Weighing and collaborative evaluation method for health status-failure consequence-management and control capability of urban sewage system

Abstract

The invention discloses a weighing and collaborative evaluation method for health status-failure consequence-management and control capability of an urban sewage system, and belongs to the field of sewage system and street management. According to the method, a sewage system whole-process evaluation system of'health state-failure consequence-management and control capability 'is constructed, and a game-fuzzy comprehensive evaluation method is adopted, so that whole-process operation evaluation of the urban sewage system is realized. Through the theory of trade-off and collaboration, the space trade-off and collaboration relation of the streets is identified to obtain three types of unbalanced streets, balanced development of the urban sewage system is realized, the management efficiency of the sewage system can be effectively improved, and blind investment is reduced.

Description

Technical Field

[0001] This invention relates to a method for balancing and coordinating the "health status, failure consequences, and control capabilities" of urban sewage systems. This method involves a full-process evaluation system for sewage systems based on the "health status, failure consequences, and control capabilities" framework. It also uses the theory of "balancing and coordinating" to identify three types of streets, which can effectively improve the management efficiency of sewage systems and reduce blind investment. This invention belongs to the field of sewage system and street management. Background Technology

[0002] Urban wastewater systems are a crucial component of urban drainage systems, bearing the critical mission of collecting, purifying, and properly disposing of urban wastewater. They also prevent environmental impacts caused by mismanagement, ensuring the safety of the urban drainage system and the quality of the urban water environment. Currently, most urban wastewater networks suffer from structural and functional defects. These health issues can lead to leaks and overflows, environmental pollution, and infiltration of external water. The "health status" of the wastewater system ensures normal urban operation and reflects its overall health. The "failure consequences" of a wastewater system failure consider the severity of its impact, which can have serious consequences for the social environment, such as loss of public property, disruption of services to critical structures, and water pollution. Furthermore, a significant proportion of wastewater infiltration occurs, impacting the influent volume and quality of wastewater treatment plants, affecting their stable operation, leading to inefficient treatment, and pollutant overflows into rivers. This severely impacts residents' quality of life and normal production and daily life, hindering the city's sustainable development. The existing sewage systems suffer from uneven distribution in terms of monitoring coverage, emergency response capabilities, operation and maintenance management scale, and dispatch control in sewage pipe networks and waterways. Evaluating the "control capabilities" of relevant sewage departments in urban sewage systems is crucial to reducing failure risks, extending the healthy lifespan of systems, and reducing resource waste.

[0003] Previous studies on prioritizing and optimizing wastewater system asset management decisions have often assessed the system from two perspectives: health status and failure consequences. Accurately assessing the health status of drainage pipelines is crucial for timely detection of potential hazards, providing a scientific basis for pipeline maintenance, repair, and upgrades, and ensuring the stable operation of urban drainage systems. Furthermore, to rationally optimize resource allocation, improve urban operation and maintenance efficiency, and enhance the city's ability to respond to sudden drainage problems, it is also necessary to evaluate the comprehensive capabilities related to wastewater system management and control. Therefore, it is essential to construct a scientific, full-process evaluation system for urban wastewater systems to provide a scientific basis for subsequent research into the dynamic interrelationships between systems, thereby achieving precise governance.

[0004] Furthermore, sewage pipe failures can have socio-economic impacts on the surrounding area. Therefore, the higher the consequences of a sewage system failure, the higher the required health status of the urban sewage system should be, and streets with high failure consequences should be equipped with more efficient management capabilities. From the perspective of optimizing resource allocation, a higher health status of the sewage system does not require a large amount of financial investment in management capabilities; instead, investment in management should be strengthened in streets with low health status. Therefore, the theory of "trade-offs and synergies" is introduced to express the spatial balanced development model of urban sewage systems. Trade-offs represent a trade-off relationship, where the score of one system decreases as the score of another system increases. Health status and management capabilities are negatively correlated, i.e., a trade-off relationship. Synergies represent a mutually reinforcing relationship, where the score of one system increases as the score of another system increases. Failure consequences, health status, and management capabilities all show a positive correlation, i.e., a synergy relationship. This approach can scientifically identify the relationship between the health status, failure consequences, and management capabilities of a sewage system, allowing decision-makers to intuitively understand complex spatial relationships, identify problem areas and priorities, achieve balanced development of urban sewage systems, and effectively improve sewage system management efficiency.

[0005] To address this, this invention proposes a method for the balanced and synergistic evaluation of "health status, failure consequences, and control capabilities" in urban wastewater systems. This method encompasses various indicators related to "health status," "failure consequences," and "control capabilities" across the entire chain, from wastewater source to the wastewater pipeline network and finally to the wastewater treatment plant. This allows for the precise identification of weak links in system operation, providing a scientific basis for subsequent research into the dynamic relationships between systems. Furthermore, it can identify the trade-offs and synergistic relationships between systems, enabling the implementation of different management plans for each street, thereby reducing blind investment, lowering wastewater system operation and maintenance costs, and achieving a synergy between economic and environmental benefits. Summary of the Invention

[0006] The purpose of this invention is to identify the health status, failure consequences, and control capabilities of urban wastewater systems. It constructs an indicator system for "health status - failure consequences - control capabilities" of urban wastewater systems and studies the significant differences in "health status - failure consequences - control capabilities" across different regions based on the theory of "trade-offs and synergies." Currently, there is a lack of wastewater system evaluation studies using this assessment method to promote balanced development in urban areas. Therefore, this invention proposes a trade-off and synergistic evaluation method for "health status - failure consequences - control capabilities" of urban wastewater systems. This method quantifies the various system indicators of "health status - failure consequences - control capabilities," achieving full-process evaluation and balanced development of urban wastewater systems. It reduces the operation and maintenance costs of wastewater systems for management departments such as urban streets, alleviating their management pressure. Furthermore, through refined management, it enables deep synergy between economic and environmental benefits within the jurisdiction of urban streets, contributing to the improvement of the living environment and sustainable development of urban areas.

[0007] A method for balancing and coordinating the "health status, failure consequences, and control capabilities" of urban wastewater systems includes the following steps:

[0008] Step 1: Construction of a balanced and collaborative evaluation index system for the urban wastewater system, encompassing "health status, failure consequences, and control capabilities." This system comprehensively considers the health status, failure consequences, and control capabilities of the entire process from the influent to the effluent flowing into the river in the urban municipal wastewater network and wastewater treatment plant. The three index systems—"health status," "failure consequences," and "control capabilities"—exist independently. "Health status" A1 primarily considers 25 health indicators C1-C25 constructed under five criteria: structural defects B1, functional defects B2, engineering attributes B3, social environment B4, and water plant health B5. "Failure consequences" D1 primarily considers 10 failure consequence indicators F1-F10 constructed under four criteria: public property loss E1, critical building service interruption E2, water resource pollution E3, and water plant failure E4. "Control capabilities" G1 primarily considers 10 control capability indicators I1-I10 constructed under three criteria: information monitoring H1, emergency maintenance H2, and dispatch control H3.

[0009] Furthermore, the detailed definitions of the 25 indicators in the "health status" indicator system A1 of the urban sewage system in step 1 are as follows:

[0010] The structural defect B1 criterion includes six indicators: cracking (C1), deformation (C2), corrosion (C3), misalignment (C4), disconnection (C5), and intrusion (C6). "Structural defects" often refer to pipe defects that damage the pipe's structure and affect its structural integrity. "Cracking (C1)" indicates the degree of cracking or damage to the drainage pipe caused by external forces exceeding its own bearing capacity. "Deformation (C2)" indicates the degree of deformation of the pipe due to foundation settlement or external pressure. "Corrosion (C3)" indicates the degree of erosion of the inner or outer wall of the pipe by the environmental medium. "Misalignment (C4)" indicates the degree of misalignment of adjacent pipe joints. "Disconnection (C5)" indicates the degree of disconnection of the pipe. "Intrusion (C6)" indicates the degree of abnormal entry or penetration of external objects (such as rocks or building foundations) into or through the drainage pipe.

[0011] The functional defect B2 criterion level includes six indicators: sedimentation (C7), scaling (C8), debris (C9), puddles (C10), blockage (C11), and tree roots (C12). "Functional defect" refers to pipeline defects that cause changes in the cross-sectional area of ​​the pipeline. "Sedimentation (C7)" refers to the accumulation of silt and other foreign matter in the water at the bottom of the drainage pipe. "Scale (C8)" refers to soft or hard scale-like substances such as grease, iron salts, and limestone adhering to or depositing on the inner surface of the drainage pipe. "Debris (C9)" refers to hard foreign objects such as broken bricks, branches, abandoned tools, and broken pipe fragments in the drainage pipe. "Puddle (C10)" refers to localized water accumulation in the drainage pipe caused by uneven foundation settlement and other factors. "Blockage (C11)" refers to sealing materials remaining in the drainage pipe. "Tree roots (C12)" refers to tree root groups that have naturally grown into the drainage pipe.

[0012] The engineering attribute B3 criterion level contains basic data for assessing the operational status of sewage pipelines, including six indicators: pipe material (C13), pipe length (C14), pipe diameter (C15), pipe age (C16), pipe burial depth (C17), and design flow rate (C18). All of the above data can be obtained from pipeline construction and design data.

[0013] The social environment B4 criterion level covers five indicators: pressure load (C19), pipeline function (C20), soil type (C21), wastewater type (C22), and groundwater depth (C23). "Pressure load (C19)" is calculated from the ground traffic or building load borne by the pipeline. "Pipeline function (C20)" indicates the specific functional classification of the pipeline in the sewage system (including main line, secondary line, household line, and branch line). "Soil type (C21)" indicates the soil properties around the pipeline. "Groundwater depth (C22)" indicates the groundwater level near the pipeline. "Wastewater type (C23)" indicates the source of wastewater contained in the sewage pipeline.

[0014] The B5 health criteria for water treatment plants explore two indicators: low influent concentration (C24) and total load overload (C25). "Low influent concentration (C24)" refers to the C / N ratio of the influent water quality of the wastewater treatment plant, while "total load overload (C25)" refers to the operating load rate of the wastewater treatment plant, which is calculated by the ratio of the actual influent volume to the designed treatment volume.

[0015] Furthermore, the detailed definitions of the 10 indicators at each level of the urban wastewater system "failure consequences" indicator system D1 constructed in step 1 are as follows:

[0016] The public property loss E1 criterion level includes two indicators: road type F1 and land use type F2. "Road type F1" indicates the level of impact on the health status of sewage pipelines based on the traffic function level of the road, and "land use type F2" indicates the land use type where the sewage pipeline is located.

[0017] The critical building service interruption E2 criterion hierarchy is divided into four indicators: distance to hospitals (F3), distance to schools (F4), distance to buildings (F5), and distance to parks / recreational facilities (F6). "Distance to hospitals (F3)" is to consider the impact of sewage pipe failure on medical services; "Distance to schools (F4)" is to consider the impact of sewage pipe failure on the normal operation of schools and students' lives; "Distance to buildings (F5)" is to consider the impact of sewage pipe failure on the structural safety of nearby buildings; and "Distance to parks / recreational facilities (F6)" is to consider the impact of sewage pipe failure on the environment and people's leisure activities in these areas. All four indicators use the neighborhood analysis tool of ArcGIS software to calculate the distance between sewage pipes and points of interest (POIs) (such as hospital point features, primary and secondary school point features, building point features, park point features, and recreational facility point features).

[0018] The E3 criterion for water pollution includes two indicators: distance to the river (F7) and distance to the deteriorated stormwater pipe (F8). "Distance to the river (F7)" indicates that a failed sewage pipe causes sewage to flow into the river, thus polluting the water environment. The nearest distance between the sewage pipe and the river's centerline is calculated using ArcGIS software's neighborhood analysis tool. "Distance to the deteriorated stormwater pipe (F8)" explores how structural defects in sewage pipes can pollute deteriorated stormwater outlets even in dry weather. Management departments use closed-circuit television (CCTV) to detect and identify the location of deteriorated stormwater pipes, and the nearest distance between the sewage pipe and the deteriorated stormwater pipe is calculated using ArcGIS software's neighborhood analysis tool.

[0019] The E4 criterion level for water plant failure includes disease transmission risk (F9) and impact on residents (F10). "Disease transmission risk (F9)" refers to the distance between the water diversion canal and the sewage treatment plant, while "impact on residents (F10)" refers to the impact on sewage pipes for residents within 500 meters after the sewage treatment plant fails.

[0020] Furthermore, the detailed definitions of the 10 indicators at each level of the urban wastewater system "management capability" indicator system G1 constructed in step 1 are as follows:

[0021] The information monitoring H1 criteria level includes the number of pipeline flow monitoring points I1, the number of pipeline liquid level monitoring points I2, the number of river flow monitoring points I3, the number of river water level monitoring points I4, the number of river water quality monitoring points I5, and the rain gauge coverage I6. All six indicators represent the number of monitoring points contained in the street.

[0022] The emergency maintenance H2 criteria include the number of emergency rescue stations (I7) and the coverage of maintenance teams (I8). The "number of emergency rescue stations (I7)" indicates the proportion of manholes accessible by emergency rescue stations within 10 minutes out of the total number of manholes in the street, while the "coverage of maintenance teams (I8)" indicates the number of maintenance teams covered by the sewage pipes in the street.

[0023] The scheduling control H3 criterion level includes the number of pump stations and valve nodes I9 and the number of river sluice gates I10, which respectively represent the number of pump stations and valves in the street's drainage network and the number of river sluice gates in the street.

[0024] Step 2: Calculation of weight matrices for each indicator in the trade-off and collaborative evaluation of "health status - failure consequences - control capability" of the urban sewage system: The weight matrices for the three systems of "health status", "failure consequences" and "control capability" are calculated separately; In the calculation of the weight matrix of the system, the subjective weight judgment matrix and the objective weight judgment matrix are compared to obtain the combined weight matrix under the system.

[0025] Furthermore, the calculation steps for the combined weight matrix of the "health status" indicator system are as follows:

[0026] (1) Calculate the subjective weight matrix of the "health status" indicator system. Where i = 1, 2, 3…25; the relative importance of each level of elements is compared by subjective scoring from the experts using the 1–9 scale method (Appendix 1);

[0027] Appendix 1 Scoring Rules for the 1-9 Scale

[0028]

[0029] The importance of the corresponding criteria levels in the health status A1 system, namely structural defects B1, functional defects B2, engineering attributes B3, social environment B4, and water plant health B5, is compared pairwise to obtain the judgment matrix A1 of health status A1, as shown in formula (1).

[0030]

[0031] Where a 12 This indicates the relative importance of structural defect B1 compared to functional defect B2; a 13 This indicates the relative importance of structural defect B1 to engineering attribute B3; a 14 This indicates the relative importance of structural defect B1 to the social environment B4; a 15 This indicates the relative importance of structural defect B1 to the water plant health B5;

[0032] a 21 This indicates the relative importance of functional defect B2 compared to structural defect B1, i.e. a 23 This indicates the relative importance of functional defect B2 to engineering attribute B3; a 24 This indicates the degree of importance of functional deficit B2 relative to the social environment B4; a 25 This indicates the degree of importance of functional defect B2 relative to the water plant health B5;

[0033] a 31 This indicates the relative importance of engineering attribute B3 compared to structural defect B1, i.e. a 32 This indicates the relative importance of engineering attribute B3 compared to functional defect B2, i.e. a 34 This indicates the degree of importance of engineering attribute B3 relative to the social environment B4; a 35 This indicates the relative importance of engineering attribute B3 to the water plant health attribute B5;

[0034] a 41 This indicates the relative importance of the social environment B4 compared to the structural defect B1, i.e.

[0035] ;a 42 This indicates the relative importance of social environment B4 compared to functional deficit B2, i.e. a 43 This indicates the relative importance of social environment B4 compared to engineering attribute B3, i.e. a 45 This indicates the relative importance of the social environment (B4) to the water plant's health (B5).

[0036] a 51 This indicates the relative importance of water plant health (B5) to structural defects (B1). a 52 This indicates the relative importance of water plant health (B5) compared to functional defect (B2). a 53 This indicates the relative importance of water plant health attribute B5 compared to engineering attribute B3, i.e. a 54 This indicates the relative importance of water plant health (B5) compared to the social environment (B4).

[0037] The importance of the corresponding index levels in the hierarchical defect B1 of the criteria are compared pairwise to obtain the judgment matrix B1 of the structural defect B1, as shown in formula (2).

