A comprehensive assessment and diagnosis method and system for urban dual drainage systems

Abstract

This invention relates to the field of urban drainage and flood control technology, and discloses a comprehensive evaluation and diagnosis method and system for urban dual drainage systems. The method first acquires geographic information and hydraulic model data of the dual drainage system, consisting of underground drainage pipe networks and surface road drainage channels, and constructs a comprehensive evaluation index system encompassing both physical and topological attributes. By extracting parameters from the data, the values ​​of each index are calculated; combining the relative importance and numerical distribution characteristics among the indicators, the final weight coefficients are determined and corrected; based on the index values ​​and weights, the system is comprehensively evaluated and a comprehensive performance score is obtained; finally, based on this score, the values ​​of each index, and their classification results, the system performance status is diagnosed, and key pipe sections, key nodes, and weak areas are identified. This invention can comprehensively and accurately locate bottlenecks and defective areas in dual drainage systems, providing a basis for system optimization or maintenance and renovation.

Description

Technical Field

[0001] This invention relates to the field of urban drainage and flood control technology, specifically to a comprehensive assessment and diagnosis method and system for urban dual drainage systems. Background Technology

[0002] With the intensification of global climate change and the frequent occurrence of extreme heavy rainfall events, urban flooding has become a major challenge restricting the safe operation and sustainable development of cities. In order to improve the ability of cities to cope with excessive rainfall, the concept of a dual drainage system has emerged. This system consists of a combined underground and surface drainage system, which is composed of traditional underground rainwater pipe networks (small drainage system) and surface drainage channels such as roads and open channels (large drainage system). Through spatial complementarity and functional linkage, it enhances the resilience of urban drainage and flood control.

[0003] Currently, assessment methods for urban drainage systems mainly fall into two categories. One category is simulation methods based on hydraulic models (such as SWMM), which assess the system's drainage capacity by calculating physical indicators such as pipe fullness, flow velocity, and node water accumulation. However, these methods struggle to reveal topological characteristics such as connectivity reliability and fault propagation paths at the network structure level. The other category applies complex network theory, using graph theory indicators (such as average degree, global efficiency, and modularity) to analyze the topological properties of the drainage network to identify key nodes or community structures. However, these indicators often ignore the decisive influence of physical attributes such as pipe diameter, length, and service area on actual water conveyance capacity, leading to a disconnect between the analysis results and the engineering hydraulic performance. Furthermore, most of these methods assess underground pipe networks or surface roads in isolation, failing to consider them as a coupled, collaborative system for integrated evaluation.

[0004] It is evident that the above scheme suffers from the dual defects of fragmented evaluation objects and single evaluation dimensions, resulting in the inability to comprehensively and accurately identify bottleneck segments and weak links in the entire system. Summary of the Invention

[0005] This invention provides a comprehensive assessment and diagnosis method and system for urban dual drainage systems, which solves the dual defects of existing technologies, namely, fragmented assessment objects and single assessment dimensions, resulting in the inability to comprehensively and accurately identify bottleneck pipe sections and weak links in the entire system.

[0006] In a first aspect, the present invention provides a method for comprehensive assessment and diagnosis of urban dual drainage systems, the method comprising: Acquire geographic information data and hydraulic model data of the target dual drainage system, and construct a comprehensive evaluation index system that includes physical attribute dimension indicators and topological attribute dimension indicators; Parameters are extracted from the geographic information data and hydraulic model data to calculate the values ​​of each indicator in the comprehensive evaluation index system; The initial weight coefficients are determined based on the relative importance of each indicator, and the indicators are classified according to the numerical distribution characteristics of each indicator to correct the initial weight coefficients and obtain the final weight coefficients. Based on the values ​​of each indicator and the final weighting coefficient, the target dual drainage system is comprehensively evaluated to obtain a comprehensive system performance score. Based on the comprehensive performance score, the values ​​of each indicator, and the classification results of each indicator, the performance status of the target dual drainage system is diagnosed, and key pipe sections, key nodes, and weak areas of the system are identified.

[0007] In one optional implementation, the target dual drainage system includes an underground drainage network subsystem and a surface road drainage channel subsystem; The physical property dimension indicators include: Horton ratio, average network density, and comprehensive hydraulic characteristic index; The topology attribute dimensions include: tree connectivity index, single-segment transport capacity, node importance index, and improved modularity.

[0008] In one alternative implementation, the tree connectivity index is obtained using the following formula: ; Among them, DCI P The tree connectivity index is... Number the nodes. Nodes extracted from the geographic information data The length of the pipe between them, Nodes extracted from the geographic information data The length of the ground road between them, L is the total length of all pipeline segments and all ground road segments extracted from the geographic information data.

[0009] In one optional implementation, the single-segment transport capacity is obtained using the following formula: ; Among them, SCFC refers to the single-segment transmission capacity. N represents the ratio of pipeline flow rate extracted from the hydraulic model data to the total flow rate at the nodes, where N is the total number of all pipeline segments and ground road segments.

[0010] In one optional implementation, the node importance index is obtained using the following formula: ; Wherein, PR is the node importance index. Here, t is the damping factor, and t is the number of iterations. This represents the total number of nodes extracted from the geographic information data. The connection identifier is extracted from the geographic information data. It is set to 1 when there is a connection between node i and node j, and 0 otherwise. The service area of ​​node i is extracted from the geographic information data. The total service area of ​​all nodes extracted from the geographic information data. The out-degree of node j extracted from the geographic information data. Let i be the set of upstream nodes pointing to node i.

[0011] In one alternative implementation, the improved modularity is obtained using the following formula: ; Among them, Q d For the improved modularity, The shape factor of sub-catchment n extracted from the geographic information data is the ratio of the perimeter of sub-catchment n to the perimeter of a circle of the same area. Let be the node importance index of node i within sub-catchment n. This refers to the service area of ​​all pipe sections and surface roads within the sub-catchment n extracted from the geographic information data. The total area of ​​sub-catchment n extracted from the geographic information data.

[0012] In one optional implementation, the comprehensive hydraulic characteristic index is obtained using the following formula: ; in, The comprehensive hydraulic characteristic index of pipeline j is... The maximum global hydraulic performance index of pipe j is calculated based on the hydraulic model data. The maximum self-hydraulic performance index of pipe j is calculated based on the hydraulic model data. This refers to the cumulative hydraulic performance index of pipe j calculated based on the hydraulic model data. All three are preset weights and their sum is 1, and C is a preset constant.

[0013] In one optional implementation, the step of determining initial weight coefficients based on the relative importance of the indicators, and classifying the indicators according to their numerical distribution characteristics to correct the initial weight coefficients, thereby obtaining final weight coefficients, includes: Each indicator is compared pairwise to construct a judgment matrix, and the initial weight coefficients are determined based on the eigenvectors of the judgment matrix. Based on the numerical distribution characteristics of each indicator, clustering is performed to divide each indicator into local indicators and global indicators. The initial weight coefficients and the classification results obtained after index division are quantified and assigned values, and the quantified and assigned values ​​are fused and normalized to obtain the final weight coefficients.

[0014] In one optional implementation, the step of diagnosing the performance status of the target dual-drainage system based on the comprehensive performance score, the values ​​of each indicator, and the classification results of each indicator, and identifying key pipe sections, key nodes, and weak areas of the system, includes: When the comprehensive hydraulic characteristic index of each pipe segment is less than the target value, the corresponding pipe segment is identified as a critical pipe segment. When the branch ratio of the Horton ratio is outside the preset reasonable range, the hierarchical region corresponding to the abnormal branch ratio is identified as a weak region. When the overall performance score of the system is lower than the preset performance threshold, it is determined that the overall performance of the system is substandard and there is a high risk of waterlogging. Based on the classification results of the indicators, nodes with a node importance index higher than a preset importance threshold are identified as key nodes, and pipe sections or ground road sections with a single-segment transport capacity lower than a preset capacity threshold are identified as weak links.

