Water supply and drainage pipe network toughness management and emergency response system in extreme weather

Abstract

The invention discloses a water supply and drainage pipe network toughness management and emergency response system in extreme weather, and belongs to the technical field of urban infrastructure management. Comprising urban infrastructure safety assessment, an intelligent monitoring and early warning system, a toughness engineering and emergency guarantee technology, a post-disaster rapid recovery technology, an emergency command and dispatch system, information technology application, environmental engineering and disaster management and system integration and optimization. The extreme weather prediction precision is improved by integrating satellite data, a Doppler radar technology and an automatic algorithm, and an emergency response strategy is optimized in combination with a risk assessment method; omnibearing management and optimization of a water supply and drainage pipe network are realized by using the Internet of Things, big data and artificial intelligence technologies, and the intelligent level and response efficiency of the system are improved; the system also covers post-disaster emergency rescue and rapid recovery technologies, and constructs a whole-process closed-loop management and control fusion command system, so as to reduce disaster accident loss and improve city safety and health.

Description

Technical Field

[0001] The present invention belongs to the technical field of urban infrastructure management, and particularly relates to a resilience management and emergency response system for water supply and drainage pipe networks under extreme weather conditions. Background Art

[0002] Development Status and Existing Problems Abroad:

[0003] Real-time Urban Drainage Network Modeling Technology: Internationally, especially in the United States, the accuracy of real-time urban drainage network modeling has been enhanced through the Crossformer algorithm and online continuous learning technology. This method overcomes the challenges of scarce monitoring data and capturing all node levels by using global state inference monitoring points as model inputs. However, these technologies may face problems in data integration and algorithm optimization in practical applications and require further research and improvement.

[0004] Climate Resilience Assessment of Urban Drainage Systems: In the research on urban drainage systems (UDS) for coping with climate change, international research has proposed new indicators for resilience profiles, unifying the concepts of reliability, robustness, resilience, and failure. Although these studies provide assessment tools, there are still deficiencies in the resilience assessment of extreme weather events such as persistent rainfall, and further research is needed to improve the assessment method.

[0005] Urban Climate Resistance Enhancement Technology: Internationally, especially in Japan, Tokyo Electric Power Company (TEPCO) implemented a smart energy network after the 2011 earthquake and tsunami, using advanced technologies such as advanced metering infrastructure to provide real-time monitoring and control of the energy network. This ability enables a faster response to power outages in emergencies and better management of energy supply. However, these technologies still face challenges in integrating renewable energy and reducing dependence on centralized facilities.

[0006] Development Status and Existing Problems in China:

[0007] Sponge City Strategy: In terms of urban drainage and flood management in China, the "Sponge City" strategy is a modern review, which emphasizes the challenges in urban flood management and rainwater management in China. Although certain progress has been made, there are still deficiencies in coping with extreme weather events and enhancing the resilience of urban drainage systems.

[0008] Urban Energy System Design: In terms of urban energy system design in China, the exploration of microgrid design and implementation is also underway to provide an energy supply that can operate independently in case of main grid failures. These microgrids are increasingly combined with renewable energy sources such as rooftop solar panels and wind turbines and with energy storage systems to generate clean, decentralized, and resilient energy sources. However, these technologies may face cost and technical limitations in actual deployment and operation.

[0009] Existing technical problems:

[0010] Safety assessment of water supply and drainage pipe networks under extreme weather: How to accurately assess the safety risks of water supply and drainage pipe networks under extreme weather conditions, including typhoons, heavy precipitation, thunderstorms, extreme high and low temperatures, etc., to prevent and reduce potential damages.

[0011] Insufficiencies of real-time monitoring and early warning systems: Existing monitoring systems may not provide sufficient data support, or the early warning systems respond not quickly enough, resulting in the inability to take timely measures to cope with extreme weather events.

[0012] Insufficient resilience of water supply and drainage pipe networks: Urban water supply and drainage pipe networks lack sufficient resilience to maintain normal operation when facing extreme weather, and it is necessary to enhance their stability and recovery ability under extreme conditions.

[0013] Low efficiency of post-disaster emergency response and recovery: Post-disaster assessment, rescue and recovery work are often inefficient, lacking effective technologies and methods to quickly restore the functions of water supply and drainage pipe networks.

[0014] Collaborative linkage problems of emergency command and dispatch systems: There is a lack of an effective emergency command and dispatch system to achieve the optimal allocation of resources and the rapid execution of emergency responses, especially under extreme weather conditions.