[0038]

[0039] Where b 12 This indicates the relative importance of fracture C1 compared to deformation C2; b13 This indicates the relative importance of fracture C1 compared to corrosion C3; b 14 This indicates the relative importance of fracture C1 to misalignment C4; b 15 This indicates the relative importance of fracture C1 compared to disintegration C5; b 16 This indicates the relative importance of rupture C1 compared to intrusion C6;

[0040] b 21 This indicates the relative importance of deformation C2 to fracture C1, i.e. b 23 This indicates the relative importance of deformation C2 compared to corrosion C3; b 24 This indicates the relative importance of deformation C2 to misalignment C4; b 25 This indicates the relative importance of deformation C2 compared to disintegration C5; b 26 This indicates the relative importance of deformation C2 compared to intrusion C6;

[0041] b 31 This indicates the relative importance of corrosion C3 compared to fracture C1, i.e. b 32 This indicates the relative importance of corrosion C3 compared to deformation C2. b 34 This indicates the relative importance of corrosion C3 compared to misalignment C4; b 35 This indicates the relative importance of corrosion C3 compared to delamination C5; b 36 This indicates the relative importance of corrosion C3 compared to penetration C6;

[0042] b 41 This indicates the relative importance of the misalignment C4 to the fracture C1, i.e. b 42 This indicates the relative importance of misalignment C4 to deformation C2, i.e. b 43 This indicates the relative importance of misalignment C4 compared to corrosion C3, i.e. b 45 This indicates the relative importance of misalignment C4 compared to disengagement C5; b 46 This indicates the relative importance of the misdirection C4 compared to the intrusion C6;

[0043] b 51 This indicates the relative importance of disintegration C5 compared to fracture C1, i.e. b 52 This indicates the relative importance of the dissociation C5 to the deformation C2, i.e. b 53 This indicates the relative importance of C5 dissociation compared to C3 corrosion, i.e. b 54 This indicates the relative importance of dislocation C5 to misalignment C4, i.e. b56 This indicates the relative importance of C5 disconnection compared to C6 intrusion;

[0044] b 61 This indicates the relative importance of intrusion C6 compared to rupture C1, i.e. b 62 This indicates the relative importance of intrusion C6 compared to deformation C2, i.e. b 63 This indicates the relative importance of intrusion C6 compared to corrosion C3, i.e. b 64 This indicates the relative importance of intrusion C6 to misalignment C4, i.e. b 65 This indicates the relative importance of intrusion C6 compared to detachment C5, i.e.

[0045] The importance of the corresponding indicator levels in the functional defect B2 of the criteria level is compared pairwise: sedimentation C7, scaling C8, debris C9, puddles C10, blockage C11, and tree roots C12. The judgment matrix B2 of functional defect B2 is obtained as shown in formula (3).

[0046]

[0047] Where b 7,8 This indicates the relative importance of deposit C7 compared to scaling C8; b 7,9 Indicates the importance of sediment C7 relative to impurity C9; b 7,10 Indicates the importance of sediment C7 relative to depression water C10; b 7,11 This indicates the relative importance of deposition C7 compared to plugging C11; b 7,12 This indicates the relative importance of sedimentary C7 compared to root C12;

[0048] b 8,7 This indicates the relative importance of scale formation C8 compared to deposition C7, i.e. b 8,9 This indicates the relative importance of scale (C8) compared to impurities (C9); b 8,10 This indicates the relative importance of scale formation C8 compared to puddles C10; b 8,11 This indicates the relative importance of scaling C8 compared to plugging C11; b 8,12 This indicates the relative importance of scale C8 compared to root C12;

[0049] b 9,7 This indicates the importance of contaminant C9 relative to sediment C7, i.e. b 9,8 This indicates the relative importance of impurities C9 compared to scale C8. b 9,10 This indicates the relative importance of debris C9 compared to puddles C10; b9,11 This indicates the relative importance of debris C9 compared to sealing C11; b 9,12 This indicates the relative importance of the debris C9 compared to the tree root C12;

[0050] b 10,7 This indicates the relative importance of C10 in the depression water compared to C7 in the sediment, i.e. b 10,8 This indicates the relative importance of puddles (C10) compared to scale (C8), i.e. b 10,9 This indicates the relative importance of the puddles (C10) to the debris (C9), i.e. b 10,11 This indicates the relative importance of the puddles C10 to the sealing of C11; b 10,12 This indicates the relative importance of C10 in the puddles compared to C12 in the tree roots;

[0051] b 11,7 This indicates the relative importance of blocking C11 compared to depositing C7, i.e. b 11,8 This indicates the relative importance of sealing C11 compared to scaling C8, i.e. b 11,9 This indicates the relative importance of blocking C11 compared to debris C9, i.e. b 11,10 This indicates the relative importance of sealing C11 compared to the puddles C10, i.e. b 11,12 This indicates the relative importance of sealing C11 compared to the tree root C12;

[0052] b 12,7 This indicates the relative importance of root C12 compared to sedimentary C7, i.e. b 12,8 This indicates the relative importance of root C12 compared to scale C8, i.e. b 12,9 This indicates the relative importance of root C12 compared to debris C9, i.e. b 12,10 This indicates the relative importance of the tree root C12 to the puddle water C10, i.e. b 12,11 This indicates the relative importance of root C12 compared to sealing C11, i.e.

[0053] The importance of the corresponding indicator levels in the engineering attribute B3 of the criteria level, namely: pipe material C13, pipe length C14, pipe diameter C15, pipe age C16, pipe burial depth C17, and design flow rate C18, is compared pairwise to obtain the judgment matrix B3 of the engineering attribute B3, as shown in formula (4).

[0054]

[0055] Where b 13,14 This indicates the relative importance of pipe material C13 to pipe length C14; b 13,15 This indicates the relative importance of pipe material C13 compared to pipe diameter C15; b 13,16 This indicates the relative importance of pipe material C13 compared to pipe age C16; b 13,17 This indicates the relative importance of pipe material C13 compared to pipe burial depth C17; b 13,18 This indicates the importance of pipe material C13 relative to the design flow rate C18;

[0056] b 14,13 This indicates the relative importance of pipe length C14 to pipe material C13, i.e. b 14,15 This indicates the relative importance of pipe length C14 to pipe diameter C15; b 14,16 This indicates the relative importance of pipe length C14 to pipe age C16; b 14,17 This indicates the importance of pipe length C14 relative to pipe burial depth C17; b 14,18 This indicates the importance of pipe length C14 relative to design flow rate C18;

[0057] b 15,13 This indicates the relative importance of pipe diameter C15 compared to pipe material C13, i.e. b 15,14 This indicates the relative importance of pipe diameter C15 compared to pipe length C14. b 15,16 This indicates the importance of pipe diameter C15 relative to pipe age C16; b 15,17 This indicates the importance of pipe diameter C15 relative to pipe burial depth C17; b 15,18 This indicates the importance of pipe diameter C15 relative to design flow rate C18;

[0058] b 16,13 This indicates the relative importance of pipe age C16 compared to pipe material C13, i.e. b 16,14 This indicates the relative importance of tube age C16 to tube length C14, i.e. b 16,15 This indicates the importance of pipe age C16 relative to pipe diameter C15, i.e. b 16,17 This indicates the importance of pipe age C16 relative to pipe burial depth C17; b 16,18 This indicates the importance of pipe age C16 relative to design flow rate C18;

[0059] b 17,13 This indicates the relative importance of pipe burial depth C17 compared to pipe material C13, i.e. b 17,14This indicates the importance of the pipe burial depth C17 relative to the pipe length C14, i.e. b 17,15 This indicates the importance of the pipe burial depth C17 relative to the pipe diameter C15, i.e. b 17,16 This indicates the importance of pipeline burial depth C17 relative to pipeline age C16, i.e. b 17,18 This indicates the importance of the pipeline burial depth C17 relative to the design flow rate C18;

[0060] b 18,13 This indicates the relative importance of the design flow rate C18 to the pipe material C13, i.e. b 18,14 This indicates the importance of the design flow rate C18 relative to the pipe length C14, i.e. b 18,15 This indicates the importance of the design flow rate C18 relative to the pipe diameter C15, i.e. b 18,16 This indicates the importance of the design flow rate C18 relative to the pipe age C16, i.e. b 18,17 This indicates the importance of the design flow rate C18 relative to the pipe burial depth C17, i.e.

[0061] The importance of the corresponding indicator levels in the social environment B4 of the criteria level is compared pairwise to obtain the judgment matrix B4 of social environment B4, as shown in formula (5).

[0062]

[0063] Where b 19,20 This indicates the relative importance of the pressure load C19 to the pipeline function C20; b 19,21 This indicates the importance of the bearing load C19 relative to soil type C21; b 19,22 This indicates the importance of the pressure load C19 relative to wastewater type C22; b 19,23 This indicates the importance of the pressure load C19 relative to the groundwater depth C23;

[0064] b 20,19 This indicates the relative importance of the pipeline function C20 to the pressure load C19, i.e. b 20,21 This indicates the relative importance of pipeline function C20 to soil type C21; b 20,22 This indicates the relative importance of pipeline function C20 to wastewater type C22; b 20,23 This indicates the relative importance of pipeline function C20 to groundwater burial depth C23;

[0065] b 21,19 This indicates the importance of soil type C21 relative to the bearing capacity C19, i.e. b 21,20 This indicates the relative importance of soil type C21 to pipeline function C20. b 21,22 This indicates the relative importance of soil type C21 to wastewater type C22; b 21,23 This indicates the importance of soil type C21 relative to groundwater depth C23;

[0066] b 22,19 This indicates the importance of wastewater type C22 relative to pressure load C19, i.e. b 22,20 This indicates the relative importance of wastewater type C22 to pipeline function C20, i.e. b 22,21 This indicates the relative importance of wastewater type C22 compared to soil type C21, i.e. b 22,23 This indicates the importance of wastewater type C22 relative to groundwater depth C23;

[0067] b 23,19 This indicates the importance of the pipeline burial depth C17 relative to the pressure load C19, i.e. b 23,20 This indicates the importance of the pipeline burial depth C17 relative to the pipeline function C20, i.e. b 23,21 This indicates the importance of pipeline burial depth C17 relative to soil type C21, i.e. b 23,22 This indicates the relative importance of the pipeline burial depth C17 to the groundwater burial depth C23, i.e.

[0068] By comparing the importance of the corresponding indicator levels in the criterion level B5 of water plant health: low influent concentration C24 and total load overload C25, the judgment matrix B5 of water plant health B5 is obtained, as shown in formula (6).

[0069]

[0070] Where b 24,25 This indicates the relative importance of low influent concentration C24 compared to total load overload C25; b 25,24 This indicates the relative importance of total overload C25 compared to the low influent concentration C24, i.e.

[0071] To ensure the correct subjective weight matrix for health status A1 is obtained. First, a consistency check needs to be passed; then, calculate the maximum eigenvalue (λ) corresponding to the judgment matrix A1 for health status A1, judgment matrix B1 for structural defects B1, judgment matrix B2 for functional defects B2, judgment matrix B3 for engineering attributes B3, judgment matrix B4 for social environment B4, and judgment matrix B5 for water plant health B5. max ), and obtain the consistency index for each judgment matrix. (λ max The largest eigenvalue of the judgment matrix is ​​represented by n; n represents the order of the judgment matrix. To compare the magnitudes of the CIs, the standard value of the random consistency index RI corresponding to the judgment matrix is ​​selected, and the test coefficients are finally obtained. (RI is selected according to the random consistency index RI value table in Appendix 2); when CR<0.1, it means that the consistency test is passed; otherwise, pairwise importance comparisons need to be performed again, the judgment matrix needs to be reconstructed, and the calculation continues until CR<0.1.

[0072] Appendix 2: Random Consistency Index (RI) Values

[0073] order 1 2 3 4 5 6 RI 0 0 0.52 0.89 1.12 1.26

[0074] After normalizing the judgment matrices A1, B1, B2, B3, B4, and B5, the subjective weight matrix of health state A1 is calculated using the arithmetic mean method.

[0075] Calculate the weight matrix U = (u1, u2, u3, u4, u5) for the criterion hierarchy, where the weight of structural defect B1 is... The weight of functional defect B2 is The weight of project attribute B3 is The weight of social environment B4 is The weight of water plant health B5 is (i,j=1,2,…,5;When i=j, a ij =1);

[0076] Calculate the hierarchical weight matrix V1 = (v1, v2, ..., v6) for the structural defect B1, where the weight of rupture C1 is... Weight of deformed C2 Weight of corrosion C3 Weight of C4 (misaligned) Disconnecting the weight of C5 Weights that intrude into C6 (i,j=1,2,…,6;When i=j, b ij =1);

[0077] The hierarchical weight matrix of the indicators for calculating functional defect B2 is V2 = (v7, v8, ..., v 12), where the weight of deposited C7 Weight of scale C8 Weight of miscellaneous item C9 Weight of C10 in puddles Weight of blocking C11 Weight of blocking C12 (i,j = 7,8,…,12; when i = j, b) ij =1);

[0078] Calculate the hierarchical weight matrix V3 of the indicator for engineering attribute B3 = (v 13 ,v 14 ,…,v 18 ), where the weight of pipe material C13 is Weight of pipe length C14 Weight of pipe diameter C15 Weight of C16 tube age Weight of pipeline burial depth C17 The weight of design flow C18 (i,j=13,14,…,18;When i=j, b ij =1);

[0079] Calculate the hierarchical weight matrix V4 of the social environment B4 indexes = (v 19 ,v 20 ,…,v 23 ), where the weight of the pressure load C19 is Weight of pipeline function C20 Weight of soil type C21 Weight of groundwater depth C22 Weight of wastewater type C23 (i = 19, 20, ..., 23; when i = j, b) ij =1);

[0080] The hierarchical weight matrix V5 for calculating the health index B5 of a water plant is: V5 = (v 24 ,v 25 ), where the weight of low influent concentration C24. Total overload weight of C25 (i = 24, 25; when i = j, b) ij =1);

[0081] The weight of the final indicator level Ci Where u n v represents the weight of the criterion level to which the i-th indicator belongs. i This indicates the weight of the indicator at which it belongs; (n ranges from 1 to 5, i ranges from 1 to 25), that is...

[0082] (2) Calculate the objective weight matrix of the "health status" indicator system. Objective weights are calculated by analyzing the correlation between indicators using standard correlation analysis; the original indicator data of sewage pipes are set as m evaluation samples, i.e., m sewage pipes, and n evaluation indicators (n=25), forming a matrix of original indicator data for "health status":

[0083]

[0084] The raw data for the 25 indicators of "health status" were dimensionless, and the formula is as follows:

[0085]

[0086] In the formula, X ij x represents the standard index value of the j-th index of the i-th sewage pipe. ij x represents the raw data of the j-th indicator for the i-th sewage pipe; max(j) and x min(j) These are the maximum and minimum values ​​of the j-th indicator across all sewage pipes, respectively.

[0087] Calculate the difference α between each indicator j The greater the difference, the stronger the evaluation intensity.

[0088]

[0089] In the formula, m represents the number of sewage pipes; X ij This represents the standard index value of the j-th indicator for the i-th sewage pipe. This represents the average value of the standard index for the j-th index across all sewage pipes;

[0090] Calculate the conflict β among the indicators j The correlation coefficient is used to represent the correlation between "health status" indicators. The stronger the correlation, the less conflict there is, and the weight assigned to this indicator should be reduced.

[0091]

[0092] In the formula, m represents the number of sewage pipes; r jk X represents the correlation coefficient between the j-th indicator level and the k-th indicator level; ij Let j be the standard index value of the j-th index of the i-th sewage pipe; X represents the average value of the standard index for the j-th index across all sewage pipes; ik Let k be the standard index value of the k-th index of the i-th sewage pipe; The k-th indicator represents the average value of the standard indicator in all sewage pipes; j, k = (1, 2, ..., 6) under the structural defect B1 criterion level; j, k = (7, 8, ..., 12) under the functional defect B2 criterion level; j, k = (13, 14, ..., 18) under the engineering attribute B3 criterion level; j, k = (19, 20, ..., 23) under the social environment B4 criterion level; j, k = (24, 25) under the water plant health B5 criterion level.

[0093] The information content C is calculated by combining standard deviation and conflict. j =α j ×β j The objective weight of the j-th indicator in the "health status" indicator system is obtained. Objective weight matrix of the "health status" indicator system

[0094] (3) Calculate the combined weight matrix W of the "health status" indicator system. A =(ω1,ω2,…ω i …,ω 25 The optimization strategy is given through formulaic calculation; the weighting of the two outcomes is weighed in combination with game theory, and the subjective weight of any indicator is determined by formula (12). and objective weight Substituting the values ​​(where i = 1, 2, ..., 25), we obtain a relatively balanced and coordinated combined weight vector μ. S and μ O The optimal weighting of this indicator The combined weights ω of the 25 indicators of "health status" i Arranged in order, the weight matrix W of the "health status" indicator system is obtained. A =(ω1,ω2,…ω i …,ω 25 );

[0095]

[0096] In the formula, This represents the subjective weight of the i-th indicator; This represents the objective weight of the i-th indicator; express transpose, express transpose;

[0097] The steps for calculating the combined weight matrix of the "failure consequences" indicator system are as follows:

[0098] (1) Calculate the subjective weight matrix of the "failure consequences" indicator system. Where i = 1, 2, ..., 10; the relative importance of each level of elements is compared by subjective scoring from the experts using the 1–9 scale method (Appendix 1);

[0099] The corresponding criteria levels in the failure consequence D1 system, namely: loss of public property E1, interruption of service of critical buildings E2, water pollution E3 and failure of water plant E4, are compared in pairs to obtain the judgment matrix D1 of failure consequence D1, as shown in formula (13).