[0015] Secondly, the present invention provides a comprehensive assessment and diagnosis system for urban dual drainage systems, the system comprising: The data preprocessing module is used to acquire geographic information data and hydraulic model data of the target dual drainage system, and to construct a comprehensive evaluation index system that includes physical attribute dimension indicators and topological attribute dimension indicators. The multi-dimensional indicator calculation module is used to extract parameters from the geographic information data and hydraulic model data in order to calculate the values ​​of each indicator in the comprehensive evaluation indicator system. The weight determination module is used to determine the initial weight coefficients based on the relative importance of each indicator, and to classify each indicator according to the numerical distribution characteristics of each indicator to correct the initial weight coefficients and obtain the final weight coefficients. The comprehensive evaluation module is used to comprehensively evaluate the target dual drainage system based on the values ​​of each indicator and the final weighting coefficient, and obtain a comprehensive system performance score. The diagnostic report generation module is used to diagnose the performance status of the target dual drainage system based on the comprehensive performance score, the values ​​of each indicator, and the classification results of each indicator, and to identify key pipe sections, key nodes, and weak areas of the system.

[0016] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the comprehensive evaluation and diagnosis method for urban dual drainage systems described in the first aspect or any corresponding embodiment.

[0017] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute a method for comprehensive evaluation and diagnosis of an urban dual drainage system as described in the first aspect or any corresponding embodiment thereof.

[0018] Fifthly, the present invention provides a computer program product, including computer instructions, which are used to cause a computer to execute the comprehensive evaluation and diagnosis method for urban dual drainage systems described in the first aspect or any corresponding embodiment thereof.

[0019] First, this invention acquires geographic information data and hydraulic model data of the target dual-drainage system and constructs an indicator system encompassing physical and topological dimensions, providing a data foundation and a unified measurement framework for subsequent evaluation. Second, parameters are extracted from the data, and the values ​​of each indicator are calculated, transforming the raw data into characteristic parameters reflecting the system's structure and performance. Third, initial weights are determined based on the relative importance of the indicators, and the weights are adjusted according to the numerical distribution characteristics of each indicator. This process takes into account both expert experience and the inherent patterns of the data, making the weight allocation more consistent with the actual system characteristics. Then, the adjusted weights are used to comprehensively evaluate the values ​​of each indicator, obtaining a comprehensive system performance score, thus achieving a quantitative representation of the overall system performance. Finally, based on the comprehensive score, the values ​​of each indicator, and the classification results, a diagnosis is performed, identifying key pipe sections, key nodes, and weak areas of the system. Therefore, the above steps, executed sequentially, form a technical process from data acquisition, indicator calculation, weight determination, performance scoring to problem localization, applicable to the performance evaluation and modification decisions of dual-drainage systems. Attached Figure Description

[0020] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of an application scenario according to an embodiment of the present invention; Figure 2This is a first flowchart of a comprehensive assessment and diagnosis method for urban dual drainage systems according to an embodiment of the present invention; Figure 3 This is a second flowchart of a comprehensive assessment and diagnosis method for urban dual drainage systems according to an embodiment of the present invention; Figure 4 This is a third flowchart of a comprehensive assessment and diagnosis method for urban dual drainage systems according to an embodiment of the present invention; Figure 5 This is a diagram illustrating the composition of the comprehensive evaluation index system for a dual drainage system according to an embodiment of the present invention. Figure 6 This is a flowchart of the index weight determination method (AHP + natural breakpoint method) according to an embodiment of the present invention; Figure 7 This is a structural block diagram of a comprehensive assessment and diagnosis system for urban dual drainage systems according to an embodiment of the present invention; Figure 8 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0024] As an optional application scenario of this invention, such as Figure 1 As shown, the comprehensive assessment and diagnosis system for the city's dual drainage system may include at least one terminal device and at least one server. Figure 1 The system is illustrated in the example, which includes a computer 101, a mobile terminal 102, and a server 103, and the terminal devices such as the computer 101 and the mobile terminal 102 are connected to the server 103 through a network 110.

[0025] The terminal devices can be smartphones, tablets, laptops, handheld computers, or desktop computers, etc., used for assessors to input geographic information data (such as pipe length, ground road length, sub-catchment area, etc.) and hydraulic model data (such as pipe flow rate, node flow rate, etc.) of the target dual drainage system, and to receive and display the system's comprehensive performance score and diagnostic results. Server 103 can be a standalone physical server, a server cluster, a distributed system, or a cloud server providing cloud services, used to perform data processing operations such as constructing the comprehensive evaluation index system, calculating the values ​​of each index, determining and correcting weights, calculating the comprehensive performance score, and diagnosing and identifying performance status. Network 110 can be a wired or wireless network, examples of which include, but are not limited to, the Internet, corporate intranets, local area networks, wide area networks, mobile communication networks, and combinations thereof.

[0026] According to an embodiment of the present invention, a method for comprehensive evaluation and diagnosis of urban dual drainage systems is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0027] This embodiment provides a comprehensive assessment and diagnosis method for urban dual drainage systems, which can be used in the aforementioned server 103. Figure 2 This is a first flowchart of a comprehensive assessment and diagnosis method for urban dual drainage systems according to an embodiment of the present invention, as shown below. Figure 2 As shown, the process includes the following steps: Step S201: Obtain geographic information data and hydraulic model data of the target dual drainage system, and construct a comprehensive evaluation index system that includes physical attribute dimension indicators and topological attribute dimension indicators.

[0028] Furthermore, this step aims to acquire the necessary foundational data for the assessment and establish an assessment framework. Urban dual-drainage systems consist of underground drainage networks and surface road drainage channels; therefore, it is necessary to acquire geographic information data describing their spatial geometry and topological connectivity, as well as hydraulic model data describing their operational status. Based on this, a comprehensive assessment index system is constructed, comprising physical attribute dimensions and topological attribute dimensions. The physical attribute dimensions characterize the system's physical structural features, capacity, and hydraulic performance; the topological attribute dimensions characterize the system's network connectivity, node correlation, and modular structural features. The construction of this dual-dimensional index system comprehensively covers the physical and topological characteristics of the dual-drainage system, providing a complete index foundation for subsequent quantitative assessment.

[0029] Step S202: Extract parameters from the geographic information data and hydraulic model data to calculate the values ​​of each indicator in the comprehensive evaluation index system.

[0030] Furthermore, this step involves extracting parameters and quantifying indicators from the aforementioned basic data. Geographic information data and hydraulic model data typically exist in the form of raw primitive attributes or data lists, which cannot be directly used for system-level evaluation. Therefore, it is necessary to extract the underlying parameters required for calculating various indicators, such as pipe segment length and node flow distribution ratio. Subsequently, based on the extracted underlying parameters, and according to the definitions and calculation rules of each indicator, the specific values ​​of physical attribute dimension indicators and topological attribute dimension indicators are calculated respectively. This step transforms the messy raw data into indicator values ​​with clear physical or topological meanings, realizing the transformation of the multidimensional characteristics of the dual drainage system from qualitative description to quantitative representation, providing data support for subsequent weight calculation and comprehensive evaluation.