[0015] Insufficient application of information technology in the management of water supply and drainage pipe networks: Information technologies, such as the Internet of Things, big data, artificial intelligence, etc., are not widely applied in the management of water supply and drainage pipe networks, and their potential in improving the intelligent level and response efficiency of the system has not been fully exploited.

[0016] Integration problems of environmental engineering and disaster management: The integration of environmental engineering and disaster management in the management of water supply and drainage pipe networks is insufficient, and more comprehensive technical solutions need to be developed to cope with extreme weather events. Summary of the Invention

[0017] The technical problem to be solved by the present invention is to provide a resilience management and emergency response system for water supply and drainage pipe networks under extreme weather in view of the deficiencies in the background technology. The system combines advanced technologies in multiple fields such as civil engineering, environmental engineering, information technology, and disaster management, aiming to provide a comprehensive, efficient, and intelligent safety guarantee solution for urban water supply and drainage pipe networks.

[0018] The present invention adopts the following technical solutions to solve the above technical problems:

[0019] A resilience management and emergency response system for water supply and drainage pipe networks under extreme weather conditions, comprising a multi-parameter extreme weather risk assessment model, a three-dimensional monitoring and early warning network based on multi-source data fusion, resilient water supply and drainage facilities and emergency support modules, a post-disaster emergency rescue support and rapid recovery module, and an emergency dispatching platform with coordinated linkage strategies;

[0020] Among them, the multi-parameter extreme weather risk assessment model is used to realize the risk assessment of urban water supply and drainage pipe networks under extreme weather conditions based on the integration of multiple data sources and algorithms; it includes satellite data collection, Doppler radar technology, automated algorithm processing, and risk assessment methods;

[0021] The three-dimensional monitoring and early warning network based on multi-source data fusion is used to realize the unified control and dynamic monitoring of urban water supply and drainage pipe networks based on multi-source data fusion technology, by integrating three-dimensional real scenes, audio-video linkage technology, and Internet of Things and big data technologies;

[0022] The resilient water supply and drainage facilities and emergency support modules are used to keep operating under extreme weather conditions and quickly respond to the needs of post-disaster reconstruction;

[0023] The post-disaster emergency rescue support and rapid recovery module is used to provide post-disaster emergency rescue support;

[0024] The emergency dispatching platform with coordinated linkage strategies is used to build an emergency dispatching platform integrating comprehensive air, space and ground perception, integrated fusion communication, Internet of Things, big data and artificial intelligence technologies, to realize the full-process closed-loop control of pre-event monitoring and early warning, rapid response during the event, joint disposal during the event, and summary and evaluation after the event, and improve the efficiency and accuracy of emergency rescue.

[0025] Compared with the prior art, the present invention adopts the above technical solutions and has the following technical effects:

[0026] The present invention relates to a technology for resilient management and emergency response of water supply and drainage pipe networks under extreme weather conditions, including safety assessment of urban infrastructure, intelligent monitoring and early warning systems, resilient engineering and emergency support technologies, rapid post-disaster recovery technologies, emergency command and dispatch systems, information technology applications, environmental engineering and disaster management, as well as system integration and optimization. The present invention improves the prediction accuracy of extreme weather events by integrating satellite data and Doppler radar technology, so as to make preparations in advance. By combining advanced risk assessment models and methods, it can more accurately assess the safety risks of water supply and drainage pipe networks under extreme weather conditions. Using Internet of Things and big data technologies, it realizes real-time monitoring of the status of water supply and drainage pipe networks and provides timely early warning information. Develop resilient water supply and drainage facilities and equipment to improve the stability and recovery ability of pipe networks under extreme weather conditions and the efficiency of emergency response. Combining advanced rescue technologies and post-disaster reconstruction experiences, it speeds up post-disaster assessment, emergency rescue and recovery work, and reduces the impact of disasters on urban operations. Through the emergency command and dispatch system, it realizes the optimal allocation of resources and improves the rapid execution ability of emergency response. Integrating multidisciplinary technologies such as civil engineering, environmental engineering, information technology, and disaster management, it provides a comprehensive safety guarantee solution. Widely applying information technologies such as Internet of Things, big data, and artificial intelligence, it improves the intelligent level of water supply and drainage pipe network management. Through the integration of environmental engineering and disaster management, it improves the environmental adaptability and disaster management ability of water supply and drainage pipe networks in the face of extreme weather events. Integrating the above technologies into a comprehensive management system, it realizes the all-round management and optimization of urban water supply and drainage pipe networks. By accurately monitoring disaster risks, scientifically mobilizing rescue resources, and coordinating the handling of emergencies, it minimizes the losses of disaster accidents. The development of comprehensive assessment tools and technologies improves urban safety and health and enhances the city's resistance to extreme weather events. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those skilled in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0028] Figure 1 It is a framework diagram of the multi-parameter extreme weather risk assessment model of the present invention;