[0100]

[0101] Where d 12 This indicates the relative importance of public property loss E1 compared to critical building service disruption E2; d 13 This indicates the relative importance of public property loss E1 compared to water pollution E3; d 14 This indicates the relative importance of public property loss E1 compared to water plant failure E4;

[0102] d 21 This indicates the relative importance of critical building service disruption E2 compared to public property loss E1, i.e. d 23 This indicates the relative importance of critical building service disruption E2 compared to water pollution E3; a 24 This indicates the relative importance of critical building service interruption E2 compared to water treatment plant failure E4;

[0103] d 31 This indicates the relative importance of water pollution E3 compared to public property loss E1, i.e. d 32 This indicates the relative importance of water pollution E3 compared to critical building service disruption E2, i.e. d 34 This indicates the relative importance of water pollution E3 compared to water plant failure E4;

[0104] d 41 This indicates the relative importance of water plant failure E4 compared to public property loss E1, i.e. d 42 This indicates the relative importance of water treatment plant failure (E4) compared to critical building service interruption (E2). d 43 This indicates the relative importance of water plant failure (E4) compared to water pollution (E3), i.e.

[0105] By comparing the importance of the corresponding indicator levels in the criteria level public property loss E1: road type F1 and land use type F2, the judgment matrix E1 of public property loss E1 is obtained, as shown in formula (14).

[0106]

[0107] Where e 12 This indicates the relative importance of road type F1 to land use type F2; e 21 This indicates the relative importance of land use type F2 to road type F1, i.e.

[0108] The importance of the corresponding indicator levels in the critical building service interruption E2 of the criterion level, namely distance to the hospital F3, distance to the school F4, distance to the building F5, and distance to the park / recreation facility F6, is compared pairwise to obtain the judgment matrix E2 of critical building service interruption E2, as shown in formula (15).

[0109]

[0110] Where e 34 This indicates the importance of the distance to the hospital (F3) relative to the service disruption caused by critical buildings (E2); e 35 This indicates the relative importance of distance F3 from the hospital compared to distance F5 from the building; e 36 This indicates the relative importance of distance F3 from the hospital compared to distance F6 from the park / recreation facility;

[0111] e 43 This indicates the relative importance of distance F4 from the school compared to distance F3 from the hospital. e 45 This indicates the relative importance of distance F4 from the school compared to distance F5 from the building; e 46 This indicates the relative importance of distance to the school (F4) compared to distance to the park / recreation facility (F6);

[0112] e 53 This indicates the relative importance of distance F5 from the building compared to distance F3 from the hospital. e 54 This indicates the relative importance of distance F5 from the building compared to distance F4 from the school. e 56 This indicates the relative importance of distance F5 from buildings compared to distance F6 from parks / recreational facilities;

[0113] e 63 This indicates the relative importance of distance F6 from the park / recreation facility compared to distance F3 from the hospital. e 64 This indicates the relative importance of distance to parks / recreational facilities (F6) compared to distance to schools (F4). e 65This indicates the relative importance of distance F6 from the park / recreation facility compared to distance F5 from the building.

[0114] By comparing the pairwise importance of the corresponding indicator levels in the criteria level E3 for water pollution: distance to the river F7 and distance to the deteriorated rainwater pipe F8, the judgment matrix E3 for water pollution E3 is obtained, as shown in formula (16).

[0115]

[0116] Where e 78 This indicates the relative importance of distance F7 from the river compared to distance F8 from the deteriorated stormwater pipes; e 87 This indicates the relative importance of distance F8 from the deteriorated storm drain pipe compared to distance F7 from the river.

[0117] By comparing the pairwise importance of the corresponding indicator levels in the criterion level water plant failure E4: disease transmission risk F9 and impact on residents F10, the judgment matrix E4 of water plant failure E4 is obtained, as shown in formula (17).

[0118]

[0119] Where e 9,10 This indicates the relative importance of the disease transmission risk F9 to the impact of the residential population on F10; e 10,9 This indicates the relative importance of the impact of residential residents on F10 compared to the risk of disease transmission F9, i.e.

[0120] To ensure the correct failure consequence D1 is obtained, the subjective weight matrix is ​​calculated. First, a consistency check needs to be passed; then, calculate the maximum eigenvalue (λ) corresponding to the judgment matrix D1 for failure consequences D1, the judgment matrix E1 for public property loss E1, the judgment matrix E2 for critical building service interruption E2, the judgment matrix E3 for water resource pollution E3, and the judgment matrix E4 for water plant failure E4. max ), to obtain the consistency index (λ max Let represent the largest eigenvalue of the judgment matrix; n represents the order of the judgment matrix. To compare the magnitudes of CI, the standard value of the random consistency index RI corresponding to the judgment matrix is ​​selected, and the final test coefficient is obtained. (RI is selected according to the random consistency index RI value table in Appendix 2); when CR<0.1, it means that the consistency test is passed; otherwise, pairwise importance comparisons need to be performed again, the judgment matrix needs to be reconstructed, and the calculation continues until CR<0.1.

[0121] After normalizing the judgment matrices D1, E1, E2, E3, and E4, the subjective weight matrix of the failure consequence D1 is calculated using the arithmetic mean method.

[0122] Calculate the weight matrix U′=(u1′,u2′,u3′,u4′) at the criterion level, where the weight of public property loss E1 is... Critical building service interruption E2 is The weight of water pollution E3 is The weight of water plant failure E4 is (i,j=1,2,3,4; when i=j, d ij =1);

[0123] The hierarchical weight matrix V1′=(v1′,v2′) is used to calculate the public property loss E1, where the weight of road type D1 is... Weight of land use type D2 (i,j=1,2; when i=j, e) ij =1);

[0124] Calculate the hierarchical weight matrix V2′=(v3′,v4′,v5′,v6′) for the critical building service interruption E2, where the weight of distance to the hospital F3 is... Distance from school, weight of F4 Weight of distance F5 from the building Distance to park / recreation facilities (F6 weight) (i,j=3,4,5,6;When i=j,e ij =1);

[0125] Calculate the hierarchical weight matrix V3′=(v7′,v8′) for water resource pollution E3, where the weight of distance to the river channel F7 is... Weight of distance F8 from deteriorated storm drain pipes (i,j=7,8;when i=j,e) ij =1);

[0126] The index hierarchy weight matrix V4′=(v9′,v4′) is used to calculate the water plant failure E4. 10 ′), where the weight of disease transmission risk F9 is ′). The weight of residents in the F10 index (i=9,10; when i=j, e ij =1);

[0127] Weights of the final indicator level Fi Where u n′ represents the weight of the criterion level to which the i-th indicator belongs, v i ′ represents the weight of the indicator level to which the i-th indicator belongs; (n takes values ​​from 1 to 4, i takes values ​​from 1 to 10), that is

[0128] (2) Calculate the objective weight matrix of the "failure consequences" indicator system. Objective weights are calculated by analyzing the correlation between indicators using standard correlation analysis; the original indicator data of sewage pipelines are set as m evaluation samples, i.e., m sewage pipelines, and n evaluation indicators (where n=10), forming an original indicator data matrix of "failure consequences":

[0129]

[0130] The raw data for the 10 indicators of "failure consequences" were dimensionless, as shown in the following formula:

[0131]

[0132] In the formula, X ij ′ represents the standard index value of the j-th indicator for the i-th sewage pipe, x ij ′ represents the raw data of the j-th indicator of the i-th sewage pipe; x max(j) ′ and x min(j) ′ and ′ represent the maximum and minimum values ​​of the j-th indicator in all sewage pipes, respectively;

[0133] Calculate the difference α between each indicator j The greater the difference, the stronger the evaluation intensity.

[0134]

[0135] In the formula, m represents the number of sewage pipes; X ij ′ represents the standard index value of the j-th indicator for the i-th sewage pipe, X j ′ represents the average value of the standard index for the j-th index across all sewage pipes;

[0136] Calculate the conflict β′ between the indicators j The correlation coefficient is used to represent the correlation between the "failure consequences" indicators. The stronger the correlation, the smaller the conflict, and the weight assigned to this indicator should be reduced.

[0137]

[0138] In the formula, m represents the number of sewage pipes; r jk ′ represents the correlation coefficient between the j-th indicator level and the k-th indicator level; X ij ′ represents the standard index value of the j-th index of the i-th sewage pipe; X represents the average value of the standard index for the j-th index across all sewage pipes; ik ′ represents the standard index value of the k-th index of the i-th sewage pipe; The k-th indicator represents the average value of the standard indicator in all sewage pipelines; j, k = (1, 2) under the E1 criterion level for public property loss; j, k = (4, 5, 6, 7) under the E2 criterion level for critical building service interruption; j, k = (7, 8) under the E3 criterion level for water pollution; j, k = (9, 10) under the E4 criterion level for water plant failure.

[0139] The information content C is calculated by combining standard deviation and conflict. j ′=α j ′×β j ′, thus obtaining the objective weight of the j-th indicator in the “failure consequences” indicator system. The objective weight matrix of the "failure consequences" indicator system

[0140] (3) Calculate the combined weight matrix W of the "failure consequences" index system. D ′=(ω1′,ω2′,…,ω 10 The optimization strategy is given through formulaic calculation; the weighting of the two results is weighed in combination with game theory, and the subjective weight of any indicator is calculated using formula (23). and objective weight Substituting the values ​​(where i = 1, 2, ..., 10), we obtain a relatively balanced and coordinated combined weight vector μ. S′ and μ O′ The optimal weighting of this indicator The combined weight ω of the 10 indicators of "failure consequences" i Arrange them in order to obtain the weight matrix W of the "failure consequences" indicator system. D ′=(ω1′,ω2′,…,ω 10 ′);

[0141]

[0142] In the formula, This represents the subjective weight of the i-th indicator; This represents the objective weight of the i-th indicator; express transpose, express transpose;

[0143] The steps for calculating the combined weight matrix of the "control capability" indicator system are as follows:

[0144] (1) Calculate the subjective weight matrix of the "control capability" indicator system. Where i = 1, 2, ..., 10; the relative importance of each level of elements is compared by subjective scoring from the experts using the 1–9 scale method (Appendix 1);

[0145] By comparing the pairwise importance of the corresponding criteria levels in the control capability G1 system: information monitoring H1, emergency maintenance H2 and dispatch control H3, the judgment matrix G1 of control capability G1 is obtained, as shown in formula (24).

[0146]

[0147] Where g 12 This indicates the relative importance of information monitoring H1 compared to emergency maintenance H2; g 13 This indicates the relative importance of information monitoring H1 compared to scheduling control H3;

[0148] g 21 This indicates the relative importance of emergency maintenance H2 compared to information monitoring H1, i.e. g 23 This indicates the relative importance of emergency maintenance H2 compared to dispatch control H3;

[0149] g 31 This indicates the relative importance of scheduling control H3 compared to information monitoring H1, i.e. g 32 This indicates the relative importance of dispatch control H3 compared to emergency maintenance H2, i.e.

[0150] The importance of the corresponding indicator levels in the criteria level information monitoring H1, namely: number of pipeline flow monitoring points I1, number of pipeline liquid level monitoring points I2, number of river flow monitoring points I3, number of river water level monitoring points I4, number of river water quality monitoring points I5, and rain gauge coverage I6, is compared pairwise to obtain the judgment matrix E1 of public property loss E1, as shown in formula (25).

[0151]

[0152] Where h 12 This indicates the relative importance of the number of pipeline flow monitoring points I1 compared to the number of pipeline liquid level monitoring points I2; h 13 This indicates the relative importance of the number of pipeline flow monitoring points I1 compared to the number of river flow monitoring points I3; h 14 This indicates the relative importance of the number of pipeline flow monitoring points I1 compared to the number of river water level monitoring points I4; h 15 This indicates the relative importance of the number of pipeline flow monitoring points I1 compared to the number of river water quality monitoring points I5; b 16 This indicates the importance of the number of pipeline flow monitoring points I1 relative to the rain gauge coverage I6;

[0153] h 21 This indicates the relative importance of the number of pipeline level monitoring points I2 compared to the number of pipeline flow monitoring points I1, i.e. h 23 This indicates the relative importance of the number of pipeline level monitoring points I2 compared to the number of river flow monitoring points I3; h 24 This indicates the relative importance of the number of pipeline level monitoring points I2 compared to the number of river level monitoring points I4; h 25 This indicates the relative importance of the number of pipeline level monitoring points I2 compared to the number of river water quality monitoring points I5; h 26 This indicates the importance of the number of pipeline level monitoring points I2 relative to the rain gauge coverage I6;

[0154] h 31 This indicates the relative importance of the number of river flow monitoring points I3 compared to the number of pipeline flow monitoring points I1, i.e. h 32 This indicates the relative importance of the number of river flow monitoring points I3 compared to the number of pipeline liquid level monitoring points I2. h 34 This indicates the relative importance of the number of river flow monitoring points I3 compared to the number of river water level monitoring points I4; h 35 This indicates the relative importance of the number of river flow monitoring points I3 compared to the number of river water quality monitoring points I5; h 36 This indicates the importance of the number of river flow monitoring points (I3) relative to the rain gauge coverage (I6);

[0155] h 41 This indicates the relative importance of the number of river water level monitoring points I4 compared to the number of pipeline flow monitoring points I1, i.e. h 42 This indicates the relative importance of the number of river water level monitoring points I4 compared to the number of pipe network liquid level monitoring points I2, i.e. h 43 This indicates the relative importance of the number of river water level monitoring points I4 compared to the number of river flow monitoring points I3. h 45 This indicates the relative importance of the number of river water level monitoring points I4 compared to the number of river water quality monitoring points I5; h 46 This indicates the importance of the number of river level monitoring points (I4) relative to the rain gauge coverage (I6);

[0156] h 51 This indicates the relative importance of the number of river water quality monitoring points I5 compared to the number of pipeline flow monitoring points I1, i.e. h 52 This indicates the relative importance of the number of river water quality monitoring points I5 compared to the number of pipe network liquid level monitoring points I2, i.e. h 53 This indicates the relative importance of the number of river water quality monitoring points I5 compared to the number of river flow monitoring points I3. h 54 This indicates the relative importance of the number of river water quality monitoring points I5 compared to the number of river water level monitoring points I4. h 56 This indicates the importance of the number of river water quality monitoring points (I5) relative to the rain gauge coverage (I6);

[0157] h 61 This indicates the importance of the rain gauge coverage I6 relative to the number of pipeline flow monitoring points I1, i.e. h 62 This indicates the importance of the rain gauge coverage I6 relative to the number of pipeline level monitoring points I2, i.e. h 63 This indicates the importance of the rain gauge coverage I6 relative to the number of river flow monitoring points I3, i.e. h 64 This indicates the importance of the rain gauge coverage I6 relative to the number of river level monitoring points I4, i.e. h 65 This indicates the importance of the rain gauge coverage I6 relative to the number of river water quality monitoring points I5, i.e.

[0158] The importance of the corresponding indicator levels in the criterion level emergency maintenance H2, namely the number of emergency rescue stations I7 and the coverage of maintenance teams I8, is compared pairwise to obtain the judgment matrix H2 of emergency maintenance H2, as shown in formula (26).

[0159]

[0160] Where h 78 This indicates the importance of the number of emergency rescue stations (I7) relative to the coverage of maintenance teams (I8); h 87 This indicates the importance of the coverage of the maintenance team (I8) relative to the number of emergency rescue stations (I7), i.e.

[0161] The importance of the corresponding indicator levels in the criterion-level scheduling control H3, namely the number of pump station valves I9 and the number of river gates and dams I10, is compared pairwise to obtain the judgment matrix H3 of scheduling control H3, as shown in formula (27).

[0162]

[0163] Where h 9,10 This indicates the relative importance of the number of pump station valves (I9) compared to the number of river sluice gates (I10); h 10,9 This indicates the relative importance of the number of river sluice gates and dams (I10) to the number of pump station valves (I9), i.e.

[0164] To ensure the correct subjective weight matrix of control capability G1 is obtained. First, a consistency check is required; then, the maximum eigenvalue (λ) corresponding to the judgment matrix G1 of control capability G1, the judgment matrix H1 of information monitoring H1, the judgment matrix H2 of emergency maintenance H2, and the judgment matrix H3 of dispatch control H3 is calculated. max ), to obtain the consistency index (λ max Let represent the largest eigenvalue of the judgment matrix; n represents the order of the judgment matrix. To compare the magnitudes of CI, the standard value of the random consistency index RI corresponding to the judgment matrix is ​​selected, and the final test coefficient is obtained. (RI is selected according to the random consistency index RI value table in Appendix 2); when CR<0.1, it means that the consistency test is passed; otherwise, pairwise importance comparisons need to be performed again, the judgment matrix needs to be reconstructed, and the calculation continues until CR<0.1.

[0165] After normalizing the judgment matrices G1, H1, H2, and H3, the subjective weight matrix of the control capability G1 is calculated using the arithmetic mean method.