[0031] Step S203: Determine the initial weight coefficients based on the relative importance of each indicator, and classify each indicator according to the numerical distribution characteristics of each indicator to correct the initial weight coefficients, thereby obtaining the final weight coefficients.

[0032] Furthermore, this step determines the weight of each indicator in the comprehensive evaluation to reflect the degree of influence of different indicators on system performance. First, pairwise comparisons are made based on the relative importance of each indicator to construct a judgment matrix and determine the initial weight coefficients. This process reflects expert experience and subjective understanding within the field. However, purely subjective weighting can easily overlook the objective laws governing the data itself. Therefore, each indicator is further classified according to its numerical distribution characteristics to distinguish the differences in its influence range. Based on this classification result, the initial weight coefficients are objectively corrected to obtain the final weight coefficients that balance subjective experience and objective data characteristics. This step effectively avoids subjective arbitrariness and improves the rationality and accuracy of weight allocation.

[0033] Step S204: Based on the values ​​of each indicator and the final weighting coefficient, a comprehensive evaluation of the target dual drainage system is performed to obtain a comprehensive system performance score.

[0034] Furthermore, this step integrates multi-dimensional indicator information into a holistic quantitative result. After obtaining the quantitative values ​​of each indicator and the final weighting coefficients reflecting their importance, the values ​​of each indicator are dimensionless to eliminate the influence of different dimensions on the calculation results. Subsequently, the standardized indicator values ​​and the corresponding final weighting coefficients are weighted and aggregated. Through this calculation process, the indicators of physical attribute dimensions and topological attribute dimensions are scientifically integrated, ultimately outputting a comprehensive system performance score. This score objectively reflects the overall operating status and health level of the target dual-drainage system under specific working conditions in the form of a single numerical value, realizing the quantitative integration from the dispersed characteristics of multiple indicators to the overall system performance.

[0035] Step S205: Based on the comprehensive performance score, the values ​​of each indicator, and the classification results of each indicator, diagnose the performance status of the target dual drainage system and identify the key pipe sections, key nodes, and weak areas of the system.

[0036] Furthermore, this step first determines the overall performance status of the system based on the comprehensive system performance score, such as identifying whether the system's overall performance is substandard or if there is a high risk of flooding. Second, it performs a refined diagnosis by combining the specific values ​​and classification results of each indicator. According to the indicator classification, for indicators affecting local structures, threshold comparisons are used to identify key pipe sections and nodes that play a decisive role in network operation; for indicators affecting global transmission, threshold comparisons are used to identify weak areas with insufficient transmission capacity or unreasonable hierarchical structures. This step combines the overall score with local indicator characteristics, not only clarifying the overall system performance compliance status but also accurately locating the specific physical location and topological link causing performance bottlenecks.

[0037] In summary, firstly, this invention acquires geographic information data and hydraulic model data of the target dual-drainage system and constructs an indicator system encompassing physical and topological dimensions, providing a data foundation and a unified measurement framework for subsequent evaluation. Secondly, it extracts parameters from the data and calculates the values ​​of each indicator, transforming the raw data into characteristic parameters reflecting the system's structure and performance. Thirdly, it determines initial weights based on the relative importance of the indicators and classifies them according to their numerical distribution characteristics to adjust the weights. This process considers both expert experience and the inherent patterns of the data, making the weight allocation more consistent with the actual system characteristics. Then, it uses the adjusted weights to comprehensively evaluate the values ​​of each indicator, obtaining a comprehensive system performance score, thus achieving a quantitative representation of the overall system performance. Finally, based on the comprehensive score, the values ​​of each indicator, and their classification results, it performs diagnostics, identifying key pipe sections, key nodes, and weak areas of the system. Therefore, the sequential execution of the above steps forms a technical process from data acquisition, indicator calculation, weight determination, performance scoring to problem localization, applicable to the performance evaluation and modification decisions of dual-drainage systems.

[0038] This embodiment provides a comprehensive assessment and diagnosis method for urban dual drainage systems, which can be used in the aforementioned server 103. Figure 3 This is a second flowchart of a comprehensive assessment and diagnosis method for urban dual drainage systems according to an embodiment of the present invention, as shown below. Figure 3 As shown, the process includes the following steps: Step S301: Obtain geographic information data and hydraulic model data of the target dual drainage system, and construct a comprehensive evaluation index system that includes physical attribute dimension indicators and topological attribute dimension indicators.

[0039] In some alternative implementations, the target dual drainage system includes an underground drainage network subsystem and a surface road drainage channel subsystem; The physical property dimension indicators include: Horton ratio, average network density, and comprehensive hydraulic characteristic index; The topology attribute dimensions include: tree connectivity index, single-segment transport capacity, node importance index, and improved modularity.

[0040] Furthermore, underground pipe networks consist of conventional stormwater pipes, while surface roads include streets, open channels, and other spaces that can serve as drainage channels for excess stormwater. The evaluation index system is divided into two dimensions: the physical attribute dimension includes Horton ratio, average network density, and comprehensive hydraulic characteristic index. Horton ratio, calculated using a river classification method, measures the branch ratio, length ratio, and area ratio, reflecting the hierarchical rationality of the pipe network structure; average network density is the total length of pipes and roads divided by the total catchment area, reflecting the coverage level; the comprehensive hydraulic characteristic index assesses the overload of the pipes themselves and their impact on upstream and downstream areas. The topological attribute dimension includes tree connectivity index, single-segment transport capacity, node importance index, and improved modularity. The tree connectivity index combines pipe length and corresponding surface road length to measure network connectivity efficiency; single-segment transport capacity is weighted by flow proportion to assess the load sharing of each pipe segment or road; the node importance index is based on an improved PageRank algorithm, incorporating service area to identify key confluence nodes; and the improved modularity introduces shape coefficients and node importance indices to evaluate the rationality of sub-catchment division. These seven indicators characterize the performance of the dual drainage system from different perspectives.

[0041] Step S302: Extract parameters from the geographic information data and hydraulic model data to calculate the values ​​of each indicator in the comprehensive evaluation index system.

[0042] In one alternative implementation, the tree connectivity index is obtained using the following formula: ; Among them, DCI P This is the tree connectivity index. Number the nodes. Nodes extracted from this geographic information data The length of the pipe between them, Nodes extracted from this geographic information data The length of the ground road between them, L is the total length of all pipeline segments and all ground road segments extracted from this geographic information data.

[0043] In one alternative implementation, the single-segment transport capacity is obtained using the following formula: ; Among them, SCFC refers to the single-segment transmission capacity. The ratio of pipeline flow rate to total node flow rate extracted from the hydraulic model data is N, where N is the total number of all pipeline segments and ground road segments.

[0044] In one alternative implementation, the node importance index is obtained using the following formula: ; Where PR is the importance index of the node. Here, t is the damping factor, and t is the number of iterations. This represents the total number of nodes extracted from the geographic information data. This is the connection identifier extracted from the geographic information data. It is set to 1 when there is a connection between node i and node j, and 0 otherwise. Let i be the service area of ​​node i extracted from this geographic information data. This represents the total service area of ​​all nodes extracted from this geographic information data. The out-degree of node j extracted from this geographic information data. Let i be the set of upstream nodes pointing to node i.

[0045] In one alternative implementation, the improved modularity is obtained using the following formula: ; Among them, Q d To improve modularity, The shape factor of sub-catchment n extracted from this geographic information data is the ratio of the perimeter of sub-catchment n to the circumference of a circle of the same area. Let be the node importance index of node i within sub-catchment n. This refers to the service area of ​​all pipe sections and surface roads within the sub-catchment n extracted from the geographic information data. This represents the total area of ​​sub-catchment n extracted from the geographic information data.