[0029] Figure 2 It is an architecture diagram of the three-dimensional monitoring and early warning network based on multi-source data fusion of the present invention;

[0030] Figure 3 It is a flow chart of the resilient water supply and drainage facilities and equipment and emergency support technology of the present invention;

[0031] Figure 4It is a schematic diagram of the post-disaster emergency rescue and relief guarantee and rapid recovery technology of the present invention;

[0032] Figure 5 It is an interface diagram of the emergency dispatching platform for the collaborative linkage strategy of the present invention;

[0033] Figure 6 It is a principle flow chart of a water supply and drainage pipe network resilience management and emergency response system under extreme weather of the present invention. Detailed implementation manners

[0034] The technical solutions of the present invention will be further described in detail below with reference to the accompanying drawings:

[0035] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention. The present invention will be described in detail below according to the accompanying drawings and preferred embodiments, and the purpose and effect of the present invention will become more apparent. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0036] A water supply and drainage pipe network resilience management and emergency response system under extreme weather includes a multi-parameter extreme weather risk assessment model, a three-dimensional monitoring and early warning network based on multi-source data fusion, resilient water supply and drainage facilities and emergency guarantee modules, a post-disaster emergency rescue and relief guarantee and rapid recovery module, and an emergency dispatching platform for collaborative linkage strategies;

[0037] Among them, the multi-parameter extreme weather risk assessment model is used to realize the risk assessment of the urban water supply and drainage pipe network under extreme weather based on integrating multiple data sources and algorithms; it includes satellite data collection, Doppler radar technology, automated algorithm processing, and risk assessment methods;

[0038] The three-dimensional monitoring and early warning network based on multi-source data fusion is used to realize the unified control and dynamic monitoring of the urban water supply and drainage pipe network based on multi-source data fusion technology, by integrating three-dimensional real scene, audio-video linkage technology, and Internet of Things and big data technology;

[0039] The resilient water supply and drainage facilities and emergency guarantee modules are used to keep running under extreme weather conditions and quickly respond to the needs of post-disaster reconstruction;

[0040] The post-disaster emergency rescue and relief guarantee and rapid recovery module is used to provide post-disaster emergency rescue and relief guarantee;

[0041] An emergency dispatch platform with a collaborative linkage strategy is used to build an emergency dispatch platform integrating comprehensive air, space and ground perception, integrated fusion communication, Internet of Things, big data, and artificial intelligence technologies, so as to achieve full-process closed-loop management and control of pre-incident monitoring and early warning, rapid response during the incident, joint disposal during the incident, and post-incident summary and evaluation, and improve the efficiency and accuracy of emergency rescue.

[0042] As Figure 1 shown in the multi-parameter extreme weather risk assessment model framework diagram, this model integrates satellite data, Doppler radar operational technology, and automated algorithms to improve the prediction accuracy of extreme weather, and combines risk assessment methods to achieve risk assessment of urban water supply and drainage pipe networks under extreme weather and optimization of emergency response strategies. The principle of the multi-parameter extreme weather risk assessment model specifically includes:

[0043] Satellite data collection: Using satellite remote sensing technology to monitor weather changes and the status of urban water supply and drainage pipe networks in real time, providing data support at the macro level;

[0044] Doppler radar technology: Monitoring precipitation intensity and distribution through Doppler radar to provide accurate precipitation data for the model;

[0045] Automated algorithm processing: Adopting advanced data processing algorithms, including the Crossformer algorithm, for real-time data analysis and processing to improve the response speed and accuracy of the model;

[0046] Risk assessment method: Assessing the risks of urban water supply and drainage pipe networks under extreme weather and optimizing emergency response strategies.