[0166] The weight matrix U″=(u1″,u2″,u3″) of the criterion hierarchy is calculated, where the weight of information monitoring H1 is... Emergency maintenance H2 is The weight of scheduling control H3 is (i,j=1,2,3; when i=j, g) ij =1);

[0167] Calculate the hierarchical weight matrix B1″=(b1″,b2″,…,v6″) for the information monitoring H1, where the weight of the number of pipeline flow monitoring points I1 is... The number of pipeline level monitoring points I2 is The weight of the number of river flow monitoring points I3 is: The weight of the number of river water level monitoring points I4 is: The weight of the number of river water quality monitoring points I5 is: The weight of rain gauge coverage I6 is (i,j=1,2,…,6;when i=j, h ij =1);

[0168] Calculate the hierarchical weight matrix V3″=(v7″,v8″) for emergency maintenance H2, where the weight of the number of emergency rescue stations I7 is... Weight of I8 in the coverage of operations and maintenance teams (i,j = 7,8; ​​when i = j, h) ij =1);

[0169] Calculate the hierarchical weight matrix V4″=(v9″,v 10 ("), where the weight of the number of valves in the pump station I9 is... Weight of the number of river sluice gates and dams I10 (i = 9, 10; when i = j, h) ij =1);

[0170] The weight of the final indicator level Hi Where u n "" represents the weight of the criterion level to which the i-th indicator belongs, v i "" indicates the weight of the indicator level to which the i-th indicator belongs; (n takes values ​​from 1 to 3, i takes values ​​from 1 to 10);

[0171] (2) Calculate the objective weight matrix of the "control capability" indicator system. Objective weights are calculated by analyzing the correlation between indicators using standard correlation analysis; the original indicator data of each street is set as m evaluation samples, i.e., m streets, and n evaluation indicators (where n=10), forming the original indicator data matrix of "control capability":

[0172]

[0173] The raw data for the 10 indicators in "Control Capability" are dimensionless, as shown in the following formula:

[0174]

[0175] In the formula, X ij "" represents the standard index value of the j-th indicator for the i-th street, x ij "" represents the raw data of the j-th indicator for the i-th street; x max(j) "and x min(j) "" represents the maximum and minimum values ​​of the j-th indicator across all streets;

[0176] Calculate the difference α between each indicator j "The greater the difference, the stronger the evaluation intensity."

[0177]

[0178] In the formula, m represents the number of streets; X ij "" represents the standard index value of the j-th indicator in the i-th street. This represents the average value of the standard indicator across all streets for the j-th indicator;

[0179] Calculate the conflict β among the indicators j "The correlation coefficient is used to represent the correlation between the "control capability" indicators. The stronger the correlation, the smaller the conflict, and the weight assigned to this indicator should be reduced."

[0180]

[0181] In the formula, m represents the number of streets; r jk "" represents the correlation coefficient between the j-th indicator level and the k-th indicator level; X ij " is the standard indicator value of the j-th indicator for the i-th street; X represents the average value of the standard indicator across all streets for the j-th indicator; ik " is the standard index value of the k-th indicator for the i-th street; The k-th indicator represents the average value of the standard indicator across all streets; j, k = (1, 2, 3, 4, 5, 6, 7) under the H1 criterion level for information monitoring; j, k = (7, 8) under the H2 criterion level for emergency maintenance; j, k = (9, 10) under the H3 criterion level for dispatch control.

[0182] The information content C is calculated by combining standard deviation and conflict. j "=α j "×β" j ", thus obtaining the objective weight of the j-th indicator in the "control capability" indicator system. The objective weighting matrix of the "control and management capability" indicator system

[0183] (3) Calculate the combined weight matrix W of the "control capability" indicator system. G "=(ω1″,ω2″,…,ω 10 The optimization strategy is given through formulaic calculation; the weighting of the two results is weighed in combination with game theory, and the subjective weight of any indicator is determined by formula (33). and objective weight Substituting the values ​​(where i = 1, 2, ..., 10), we obtain a relatively balanced and coordinated combined weight vector μ. S″ and μ O″ The optimal weighting of this indicator The combined weight ω of the 10 indicators of "control capability" i The weight matrix W of the "control capability" indicator system is obtained by arranging them in order. G "=(ω1″,ω2″,…,ω 10 ");

[0184]

[0185] In the formula, This represents the subjective weight of the i-th indicator; This represents the objective weight of the i-th indicator; express transpose, express transpose;

[0186] Step 3, Calculation of the data matrix for the trade-off and collaborative evaluation of the "health status-failure consequences-control capability" of the urban sewage system: The data matrix is ​​calculated separately for the three systems of "health status", "failure consequences" and "control capability".

[0187] The steps for calculating the data matrix of the "health status" indicator system are as follows:

[0188] (1) Determine the evaluation index set and comment set of the "health status" indicator system; based on the quantity of original sewage pipeline data, there are n evaluation indicators, then the evaluation index set can be represented as γ A =(γ1,γ2,…,γ n (n=25); According to the principle of determining the classification level of the indicators of the "health status" indicator system of urban sewage system (Appendix 3), each indicator is divided into four evaluation levels {I,II,III,IV}; the corresponding evaluation score value set is δ=(10,6.7,3.3,0);

[0189] (2) Determine the data matrix for the "health status" indicator system The percentage of the i-th evaluation indicator among the four rating levels is represented by fuzzy set R. Ai =(r i1 ,r i2 ,r i3 ,r i4 ), where the evaluation index set γ A The i-th evaluation indicator represents the percentage of the i-th comment's grade in the comment set. i1 The percentage of the second rating indicates r. i2 And so on; the evaluation indicator set and the comment set are divided into qualitative indicators and quantitative indicators, among which the qualitative indicators are directly constructed based on the indicator classification levels in Appendix 3. Ai For qualitative indicators, the percentage of the indicator in the four evaluation levels is 100%, while the percentage in the other three levels is 0. The fuzzy set calculation process for qualitative indicators is as follows: For example, if the degree of rupture of the first sewage pipe is "cracks appear (crack width < 2mm)," it belongs to Level II, and its fuzzy set R... Ai = (0,1,0,0); Quantitative indicators (such as "pipe length C14", "pipe diameter C15", "pipe age C16", etc.) are classified and graded according to the indicators in Appendix 3 to construct R. Ai Among them, according to the fuzzy set R in Appendix 3, the number of levels increases from I to IV.Ai Represented as According to the fuzzy set R in Appendix 3, the number of levels decreases from I to IV. Ai Represented as x represents a specific quantitative value, a represents the minimum / maximum value of rating level I (the higher the level, the greater the increase in quantity) / maximum value (the higher the level, the less the quantity), b represents the boundary between rating levels II and III, c represents the boundary between rating levels III and IV, and d represents the maximum / minimum value of rating level IV (the higher the level, the greater the increase in quantity) / maximum value (the higher the level, the less the quantity). Values ​​that are not found or do not meet the criteria are 0. For example, in the fuzzy set calculation process for quantitative indicators: when the length of the first sewage pipe is 40.00 meters, a = 20, b = 50, c = 100, d = 150. r i3 =0, r i4 =0, the first sewage pipe is a combination of 33% I and 67% II, denoted as R. 管长1 =(r i1 ,r i2 ,r i3 ,r i4 = (0.33, 0.67, 0, 0);

[0190] (3) Determine the fuzzy vector ε of the "health status" indicator system. A =R A *W A = (ε1, ε2, ε3, ε4), R A W represents the data matrix of the "health status" indicator system. A A weighted matrix representing the combined weights of the "health status" indicator system;

[0191] (4) Determine the evaluation score S of the "health status" indicator system. A Calculate the evaluation score of the sewage pipeline based on the original data of the "health status" indicator system, which is S. A ′=ε A *δ T , ε A δ represents a fuzzy vector representing the "health status" indicator system. T This represents the transpose of the set of evaluation scores; to allow management departments to manage urban wastewater systems at the street level, the evaluation score S of wastewater pipes in the "health status" indicator system is used. A Using the formula (S in the formula) Ai ′ represents the evaluation score of the i-th sewage pipe in the "health status" indicator system, l i Let ∑l represent the length of the i-th sewage pipe. iLet m represent the sum of the lengths of all sewage pipes within the street, and m represent the total number of sewage pipes in the "health status" index system. Weighting these values ​​to the street scale yields the evaluation score S of the "health status" index system. A ;

[0192] Appendix 3: Principles for Determining the Indicator Classification Levels of the "Health Status" Indicator System for Urban Wastewater Systems

[0193]

[0194]

[0195] Furthermore, the calculation steps for the data matrix of the "failure consequences" indicator system are as follows:

[0196] (1) Determine the evaluation index set and comment set of the "failure consequences" index system; based on the quantity of original sewage pipeline data, there are n evaluation indicators, then the evaluation index set can be represented as γ D ′=(γ1′,γ2′,…,γ n ′)(n=10); According to the principle of determining the classification level of the indicators of the "failure consequences" indicator system of urban sewage system (Appendix 4), each indicator is divided into four evaluation levels {I,II,III,IV}; the corresponding evaluation score value set is δ=(10,6.7,3.3,0).

[0197] (2) Determine the data matrix for the "failure consequences" indicator system. The data proportion of the i-th evaluation indicator is represented by fuzzy set R. Di =(r i1 ′,r i2 ′,r i3 ′,r i4 ′), where the evaluation index set γ D The i-th evaluation indicator represents the percentage of the first comment grade in the comment set. i1 ′, the percentage of the second comment level represents r i2 ', and so on; the evaluation indicator set and the comment set are divided into qualitative indicators and quantitative indicators. The qualitative indicators are directly constructed based on the indicator classification levels in Appendix 4 to form R. Di For qualitative indicators, the percentage of the indicator in the four evaluation levels is 100%, while the percentage in the other three levels is 0. The fuzzy set calculation process for qualitative indicators is as follows: if the road type where the first sewage pipe is located is "railway," then it belongs to level III, and its fuzzy set R... Ai = (0,0,1,0); Quantitative indicators (such as "distance to hospital F3", "distance to school F4", etc.) are classified into levels according to the indicators in Appendix 3 to construct R. Di According to the fuzzy set R in Appendix 3, the number of levels increases from I to IV.Ai Represented as According to the fuzzy set R in Appendix 3, the number of levels decreases from I to IV. Ai Represented as x represents a specific quantitative value, a represents the minimum / maximum value of rating level I (a type where the higher the level, the greater the quantity) / maximum value (a type where the higher the level, the less ... quantity, the more the quantity) / maximum value (a type where the quantity, the more the quantity) / maximum value (a type where the quantity, the more the quantity) / maximum value (a type where the quantity, the more the quantity) / maximum value (a type where the quantity, the more the quantity) / maximum value (a type where the quantity, the more the quantity) / maximum value (a type where the quantity, the more the quantity) / maximum value (a type where the quantity, the more the quantity) / maximum value (a type where i1 ′=0, r i2 ′=0, The first sewage pipe is a combination of 40% IV and 60% V, denoted as R. 与医院的距离1 =(r i1 ′,r i2 ,′,r i3 ′,r i4 ′)=(0,0,0.4,0.6);

[0198] (3) Determine the fuzzy vector ε of the "failure consequences" indicator system. D =R D *W D =(ε1′,ε2′,ε3′,ε4′), R D W represents the data matrix of the "failure consequences" indicator system. D A combined weight matrix representing the "failure consequences" indicator system;

[0199] (4) Determine the evaluation score S of the "failure consequences" indicator system. D Calculate the original data of the "failure consequences" indicator system to determine the evaluation score of the sewage pipeline as S. D ′=ε D *δ T , ε D δ represents the fuzzy vector of the "failure consequences" indicator system. T This represents the transpose of the set of evaluation scores; to allow management departments to manage urban wastewater systems at the street level, the evaluation score S of wastewater pipes in the "failure consequences" indicator system is used. D Using the formula (S in the formula) Di ′ represents the evaluation score of the i-th sewage pipe in the "failure consequences" indicator system, l i Let ∑l represent the length of the i-th sewage pipe. iLet m represent the sum of the lengths of all sewage pipes within the street, and m represent the total number of sewage pipes in the "failure consequences" index system. Weighting these values ​​to the street scale yields the evaluation score S for the "failure consequences" index system. D ;

[0200] Appendix 4: Principles for Determining the Indicator Classification Levels of the "Failure Consequences" Indicator System for Urban Wastewater Systems

[0201]

[0202] Furthermore, the calculation steps for the data matrix of the "control capability" indicator system are as follows:

[0203] (1) Determine the evaluation indicator set and comment set of the "control capability" indicator system; based on the amount of original data from the street, there are n evaluation indicators, then the evaluation indicator set can be represented as γ G =(γ1″,γ2″,…,γ n (n=10); According to the principle of determining the grade of indicators in the "control capacity" indicator system of urban sewage system (Appendix 5), each indicator is divided into four evaluation grades {I,II,III,IV}; the corresponding evaluation score value set is δ=(10,6.7,3.3,0).

[0204] (2) Determine the data matrix for the "control capability" indicator system. The data result of the i-th evaluation index is represented by a fuzzy set R. Gi =(r i1 ″,r i2 ″,r i3 ″,r i4 ″), where the evaluation index set γ G The i-th evaluation indicator represents the percentage of the first comment grade in the comment set. i1 "″, the percentage of the second comment level indicates r i2 ", and so on; directly construct the R level based on the indicators in Appendix 5." Gi The indicators (such as "number of pipeline flow monitoring points I1" and "number of pipeline liquid level monitoring points I2") are classified according to the indicators in Appendix 5 to construct R. Gi Among them, according to the fuzzy set R in Appendix 3, the number of levels increases from I to IV. Ai Represented as According to the fuzzy set R in Appendix 3, the number of levels decreases from I to IV. Ai Represented as x represents a specific quantitative value, a represents the minimum / maximum value of rating level I (the higher the level, the greater the quantity) / maximum value (the higher the level, the less the quantity), b represents the boundary between rating levels II and III, c represents the boundary between rating levels III and IV, and d represents the maximum / minimum value of rating level IV (the higher the level, the greater the quantity) / maximum value (the higher the level, the less the quantity). The quantitative indicator fuzzy set calculation process is as follows: When the number of pipeline flow monitoring points in the first street is 6, a = 20, b = 10, c = 5, d = 0, r i1 " = 0, r i4 " = 0, the first street is a combination of 20% II and 80% III, denoted as R 管长1 =(r i1 ″,r i2 ″,r i3 ″,r i4 ″)=(0,0.2,0.8,0);

[0205] (3) Determine the fuzzy vector ε of the "control capability" indicator system. G =R G *W G ″=(ε1″,ε2″,ε3″,ε4″), R G W represents the data matrix of the "control capability" indicator system. G "" represents the combined weight matrix of the "control capability" indicator system;

[0206] (4) Determine the evaluation score S of the "control capability" indicator system. G Calculate the evaluation score S of the "control and management capability" indicator system. G =ε G *δ T , ε G δ represents the fuzzy vector of the "control capability" indicator system. T This represents the transpose of the set of possible score values ​​for the comments;

[0207] Appendix 5: Principles for Determining the Indicator Classification Levels of the "Management Capacity" Indicator System for Urban Wastewater Systems

[0208]

[0209] Step 4, Trade-off and Collaborative Evaluation of Urban Wastewater System "Health Status-Failure Consequences-Control Capability": Based on the area of ​​the street and the total scores of each pair of systems (health status-failure consequences, failure consequences-control capability, health status-control capability), a regression model is built to obtain the regression coefficients between each pair of systems (health status-failure consequences, failure consequences-control capability, health status-control capability) in each street, thereby determining whether the pairs of systems have a trade-off or a collaborative relationship;

[0210] Furthermore, the "health-failure-control" trade-off and synergistic evaluation of the urban wastewater system in step 4 is performed using a geographic weighted regression model in ArcGIS software for spatial calculation of the trade-offs and synergies. The mathematical expression of the model is X. i =α0(x i ,y i )+α k (x i ,y i )x jk +ψ i , its (x i ,y i ) represents the spatial location of the i-th street, i.e., the spatial latitude and longitude information of each street (the information data is in the .shp format of ArcGIS software); X i x is the dependent variable. jk Let S be the independent variable, where the health value is S. A / Failure value S D / Control value S G Both can be dependent and independent variables, thus corresponding to pairwise systems; ψ i For random error; α0(x) i ,y i ) represents the intercept of the i-th street; α k (x i ,y i )x jk Represents regression coefficients; for example: the health value S of the first street. A =7.65389, failure value S D =6.941844, control value S G =2.198928, input health value S A Failure value S D Based on the spatial location latitude and longitude information of the street, the intercept α0(x) is obtained. i ,y i ) = 8.188471, random error ψ i =0.096537, the regression coefficient α between the health status and failure consequences pairs in this street. k (x i ,y i )xjk = -0.090915; Input health value S A Control value S G Based on the spatial location latitude and longitude information of the street, the intercept α0(x) is obtained. i ,y i ) = 7.573596, random error ψ i =0.068428, the regression coefficient α between the health status and failure consequences pairs in this street. k (x i ,y i )x jk =0.005396; Input failure value S D Control value S G Based on the spatial location latitude and longitude information of the street, the intercept α0(x) is obtained. i ,y i ) = 6.352404, random error ψ i =0.474025, the regression coefficient α between the health status and failure consequences pairs in this street. k (x i ,y i )x jk =0.052487; According to the obtained regression coefficients, the positive regression coefficients indicate that the scores of the two systems are spatially cooperative, while the negative regression coefficients reflect that the scores of the two systems are spatially trade-off.

[0211] Step 5, Identifying Spatially Imbalanced Streets under the Trade-off and Collaborative Evaluation of the "Health-Failure-Control" of Urban Sewage Systems: The identification of spatially imbalanced streets can be divided into the following three situations. If any one of them is met, it can be defined as a spatially imbalanced street. If none of the three conditions are met, it is defined as a spatially balanced street.

[0212] (1) The failure of sewage pipes will have socio-economic impacts on the surrounding area. The higher the consequences of sewage system failure, the higher the health status of the urban sewage system is required. Therefore, the two indicator systems of "health status" and "failure consequences" are defined as having a spatial synergistic relationship (the score of one indicator system increases as the score of the other indicator system increases). If a spatial trade-off relationship is calculated (the score of one indicator system decreases as the score of the other indicator system increases), then the street is defined as a spatially unbalanced street.