[0046] In one alternative implementation, the comprehensive hydraulic characteristic index is obtained using the following formula: ; in, This is the comprehensive hydraulic characteristic index of pipeline j. The maximum global hydraulic performance index of pipe j is calculated based on the hydraulic model data. The maximum self-hydraulic performance index of pipe j is calculated based on the hydraulic model data. This is the cumulative hydraulic performance index of pipe j calculated based on the hydraulic model data. All three are preset weights and their sum is 1, and C is a preset constant.

[0047] Furthermore, as in the formulas above, the tree connectivity index is calculated by dividing the product of the pipe length between nodes and the length of the surface road by the square of the total system length, quantifying the spatial connectivity coupling between underground and surface areas. The single-segment transport capacity is calculated by combining the pipe flow ratio and the pipe length, objectively reflecting the efficiency of coordinated flow transport between the two channels. The node importance index incorporates damping factors, the node service area ratio, and the node exit degree for iterative calculation, accurately assessing the criticality of nodes in the topology network and water catchment allocation. The improved modularity integrates the sub-catchment shape coefficient, the node importance index within the region, and the service area ratio, precisely characterizing the structural and functional clustering features of the sub-region. The comprehensive hydraulic characteristic index integrates three sub-indicators: maximum global hydraulic performance, maximum self-hydraulic performance, and cumulative hydraulic performance, comprehensively representing the comprehensive hydraulic health status of the pipe segment under different operating conditions.

[0048] Step S303: Perform pairwise importance comparisons on each indicator to construct a judgment matrix, and determine the initial weight coefficients based on the eigenvectors of the judgment matrix.

[0049] Furthermore, for the seven identified evaluation indicators (Houghton ratio, average network density, comprehensive hydraulic characteristic index, tree connectivity index, single-segment transport capacity, node importance index, and improvement modularity), domain experts or engineers score the relative importance of each pair of indicators. For example, they compare whether the node importance index or the single-segment transport capacity has a greater impact on system performance. All comparison results constitute a judgment matrix, which is a square matrix whose elements represent the importance of row indicators relative to column indicators. Then, the judgment matrix is ​​normalized, and its eigenvector is calculated. Each component in the eigenvector is the initial weight coefficient of the corresponding indicator. The advantage of this method is that it quantifies subjective experience into numerical values, and the consistency check can determine the rationality of the expert judgment. The initial weight coefficients reflect the importance ranking of each indicator under ideal conditions, but have not yet considered the actual data distribution characteristics, so further adjustments are needed.

[0050] Step S304: Based on the numerical distribution characteristics of each indicator, perform clustering to divide each indicator into local indicators and global indicators.

[0051] Furthermore, this step involves clustering based on the numerical distribution characteristics of each indicator to distinguish between local and global indicators. Local indicators are those with significant numerical differences across different sub-regions or pipe sections, reflecting local characteristics; global indicators are those with relatively stable values ​​throughout the system, reflecting overall characteristics. Specifically, the calculation results of each of the seven indicators (i.e., the value of each indicator, which may contain multiple samples, such as a corresponding comprehensive hydraulic characteristic index for each pipe) are treated as a set of ordered data, and then clustered. A commonly used clustering method is variance minimization clustering: all values ​​are sorted in ascending order, attempting to divide them into two categories, calculating the sum of squared deviations within each category, and minimizing the sum of squared deviations between the two categories. After iterative adjustments, the optimal split point is found. Categories with smaller values ​​are labeled as local indicators, and categories with larger values ​​are labeled as global indicators. This classification provides a basis for subsequent weight adjustments: local indicators should be given appropriately higher weights in the comprehensive evaluation (reflecting the system's variability); the weights of global indicators can be relatively reduced.

[0052] Step S305: Quantify and assign values ​​to the initial weight coefficient and the classification results obtained after index division, and perform fusion and normalization processing on the quantization results to obtain the final weight coefficient.

[0053] Furthermore, this step merges the initial weight coefficients and classification results to obtain the final weight coefficients. First, the initial weight coefficients and classification results need to be quantified and assigned values ​​to ensure they are on the same scale. For the initial weight coefficients, since they are numerical values ​​(summing up to 1), they can be used directly or linearly scaled. For the classification results, local and global indicators need to be converted to numerical values. For example, local indicators can be assigned higher scores (e.g., 10 points), and global indicators can be assigned lower scores (e.g., 5 points). Specific scores can be determined based on engineering experience or through experimentation. Then, the initial weight coefficients for each indicator are merged with the classification result values. This merging method can be addition or multiplication to obtain the median value for each indicator. Finally, the median values ​​for all indicators are normalized by dividing each median value by the sum of all median values ​​to obtain the final weight coefficients for each indicator. The weights obtained in this way reflect both the expert's subjective judgment of the indicator's importance and the global or local characteristics of the indicator in the actual data, making the evaluation results more objective and adaptable to the characteristics of different systems.

[0054] Step S306: Perform dimensionless processing on the values ​​of each indicator to obtain the standardized values ​​of each indicator.

[0055] Furthermore, since the seven evaluation indicators have different dimensions and orders of magnitude, and the node importance index is a dimensionless relative value, typically between 0 and 1, directly multiplying these raw values ​​by their weights and summing them would allow indicators with larger dimensions to dominate the result, leading to a distorted overall evaluation. Therefore, before weighted summation, the values ​​of each indicator need to be dimensionless. After dimensionless summation, each indicator obtains a standardized value. These standardized values ​​eliminate dimensional differences, making different indicators comparable. The standardized results are typically between 0 and 1, facilitating subsequent weighted summation.

[0056] Step S307: The standardized values ​​of each indicator are weighted and summed with the corresponding final weight coefficients to obtain the overall performance score of the system.

[0057] In some alternative implementations, step S307 includes: The values ​​of each indicator are dimensionless to obtain their standardized values. The standardized values ​​of each indicator are weighted and summed with their corresponding final weight coefficients to obtain the overall performance score of the system.

[0058] Furthermore, this step calculates the overall system performance score through weighted summation. First, the standardized value of each indicator obtained in step S306 is multiplied by the corresponding final weight coefficient (from step S305) to obtain the weighted contribution value of each indicator. The final weight coefficient reflects the importance of the indicator in the comprehensive evaluation, and the sum of the weight coefficients of all indicators is 1. Then, the weighted contribution values ​​of all indicators are added together, and the result is the overall system performance score. The higher the score, the better the overall performance of the dual drainage system, i.e., strong drainage capacity, reasonable structure, sufficient redundancy, and low risk of waterlogging; the lower the score, the more problems or defects exist in the system. This score can be used for horizontal comparison of different drainage schemes, and can also be used for effect evaluation before and after the same system is modified, providing a quantitative basis for decision-making.

[0059] Step S308: Based on the comprehensive performance score, the values ​​of each indicator, and the classification results of each indicator, diagnose the performance status of the target dual drainage system and identify the key pipe sections, key nodes, and weak areas of the system.

[0060] In one optional implementation, step S308 includes: When the comprehensive hydraulic characteristic index of each pipe segment is less than the target value, the corresponding pipe segment is identified as a critical pipe segment. When the branch ratio of the Horton ratio is outside the preset reasonable range, the hierarchical region corresponding to the abnormal branch ratio is identified as a weak region. When the overall performance score of the system is lower than the preset performance threshold, it is determined that the overall performance of the system is substandard and there is a high risk of waterlogging. Based on the classification results of each indicator, nodes whose importance index is higher than the preset importance threshold are identified as critical nodes, and pipe sections or ground road sections whose single-segment transport capacity is lower than the preset capacity threshold are identified as weak links.