[0047] Calculation model, specifically as follows:

[0048] Chicago rain pattern method calculation formula: Pre-peak formula: i(t1) = A·b·r·(1 + r)·n·t b·r ; where, i(t1) is the instantaneous rainfall intensity before the peak, A is the rainfall intensity parameter, n is the rainstorm attenuation index, b is the rainfall duration correction parameter, r is the rain peak position coefficient, and t is time;

[0049] Post-peak formula: i(t2) = A·b·r·(1 + r)·n·t b·r ; where, i(t*2*) is the rainfall intensity after the peak;

[0050] Equipment failure rate calculation formula under meteorological disasters: Equipment failure rate: where, λ x is the failure rate of type e power equipment under meteorological disaster x, n x,e is the number of failures of type e power equipment under meteorological disaster x, and T is the duration of the meteorological disaster;

[0051] Goodwin Model for Transmission Line Icing Prediction: Icing Thickness: Among them, ρ0ρ i are the density of water and the density of ice coating respectively; H g is the precipitation during the ice coating period; v v is the speed of raindrops acting on the structure.

[0052] As Figure 2 shown in the three-dimensional monitoring and early warning network architecture diagram based on multi-source data fusion, the technical principle of the present invention is based on multi-source data fusion technology. By integrating three-dimensional real scene, audio-video linkage technology, as well as Internet of Things and big data technology, unified management and dynamic monitoring of urban water supply and drainage pipe networks are realized. This technology can improve the response speed and accuracy to extreme weather events, specifically including the following aspects:

[0053] Three-dimensional real scene and real-time video fusion: used to seamlessly dock the real-time video stream from monitoring devices with the three-dimensional scene or model, achieving unity in the spatial and temporal dimensions;

[0054] Internet of Things application: using sensors and wireless communication networks to transmit key parameter data such as water level, flow rate, and water quality of the drainage pipe network to the centralized management platform in real time;

[0055] Big data analysis: in the data center, through cloud computing and big data analysis technology, the data transmitted by sensors is stored, processed, and analyzed to predict the operation trend of the drainage system and provide decision-making support;

[0056] Calculation models are as follows:

[0057] Drainage pipe network flow prediction formula: using fluid mechanics and statistical methods, combined with historical data and real-time monitoring data, to predict the flow change of the drainage pipe network under different weather conditions: Q = A·C·R n ; among them, Q is the flow rate, A is the cross-sectional area, C is the Chezy coefficient, R is the hydraulic radius, and n is the flow regime index;

[0058] Drainage pipe network health assessment formula: using GIS technology and big data analysis to evaluate the health of the drainage pipe network: Among them, H is the pipe network health, w i is the weight, h i is the health of each index, and N is the total number of indexes;

[0059] Early warning threshold setting formula: combining historical data and real-time monitoring data to set the early warning threshold: T = μ + k·σ; where T is the early warning threshold, μ is the average value, σ is the standard deviation, and k is the risk coefficient.

[0060] As Figure 3As shown in the figure, the technical flow chart of the resilient water supply and drainage facilities and emergency guarantee of the present invention. The principle of the resilient water supply and drainage facilities and emergency guarantee module is specifically calculated as follows:

[0061] Develop a series of resilient water supply and drainage facilities and equipment, which have the ability to operate under extreme weather conditions and can quickly respond to the needs of post-disaster reconstruction, combined with the Doppler radar research and development and model improvement technology of the National Severe Storms Laboratory (NSSL) in the United States.

[0062] The technical principle of the present invention lies in developing a series of resilient water supply and drainage facilities and equipment, which can operate under extreme weather conditions and quickly respond to the needs of post-disaster reconstruction. The technical core includes:

[0063] Resilient infrastructure design: Based on the ability of urban infrastructure to ensure normal operation after absorbing a certain degree of disasters, enhance the robustness, redundancy, recoverability, adaptability and intelligence of water supply and drainage facilities.

[0064] Application of Doppler radar technology: Combine the Doppler radar research and development and model improvement technology of the National Severe Storms Laboratory (NSSL) in the United States to improve the monitoring and early warning ability of extreme weather.

[0065] Risk assessment and emergency capacity assessment: Refer to the EPA standard to identify high-risk elements affecting the safety of the water supply system, and establish an identification technology for high-risk elements related to the urban water supply system to evaluate the emergency capacity of the urban water supply system.

[0066] Calculation formula for the real-time rain load of transmission lines: Assume that the raindrop diameters are the same. The real-time rain load L R of the transmission line is: L R =29πd 3 ρd p n(d)V 2 ; where ρ is the density of raindrops, V is the velocity of raindrops acting on the structure, d is the outer diameter of the wire, and d p is the horizontal span of the pole tower;

[0067] Calculation formula for the total load of transmission lines: The load mainly considers the rain load L R (t) and the fixed load L G in two parts; the fixed load is the permanent load, mainly the self-weight of the components; the rain load is the variable load, which is related to time, and the rain load at a certain moment is a fixed value; considering the more serious situation, that is, the rain load and the fixed load are in the same direction: S(t) = L G +L R (t); where S(t) is the total load borne by the transmission line;

[0068] Calculation formula for the failure probability of transmission lines: Under rainstorm conditions, the failure probability P(t) of a transmission line is the probability that the line strength is less than the load: P(t) = P[Z(t) < 0] = P[R d -S(t) < 0]; where R d is the design strength of the transmission line.