[0213] (2) Streets with high failure consequences should be equipped with more efficient control capabilities. Therefore, the two indicator systems of "failure consequences" and "control capabilities" are defined as having a spatial synergistic relationship (the score of one indicator system increases as the score of the other indicator system increases). If a spatial trade-off relationship is calculated (the score of one indicator system decreases as the score of the other indicator system increases), then the street is defined as a spatially unbalanced street.

[0214] (3) From the perspective of optimizing resource allocation, the higher the health status of the sewage system, the less financial investment is needed in management and control capabilities. Instead, investment in management and control should be strengthened in streets with low health status. Therefore, the relationship between the two indicator systems of "health status" and "management and control capabilities" is defined as a spatial trade-off (the score of one indicator system decreases as the score of the other indicator system increases). If a spatial synergy relationship is calculated (the score of one indicator system increases as the score of the other indicator system increases), then the street is defined as a spatially unbalanced street.

[0215] Step 6: Identifying streets with functional imbalances under the "health-failure-control" trade-off and collaborative evaluation of urban sewage systems: according to the formula (S D S represents the evaluation score of the "failure consequences" indicator system. A S represents the evaluation score of the "health status" indicator system. G The evaluation score of the "control capacity" indicator system is used to rank all streets in ascending order. The top 75% of streets are defined as functionally unbalanced streets, and the bottom 25% of streets are defined as functionally balanced streets.

[0216] Step 7: Corresponding to the management scale of the sewage management department, municipal streets are divided into three categories: Category A streets, Category B streets, and Category C streets. Precise management can be carried out according to the category of the street. Category A streets represent streets with balanced space and function. When the government's finances are limited and the sewage system is in good condition, there is no need to increase investment in these streets. Category B streets represent streets with unbalanced space and balanced function. It is necessary to strengthen the control and management of these streets. These streets have a good foundation, and investment in operation and maintenance can effectively reduce resource waste. Category C streets represent streets with unbalanced space and function. It is necessary to strengthen both infrastructure construction and control and management.

[0217] Each street is annotated on the municipal street map.

[0218] Appendix Explanation

[0219] Appendix 1 shows the scoring rules for the 1-9 scale.

[0220] Appendix 2 is a table of values ​​for the random consistency index RI.

[0221] Appendix 3 outlines the principles for determining the classification levels of indicators in the "health status" indicator system for urban wastewater systems.

[0222] Appendix 4 outlines the principles for determining the classification levels of indicators in the "failure consequences" indicator system for urban wastewater systems.

[0223] Appendix 5 outlines the principles for determining the classification levels of indicators in the "Management Capacity" indicator system for urban wastewater systems.

[0224] Appendix 6 shows the subjective weight, objective weight, and combined weight of each indicator in the "Health Status" indicator system;

[0225] Appendix 7 shows the subjective weight, objective weight, and combined weight of each indicator in the "Failure Consequences" indicator system;

[0226] Appendix 8 shows the subjective weight, objective weight, and combined weight of each indicator in the "Control Capability" indicator system; Attached Figure Description

[0227] The present invention will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings:

[0228] Appendix Figure 1 This is a flowchart of the method for balancing and coordinating the "health status-failure consequences-control capability" of urban sewage systems according to an embodiment of the present invention;

[0229] Appendix Figure 2 This invention relates to an index system for the "health status" of urban wastewater systems.

[0230] Appendix Figure 3 This invention is a "failure consequences" index system for urban sewage systems;

[0231] Appendix Figure 4 This invention is a system of indicators for the "control and management capabilities" of urban wastewater systems.

[0232] Appendix Figure 5 This is a spatial distribution diagram of the scores of the "health status" index system of the urban sewage system according to an embodiment of the present invention;

[0233] Appendix Figure 6 This is a spatial distribution diagram of the scores of the "failure consequences" index system of the urban sewage system according to an embodiment of the present invention;

[0234] Appendix Figure 7 This is a spatial distribution diagram of the scores of the "control and management capability" index system for urban sewage systems in an embodiment of the present invention;

[0235] Appendix Figure 8 This invention relates to the trade-offs and synergistic relationships between two indicator systems in the urban wastewater system.

[0236] Appendix Figure 9 This is a spatial distribution map of streets of categories A, B, and C according to the present invention; Detailed Implementation

[0237] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the claims. All inventions utilizing the concept of the present invention are protected.

[0238] This embodiment of the evaluation method for the trade-off and synergistic assessment of the "health status-failure consequences-control capability" of urban sewage systems selects the area within the Fifth Ring Road of Beijing as the core study area. The data in this embodiment includes sewage pipeline data with a total length of approximately 263 kilometers and data of 101 streets within the study area; it identifies the relevant indicators of the "health status-failure consequences-control capability" of urban sewage systems, calculates the spatial distribution of scores for each indicator system, and further obtains the spatial trade-off and synergistic relationship, thereby identifying streets of categories A, B, and C;

[0239] A method for balancing and coordinating the "health status, failure consequences, and control capabilities" of urban wastewater systems. Figure 1 The process involved in this method is illustrated;

[0240] Step 1: Construction of a balanced and collaborative evaluation index system for the "health status - failure consequences - control capabilities" of urban sewage systems: This system comprehensively considers the health status, failure consequences, and control capabilities of the entire process from the influent to the effluent from the sewage treatment plant to the river. The three index systems of "health status", "failure consequences", and "control capabilities" exist independently of each other.

[0241] The "Health Status" A1 mainly considers 25 health indicators C1-C25 constructed under five criteria: structural defects B1, functional defects B2, engineering attributes B3, social environment B4, and water plant health B5. The "Health Status" indicator system is constructed with reference to... Figure 2 ;

[0242] The "Failure Consequences" D1 primarily considers 10 failure consequence indicators F1-F10 constructed under four criteria: loss of public property (E1), interruption of service of critical buildings (E2), water pollution (E3), and water plant failure (E4). The construction of the "Failure Consequences" indicator system references... Figure 3 ;

[0243] The "Control Capability" G1 is mainly constructed based on three criteria: information monitoring (H1), emergency maintenance (H2), and dispatch control (H3), comprising 10 control capability indicators I1-I10. The construction of the "Control Capability" indicator system is based on... Figure 4 ;

[0244] Step 2: Calculation of the weight matrix for each indicator in the trade-off and collaborative evaluation of the "health status - failure consequences - control capability" of the urban sewage system: The weight matrix of indicators for the three systems of "health status", "failure consequences" and "control capability" is calculated separately.

[0245] In the calculation of the indicator weight matrix of the "health status" indicator system, the subjective weights of 25 indicators are calculated to obtain the subjective weight judgment matrix. The objective weights of the 25 indicators were calculated to obtain the objective weight matrix. After the game, the combined weight matrix WA under this system was obtained; the calculation results of the weights of the 25 indicators are shown in Table 4.

[0246] Appendix 4: Subjective weight, objective weight, and combined weight of each indicator in the "Health Status" indicator system

[0247]

[0248] In the calculation of the indicator weight matrix of the "failure consequences" indicator system, the subjective weights of the 10 indicators are calculated to obtain the subjective weight judgment matrix. The objective weights of the 10 indicators were calculated to obtain the objective weight matrix. After the game, the combined weight matrix W under this system is obtained. D The weight calculation results for the 10 indicators are shown in Table 5.

[0249] Appendix 5: Subjective weight, objective weight, and combined weight of each indicator in the "Failure Consequences" indicator system

[0250]

[0251] In the calculation of the indicator weight matrix of the "control capability" indicator system, the subjective weights of the 10 indicators are calculated to obtain the subjective weight judgment matrix. The objective weights of the 10 indicators were calculated to obtain the objective weight matrix. After the game, the combined weight matrix W under this system is obtained. G The weight calculation results for the 10 indicators are shown in Table 6.

[0252] Appendix 6: Subjective weight, objective weight, and combined weight of each indicator in the "Control Capability" indicator system

[0253]

[0254] Step 3: Calculation of the data matrix for the trade-off and synergistic evaluation of the "health status - failure consequences - control capability" of the urban wastewater system: The data matrix for each of the three systems—"health status," "failure consequences," and "control capability"—is calculated separately; the spatial distribution map of the "health status" indicator system scores is provided for reference. Figure 5Reference for the score space distribution chart of the "failure consequences" indicator system Figure 6 Reference for the score space distribution chart of the "control and management capability" indicator system Figure 7 ;

[0255] Step 4, Trade-off and Collaborative Evaluation of Urban Wastewater System's "Health Status - Failure Consequences - Control Capability": Based on the street area and the total scores of each pair of systems (Health Status - Failure Consequences, Failure Consequences - Control Capability, Health Status - Control Capability), a regression model is constructed to obtain the regression coefficients between each pair of systems in each street (Health Status - Failure Consequences, Failure Consequences - Control Capability, Health Status - Control Capability), thereby determining the trade-off and collaborative relationships; (Reference) Figure 8 This indicates the trade-off and synergistic relationship between the two indicator systems of the urban wastewater system;

[0256] Corresponding to the management standards of the wastewater management department, refer to Figure 9 Municipal streets are divided into three categories: Category A, Category B, and Category C, which allows for precise management based on the street category.

Claims

1. A method for balancing and coordinating the "health status, failure consequences, and control capabilities" of an urban wastewater system, characterized in that... Includes the following steps: Step 1: Construction of the "Health Status-Failure Consequences-Control Capability" Trade-off and Collaborative Evaluation Index System for Urban Wastewater System: The system comprehensively considers the health status, failure consequences, and control capability of the entire process from the influent to the effluent from the wastewater treatment plant to the river. The three index systems of "Health Status", "Failure Consequences", and "Control Capability" exist independently of each other. Among them, "Health Status" A1 mainly considers 25 health indicators C1-C25 constructed under five criteria: structural defects B1, functional defects B2, engineering attributes B3, social environment B4, and water plant health B5; "Failure Consequences" D1 mainly considers 10 failure consequence indicators F1-F10 constructed under four criteria: loss of public property E1, interruption of service of critical buildings E2, water pollution E3, and water plant failure E4; "Control Capability" G1 mainly considers 10 control capability indicators I1-I10 constructed under three criteria: information monitoring H1, emergency maintenance H2, and dispatch control H3. Step 2: Calculation of the weight matrix for each indicator in the trade-off and collaborative evaluation of "health status - failure consequences - control capability" of the urban sewage system: The weight matrix of indicators for the three systems of "health status", "failure consequences" and "control capability" is calculated separately; In the calculation of the weight matrix of the system, the subjective weight judgment matrix and the objective weight judgment matrix are compared to obtain the combined weight matrix under the system. Step 3, Calculation of the data matrix for the trade-off and collaborative evaluation of the "health status - failure consequences - control capability" of the urban sewage system: The data matrix is ​​calculated separately for the three systems of "health status", "failure consequences" and "control capability". Step 4, Trade-off and Collaborative Evaluation of Urban Wastewater System's "Health Status-Failure Consequences-Control Capability": Based on the area of ​​the street and the total scores of each pair of systems: health status-failure consequences, failure consequences-control capability, and health status-control capability, a regression model is constructed to obtain the regression coefficients between each pair of systems in each street: health status-failure consequences, failure consequences-control capability, and health status-control capability, thereby determining whether the pairs of systems have a trade-off or a collaborative relationship. Step 5, Identifying Spatially Imbalanced Streets under the "Health-Failure-Control" Trade-off and Collaborative Evaluation of Urban Wastewater Systems: The identification of spatially imbalanced streets can be divided into the following three situations. If any one of them is met, it can be defined as a spatially imbalanced street. If none of the three conditions are met, it is defined as a spatially balanced street. (1) The failure of sewage pipes will have socio-economic impacts on the surrounding area. The higher the consequences of sewage system failure, the higher the health status of the urban sewage system is required. Therefore, the two indicator systems of "health status" and "failure consequences" are defined as spatial synergy. If the spatial trade-off relationship is calculated, the street is defined as a spatially unbalanced street. (2) Streets with high failure consequences should be equipped with more efficient control capabilities. Therefore, the two indicator systems of "failure consequences" and "control capabilities" are defined as having a spatial synergy relationship. If a spatial trade-off relationship is obtained through calculation, the street is defined as a spatially unbalanced street. (3) From the perspective of optimizing resource allocation, the higher the health status of the sewage system, the less financial investment is needed in management and control capabilities. Instead, management and control investment should be strengthened in streets with low health status. The two indicator systems of "health status" and "management and control capabilities" are defined as a spatial trade-off relationship. If the spatial synergy relationship is obtained by calculation, the street is defined as a street with spatial imbalance. Step 6: Identifying streets with functional imbalances under the "health-failure-control" trade-off and collaborative evaluation of urban sewage systems: according to the formula S D S represents the evaluation score of the "failure consequences" indicator system. A S represents the evaluation score of the "health status" indicator system. G The evaluation score of the "control capacity" indicator system is used to rank all streets in ascending order of their scores. The top 75% of streets are defined as functionally unbalanced streets, and the bottom 25% of streets are defined as functionally balanced streets. Step 7: Corresponding to the management scale of the sewage management department, municipal streets are divided into three categories: Category A streets, Category B streets, and Category C streets. Precise management can be carried out according to the category of the street. Category A streets represent streets with balanced space and function. When the government's finances are limited and the sewage system is in good condition, there is no need to increase investment in these streets. Category B streets represent streets with unbalanced space and balanced function. It is necessary to strengthen the control and management of these streets. These streets have a good foundation, and investment in operation and maintenance can effectively reduce resource waste. Category C streets represent streets with unbalanced space and function. It is necessary to strengthen both infrastructure construction and control and management.

2. The method according to claim 1, characterized in that, The detailed definitions of the 25 indicators in the "health status" indicator system A1 of the urban sewage system in step 1 are as follows: The structural defect B1 criterion level includes six indicators: cracking (C1), deformation (C2), corrosion (C3), misalignment (C4), disconnection (C5), and intrusion (C6). "Structural defects" often refer to pipeline defects that damage the pipe body itself and affect the integrity of the pipeline structure. "Cracking (C1)" indicates the degree of cracking or damage to the drainage pipe caused by external forces exceeding its own bearing capacity. "Deformation (C2)" indicates the degree of deformation of the pipe due to foundation settlement or external pressure. "Corrosion (C3)" indicates the degree of erosion of the inner or outer wall of the pipe by the environmental medium. "Misalignment (C4)" indicates the degree of misalignment of adjacent pipe joints. "Disconnection (C5)" indicates the degree of disconnection of the pipe connection. "Intrusion (C6)" indicates the degree of abnormal entry or penetration of external objects into or through the drainage pipe. The Functional Defect B2 criterion level includes six indicators: sedimentation (C7), scaling (C8), debris (C9), puddles (C10), blockage (C11), and tree roots (C12). "Functional defect" refers to pipe defects that cause changes in the cross-sectional area of ​​the pipe. "Sedimentation (C7)" refers to sediment and other foreign matter in the water that accumulates at the bottom of the drainage pipe. "Scale (C8)" refers to soft or hard scale that adheres to or deposits on the inner surface of the drainage pipe, such as grease, iron salts, and lime. "Debris (C9)" refers to hard foreign objects such as broken bricks, branches, abandoned tools, and broken pipe fragments in the drainage pipe. "Puddle (C10)" refers to localized water accumulation in the drainage pipe caused by uneven foundation settlement. "Blockage (C11)" refers to sealing materials remaining in the drainage pipe. "Tree roots (C12)" refers to tree root groups that have grown into the drainage pipe naturally. The engineering attribute B3 criterion level contains basic data for assessing the operational status of sewage pipelines, including six indicators: pipe material (C13), pipe length (C14), pipe diameter (C15), pipe age (C16), pipe burial depth (C17), and design flow rate (C18). All of the above data can be obtained from pipeline construction and design data. The social environment B4 criterion level covers five indicators: pressure load (C19), pipeline function (C20), soil type (C21), wastewater type (C22), and groundwater depth (C23). "Pressure load (C19)" is calculated from the ground traffic or building load borne by the pipeline. "Pipeline function (C20)" indicates the specific functional classification of the pipeline in the sewage system, including main line, secondary line, household line, and branch line. "Soil type (C21)" indicates the soil properties around the pipeline. "Groundwater depth (C22)" indicates the groundwater level near the pipeline. "Wastewater type (C23)" indicates the source of wastewater contained in the sewage pipeline. The B5 health criteria for water treatment plants explore two indicators: low influent concentration (C24) and total load overload (C25). "Low influent concentration (C24)" refers to the C / N ratio of the influent water quality of the wastewater treatment plant, while "total load overload (C25)" refers to the operating load rate of the wastewater treatment plant, which is calculated by the ratio of the actual influent volume to the designed treatment volume. The detailed definitions of the 10 indicators at each level in the construction of the urban wastewater system "failure consequences" indicator system D1 in step 1 are as follows: The public property loss E1 criterion level includes two indicators: road type F1 and land use type F2. "Road type F1" indicates the level of impact on the health status of sewage pipelines based on the traffic function level of the road, and "land use type F2" indicates the land use type where the sewage pipeline is located. The critical building service interruption E2 criterion hierarchy is divided into four indicators: distance to hospitals (F3), distance to schools (F4), distance to buildings (F5), and distance to parks / recreational facilities (F6). "Distance to hospitals (F3)" is to consider the impact of sewage pipe failure on medical services; "Distance to schools (F4)" is to consider the impact of sewage pipe failure on the normal operation of schools and students' lives; "Distance to buildings (F5)" is to consider the impact of sewage pipe failure on the structural safety of nearby buildings; and "Distance to parks / recreational facilities (F6)" is to consider the impact of sewage pipe failure on the environment and people's leisure activities in these areas. All four indicators are calculated using the neighborhood analysis tool of ArcGIS software to determine the distance between sewage pipes and points of interest (POIs). The E3 criterion for water pollution includes two indicators: distance to the river (F7) and distance to the deteriorated stormwater pipe (F8). "Distance to the river (F7)" indicates that a failed sewage pipe causes sewage to flow into the river, polluting the water environment. The nearest distance between the sewage pipe and the river's centerline is calculated using ArcGIS software's neighborhood analysis tool. "Distance to the deteriorated stormwater pipe (F8)" explores how structural defects in sewage pipes can pollute deteriorated stormwater outlets even in dry weather. Management departments use closed-circuit television (CCTV) to detect and identify the location of deteriorated stormwater pipes, and ArcGIS software's neighborhood analysis tool is used to calculate the nearest distance between the sewage pipe and the deteriorated stormwater pipe. The E4 criterion level for water plant failure includes disease transmission risk (F9) and impact on residents (F10). "Disease transmission risk (F9)" refers to the distance between the water diversion canal and the sewage treatment plant, while "impact on residents (F10)" refers to the impact on the sewage pipes of residents within 500 meters after the sewage treatment plant fails. The detailed definitions of the 10 indicators in the "management capacity" indicator system G1 of the urban wastewater system in step 1 are as follows: The information monitoring H1 criteria level includes the number of pipeline flow monitoring points I1, the number of pipeline liquid level monitoring points I2, the number of river flow monitoring points I3, the number of river water level monitoring points I4, the number of river water quality monitoring points I5, and the rain gauge coverage I6. All six indicators represent the number of monitoring points contained in the street. The emergency maintenance H2 criteria include the number of emergency rescue stations (I7) and the coverage of maintenance teams (I8). "Number of emergency rescue stations (I7)" indicates the proportion of manholes accessible by emergency rescue stations within 10 minutes out of the total number of manholes in the street. "Coverage of maintenance teams (I8)" indicates the number of maintenance teams covering the sewage pipes in the street. The scheduling control H3 criterion level includes the number of pump stations and valve nodes I9 and the number of river sluice gates I10, which respectively represent the number of pump stations and valves in the street's drainage network and the number of river sluice gates in the street.