[0061] Furthermore, the diagnostic process follows these rules. First, for each pipeline segment, its comprehensive hydraulic characteristic index is compared with the target value. The target value is typically set to 0: when the index is less than 0, it indicates that upstream flooding has a relatively small impact on the pipeline segment, and the pipeline's drainage capacity is good; when the index is greater than 0, it indicates that upstream flooding has a significant impact on the pipeline segment, and the pipeline has flooding problems. Therefore, if the index is less than the target value, the pipeline segment is identified as a critical segment and needs to be prioritized for renovation. Second, regarding the branch ratio of the Horton ratio, if this value is not within the preset reasonable range (e.g., between 1.5 and 4), it indicates that the hierarchical structure of the system is unreasonable, such as too many or too few branches. In this case, the hierarchical area corresponding to the abnormal branch ratio (such as a certain level of pipeline and its sub-catchment area) is identified as a weak area. Third, the system's comprehensive performance score is compared with the preset performance compliance threshold. If it is lower than the threshold, the overall system performance is determined to be substandard, and there is a high risk of flooding. Furthermore, based on the classification results of each indicator (local or global), nodes with an importance index higher than a preset threshold are identified as critical nodes, as failure of these nodes would affect large-scale drainage; pipe sections or road sections with a single-segment transport capacity lower than a preset capacity threshold are identified as weak links, indicating that they are under excessive load or have insufficient capacity. Through these diagnoses, key problem areas can be systematically identified.

[0062] The following is a general description of the disclosure in this embodiment: Please see Figure 4 The diagram illustrates a third flowchart of a comprehensive assessment and diagnosis method for urban dual drainage systems. In practical applications, the first step is to acquire geographic information data and hydraulic model data of the target dual drainage system. As a specific example of this implementation, SWMM simulation software is used to build a model of a drainage area. Relevant reports are read from the SWMM simulation results, and the data required to calculate various indicators is extracted. Geographic information data includes: pipe length and diameter of the underground drainage network subsystem, road length and cross-sectional area of ​​the surface road drainage channel subsystem, and node soil cover depth, etc. Hydraulic model data includes: pipe flow rate, node flow rate, and node overload depth, etc. The extracted data is formatted and the data units are standardized.

[0063] Please see Figure 5 The diagram showing the composition of the comprehensive evaluation index system for dual drainage systems and... Figure 6The flowchart shown illustrates the method for determining indicator weights (AHP + Natural Breakpoint Method). Based on the data obtained above, the values ​​of the seven core evaluation indicators are calculated using the following method. These seven indicators include: Horton Ratio, Average Network Density, Comprehensive Hydraulic Properties Index (CHPI), Tree Connectivity Index (DCI), and others. P Single-segment transport capacity (SCFC), node importance index (PR), and improved modularity (Q) d ).

[0064] For the Horton ratio, the Strahler river classification method was used to classify the underground drainage network subsystem and the surface road drainage channel subsystem into different levels. The branch ratio, length ratio, and area ratio were calculated for each level, using the following formulas: Branch ratio: ; Pipe length ratio: ; Pipeline service area ratio: ; in, The number of drainage pipes. , The first Level and First The number of drainage pipes; For the average pipe length, and The first Level and First The average length of the Class I drainage pipe; For average service area, and They are respectively Level and The average service area of ​​a Class I drainage pipeline; w represents the pipeline class. .

[0065] Network average density measures the coverage and service availability of a dual-drainage system network within a region; a higher value indicates a larger service area. The calculation formula is: ; Where L is the sum of the lengths of all pipeline segments and all ground road segments; This represents the total area of ​​the catchment area.

[0066] The Comprehensive Hydraulic Performance Index (CHPI) is used to assess pipeline drainage capacity. It is calculated by weighting the Maximum Global Hydraulic Performance Index (MGHPI), the Maximum Self-Hydraulic Performance Index (MSHPI), and the Accumulated Hydraulic Performance Index (AHPI). This index reflects both the pipeline's own overload level and its impact on upstream pipeline overload, while also taking into account the temporal and spatial variations in pipeline drainage capacity and addressing abrupt changes in pipeline elevation.

[0067] Global Hydraulic Performance Index (GHPI): Reflects the impact of pipelines on the overall system's drainage capacity. The calculation formula is: ; ; ; Self-Hydraulic Performance Index (SHPI): Reflects the degree of overload on the pipeline itself. The calculation formula is: ; The Accumulative Hydraulic Performance Index (AHPI) reflects the change in a pipeline's drainage capacity over a specific period. The calculation formula is as follows: ; ; in, The responsibility that pipeline J should bear for its own overloading; The responsibility that pipeline j should bear for overloading upstream pipeline k; The overload depth at the end of pipe j-1; Let J be the overload depth at the end of pipe j; The soil cover thickness at the beginning of pipe j; The responsibility that the upstream pipeline and the pipeline itself should bear for its overloading; The comprehensive hydraulic performance index of pipeline j; The maximum global hydraulic performance index (or classification value) for pipe j. is the maximum self-hydraulic performance index (or classification value) of pipe j. The cumulative hydraulic performance index (or classification value) of pipe j. for The weights are between 0 and 1; for The weights are between 0 and 1; for The weights are set to 0-1; C is a constant. , and The sum equals 1. The constant C is added to deal with reverse slope pipes, because there are no reverse slope pipes without problems.

[0068] Tree connectivity index (DCI) P The calculation formula is: ; Among them, DCI P The tree connectivity index is... Number the nodes. Nodes extracted from the geographic information data The length of the pipe between them, Nodes extracted from the geographic information data The length of the ground road between them, L is the total length of all pipeline segments and all ground road segments extracted from the geographic information data.

[0069] The formula for calculating the single-segment transport capacity (SCFC) is as follows: ; Among them, SCFC refers to the single-segment transmission capacity. N represents the ratio of pipeline flow rate extracted from the hydraulic model data to the total flow rate at the nodes, where N is the total number of all pipeline segments and ground road segments.

[0070] The formula for calculating the node importance index (PR) based on the improved PageRank algorithm is as follows: ; Wherein, PR is the node importance index. Here, t is the damping factor, and t is the number of iterations. This represents the total number of nodes extracted from the geographic information data. The connection identifier is extracted from the geographic information data. It is set to 1 when there is a connection between node i and node j, and 0 otherwise. The service area of ​​node i is extracted from the geographic information data. The total service area of ​​all nodes extracted from the geographic information data. The out-degree of node j extracted from the geographic information data. Let i be the set of upstream nodes pointing to node i.

[0071] Improved modularity of sub-catchment areas Q d The calculation formula is: ; Among them, Q d For the improved modularity, The shape factor of sub-catchment n extracted from the geographic information data is the ratio of the perimeter of sub-catchment n to the perimeter of a circle of the same area. Let be the node importance index of node i within sub-catchment n. This refers to the service area of ​​all pipe sections and surface roads within the sub-catchment n extracted from the geographic information data. The total area of ​​sub-catchment n extracted from the geographic information data.

[0072] After completing the numerical calculations for the seven indicators, it is necessary to determine the weight coefficients of each indicator in the comprehensive evaluation. The weight determination process consists of three sub-steps: calculating the initial weight coefficients using the Analytic Hierarchy Process (AHP); classifying each indicator using the natural breakpoint method to distinguish between global and local indicators; and correcting the initial weight coefficients based on the classification results to obtain the final weight coefficients.