[0069] As Figure 4 shown in the figure, it is a schematic diagram of the post-disaster emergency rescue and rapid restoration technology of the present invention. The technical principle of the present invention combines advanced technologies in the emergency equipment modernization project in the United States, such as intelligent unmanned search and rescue, underwater rescue robots, etc., and the orderly progress and experience in post-disaster reconstruction in Japan, aiming to develop post-disaster emergency rescue and rapid restoration technology; including:

[0070] Intelligent unmanned search and rescue technology: Use drones and unmanned vehicles for rapid search and rescue in the air and on the ground to improve search and rescue efficiency and safety;

[0071] UAV path planning model: The problem of the rapid delivery path of UAVs in emergency rescue in complex mountainous areas is regarded as a multi-stage decision-making problem. A dynamic programming model is established, and the optimal rescue path of the UAV is calculated by solving the model. The dynamic programming model formula: V(s) = max a∈A(s) [R(s,a) + γmin s′∈S V(s′)]; where V(s) is the value of state s, A(s) is all possible actions in state s, R(s,a) is the immediate reward obtained after executing action a, γ is the discount factor, and S is the set of all possible states;

[0072] Underwater rescue robot technology: Develop robots that can perform rescue tasks in underwater environments, integrating advanced sensor technologies, artificial intelligence, and autonomous navigation capabilities;

[0073] Underwater robot positioning and navigation algorithm: Use sonar detection technology combined with GPS navigation system and marine battery energy technology to quickly search for the life information of victims by intelligent search and rescue equipment; positioning algorithm formula:

[0074] where, P(x,y) is the optimal position of the robot, (x i ,y i ) is the point detected by sonar, and d is the corresponding distance.

[0075] Post-disaster reconstruction experience: Learn from the orderly progress and experience in post-disaster reconstruction in Japan, and formulate a detailed post-disaster recovery plan, including restoring living order, industrial and economic recovery, and building a safer transportation network.

[0076] As Figure 5As shown in the figure, it is the interface diagram of the emergency dispatch platform for the collaborative linkage strategy of the present invention. The technical principle of the present invention is based on constructing an emergency dispatch platform integrating technologies such as comprehensive space-air-ground perception, integrated communication, Internet of Things, big data, and artificial intelligence. The platform aims to achieve full-process closed-loop control of "pre-event monitoring and early warning, rapid response during the event, joint disposal during the event, and post-event summary and evaluation", improving the efficiency and accuracy of emergency rescue.

[0077] Comprehensive space-air-ground perception technology: Through the complementary advantages of space-based satellite networks, air-based ad hoc networks, and ground cellular networks, multi-domain all-weather emergency communication services are realized.

[0078] Integrated communication technology: Construct a scientific and complete command and rescue system, create a full-chain and cross-level and cross-department collaborative disposal process, and enhance the cross-department collaborative disposal ability.

[0079] Internet of Things technology: Using technologies such as Internet of Things perception and video intelligent recognition, dynamically perceive and actively identify high-risk risks, automatically alarm, and comprehensively master the risk situation.

[0080] Big data technology: Use big data to intelligently judge the possible risks, analyze the possible impacts, scopes, and trends caused by emergencies, and help managers master the risk situation.

[0081] Artificial intelligence technology: Through AI technologies such as machine learning, achieve adaptive and dynamic optimization of task scheduling, and improve the emergency support ability.

[0082] Task scheduling optimization model: Based on a multi-layer collaborative space-air-ground integrated task scheduling framework, use optimization algorithms to solve task-resource matching, trajectory planning, edge computing, and multi-layer collaborative task scheduling problems;

[0083] Optimization model formula: Among them, x ij represents whether task i is assigned to resource j, c ij cj is the assignment cost, u i is the penalty cost of task i, b i is a binary variable indicating whether the task is completed;

[0084] Resource allocation and optimization algorithm: Use multi-objective optimization algorithms such as NSGA-II to achieve optimization of resource allocation, considering various factors such as task priority, complexity, data volume, latency requirements, and the computing power, communication bandwidth, and load conditions of edge servers;

[0085] Multi-objective optimization algorithm formula: Among them, g k (x) is the kth objective function, w k is the weight of the kth objective.