3. The method according to claim 1, characterized in that, Step 2, The steps for calculating the combined weight matrix of the "health status" indicator system are as follows: (1) Calculate the subjective weight matrix of the "health status" indicator system. Where i = 1, 2, 3…25; the relative importance of each level of elements is compared by subjective scoring from the experts using the 1–9 scale method (Appendix 1); Appendix 1 Scoring Rules for the 1-9 Scale The importance of the corresponding criteria levels in the health status A1 system, namely structural defects B1, functional defects B2, engineering attributes B3, social environment B4, and water plant health B5, is compared pairwise to obtain the judgment matrix A1 of health status A1, as shown in formula (1). Where a 12 This indicates the relative importance of structural defect B1 compared to functional defect B2; a 13 This indicates the relative importance of structural defect B1 to engineering attribute B3; a 14 This indicates the relative importance of structural defect B1 to the social environment B4; a 15 This indicates the relative importance of structural defect B1 to the water plant health B5; a 21 This indicates the relative importance of functional defect B2 compared to structural defect B1, i.e. a 23 This indicates the relative importance of functional defect B2 to engineering attribute B3; a 24 This indicates the degree of importance of functional deficit B2 relative to the social environment B4; a 25 This indicates the degree of importance of functional defect B2 relative to the water plant health B5; a 31 This indicates the relative importance of engineering attribute B3 compared to structural defect B1, i.e. a 32 This indicates the relative importance of engineering attribute B3 compared to functional defect B2, i.e. a 34 This indicates the degree of importance of engineering attribute B3 relative to the social environment B4; a 35 This indicates the relative importance of engineering attribute B3 to the water plant health attribute B5; a 41 This indicates the relative importance of the social environment B4 compared to the structural defect B1, i.e. ; a 42 This indicates the relative importance of social environment B4 compared to functional deficit B2, i.e. a 43 This indicates the relative importance of social environment B4 compared to engineering attribute B3, i.e. a 45 This indicates the relative importance of the social environment (B4) to the water plant's health (B5). a 51 This indicates the relative importance of water plant health (B5) to structural defects (B1). a 52 This indicates the relative importance of water plant health (B5) compared to functional defect (B2). a 53 This indicates the relative importance of water plant health attribute B5 compared to engineering attribute B3, i.e. a 54 This indicates the relative importance of water plant health (B5) compared to the social environment (B4). The importance of the corresponding index levels in the hierarchical defect B1 of the criteria are compared pairwise to obtain the judgment matrix B1 of the structural defect B1, as shown in formula (2). Where b 12 This indicates the relative importance of fracture C1 compared to deformation C2; b 13 This indicates the relative importance of fracture C1 compared to corrosion C3; b 14 This indicates the relative importance of fracture C1 to misalignment C4; b 15 This indicates the relative importance of fracture C1 compared to disintegration C5; b 16 This indicates the relative importance of rupture C1 compared to intrusion C6; b 21 This indicates the relative importance of deformation C2 to fracture C1, i.e. b 23 This indicates the relative importance of deformation C2 compared to corrosion C3; b 24 This indicates the relative importance of deformation C2 to misalignment C4; b 25 This indicates the relative importance of deformation C2 compared to disintegration C5; b 26 This indicates the relative importance of deformation C2 compared to intrusion C6; b 31 This indicates the relative importance of corrosion C3 compared to fracture C1, i.e. b 32 This indicates the relative importance of corrosion C3 compared to deformation C2. b 34 This indicates the relative importance of corrosion C3 compared to misalignment C4; b 35 This indicates the relative importance of corrosion C3 compared to delamination C5; b 36 This indicates the relative importance of corrosion C3 compared to penetration C6; b 41 This indicates the relative importance of the misalignment C4 to the fracture C1, i.e. b 42 This indicates the relative importance of misalignment C4 to deformation C2, i.e. b 43 This indicates the relative importance of misalignment C4 compared to corrosion C3, i.e. b 45 This indicates the relative importance of misalignment C4 compared to disengagement C5; b 46 This indicates the relative importance of the misdirection C4 compared to the intrusion C6; b 51 This indicates the relative importance of disintegration C5 compared to fracture C1, i.e. b 52 This indicates the relative importance of the dissociation C5 to the deformation C2, i.e. b 53 This indicates the relative importance of C5 dissociation compared to C3 corrosion, i.e. b 54 This indicates the relative importance of dislocation C5 to misalignment C4, i.e. b 56 This indicates the relative importance of C5 disconnection compared to C6 intrusion; b 61 This indicates the relative importance of intrusion C6 compared to rupture C1, i.e. b 62 This indicates the relative importance of intrusion C6 compared to deformation C2, i.e. b 63 This indicates the relative importance of intrusion C6 compared to corrosion C3, i.e. b 64 This indicates the relative importance of intrusion C6 to misalignment C4, i.e. b 65 This indicates the relative importance of intrusion C6 compared to detachment C5, i.e. The importance of the corresponding indicator levels in the functional defect B2 of the criteria level is compared pairwise: sedimentation C7, scaling C8, debris C9, puddles C10, blockage C11, and tree roots C12. The judgment matrix B2 of functional defect B2 is obtained as shown in formula (3). Where b 7，8 This indicates the relative importance of deposit C7 compared to scaling C8; b 7，9 Indicates the importance of sediment C7 relative to impurity C9; b 7，10 Indicates the importance of sediment C7 relative to depression water C10; b 7，11 This indicates the relative importance of deposition C7 compared to plugging C11; b 7，12 This indicates the relative importance of sedimentary C7 compared to root C12; b 8，7 This indicates the relative importance of scale formation C8 compared to deposition C7, i.e. b 8,9 This indicates the relative importance of scale (C8) compared to impurities (C9); b 8,10 This indicates the relative importance of scale formation C8 compared to puddles C10; b 8,11 This indicates the relative importance of scaling C8 compared to plugging C11; b 8，12 This indicates the relative importance of scale C8 compared to root C12; b 9,7 This indicates the importance of contaminant C9 relative to sediment C7, i.e. b 9,8 This indicates the relative importance of impurities C9 compared to scale C8. b 9,10 This indicates the relative importance of debris C9 compared to puddles C10; b 9,11 This indicates the relative importance of debris C9 compared to sealing C11; b 9,12 This indicates the relative importance of the debris C9 compared to the tree root C12; b 10,7 This indicates the relative importance of C10 in the depression water compared to C7 in the sediment, i.e. b 10,8 This indicates the relative importance of puddles (C10) compared to scale (C8), i.e. b 10，9 This indicates the relative importance of the puddles (C10) to the debris (C9), i.e. b 10，11 This indicates the relative importance of the puddles C10 to the sealing of C11; b 10，12 This indicates the relative importance of C10 in the puddles compared to C12 in the tree roots; b 11,7 This indicates the relative importance of blocking C11 compared to depositing C7, i.e. b 11,8 This indicates the relative importance of sealing C11 compared to scaling C8, i.e. b 11， 9 indicates the relative importance of blocking C11 compared to debris C9, i.e. b 11，10 This indicates the relative importance of sealing C11 compared to the puddles C10, i.e. b 11，12 This indicates the relative importance of sealing C11 compared to the tree root C12; b 12，7 This indicates the relative importance of root C12 compared to sedimentary C7, i.e. b 12，8 This indicates the relative importance of root C12 compared to scale C8, i.e. b 12,9 This indicates the relative importance of root C12 compared to debris C9, i.e. b 12,10 This indicates the relative importance of the tree root C12 to the puddle water C10, i.e. b 12,11 This indicates the relative importance of root C12 compared to sealing C11, i.e. The importance of the corresponding indicator levels in the engineering attribute B3 of the criteria level, namely: pipe material C13, pipe length C14, pipe diameter C15, pipe age C16, pipe burial depth C17, and design flow rate C18, is compared pairwise to obtain the judgment matrix B3 of the engineering attribute B3, as shown in formula (4). Where b 13,14 This indicates the relative importance of pipe material C13 to pipe length C14; b 13,15 This indicates the relative importance of pipe material C13 compared to pipe diameter C15; b 13,16 This indicates the relative importance of pipe material C13 compared to pipe age C16; b13,17 This indicates the relative importance of pipe material C13 compared to pipe burial depth C17; b 13,18 This indicates the importance of pipe material C13 relative to the design flow rate C18; b 14,13 This indicates the relative importance of pipe length C14 to pipe material C13, i.e. b 14，15 This indicates the relative importance of pipe length C14 to pipe diameter C15; b 14,16 This indicates the relative importance of pipe length C14 to pipe age C16; b 14，17 This indicates the importance of pipe length C14 relative to pipe burial depth C17; b 14，18 This indicates the importance of pipe length C14 relative to design flow rate C18; b 15，13 This indicates the relative importance of pipe diameter C15 compared to pipe material C13, i.e. b 15，14 This indicates the relative importance of pipe diameter C15 compared to pipe length C14. b 15，16 This indicates the importance of pipe diameter C15 relative to pipe age C16; b 15,17 This indicates the importance of pipe diameter C15 relative to pipe burial depth C17; b 15,18 This indicates the importance of pipe diameter C15 relative to design flow rate C18; b 16,13 This indicates the relative importance of pipe age C16 compared to pipe material C13, i.e. b 16，14 This indicates the relative importance of tube age C16 to tube length C14, i.e. b 16,15 This indicates the importance of pipe age C16 relative to pipe diameter C15, i.e. b 16,17 This indicates the importance of pipe age C16 relative to pipe burial depth C17; b 16,18 This indicates the importance of pipe age C16 relative to design flow rate C18; b 17,13 This indicates the relative importance of pipe burial depth C17 compared to pipe material C13, i.e. b 17,14 This indicates the importance of the pipe burial depth C17 relative to the pipe length C14, i.e. b 17,15 This indicates the importance of the pipe burial depth C17 relative to the pipe diameter C15, i.e. b 17,16 This indicates the importance of pipeline burial depth C17 relative to pipeline age C16, i.e. b 17，18 This indicates the importance of the pipeline burial depth C17 relative to the design flow rate C18; b 18，13 This indicates the relative importance of the design flow rate C18 to the pipe material C13, i.e. b 18，14 This indicates the importance of the design flow rate C18 relative to the pipe length C14, i.e. b 18,15 This indicates the importance of the design flow rate C18 relative to the pipe diameter C15, i.e. b 18,16 This indicates the importance of the design flow rate C18 relative to the pipe age C16, i.e. b 18，17 This indicates the importance of the design flow rate C18 relative to the pipe burial depth C17, i.e. The importance of the corresponding indicator levels in the social environment B4 of the criteria level is compared pairwise to obtain the judgment matrix B4 of social environment B4, as shown in formula (5). Where b 19，20 This indicates the relative importance of the pressure load C19 to the pipeline function C20; b 19，21 This indicates the importance of the bearing load C19 relative to soil type C21; b 19，22 This indicates the importance of the pressure load C19 relative to wastewater type C22; b 19，23 This indicates the importance of the pressure load C19 relative to the groundwater depth C23; b 20，19 This indicates the relative importance of the pipeline function C20 to the pressure load C19, i.e. b 20，21 This indicates the relative importance of pipeline function C20 to soil type C21; b 20，22 This indicates the relative importance of pipeline function C20 to wastewater type C22; b 20，23 This indicates the relative importance of pipeline function C20 to groundwater burial depth C23; b 21，19 This indicates the importance of soil type C21 relative to the bearing capacity C19, i.e. b 21，20 This indicates the relative importance of soil type C21 to pipeline function C20. b 21,22 This indicates the relative importance of soil type C21 to wastewater type C22; b 21,23 This indicates the importance of soil type C21 relative to groundwater depth C23; b 22，19 This indicates the importance of wastewater type C22 relative to pressure load C19, i.e. b 22，20 This indicates the relative importance of wastewater type C22 to pipeline function C20, i.e. b 22，21 This indicates the relative importance of wastewater type C22 compared to soil type C21, i.e. b 22，23 This indicates the importance of wastewater type C22 relative to groundwater depth C23; b 23，19 This indicates the importance of the pipeline burial depth C17 relative to the pressure load C19, i.e. b 23，20 This indicates the importance of the pipeline burial depth C17 relative to the pipeline function C20, i.e. b 23，21 This indicates the importance of pipeline burial depth C17 relative to soil type C21, i.e. b 23，22 This indicates the relative importance of the pipeline burial depth C17 to the groundwater burial depth C23, i.e. By comparing the importance of the corresponding indicator levels in the criterion level B5 of water plant health: low influent concentration C24 and total load overload C25, the judgment matrix B5 of water plant health B5 is obtained, as shown in formula (6). Where b 24，25 This indicates the relative importance of low influent concentration C24 compared to total load overload C25; b 25，24 This indicates the relative importance of total overload C25 compared to the low influent concentration C24, i.e. To ensure the correct subjective weight matrix for health status A1 is obtained. A consistency check is required first; Calculate the maximum eigenvalue (λ) corresponding to the judgment matrix A1 for health status A1, judgment matrix B1 for structural defects B1, judgment matrix B2 for functional defects B2, judgment matrix B3 for engineering attributes B3, judgment matrix B4 for social environment B4, and judgment matrix B5 for water plant health B5, respectively. max ), and obtain the consistency index for each judgment matrix. (λ max The largest eigenvalue of the judgment matrix is ​​represented by n; n represents the order of the judgment matrix. To compare the magnitudes of the CIs, the standard value of the random consistency index RI corresponding to the judgment matrix is ​​selected, and the test coefficients are finally obtained. (RI is selected according to the random consistency index RI value table in Appendix 2); when CR<0.1, it means that the consistency test is passed; otherwise, pairwise importance comparisons need to be performed again, the judgment matrix needs to be reconstructed, and the calculation continues until CR<0.