[0073] Using a 1-9 scale, industry experts or engineers were invited to evaluate the pairwise importance of the indicator system constructed in this invention, thus building a judgment matrix for the corresponding level. Following the conventional calculation rules of the Analytic Hierarchy Process (AHP), the indicator weights corresponding to each expert were calculated. The weights obtained from multiple experts or engineers were then arithmetically averaged to obtain the final combined weight of each evaluation indicator, quantifying the impact of each indicator on the operational characteristics of the dual-drainage system.

[0074] A judgment matrix A is constructed by experts comparing the relative importance of each pair of indicators. The indicator comparison judgment relies on a 1-9 comparison scale, which facilitates structured decision-making; the scale uses positive integers from 1 to 9. If A... j Compared to A i Important, corresponding to a ji =1 / n.

[0075] ; Normalize the judgment matrix: ; Add the elements of the normalized matrix together: ; After normalization, the initial weight coefficients of each indicator are obtained: ; in, For matrix elements, To determine the first... line, number The data in the column, The first normalized matrix line, number The data in the column, For the first The weight of each indicator.

[0076] The initial weight coefficients for each indicator are obtained by arithmetically averaging the weights obtained from multiple experts or engineers.

[0077] The natural breakpoint method is used to automatically classify the weights of the AHP index combination, dividing all samples into two level intervals. The smaller value is called Class I, which represents local indicators, and the larger value is called Class II, which represents global indicators.

[0078] For an ordered data First, calculate the sum of squared deviations of the mean of the data: ; in, is the data mean; n is the number of data points.

[0079] Then, the data is randomly grouped according to the number of input categories, and this grouping is used as the initial clustering result. And calculate the sum of squared deviations of the class mean for each class: ; Where K is the number of categories; For the i-th class, for The number of data items contained; for The j-th data point; Let be the mean of the i-th class.

[0080] Using SDCM as the optimization objective, different clusters are iteratively combined, and the cluster combination with the smallest SDCM value is selected as the data result of the natural breakpoint method. The clustering effect is expressed as variance fit.

[0081] ; The initial weight coefficients calculated by the Analytic Hierarchy Process (AHP) and the indicator classification results obtained by the natural breakpoint method are each assigned a 10-point scale. For example, the initial weight coefficients are linearly mapped to a 0-10 point range, with higher scores assigned to local indicators and lower scores assigned to global indicators. The 10-point scale scores for each indicator are then merged and summarized (e.g., added or multiplied), and the merged results are normalized to obtain the final weight coefficients for each indicator. The weights obtained in this way reflect both the expert's subjective judgment of the importance of each indicator and the global or local characteristics of the indicators revealed by the data itself.

[0082] After obtaining the final weighting coefficients for each indicator, a weighted summation method is used to comprehensively evaluate the dual-drainage system. First, the raw values ​​of each indicator are dimensionless (i.e., standardized) to eliminate the influence of different dimensions and orders of magnitude, resulting in standardized values ​​for each indicator. Then, the standardized value of each indicator is multiplied by its corresponding final weighting coefficient, and all products are summed to obtain the overall system performance score. The calculation formula is as follows: ; in, ~ These are the Horton ratio and the average network density, respectively. Hydraulic Characteristic Index (CHPI) and Dendritic Connectivity Index (DCI) P Single-segment transport capacity (SCFC), node importance index (PR), and improved modularity ( The weighting coefficients of H, ρ, C, and D. P S, PR, Q d These are the Horton ratio, network average density (ρ), hydraulic characteristic index (CHPI), and dendritic connectivity index (DCI). P Single-segment transport capacity (SCFC), node importance index (PR), and improved modularity (Q) d The standardized value of ).

[0083] By constructing evaluation criteria (see Table 1), the calculation results are analyzed and interpreted to identify key pipe sections, key nodes, and weak areas of the system. The optimal numerical range and the meaning of the results for each indicator are shown in Table 1.

[0084] Table 1

[0085] Based on the above evaluation criteria and the calculated values ​​of each indicator, the comprehensive performance score, and the indicator classification results, the following diagnoses are made: If the Comprehensive Hydraulic Characteristics Index (CHPI) is positive, the corresponding pipe section is determined to have waterlogging problems; if the branch ratio of the Horton ratio is not within the range of 1.5-4, the system's hierarchical structure is determined to be unreasonable; if the system's comprehensive performance score is lower than the preset threshold, the overall system performance is determined to be substandard, with a high risk of waterlogging. Simultaneously, based on the classification results of each indicator (local or global indicators), key pipe sections, key nodes, and weak areas are identified, providing specific guidance for the system's optimization and transformation.

[0086] The technical solution of the present invention will be verified through a simple example below.

[0087] Example 1: This example uses a drainage area in City Q (hereinafter referred to as Case Q) as an example to demonstrate the specific application process of the comprehensive assessment and diagnosis method for dual drainage systems.

[0088] Case Q covers a service area of ​​136 hectares, comprising 28 sub-catchments, 34 nodes (including 4 outlets), 30 drainage pipes, and 26 surface roads. The average impermeable area within the region is approximately 62.5%. The simulation report for this case was retrieved from the SWMM simulation software, extracting parameters such as pipe length and diameter for the stormwater drainage system, road length and cross-sectional area for the surface road system, and node cover depth. Data formatting and unit standardization were then performed. Based on the calculation formulas for the aforementioned seven indicators (Houghton ratio, average network density, comprehensive hydraulic characteristic index, tree connectivity index, single-segment transport capacity, node importance index, and improved modularity), quantitative calculations were performed sequentially using MATLAB to obtain the numerical values ​​for each indicator.

[0089] For comparison, Example7 (hereinafter referred to as the SWMM Case), a case file included with the SWMM software, was selected. This case covers a service area of ​​11.74 hectares, comprising 7 sub-catchments, 16 nodes (including 1 outlet), 8 drainage pipes, and 15 sections of surface roads. The average impermeable area within the region is approximately 56%. The same calculation method was used to obtain the values ​​for each indicator in the SWMM Case. The calculation results and overall performance scores for the two cases are shown in Table 2.

[0090] Table 2

[0091] Table 2 shows that among the seven evaluation indicators, the SWMM case outperforms the Q case in six indicators: tree connectivity index, single-segment transport capacity, node importance index, improved modularity, average network density, and comprehensive hydraulic characteristic index (high proportion of locally positive pipelines). The Q case is comparable to the SWMM case only in terms of Horton ratio branch ratio. After standardization and weighting, the comprehensive performance scores are: SWMM case 0.556, Q case 0.343, indicating that the comprehensive performance of the SWMM case is significantly better than that of the Q case.

[0092] Overall assessment: The SWMM case demonstrates stable system operation and good performance, with the ability to cope with extreme weather and a low risk of flooding; the Q case, on the other hand, exhibits unstable overall operation. Although it can meet daily drainage needs, it has a poor ability to cope with extreme weather risks and is prone to flooding disasters, requiring subsequent maintenance and renovation.

[0093] In response to the issues identified in the Q case evaluation, the following optimization suggestions are proposed: First, prioritize the addition of drainage pipelines in areas with extremely low pipe network density, such as S14 and S16 in the sub-catchment areas, to increase the system's average density from 10.65 km / km² to the planned standard, thereby enhancing coverage capacity; Second, prioritize the expansion of pipe diameters or the addition of storage facilities for pipelines such as C10 and C11 with a positive Comprehensive Hydraulic Performance Index (CHPI) (i.e., CHPI ≥ 0), and pipelines such as C26 and C17 with a MSHPI of Class A, to alleviate their continuous overload pressure; Third, regarding the branch ratio R... b The issue of the value being too high (6.86) can be addressed by appropriately adding branch pipes to pipeline 3 to optimize flow distribution.