[0086] As Figure 6 shown, the principle flowchart of a resilience management and emergency response system for water supply and drainage pipe networks under extreme weather is as follows:

[0087] Multi-parameter extreme weather risk assessment model

[0088] Data collection and preprocessing: Use satellite and Doppler radar technologies to collect weather and urban water supply and drainage pipe network data, and perform preprocessing.

[0089] Risk assessment model construction: Based on the collected data, construct a risk assessment model with multiple parameters, and use calculation formulas for risk quantification analysis.

[0090] Model training and optimization: Adopt automated algorithms, such as the Crossformer algorithm, to train and optimize the model.

[0091] Risk assessment and emergency response strategy optimization: Combine the risk assessment method in the Japanese post-disaster reconstruction plan to optimize the emergency response strategy of urban water supply and drainage pipe networks under extreme weather.

[0092] Model verification and application: Apply the model in the actual urban water supply and drainage pipe network, and verify and adjust according to the actual effect.

[0093] Three-dimensional monitoring and early warning network based on multi-source data fusion

[0094] Data collection and preprocessing: Install sensors at key positions of the drainage pipe network for real-time monitoring of pipe network data.

[0095] Data fusion and three-dimensional real-scene construction: Use three-dimensional real-scene and real-time video fusion technology to construct a three-dimensional model of the drainage pipe network and achieve seamless docking of real-time video.

[0096] Data transmission and processing: The data collected by sensors is transmitted to the cloud data center through a wireless communication network, and cloud computing and big data analysis technologies are used for storage, processing, and analysis.

[0097] Real-time monitoring and early warning: The application of Internet of Things technology makes the monitoring of the urban drainage system change from passive to active. Managers can view the operation status of the drainage system in real time through the monitoring platform, and the system automatically triggers the early warning mechanism.

[0098] Intelligent scheduling and optimization: Through Internet of Things technology, the management of the urban drainage system can be more intelligent and efficient, realizing intelligent scheduling and optimization.

[0099] Visualization display and information sharing: Use GIS technology to achieve 24-hour continuous monitoring of the operation status of the drainage pipe network, and centrally monitor the entire drainage pipe network to improve the efficiency of information management.

[0100] Resilient water supply and drainage facilities and emergency support technologies:

[0101] Resilient infrastructure design: From the perspective of system risk resistance, transform the traditional large-scale centralized design concept, combine centralization and decentralization, and ensure that the basic functions of facilities are not all lost during disasters and can be quickly restored.

[0102] Risk assessment and emergency capacity assessment: For the identified high-risk elements, study corresponding planning control technologies, and evaluate the emergency capacity of the urban water supply system by correlating assessment indicators.

[0103] Application of Doppler radar technology: Utilize the Doppler radar technology of NSSL to monitor and warn of extreme weather, and improve the emergency response capacity of water supply and drainage facilities and equipment.

[0104] Technical implementation ideas: Define risk scenario elements, and based on the thresholds under normal grid operation conditions, determine the confidence value for risk scenario judgment; construct a comprehensive full-scenario assessment framework; establish a probability model for the occurrence of extreme weather; according to the risk scenario elements and historical grid source-load data, obtain the initial source-load power set and feature vector set, and use the approximate distance method for screening to obtain the optimal source-load power set and the corresponding system source-load state probability, and then determine the source-load power probability model.

[0105] Post-disaster emergency rescue and rapid restoration technologies

[0106] Intelligent unmanned search and rescue system: A dynamic solution based on multiple network technologies of drones, which supports rescue and survivor search operations by using different communication technologies.

[0107] Application of underwater rescue robot technology: Design a fast, accurate, scientific and effective intelligent rescue device that breaks through the capabilities and levels of maritime search and rescue, and utilizes sonar detection technology combined with GPS navigation system and marine battery energy technology.

[0108] Post-disaster reconstruction and rapid restoration: Formulate a detailed post-disaster recovery plan, including restoring living order as soon as possible, revitalizing industries and the economy, and constructing a safer and more disaster-resistant transportation network.

[0109] Emergency dispatch platform for collaborative linkage strategy

[0110] Omnidirectional multi-scenario monitoring and early warning: Utilize technologies such as Internet of Things sensing and video intelligent recognition to dynamically sense, actively identify high-risk hazards, and automatically alarm to comprehensively grasp the risk situation.

[0111] Intelligent judgment of risk situation: Utilize big data to intelligently judge the possible risks, analyze the impacts, scopes, and trends that emergencies may cause, and help managers master the risk situation.