1. Appendix 2: Random Consistency Index (RI) Values After normalizing the judgment matrices A1, B1, B2, B3, B4, and B5, the subjective weight matrix of health state A1 is calculated using the arithmetic mean method. Calculate the weight matrix U = (u1, u2, u3, u4, u5) for the criterion hierarchy, where the weight of structural defect B1 is... The weight of functional defect B2 is The weight of project attribute B3 is The weight of social environment B4 is The weight of water plant health B5 is (i,j=1,2,…,5;When i=j, a ij =1); Calculate the hierarchical weight matrix V1 = (v1, v2, ..., v6) for the structural defect B1, where the weight of rupture C1 is... Weight of deformed C2 Weight of corrosion C3 Weight of C4 (misaligned) Disconnecting the weight of C5 Weights that intrude into C6 (i,j=1,2,…,6;When i=j, b ij =1); The hierarchical weight matrix of the indicators for calculating functional defect B2 is V2 = (v7, v8, ..., v 12 ), where the weight of deposited C7 Weight of scale C8 Weight of miscellaneous item C9 Weight of C10 in puddles Weight of blocking C11 Weight of blocking C12 (i,j = 7,8,…,12; when i = j, b) ij =1); Calculate the hierarchical weight matrix V3 of the indicator for engineering attribute B3 = (v 13 ,v 14 ,…,v 18 ), where the weight of pipe material C13 is Weight of pipe length C14 Weight of pipe diameter C15 Weight of C16 tube age Weight of pipeline burial depth C17 The weight of design flow C18 (i,j=13,14,…,18;When i=j, b ij =1); Calculate the hierarchical weight matrix V4 of the social environment B4 indexes = (v 19 ,v 20 ,…,v 23 ), where the weight of the pressure load C19 is Weight of pipeline function C20 Weight of soil type C21 Weight of groundwater depth C22 Weight of wastewater type C23 (i = 19, 20, ..., 23; when i = j, b) ij =1); The hierarchical weight matrix V5 for calculating the health index B5 of a water plant is: V5 = (v 24 ,v 25 ), where the weight of low influent concentration C24. Total overload weight of C25 (i = 24, 25; when i = j, b) ij =1); The weight of the final indicator level Ci Where u n v represents the weight of the criterion level to which the i-th indicator belongs. i This indicates the weight of the indicator at which it belongs; (n ranges from 1 to 5, i ranges from 1 to 25), that is... (2) Calculate the objective weight matrix of the "health status" indicator system. Objective weights are calculated by analyzing the correlation between indicators using standard correlation analysis; the original indicator data of sewage pipes are set as m evaluation samples, i.e., m sewage pipes, and n evaluation indicators (n=25), forming a matrix of original indicator data for "health status": The raw data for the 25 indicators of "health status" were dimensionless, and the formula is as follows: In the formula, X ij x represents the standard index value of the j-th index of the i-th sewage pipe. ij x represents the raw data of the j-th indicator for the i-th sewage pipe; max(j) and x min(j) These are the maximum and minimum values ​​of the j-th indicator across all sewage pipes, respectively. Calculate the difference α between each indicator j The greater the difference, the stronger the evaluation intensity. In the formula, m represents the number of sewage pipes; X ij This represents the standard index value of the j-th indicator for the i-th sewage pipe. This represents the average value of the standard index for the j-th index across all sewage pipes; Calculate the conflict β among the indicators j The correlation coefficient is used to represent the correlation between "health status" indicators. The stronger the correlation, the less conflict there is, and the weight assigned to this indicator should be reduced. In the formula, m represents the number of sewage pipes; r jk X represents the correlation coefficient between the j-th indicator level and the k-th indicator level; ij Let j be the standard index value of the j-th index of the i-th sewage pipe; X represents the average value of the standard index for the j-th index across all sewage pipes; ik Let k be the standard index value of the k-th index of the i-th sewage pipe; This represents the average value of the standard index for the k-th index across all sewage pipes; Structural defects B1 criterion level: j, k = (1, 2, ..., 6); Functional defects B2 criterion level: j, k = (7, 8, ..., 12); Engineering attributes B3 criterion level: j, k = (13, 14, ..., 18); Social environment B4 criterion level: j, k = (19, 20, ..., 23); Water plant health B5 criterion level: j, k = (24, 25). The information content C is calculated by combining standard deviation and conflict. j =α j ×β j The objective weight of the j-th indicator in the "health status" indicator system is obtained. Objective weight matrix of the "health status" indicator system (3) Calculate the combined weight matrix W of the "health status" indicator system. A =(ω1,ω2,…ω i …,ω 25 The optimization strategy is given through formulaic calculation; the weighting of the two outcomes is weighed in combination with game theory, and the subjective weight of any indicator is determined by formula (12). and objective weight Substituting the values ​​(where i = 1, 2, ..., 25), we obtain a relatively balanced and coordinated combined weight vector μ. S and μ O The optimal weighting of this indicator The combined weight ω of the 25 indicators of "health status" i Arranged in order, the weight matrix W of the "health status" indicator system is obtained. A =(ω1,ω2,…ω i …,ω 25 ); In the formula, This represents the subjective weight of the i-th indicator; This represents the objective weight of the i-th indicator; express transpose, express transpose; The steps for calculating the combined weight matrix of the "failure consequences" indicator system are as follows: (1) Calculate the subjective weight matrix of the "failure consequences" indicator system. Where i = 1, 2, ..., 10; the relative importance of each level of elements is compared by subjective scoring from the experts using the 1–9 scale method (Appendix 1); The corresponding criteria levels in the failure consequence D1 system, namely: loss of public property E1, interruption of service of critical buildings E2, water pollution E3 and failure of water plant E4, are compared in pairs to obtain the judgment matrix D1 of failure consequence D1, as shown in formula (13). Where d 12 This indicates the relative importance of public property loss E1 compared to critical building service disruption E2; d 13 This indicates the relative importance of public property loss E1 compared to water pollution E3; d 14 This indicates the relative importance of public property loss E1 compared to water plant failure E4; d 21 This indicates the relative importance of critical building service disruption E2 compared to public property loss E1, i.e. d 23 This indicates the relative importance of critical building service disruption E2 compared to water pollution E3; a 24 This indicates the relative importance of critical building service interruption E2 compared to water treatment plant failure E4; d 31 This indicates the relative importance of water pollution E3 compared to public property loss E1, i.e. d 32 This indicates the relative importance of water pollution E3 compared to critical building service disruption E2, i.e. d 34 This indicates the relative importance of water pollution E3 compared to water plant failure E4; d 41 This indicates the relative importance of water plant failure E4 compared to public property loss E1, i.e. d 42 This indicates the relative importance of water treatment plant failure (E4) compared to critical building service interruption (E2). d 43 This indicates the relative importance of water plant failure (E4) compared to water pollution (E3), i.e. By comparing the importance of the corresponding indicator levels in the criteria level public property loss E1: road type F1 and land use type F2, the judgment matrix E1 of public property loss E1 is obtained, as shown in formula (14). Where e 12 This indicates the relative importance of road type F1 to land use type F2; e 21 This indicates the relative importance of land use type F2 to road type F1, i.e. The importance of the corresponding indicator levels in the critical building service interruption E2 of the criterion level, namely distance to the hospital F3, distance to the school F4, distance to the building F5, and distance to the park / recreation facility F6, is compared pairwise to obtain the judgment matrix E2 of critical building service interruption E2, as shown in formula (15). Where e 34 This indicates the importance of the distance to the hospital (F3) relative to the service disruption caused by critical buildings (E2); e 35 This indicates the relative importance of distance F3 from the hospital compared to distance F5 from the building; e 36 This indicates the relative importance of distance F3 from the hospital compared to distance F6 from the park / recreation facility; e 43 This indicates the relative importance of distance F4 from the school compared to distance F3 from the hospital. e 45 This indicates the relative importance of distance F4 from the school compared to distance F5 from the building; e 46 This indicates the relative importance of distance to the school (F4) compared to distance to the park / recreation facility (F6); e 53 This indicates the relative importance of distance F5 from the building compared to distance F3 from the hospital. e 54 This indicates the relative importance of distance F5 from the building compared to distance F4 from the school. e 56 This indicates the relative importance of distance F5 from buildings compared to distance F6 from parks / recreational facilities; e 63 This indicates the relative importance of distance F6 from the park / recreation facility compared to distance F3 from the hospital. e 64 This indicates the relative importance of distance to parks / recreational facilities (F6) compared to distance to schools (F4). e 65 This indicates the relative importance of distance F6 from the park / recreation facility compared to distance F5 from the building. By comparing the pairwise importance of the corresponding indicator levels in the criteria level E3 for water pollution: distance to the river F7 and distance to the deteriorated rainwater pipe F8, the judgment matrix E3 for water pollution E3 is obtained, as shown in formula (16). Where e 78 This indicates the relative importance of distance F7 from the river compared to distance F8 from the deteriorated stormwater pipes; e 87 This indicates the relative importance of distance F8 from the deteriorated storm drain pipe compared to distance F7 from the river. By comparing the pairwise importance of the corresponding indicator levels in the criterion level water plant failure E4: disease transmission risk F9 and impact on residents F10, the judgment matrix E4 of water plant failure E4 is obtained, as shown in formula (17). Where e 9,10 This indicates the relative importance of the disease transmission risk F9 to the impact of the residential population on F10; e 10,9 This indicates the relative importance of the impact of residential residents on F10 compared to the risk of disease transmission F9, i.e. To ensure the correct failure consequence D1 is obtained, the subjective weight matrix is ​​calculated. First, a consistency check needs to be passed; then, calculate the maximum eigenvalue (λ) corresponding to the judgment matrix D1 for failure consequences D1, the judgment matrix E1 for public property loss E1, the judgment matrix E2 for critical building service interruption E2, the judgment matrix E3 for water resource pollution E3, and the judgment matrix E4 for water plant failure E4. max ), to obtain the consistency index (λ max This represents the largest eigenvalue corresponding to the judgment matrix; n represents the order of the judgment matrix. To compare the magnitudes of the CIs, the standard value of the random consistency index (RI) corresponding to the judgment matrix is ​​selected, ultimately yielding the test coefficients. (RI is selected according to the random consistency index RI value table in Appendix 2); when CR<0.1, it means that the consistency test is passed; otherwise, pairwise importance comparisons need to be performed again, the judgment matrix needs to be reconstructed, and the calculation continues until CR<0.

1. After normalizing the judgment matrices D1, E1, E2, E3, and E4, the subjective weight matrix of the failure consequence D1 is calculated using the arithmetic mean method. Calculate the weight matrix U′=(u1′,u2′,u3′,u4′) at the criterion level, where the weight of public property loss E1 is... Critical building service interruption E2 is The weight of water pollution E3 is The weight of water plant failure E4 is (i,j=1,2,3,4; when i=j, d ij =1); The hierarchical weight matrix V1′=(v1′,v2′) is used to calculate the public property loss E1, where the weight of road type D1 is... Weight of land use type D2 (i,j=1,2; when i=j, e) ij =1); Calculate the hierarchical weight matrix V2′=(v3′,v4′,v5′,v6′) for the critical building service interruption E2, where the weight of distance to the hospital F3 is... Distance from school, weight of F4 Weight of distance F5 from the building Distance to park / recreation facilities (F6 weight) (i,j=3,4,5,6;When i=j,e ij =1); Calculate the hierarchical weight matrix V3′=(v7′,v8′) for water resource pollution E3, where the weight of distance to the river channel F7 is... Weight of distance F8 from deteriorated storm drain pipes (i,j = 7,8; When i = j, e ij =1); The index hierarchy weight matrix V4′=(v9′,v4′) is used to calculate the water plant failure E4. 10 ′), where the weight of disease transmission risk F9 is ′). The weight of residents in the F10 index (i=9,10; when i=j, e ij =1); Weights of the final indicator level Fi Where u n ′ represents the weight of the criterion level to which the i-th indicator belongs, v i ′ represents the weight of the indicator level to which the i-th indicator belongs; (n takes values ​​from 1 to 4, i takes values ​​from 1 to 10), that is (2) Calculate the objective weight matrix of the "failure consequences" indicator system. Objective weights are calculated by analyzing the correlation between indicators using standard correlation analysis; the original indicator data of sewage pipelines are set as m evaluation samples, i.e., m sewage pipelines, and n evaluation indicators (where n=10), forming an original indicator data matrix of "failure consequences": The raw data for the 10 indicators of "failure consequences" were dimensionless, as shown in the following formula: In the formula, X ij ′ represents the standard index value of the j-th indicator for the i-th sewage pipe, x ij ′ represents the raw data of the j-th indicator of the i-th sewage pipe; x max(j) ′ and x min(j) ′ and ′ represent the maximum and minimum values ​​of the j-th indicator in all sewage pipes, respectively; Calculate the difference α between each indicator j The greater the difference, the stronger the evaluation intensity. In the formula, m represents the number of sewage pipes; X ij ′ represents the standard index value of the j-th indicator for the i-th sewage pipe, X j ′ represents the average value of the standard index for the j-th index across all sewage pipes; Calculate the conflict β′ between the indicators j The correlation coefficient is used to represent the correlation between the "failure consequences" indicators. The stronger the correlation, the smaller the conflict, and the weight assigned to this indicator should be reduced. In the formula, m represents the number of sewage pipes; r jk ′ represents the correlation coefficient between the j-th indicator level and the k-th indicator level; X ij ′ represents the standard index value of the j-th index of the i-th sewage pipe; X represents the average value of the standard index for the j-th index across all sewage pipes; ik ′ represents the standard index value of the k-th index of the i-th sewage pipe; The k-th indicator represents the average value of the standard indicator in all sewage pipelines; j, k = (1, 2) under the E1 criterion level for public property loss; j, k = (4, 5, 6, 7) under the E2 criterion level for critical building service interruption; j, k = (7, 8) under the E3 criterion level for water pollution; j, k = (9, 10) under the E4 criterion level for water plant failure. The information content C is calculated by combining standard deviation and conflict. j ′=α j ′×β j ′, thus obtaining the objective weight of the j-th indicator in the "failure consequences" indicator system. Objective weight matrix of the "failure consequences" indicator system (3) Calculate the combined weight matrix W of the "failure consequences" index system. D ′=(ω1′,ω2′,…,ω 10 The optimization strategy is given through formulaic calculation; the weighting of the two results is weighed in combination with game theory, and the subjective weight of any indicator is calculated using formula (23). and objective weight Substituting the values ​​(where i = 1, 2, ..., 10), we obtain a relatively balanced and coordinated combination of weights. weight vector μ S′ and μ O′ The optimal weighting of this indicator The combined weight ω′ of the 10 indicators of "failure consequences" i Arranged in order, the weight matrix W of the "failure consequences" indicator system is obtained. D ′=(ω1′,ω2′,…,ω 10 ′); In the formula, This represents the subjective weight of the i-th indicator; This represents the objective weight of the i-th indicator; express transpose, express transpose; The steps for calculating the combined weight matrix of the "control capability" indicator system are as follows: (1) Calculate the subjective weight matrix of the "control capability" indicator system. Where i = 1, 2, ..., 10; the relative importance of each level of elements is compared by subjective scoring from the experts using the 1–9 scale method (Appendix 1); By comparing the pairwise importance of the corresponding criteria levels in the control capability G1 system: information monitoring H1, emergency maintenance H2 and dispatch control H3, the judgment matrix G1 of control capability G1 is obtained, as shown in formula (24). Where g 12 This indicates the relative importance of information monitoring H1 compared to emergency maintenance H2; g 13 This indicates the relative importance of information monitoring H1 compared to scheduling control H3; g 21 This indicates the relative importance of emergency maintenance H2 compared to information monitoring H1, i.e. g 23 This indicates the relative importance of emergency maintenance H2 compared to dispatch control H3; g 31 This indicates the relative importance of scheduling control H3 compared to information monitoring H1, i.e. g 32 This indicates the relative importance of dispatch control H3 compared to emergency maintenance H2, i.e. The importance of the corresponding indicator levels in the criteria level information monitoring H1, namely: number of pipeline flow monitoring points I1, number of pipeline liquid level monitoring points I2, number of river flow monitoring points I3, number of river water level monitoring points I4, number of river water quality monitoring points I5, and rain gauge coverage I6, is compared pairwise to obtain the judgment matrix E1 of public property loss E1, as shown in formula (25). Where h 12 This indicates the relative importance of the number of pipeline flow monitoring points I1 compared to the number of pipeline liquid level monitoring points I2; h 13 This indicates the relative importance of the number of pipeline flow monitoring points I1 compared to the number of river flow monitoring points I3; h 14 This indicates the relative importance of the number of pipeline flow monitoring points I1 compared to the number of river water level monitoring points I4; h 15 This indicates the relative importance of the number of pipeline flow monitoring points I1 compared to the number of river water quality monitoring points I5; b 16 This indicates the importance of the number of pipeline flow monitoring points I1 relative to the rain gauge coverage I6; h 21 This indicates the relative importance of the number of pipeline level monitoring points I2 compared to the number of pipeline flow monitoring points I1, i.e. h 23 This indicates the relative importance of the number of pipeline level monitoring points I2 compared to the number of river flow monitoring points I3; h 24 This indicates the relative importance of the number of pipeline level monitoring points I2 compared to the number of river level monitoring points I4; h 25 This indicates the relative importance of the number of pipeline level monitoring points I2 compared to the number of river water quality monitoring points I5; h 26 This indicates the importance of the number of pipeline level monitoring points I2 relative to the rain gauge coverage I6; h 31 This indicates the relative importance of the number of river flow monitoring points I3 compared to the number of pipeline flow monitoring points I1, i.e. h 32 This indicates the relative importance of the number of river flow monitoring points I3 compared to the number of pipeline liquid level monitoring points I2. h 34 This indicates the relative importance of the number of river flow monitoring points I3 compared to the number of river water level monitoring points I4; h 35 This indicates the relative importance of the number of river flow monitoring points I3 compared to the number of river water quality monitoring points I5; h 36 This indicates the importance of the number of river flow monitoring points (I3) relative to the rain gauge coverage (I6); h 41 This indicates the relative importance of the number of river water level monitoring points I4 compared to the number of pipeline flow monitoring points I1, i.e. h 42 This indicates the relative importance of the number of river water level monitoring points I4 compared to the number of pipe network liquid level monitoring points I2, i.e. h 43 This indicates the relative importance of the number of river water level monitoring points I4 compared to the number of river flow monitoring points I3. h 45 This indicates the relative importance of the number of river water level monitoring points I4 compared to the number of river water quality monitoring points I5; h 46 This indicates the importance of the number of river level monitoring points (I4) relative to the rain gauge coverage (I6); h 51 This indicates the relative importance of the number of river water quality monitoring points I5 compared to the number of pipeline flow monitoring points I1, i.e. h 52 This indicates the relative importance of the number of river water quality monitoring points I5 compared to the number of pipe network liquid level monitoring points I2, i.e. h 53 This indicates the relative importance of the number of river water quality monitoring points I5 compared to the number of river flow monitoring points I3. h 54 This indicates the relative importance of the number of river water quality monitoring points I5 compared to the number of river water level monitoring points I4. h 56 This indicates the importance of the number of river water quality monitoring points (I5) relative to the rain gauge coverage (I6); h 61 This indicates the importance of the rain gauge coverage I6 relative to the number of pipeline flow monitoring points I1, i.e. h 62 This indicates the importance of the rain gauge coverage I6 relative to the number of pipeline level monitoring points I2, i.e. h 63 This indicates the importance of the rain gauge coverage I6 relative to the number of river flow monitoring points I3, i.e. h 64 This indicates the importance of the rain gauge coverage I6 relative to the number of river level monitoring points I4, i.e. h 65 This indicates the importance of the rain gauge coverage I6 relative to the number of river water quality monitoring points I5, i.e. The importance of the corresponding indicator levels in the criterion level emergency maintenance H2, namely the number of emergency rescue stations I7 and the coverage of maintenance teams I8, is compared pairwise to obtain the judgment matrix H2 of emergency maintenance H2, as shown in formula (26). Where h 78 This indicates the importance of the number of emergency rescue stations (I7) relative to the coverage of maintenance teams (I8); h 87 This indicates the importance of the coverage of the maintenance team (I8) relative to the number of emergency rescue stations (I7), i.e. The importance of the corresponding indicator levels in the criterion-level scheduling control H3, namely the number of pump station valves I9 and the number of river gates and dams I10, is compared pairwise to obtain the judgment matrix H3 of scheduling control H3, as shown in formula (27). Where h 9,10 This indicates the relative importance of the number of pump station valves (I9) compared to the number of river sluice gates (I10); h 10,9 This indicates the relative importance of the number of river sluice gates and dams (I10) to the number of pump station valves (I9), i.e. To ensure the correct subjective weight matrix of control capability G1 is obtained. First, a consistency check is required; then, the maximum eigenvalue (λ) corresponding to the judgment matrix G1 of control capability G1, the judgment matrix H1 of information monitoring H1, the judgment matrix H2 of emergency maintenance H2, and the judgment matrix H3 of dispatch control H3 is calculated. max ), to obtain the consistency index (λ max This represents the largest eigenvalue corresponding to the judgment matrix; n represents the order of the judgment matrix. To compare the magnitudes of the CIs, the standard value of the random consistency index (RI) corresponding to the judgment matrix is ​​selected, ultimately yielding the test coefficients. (RI is selected according to the random consistency index RI value table in Appendix 2); when CR<0.1, it means that the consistency test is passed; otherwise, pairwise importance comparisons need to be performed again, the judgment matrix needs to be reconstructed, and the calculation continues until CR<0.