[0094] Example 2: This example compares and analyzes the evaluation metrics of this invention with those commonly used in other complex networks to verify the superiority and engineering suitability of this invention.

[0095] We compared the topology metrics commonly used in other complex network research (average degree, global efficiency, modularity, eigenvector centrality) with the topology attribute-related metrics (tree connectivity index, single-segment transport capacity, improved modularity) in the evaluation metrics of this invention. The comparison results are shown in Table 3.

[0096] Table 3

[0097] Comparative results show that: by introducing pipe length and path length, the tree-like connectivity index more clearly characterizes the network scale and connectivity than the average degree; the single-segment transport capacity can directly represent the system's drainage capacity, which is superior to the global efficiency that can only evaluate information transmission; by introducing service area, the improved node importance index (based on the PageRank algorithm) can more accurately identify key pipelines and nodes; the improved modularity can simultaneously reflect the details within sub-catchments and the overall modularity of the system. Comprehensive comparative analysis shows that the evaluation index (topology attribute related) of this invention can more comprehensively characterize the structure, discharge capacity, and other characteristics of a dual-drainage system, and the evaluation results are superior to other commonly used indicators for complex networks.

[0098] In summary, through the verification of the above embodiments, the present invention has the following technical effects: First, by constructing a comprehensive evaluation index system covering physical attribute indicators (Houghton ratio, average network density, comprehensive hydraulic characteristic index) and topological attribute indicators (tree connectivity index, single-segment transport capacity, node importance index, and improved modularity), it overcomes the shortcomings of traditional methods in terms of fragmented evaluation objects and single evaluation dimensions, and can simultaneously quantify the hydraulic performance and network structure of a dual-drainage system; Second, by modifying the tree connectivity index (introducing the product of pipe length and road length) and improving modularity (introducing shape coefficient and node importance index), the present invention achieves the following effects: The method integrates engineering physical parameters and network topology attributes, making the evaluation results more consistent with actual drainage performance. Third, it uses a weighting method combining the analytic hierarchy process (AHP) and the natural breakpoint method, along with the Comprehensive Hydraulic Characteristics Index (CHPI) for identifying problematic pipe sections, providing a quantifiable basis for the planning, renovation, and risk management of dual drainage systems. Fourth, verification through two cases of different scales and structures (SWMM and Q cases) demonstrates that this method has good applicability to coupled drainage systems of different scales.

[0099] This embodiment also provides a comprehensive assessment and diagnosis system for urban dual drainage systems. This system is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. Although the system described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0100] This embodiment provides a comprehensive assessment and diagnosis system for urban dual drainage systems, such as... Figure 7 As shown, it includes: The data preprocessing module 701 is used to acquire geographic information data and hydraulic model data of the target dual drainage system, and to construct a comprehensive evaluation index system that includes physical attribute dimension indicators and topological attribute dimension indicators. The multi-dimensional indicator calculation module 702 is used to extract parameters from the geographic information data and hydraulic model data in order to calculate the values ​​of each indicator in the comprehensive evaluation indicator system. The weight determination module 703 is used to determine the initial weight coefficients based on the relative importance of each indicator, and to classify each indicator according to the numerical distribution characteristics of each indicator to correct the initial weight coefficients and obtain the final weight coefficients. The comprehensive evaluation module 704 is used to conduct a comprehensive evaluation of the target dual drainage system based on the values ​​of each indicator and the final weighting coefficient, and obtain a comprehensive system performance score. The diagnostic report generation module 705 is used to diagnose the performance status of the target dual drainage system based on the comprehensive performance score, the values ​​of each indicator, and the classification results of each indicator, and to identify the key pipe sections, key nodes, and weak areas of the system.

[0101] In some alternative implementations, the target dual drainage system includes an underground drainage network subsystem and a surface road drainage channel subsystem; The physical property dimension indicators include: Horton ratio, average network density, and comprehensive hydraulic characteristic index; The topology attribute dimensions include: tree connectivity index, single-segment transport capacity, node importance index, and improved modularity.

[0102] In some alternative implementations, the tree connectivity index is obtained using the following formula: ; Among them, DCI P This is the tree connectivity index. Number the nodes. Nodes extracted from this geographic information data The length of the pipe between them, Nodes extracted from this geographic information data The length of the ground road between them, L is the total length of all pipeline segments and all ground road segments extracted from this geographic information data.

[0103] In some alternative implementations, the single-segment transport capacity is obtained using the following formula: ; Among them, SCFC refers to the single-segment transmission capacity. The ratio of pipeline flow rate to total node flow rate extracted from the hydraulic model data is N, where N is the total number of all pipeline segments and ground road segments.

[0104] In some optional implementations, the node importance index is obtained using the following formula: ; Where PR is the importance index of the node. Here, t is the damping factor, and t is the number of iterations. This represents the total number of nodes extracted from the geographic information data. This is the connection identifier extracted from the geographic information data. It is set to 1 when there is a connection between node i and node j, and 0 otherwise. Let i be the service area of ​​node i extracted from this geographic information data. This represents the total service area of ​​all nodes extracted from this geographic information data. The out-degree of node j extracted from this geographic information data. Let i be the set of upstream nodes pointing to node i.

[0105] In some alternative implementations, this improved modularity is obtained using the following formula: ; Among them, Q d To improve modularity, The shape factor of sub-catchment n extracted from this geographic information data is the ratio of the perimeter of sub-catchment n to the circumference of a circle of the same area. Let be the node importance index of node i within sub-catchment n. This refers to the service area of ​​all pipe sections and surface roads within the sub-catchment n extracted from the geographic information data. This represents the total area of ​​sub-catchment n extracted from the geographic information data.

[0106] In some alternative implementations, the comprehensive hydraulic characteristic index is obtained using the following formula: ; in, This is the comprehensive hydraulic characteristic index of pipeline j. The maximum global hydraulic performance index of pipe j is calculated based on the hydraulic model data. The maximum self-hydraulic performance index of pipe j is calculated based on the hydraulic model data. This is the cumulative hydraulic performance index of pipe j calculated based on the hydraulic model data. All three are preset weights and their sum is 1, and C is a preset constant.

[0107] In some alternative implementations, the weight determination module 703 is further configured to: Each indicator is compared pairwise to construct a judgment matrix, and the initial weight coefficient is determined based on the eigenvectors of the judgment matrix. Based on the numerical distribution characteristics of each indicator, clustering is performed to divide the indicators into local indicators and global indicators. The initial weight coefficient and the classification results obtained after index division are quantified and assigned values ​​respectively, and the quantified and assigned values ​​are fused and normalized to obtain the final weight coefficient.

[0108] In some alternative implementations, the diagnostic report generation module 705 is further configured to: When the comprehensive hydraulic characteristic index of each pipe segment is less than the target value, the corresponding pipe segment is identified as a critical pipe segment. When the branch ratio of the Horton ratio is outside the preset reasonable range, the hierarchical region corresponding to the abnormal branch ratio is identified as a weak region. When the overall performance score of the system is lower than the preset performance threshold, it is determined that the overall performance of the system is substandard and there is a high risk of waterlogging. Based on the classification results of each indicator, nodes whose importance index is higher than the preset importance threshold are identified as critical nodes, and pipe sections or ground road sections whose single-segment transport capacity is lower than the preset capacity threshold are identified as weak links.