[0112] Cross - department and multi - system collaborative operation: By integrating various technical means such as communication, digital twin, mobile phones, and individual combat equipment, a scientific and complete command and rescue system is constructed to create a full - chain and cross - level and cross - department collaborative disposal process.

[0113] One emergency map: During the emergency disposal process, it provides a remote collaborative consultation function based on the GIS map, realizing functions such as audio - video consultation, collaborative plotting, text consultation, file sharing, and comprehensive control of the consultation.

[0114] Emergency command and dispatch: It has an auxiliary decision - making function. Using prediction analysis and research results, combined with the emergency organization system, work processes, on - site emergency rescue forces, and emergency rescue materials, etc., it provides a guiding process and an auxiliary decision - making plan for dealing with emergencies.

[0115] Emergency data cockpit: Relying on resource data and hidden danger data, an integrated data control room is formed to analyze various factors that need to be considered in the emergency scenario in a more efficient and accurate way, so as to better guide decision - makers to handle emergency events.

[0116] Example 1: Smart water service in Nanjing Jiangbei New Area

[0117] Background: As a pioneer area for smart city construction, Nanjing Jiangbei New Area needs to establish a smart water service system to improve the management efficiency of urban water supply and drainage pipe networks and the ability to respond to extreme weather.

[0118] Implementation steps:

[0119] Data collection and pre - processing: Install intelligent sensors at key drainage nodes in Jiangbei New Area to monitor water level, flow, and water quality in real - time. Use satellite and Doppler radar technologies to collect weather data and perform pre - processing to meet the model input requirements.

[0120] Risk assessment model construction: Based on the collected data, construct a risk assessment model containing multiple parameters and use calculation formulas for risk quantification analysis.

[0121] Model training and optimization: Adopt automated algorithms, such as the Crossformer algorithm, to train and optimize the model to improve the prediction accuracy and response speed.

[0122] Risk assessment and emergency response strategy optimization: Combine the risk assessment method in the Japanese post - disaster reconstruction plan to adjust the model and optimize the emergency response strategy of urban water supply and drainage pipe networks under extreme weather.

[0123] Intelligent scheduling and optimization: Use Internet of Things technology to achieve intelligent scheduling and optimization and improve the management efficiency of the drainage system in Jiangbei New Area.

[0124] Visual display and information sharing: By using GIS technology, continuous 24-hour monitoring of the operation status of the drainage pipe network is realized, and the entire drainage pipe network is centrally monitored to improve the efficiency of information management.

[0125] Technical effect evaluation: Regularly evaluate the effect of the intelligent water service system, verify and adjust according to the actual effect to achieve the best emergency guarantee effect.

[0126] Example 2: Flood control response on Yanshan Road in Jianye District, Nanjing

[0127] Background: Yanshan Road in Jianye District, Nanjing is prone to waterlogging in extreme weather, and effective emergency guarantee measures need to be taken to reduce the impact of waterlogging.

[0128] Implementation steps:

[0129] Post-disaster assessment:

[0130] Quickly assess the waterlogging situation on Yanshan Road to determine the affected scope and degree.

[0131] Formulation of emergency response plan: According to the assessment results, formulate an emergency response plan, including resource allocation and rescue operations.

[0132] Intelligent unmanned search and rescue system: Use drones and unmanned vehicles for rapid aerial and ground search and rescue to improve search and rescue efficiency and safety.

[0133] Application of underwater rescue robot technology: Develop robots that can perform rescue tasks in underwater environments, integrating advanced sensor technology, artificial intelligence, and autonomous navigation capabilities.

[0134] Post-disaster reconstruction and rapid recovery: Formulate a detailed post-disaster recovery plan, including restoring living order as soon as possible, revitalizing industries and the economy, and building a safer and more disaster-resistant transportation network.

[0135] Emergency dispatch platform with collaborative linkage strategy: Build an emergency dispatch platform integrating technologies such as comprehensive air, space, and ground perception, integrated fusion communication, Internet of Things, big data, and artificial intelligence to achieve full-process closed-loop control of "pre-event monitoring and early warning, rapid response during the event, joint disposal during the event, and post-event summary and evaluation".

[0136] Technical effect evaluation: Evaluate the effects of emergency response and post-disaster reconstruction, verify and adjust according to the actual effects to achieve the best emergency guarantee effects.