1. After normalizing the judgment matrices G1, H1, H2, and H3, the subjective weight matrix of the control capability G1 is calculated using the arithmetic mean method. The weight matrix U″=(u1″,u2″,u3″) of the criterion hierarchy is calculated, where the weight of information monitoring H1 is... Emergency maintenance H2 is The weight of scheduling control H3 is (i,j=1,2,3; when i=j, g) ij =1); Calculate the hierarchical weight matrix V1″=(v1″,v2″,…,v6″) for the information monitoring H1, where the weight of the number of pipeline flow monitoring points I1 is... The number of pipeline level monitoring points I2 is The weight of the number of river flow monitoring points I3 is: The weight of the number of river water level monitoring points I4 is: The weight of the number of river water quality monitoring points I5 is: The weight of rain gauge coverage I6 is (i,j=1,2,…,6;when i=j, h ij =1); Calculate the hierarchical weight matrix V3″=(v7″,v8″) for emergency maintenance H2, where the weight of the number of emergency rescue stations I7 is... Weight of I8 in the coverage of operations and maintenance teams (i,j = 7,8; ​​when i = j, h) ij =1); Calculate the hierarchical weight matrix V4″=(v9″,v 10 ("), where the weight of the number of valves in the pump station I9 is... Weight of the number of river sluice gates and dams I10 (i=9,10; when i= When j, h ij =1); The weight of the final indicator level Hi Where u n "" represents the weight of the criterion level to which the i-th indicator belongs, v i "" indicates the weight of the indicator level to which the i-th indicator belongs; (n takes values ​​from 1 to 3, i takes values ​​from 1 to 10); (2) Calculate the objective weight matrix of the "control capability" indicator system. Objective weights are calculated by analyzing the correlation between indicators using standard correlation analysis; the original indicator data of each street is set as m evaluation samples, i.e., m streets, and n evaluation indicators (where n=10), forming the original indicator data matrix of "control capability": The raw data for the 10 indicators in "Control Capability" are dimensionless, as shown in the following formula: In the formula, X ij "" represents the standard index value of the j-th indicator for the i-th street, x ij "" represents the raw data of the j-th indicator for the i-th street; x max(j) "and x min(j) "" represents the maximum and minimum values ​​of the j-th indicator across all streets; Calculate the difference α between each indicator j "The greater the difference, the stronger the evaluation intensity." In the formula, m represents the number of streets; X ij "" represents the standard index value of the j-th indicator in the i-th street. This represents the average value of the standard indicator across all streets for the j-th indicator; Calculate the conflict β among the indicators j "The correlation coefficient is used to represent the correlation between the "control capability" indicators. The stronger the correlation, the smaller the conflict. The weight assigned to this indicator should be reduced." In the formula, m represents the number of streets; r jk " represents the correlation coefficient between the j-th indicator level and the k-th indicator level; X" ij Let j be the standard index value of the j-th indicator for the i-th street. X represents the average value of the standard indicator across all streets for the j-th indicator; ik " is the standard index value of the k-th indicator for the i-th street; The k-th indicator represents the average value of the standard indicator across all streets; j, k = (1, 2, 3, 4, 5, 6, 7) under the H1 criterion level for information monitoring; j, k = (7, 8) under the H2 criterion level for emergency maintenance; j, k = (9, 10) under the H3 criterion level for dispatch control. The information content C is calculated by combining standard deviation and conflict. j "=α j "×β" j ", thus obtaining the objective weight of the j-th indicator in the "control capability" indicator system. The objective weight matrix of the "control and management capability" indicator system (3) Calculate the combined weight matrix W of the "control capability" indicator system. G ″=(ω1″,ω2″,…,ω 10 The optimization strategy is given through formulaic calculation; the weighting of the two results is weighed in combination with game theory, and the subjective weight of any indicator is determined by formula (33). and objective weight Substituting the values ​​(where i = 1, 2, ..., 10), we obtain a relatively balanced and coordinated combined weight vector μ. S′ and μ O′ The optimal weighting of this indicator The combined weight ω of the 10 indicators of "control capability" i The weight matrix W of the "control capability" indicator system is obtained by arranging them in order. G "=(ω1″,ω2″,…,ω 10 "); In the formula, This represents the subjective weight of the i-th indicator; This represents the objective weight of the i-th indicator; express transpose, express The transpose of .

4. The method according to claim 1, characterized in that, In step 3, the calculation steps for the data matrix of the "health status" indicator system are as follows: (1) Determine the evaluation index set and comment set of the "health status" index system; based on the quantity of original sewage pipeline data, there are n evaluation indicators, then the evaluation index set can be represented as γ A =(γ1,γ2,…,γ n (n=25); According to the principle of determining the classification level of the indicators of the "health status" indicator system of urban sewage system (Appendix 3), each indicator is divided into four evaluation levels {I,II,III,IV}; the corresponding evaluation score value set is δ=(10,6.7,3.3,0). (2) Determine the data matrix for the "health status" indicator system. The percentage of the i-th evaluation indicator among the four rating levels is represented by fuzzy set R. Ai =(r i1 ,r i2 ,r i3 ,r i4 ), where the evaluation index set γ A The i-th evaluation indicator represents the percentage of the i-th comment's grade in the comment set. i1 The percentage of the second rating indicates r. i2 And so on; the evaluation indicator set and the comment set are divided into qualitative indicators and quantitative indicators, among which the qualitative indicators are directly constructed based on the indicator classification levels in Appendix 3. Ai For qualitative indicators, the percentage of the indicator in the four evaluation levels is 100%, while the percentage in the other three levels is 0. The fuzzy set calculation process for qualitative indicators is as follows: For example, if the degree of rupture of the first sewage pipe is "cracks appear (crack width < 2mm)," it belongs to Level II, and its fuzzy set R... Ai = (0,1,0,0); Quantitative indicators (such as "pipe length C14", "pipe diameter C15", "pipe age C16", etc.) are classified and graded according to the indicators in Appendix 3 to construct R. Ai Among them, according to the fuzzy set R in Appendix 3, the number of levels increases from I to IV. Ai Represented as According to the fuzzy set R in Appendix 3, the number of levels decreases from I to IV. Ai Represented as x represents a specific quantitative value, a represents the minimum value (the higher the level, the greater the quantity) / maximum value (the higher the level, the less the quantity) of comment level I, b represents the dividing point between comment level II and level III, c represents the dividing point between comment level III and level IV, and d represents the maximum value (the higher the level, the greater the quantity) / minimum value (the higher the level, the less the quantity) of comment level IV. (3) Determine the fuzzy vector ε of the "health status" indicator system. A =R A *W A =(ε1) , ε2,ε3,ε4), R A W represents the data matrix of the "health status" indicator system. A A weighted matrix representing the combined indicators of "health status"; (4) Determine the evaluation score S of the "health status" indicator system. A Calculate the evaluation score of the sewage pipeline based on the original data of the "health status" indicator system, which is S. A ′=ε A *δ T , ε A δ represents a fuzzy vector representing the "health status" indicator system. T This represents the transpose of the set of evaluation scores; to allow management departments to manage urban wastewater systems at the street level, the evaluation score S of wastewater pipes in the "health status" indicator system is used. A Using the formula The weighted average at the street level yields the evaluation score S of the "health status" index system. A In the formula, S Ai ′ represents the evaluation score of the i-th sewage pipe in the "health status" indicator system, l i Let ∑l represent the length of the i-th sewage pipe. i This represents the sum of the lengths of all sewage pipes within the street, where m represents the total number of sewage pipes in the "health status" indicator system. Appendix 3: Principles for Determining the Indicator Classification Levels of the "Health Status" Indicator System for Urban Wastewater Systems The calculation steps for the data matrix of the "failure consequences" indicator system are as follows: (1) Determine the evaluation index set and comment set of the "failure consequences" index system; based on the quantity of original sewage pipeline data, there are n evaluation indicators, then the evaluation index set can be represented as γ D ′=(γ1′,γ2′,…,γ n ′)(n=10); According to the principle of determining the classification level of the indicator system of "failure consequences" of urban sewage system, each indicator is divided into four evaluation levels {I,II,III,IV}; the corresponding evaluation score value set is δ=(10,6.7,3.3,0); (2) Determine the data matrix for the "failure consequences" indicator system. The data proportion of the i-th evaluation indicator is represented by fuzzy set R. Di =(r i1 ′,r i2 ′,r i3 ′,r i4 ′), where the evaluation index set γ D The i-th evaluation indicator represents the percentage of the first comment grade in the comment set. i1 ′, the percentage of the second comment level represents r i2 ', and so on; the evaluation indicator set and the comment set are divided into qualitative indicators and quantitative indicators. The qualitative indicators are directly constructed based on the indicator classification levels in Appendix 4 to form R. Di For qualitative indicators, the percentage of the level within the four rating scales is 100%, while the other three are 0%. Quantitative indicators are constructed using the rating scales in Appendix 3. Di According to the fuzzy set R in Appendix 3, the number of levels increases from I to IV. Ai Represented as According to the fuzzy set R in Appendix 3, the number of levels decreases from I to IV. Ai Represented as x represents a specific quantitative value, a represents the minimum value (the higher the level, the greater the quantity) / maximum value (the higher the level, the less the quantity) of comment level I, b represents the dividing point between comment level II and level III, c represents the dividing point between comment level III and level IV, and d represents the maximum value (the higher the level, the greater the quantity) / minimum value (the higher the level, the less the quantity) of comment level IV. (3) Determine the fuzzy vector ε of the "failure consequences" indicator system. D =R D *W D =(ε1′,ε2′,ε3′,ε4′), R D W represents the data matrix of the "failure consequences" indicator system. D A combined weight matrix representing the "failure consequences" indicator system; (4) Determine the evaluation score S of the "failure consequences" indicator system. D Calculate the original data of the "failure consequences" indicator system to determine the evaluation score of the sewage pipeline as S. D ′=ε D *δ T , ε D δ represents the fuzzy vector of the "failure consequences" indicator system. T This represents the transpose of the set of evaluation scores; to allow management departments to manage urban wastewater systems at the street level, the evaluation score S of wastewater pipes in the "failure consequences" indicator system is used. D Using the formula The weighted average at the street scale yields the evaluation score S of the "failure consequences" index system. D In the formula, S Di ′ represents the evaluation score of the i-th sewage pipe in the "failure consequences" indicator system, l i Let ∑l represent the length of the i-th sewage pipe. i This represents the sum of the lengths of all sewage pipes within the street, where m represents the total number of sewage pipes in the "failure consequences" indicator system. Appendix 4: Principles for Determining the Indicator Classification Levels of the "Failure Consequences" Indicator System for Urban Wastewater Systems The calculation steps for the data matrix of the "control and management capability" indicator system are as follows: (1) Determine the evaluation indicator set and comment set of the "control capability" indicator system; based on the amount of original data from the street, there are n evaluation indicators, then the evaluation indicator set can be represented as γ G =(γ1″,γ2″,…,γ n (n=10); According to the principle of determining the grade of indicators in the "control capacity" indicator system of urban sewage system (Appendix 5), each indicator is divided into four evaluation grades {I,II,III,IV}; the corresponding evaluation score value set is δ=(10,6.7,3.3,0). (2) Determine the data matrix for the "control capability" indicator system. The data result of the i-th evaluation index is represented by a fuzzy set R. Gi =(r i1 ″,r i2 ″,r i3 ″,r i4 ″), where the evaluation index set γ G The i-th evaluation indicator represents the percentage of the first comment grade in the comment set. i1 "″, the percentage of the second comment level indicates r i2 ", and so on; R is constructed directly based on the indicators in Appendix 5 to classify the levels. Gi The indicators are classified and graded according to the indicators in Appendix 5 to construct R. Gi Among them, according to the fuzzy set R in Appendix 3, the number of levels increases from I to IV. Ai Represented as According to the fuzzy set R in Appendix 3, the number of levels decreases from I to IV. Ai Represented as x represents a specific quantitative value, a represents the minimum value (the higher the level, the greater the quantity) / maximum value (the higher the level, the less the quantity) of comment level I, b represents the dividing point between comment level II and level III, c represents the dividing point between comment level III and level IV, and d represents the maximum value (the higher the level, the greater the quantity) / minimum value (the higher the level, the less the quantity) of comment level IV. (3) Determine the fuzzy vector ε of the "control capability" indicator system. G =R G *W G ″=(ε1″, ε2″, ε3″, ε4″), R G W represents the data matrix of the "control capability" indicator system. G "" represents the combined weight matrix of the "control capability" indicator system; (4) Determine the evaluation score S of the "control capability" indicator system. G Calculate the evaluation score S of the "control and management capability" indicator system. G =ε G *δ T , ε G δ represents the fuzzy vector of the "control capability" indicator system. T This represents the transpose of the set of possible score values ​​for the comments; Appendix 5: Principles for Determining the Indicator Classification Levels of the "Management Capacity" Indicator System for Urban Wastewater Systems 5. The method according to claim 1, characterized in that, The "health-failure-control" trade-off and synergistic evaluation of the urban wastewater system in step 4 is performed using a geographic weighted regression model in ArcGIS software for spatial calculation of the trade-offs and synergies. The mathematical expression of the model is X. i =α0(x i ,y i )+α k (x i ,y i )x jk +ψ i , its (x i ,y i ) represents the spatial location of the i-th street, i.e., the spatial latitude and longitude information of each street (the information data is in the .shp format of ArcGIS software); X i x is the dependent variable. jk Let S be the independent variable, where the health value is S. A / Failure value S D / Control value S G Both can be dependent and independent variables, thus corresponding to pairwise systems; ψ i For random error; α0(x) i ,y i ) represents the intercept of the i-th street; α k (x i ,y i )x jk The regression coefficients are represented by the coefficients. According to the obtained regression coefficients, the positive regression coefficients indicate that the scores of the two systems are spatially synergistic, while the negative regression coefficients reflect that the scores of the two systems are spatially trade-off.

6. The method according to claim 1, characterized in that, After step 6, label each street as a Class A street, Class B street, or Class C street on the municipal street map.

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