[0109] The comprehensive assessment and diagnosis system for urban dual drainage systems provided in this embodiment of the invention can execute the comprehensive assessment and diagnosis method for urban dual drainage systems provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method. Further functional descriptions of the above modules and units are the same as in the corresponding embodiments described above, and will not be repeated here.

[0110] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0111] The following is a detailed reference. Figure 8 The diagram illustrates a structural schematic suitable for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 801, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 802 or a program loaded from memory 808 into random access memory (RAM) 803. The RAM 803 also stores various programs and data required for the operation of the electronic device. The processor 801, ROM 802, and RAM 803 are interconnected via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0112] Typically, the following devices can be connected to I / O interface 805: input devices 806 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 807 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 808 including, for example, magnetic tapes, hard disks, etc.; and communication devices 809. Communication device 809 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 8 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0113] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 809, or installed from a memory 808, or installed from a ROM 802. When the computer program is executed by the processor 801, it performs the functions defined in the method for comprehensive assessment and diagnosis of an urban dual drainage system according to embodiments of the present invention.

[0114] Figure 8 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of the present invention.

[0115] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, it implements the comprehensive assessment and diagnosis method for urban dual drainage systems shown in the above embodiments.

[0116] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0117] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and all such modifications and variations fall within the scope defined by the invention.

Claims

1. A comprehensive assessment and diagnosis method for urban dual drainage systems, characterized in that, The method includes: Acquire geographic information data and hydraulic model data of the target dual drainage system, and construct a comprehensive evaluation index system that includes physical attribute dimension indicators and topological attribute dimension indicators; Parameters are extracted from the geographic information data and hydraulic model data to calculate the values ​​of each indicator in the comprehensive evaluation index system; The initial weight coefficients are determined based on the relative importance of each indicator, and the indicators are classified according to the numerical distribution characteristics of each indicator to correct the initial weight coefficients and obtain the final weight coefficients. Based on the values ​​of each indicator and the final weighting coefficient, the target dual drainage system is comprehensively evaluated to obtain a comprehensive system performance score. Based on the comprehensive performance score, the values ​​of each indicator, and the classification results of each indicator, the performance status of the target dual drainage system is diagnosed, and key pipe sections, key nodes, and weak areas of the system are identified.

2. The method according to claim 1, characterized in that, The target dual drainage system includes an underground drainage pipe network subsystem and a surface road drainage channel subsystem; The physical property dimension indicators include: Horton ratio, average network density, and comprehensive hydraulic characteristic index; The topology attribute dimensions include: tree connectivity index, single-segment transport capacity, node importance index, and improved modularity.

3. The method according to claim 2, characterized in that, The tree connectivity index is obtained using the following formula: ； Among them, DCI P The tree connectivity index is... Number the nodes. Nodes extracted from the geographic information data The length of the pipe between them, Nodes extracted from the geographic information data The length of the ground road between them, L is the total length of all pipeline segments and all ground road segments extracted from the geographic information data.

4. The method according to claim 3, characterized in that, The single-segment transport capacity is obtained using the following formula: ； Among them, SCFC refers to the single-segment transmission capacity. N represents the ratio of pipeline flow rate extracted from the hydraulic model data to the total flow rate at the nodes, where N is the total number of all pipeline segments and ground road segments.

5. The method according to claim 2, characterized in that, The node importance index is obtained using the following formula: ； Wherein, PR is the node importance index. Here, t is the damping factor, and t is the number of iterations. This represents the total number of nodes extracted from the geographic information data. The connection identifier is extracted from the geographic information data. It is set to 1 when there is a connection between node i and node j, and 0 otherwise. The service area of ​​node i is extracted from the geographic information data. The total service area of ​​all nodes extracted from the geographic information data. The out-degree of node j extracted from the geographic information data. Let i be the set of upstream nodes pointing to node i.

6. The method according to claim 2, characterized in that, The improved modularity is obtained using the following formula: ； Among them, Q d For the improved modularity, The shape factor of sub-catchment n extracted from the geographic information data is the ratio of the perimeter of sub-catchment n to the perimeter of a circle of the same area. Let be the node importance index of node i within sub-catchment n. This refers to the service area of ​​all pipe sections and surface roads within the sub-catchment n extracted from the geographic information data. The total area of ​​sub-catchment n extracted from the geographic information data.

7. The method according to claim 2, characterized in that, The comprehensive hydraulic characteristic index is obtained using the following formula: ； in, The comprehensive hydraulic characteristic index of pipeline j is... The maximum global hydraulic performance index of pipe j is calculated based on the hydraulic model data. The maximum self-hydraulic performance index of pipe j is calculated based on the hydraulic model data. This refers to the cumulative hydraulic performance index of pipe j calculated based on the hydraulic model data. All three are preset weights and their sum is 1, and C is a preset constant.

8. The method according to claim 2, characterized in that, The process of determining initial weight coefficients based on the relative importance of each indicator, and classifying each indicator according to its numerical distribution characteristics to correct the initial weight coefficients, to obtain the final weight coefficients, includes: Each indicator is compared pairwise to construct a judgment matrix, and the initial weight coefficients are determined based on the eigenvectors of the judgment matrix. Based on the numerical distribution characteristics of each indicator, clustering is performed to divide each indicator into local indicators and global indicators. The initial weight coefficients and the classification results obtained after index division are quantified and assigned values, and the quantified and assigned values ​​are fused and normalized to obtain the final weight coefficients.

9. The method according to any one of claims 2 to 8, characterized in that, Based on the comprehensive performance score, the values ​​of each indicator, and the classification results of each indicator, the performance status of the target dual drainage system is diagnosed, and key pipe sections, key nodes, and weak areas of the system are identified, including: When the comprehensive hydraulic characteristic index of each pipe segment is less than the target value, the corresponding pipe segment is identified as a critical pipe segment. When the branch ratio of the Horton ratio is outside the preset reasonable range, the hierarchical region corresponding to the abnormal branch ratio is identified as a weak region. When the overall performance score of the system is lower than the preset performance threshold, it is determined that the overall performance of the system is substandard and there is a high risk of waterlogging. Based on the classification results of the indicators, nodes with a node importance index higher than a preset importance threshold are identified as key nodes, and pipe sections or ground road sections with a single-segment transport capacity lower than a preset capacity threshold are identified as weak links.

10. A comprehensive assessment and diagnostic system for urban dual drainage systems, characterized in that, The system includes: The data preprocessing module is used to acquire geographic information data and hydraulic model data of the target dual drainage system, and to construct a comprehensive evaluation index system that includes physical attribute dimension indicators and topological attribute dimension indicators. The multi-dimensional indicator calculation module is used to extract parameters from the geographic information data and hydraulic model data in order to calculate the values ​​of each indicator in the comprehensive evaluation indicator system. The weight determination module is used to determine the initial weight coefficients based on the relative importance of each indicator, and to classify each indicator according to the numerical distribution characteristics of each indicator to correct the initial weight coefficients and obtain the final weight coefficients. The comprehensive evaluation module is used to comprehensively evaluate the target dual drainage system based on the values ​​of each indicator and the final weighting coefficient, and obtain a comprehensive system performance score. The diagnostic report generation module is used to diagnose the performance status of the target dual drainage system based on the comprehensive performance score, the values ​​of each indicator, and the classification results of each indicator, and to identify key pipe sections, key nodes, and weak areas of the system.

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