based on basic attributes are performed to obtain valid heterogeneous data. The data validator is composed of a knowledge rule base and a forward reasoning mechanism, and obtains threshold dynamic rules by executing the self-combination and extension of basic verification rules. The effective heterogeneous data is subjected to standardized transformation under the pipeline facility attribute architecture to determine multi-channel data. Based on the second, third and fourth verification thresholds configured by dynamic rules, threshold cascade verification and alignment fusion are performed to obtain pipeline verification data. The multi-channel data corresponds one-to-one with the effective heterogeneous data. The pipeline verification data is updated to the pipeline area of ​​the map sheet and displayed on the terminal interface.

2. The method for verifying multi-source heterogeneous underground pipeline data in research institutes as described in claim 1, characterized in that, The data validator includes: The inspection rules are divided into priority levels according to logical dependencies, and cascading verification thresholds are deployed. The basic verification rules are invoked and stored in the knowledge rule base. The inference mechanism is derived from the combination of adaptive rules and rule expansion under the basic verification rule matching under the verification threshold adaptation, and a forward inference engine is deployed. Based on the cascaded verification threshold as the basic architecture, the knowledge rule base and the forward inference engine are used to dynamically generate verification rules, and the data verifier is deployed.

3. The method for verifying multi-source heterogeneous underground pipeline data in research institute areas as described in claim 2, characterized in that, The cascaded verification thresholds include a first verification threshold based on basic attributes, a second verification threshold based on point-line reference relationships, a third verification threshold based on topological connectivity, and a fourth verification threshold based on three-dimensional cross-collision.

4. The method for verifying multi-source heterogeneous underground pipeline data in research institutes as described in claim 1, characterized in that, Perform a standardized transformation of the pipeline facility attribute architecture on the aforementioned valid heterogeneous data, including: The effective heterogeneous data is standardized and transformed according to the pipeline facility attribute architecture to obtain multi-channel data; The standardized conversion methods include: The effective heterogeneous data are input into the corresponding channels in the multi-channel network. A unified spatial coordinate system is used to construct a heterogeneous graph structure with pipe points as nodes and pipelines as edges. The node attributes include pipe point type, burial depth, elevation and material information, and the edge attributes include pipe diameter, flow direction and connection method. Each channel extracts the topological feature subspaces of the heterogeneous graph structure that are of the same origin, and associates them through a cross-channel attention mechanism to obtain multi-channel data.

5. The method for verifying multi-source heterogeneous underground pipeline data in research institute areas as described in claim 1, characterized in that, Based on the second, third, and fourth verification thresholds configured with dynamic rules, threshold cascading verification and alignment fusion are performed to obtain pipeline verification data, including: For the multi-channel data, threshold rule generation and rule initialization are performed channel by channel to configure the verification threshold parameters, resulting in the initialized second verification threshold, third verification threshold and fourth verification threshold; Based on the second, third, and fourth verification thresholds, multi-source heterogeneous feature alignment and fusion under threshold cascade verification are performed on the multi-channel data to obtain pipeline verification data.

6. The method for verifying multi-source heterogeneous underground pipeline data in research institute areas as described in claim 5, characterized in that, The threshold parameter set is initialized with the point-line reference consistency rule corresponding to the second verification threshold. The first threshold is dynamically generated based on the topological reference relationship between pipeline points and pipelines. The basic threshold condition for the first threshold is that the same pipeline endpoint must reference one and only one pipeline point, and the number of times a pipeline point is referenced is equal to the number of pipelines it connects to. The second threshold is generated based on the topological connectivity rules corresponding to the third verification threshold. The basic threshold conditions for the second threshold are: the pipeline network is fully connected, there are no isolated pipe points or suspended pipelines, the flow direction is along the direction of decreasing elevation, and there are no back loops. The third threshold is generated based on the three-dimensional cross-collision rules corresponding to the fourth verification threshold. The basic threshold conditions for the third threshold are that the elevation difference between intersecting pipelines in space is greater than the safe distance and the pipelines maintain a net distance from the outer wall of the structure.

7. The method for verifying multi-source heterogeneous underground pipeline data in research institute areas as described in claim 5, characterized in that, For the multi-channel data, N verification data and N channel weights are determined sequentially for N channel data pairs. Through data alignment and weighted fusion, the pipeline verification data is obtained, where N is the number of heterogeneous data sources and the N verification data correspond one-to-one with the multi-channel data.

8. The method for verifying multi-source heterogeneous underground pipeline data in research institute areas as described in claim 6, characterized in that, Determine the N checksums and N channel weights for N channel data pairs, including: The first channel data is subjected to cascaded verification of the verification threshold to obtain the first verification data. The first verification data is identified by the verification pass rate and the abnormal distribution. Each abnormal node in the abnormal distribution is identified by spatial coordinates and attribute deviation. The first channel data is any channel data in the multi-channel data. The weight of the first channel is determined based on the pass rate and anomaly distribution.

9. The method for verifying multi-source heterogeneous underground pipeline data in research institute areas as described in claim 1, characterized in that, The pipeline verification data is written into the pipeline layer of the map area, and the pipeline network is displayed in the terminal interface in a layer overlay manner. In this approach, a pipeline element and its corresponding attribute information are stored and managed as a single layer.

10. A data verification system for multi-source heterogeneous underground pipelines in research institutes, characterized in that: The system is used to implement the data verification method for multi-source heterogeneous underground pipelines in research institute areas as described in any one of claims 1-9, and the system includes: The multi-source heterogeneous data upload module is used to locate the map sheet pipeline area that needs to be updated through the map sheet spatial index, and upload multi-source heterogeneous data by combining pipeline attribute information and pipeline connection relationship. The heterogeneous data acquisition module is used to perform verification and filtering based on basic attributes on the multi-source heterogeneous data through the first verification threshold of the data validator to obtain effective heterogeneous data. The data validator is composed of a knowledge rule base and a forward reasoning mechanism, and obtains threshold dynamic rules by executing the self-combination and extension of basic verification rules. The pipeline verification data acquisition module is used to perform standardized transformation under the pipeline facility attribute architecture on the effective heterogeneous data, determine multi-channel data, and perform threshold cascade verification and alignment fusion based on the second, third and fourth verification thresholds configured by dynamic rules to obtain pipeline verification data, wherein the multi-channel data corresponds one-to-one with the effective heterogeneous data; The terminal interface display module is used to update the pipeline verification data to the pipeline area of ​​the map sheet and display it on the terminal interface.

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