[0137] Those of ordinary skill in the art can understand that the above are only preferred examples of the invention and are not used to limit the invention. Although the invention has been described in detail with reference to the foregoing examples, those skilled in the art can still modify the technical solutions described in the foregoing examples or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, etc. made within the spirit and principle of the invention shall be included within the protection scope of the invention. All technical features in this embodiment can be freely combined according to actual needs.

[0138] Finally, it should be noted that the above are only preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A resilience management and emergency response system for water supply and drainage pipe networks under extreme weather conditions, characterized in that: An emergency dispatching platform that includes a multi-parameter extreme weather risk assessment model, a three-dimensional monitoring and early warning network based on multi-source data fusion, resilient water supply and drainage facilities and equipment and emergency support modules, a post-disaster emergency rescue support and rapid recovery module, and a collaborative linkage strategy; Among them, the multi-parameter extreme weather risk assessment model is used to realize the risk assessment of urban water supply and drainage pipe networks under extreme weather based on integrating multiple data sources and algorithms; it includes satellite data collection, Doppler radar technology, automated algorithm processing, and risk assessment methods; The three-dimensional monitoring and early warning network based on multi-source data fusion is used to realize the unified management and dynamic monitoring of urban water supply and drainage pipe networks based on multi-source data fusion technology, by integrating three-dimensional real scenes, audio-visual linkage technology, and Internet of Things and big data technology; The resilient water supply and drainage facilities and equipment and emergency support module is used to keep operating under extreme weather conditions and quickly respond to the needs of post-disaster reconstruction; The post-disaster emergency rescue support and rapid recovery module is used to provide post-disaster emergency rescue support; The emergency dispatching platform with a collaborative linkage strategy is used to build an emergency dispatching platform integrating comprehensive perception of air, space and ground, integrated fusion communication, Internet of Things, big data, and artificial intelligence technologies, to realize the full-process closed-loop management and control of pre-event monitoring and early warning, rapid response during the event, joint disposal during the event, and summary and evaluation after the event, and improve the efficiency and accuracy of emergency rescue.

2. The resilient management and emergency response system for water supply and drainage pipe networks under extreme weather according to claim 1, wherein: The principle of the multi-parameter extreme weather risk assessment model specifically includes: Satellite data collection: Using satellite remote sensing technology to monitor weather changes and the status of urban water supply and drainage pipe networks in real time, providing data support at the macro level; Doppler radar technology: Monitoring precipitation intensity and distribution through Doppler radar, providing accurate precipitation data for the model; Automated algorithm processing: Adopting advanced data processing algorithms, including the Crossformer algorithm, for real-time data analysis and processing, improving the response speed and accuracy of the model; Risk assessment method: Assessing the risks of urban water supply and drainage pipe networks under extreme weather and optimizing emergency response strategies. The calculation model is as follows: Chicago rain pattern calculation formula: formula before peak: i(t1) = A·b·r·(1 + r)·n·t b·r ; where, i(t1) is the instantaneous rainfall intensity before peak, A is the rainfall force parameter, n is the storm attenuation index, b is the rainfall duration correction parameter, r is the rain peak position coefficient, and t is time; Post-peak formula: i(t2) = A·b·r·(1 + r)·n·t b·r where i(t2) is the rainfall intensity after the peak; Calculation formula for equipment failure rate under meteorological disasters: Equipment failure rate: Among them, λ x is the failure rate of type e power equipment under meteorological disaster x, n x,e is the number of failures of type e power equipment under meteorological disaster x, and T is the duration of the meteorological disaster; Goodwin Model for Transmission Line Ice Accretion Prediction: Ice Accretion Thickness: where ρ0 and ρ i are the density of water and the density of ice accretion respectively; H g is the precipitation during the ice accretion period; v v is the velocity of raindrops acting on the structure.

3. The resilient management and emergency response system for water supply and drainage pipe networks under extreme weather according to claim 1, wherein: The principle of the three-dimensional monitoring and early warning network based on multi-source data fusion specifically includes the following: Three-dimensional real scene and real-time video fusion: Used to seamlessly dock the real-time video stream from monitoring devices with three-dimensional scenes or models, realizing unity in the spatial and temporal dimensions; Internet of Things application: Using sensors and wireless communication networks to transmit key parameter data such as water level, flow rate, and water quality of drainage pipe networks to the centralized management platform in real time; Big data analysis: In the data center, through cloud computing and big data analysis technologies, storing, processing, and analyzing the data transmitted by sensors, predicting the operation trend of the drainage system, and providing decision-making support; The calculation model is as follows: Drainage network flow prediction formula: Using fluid mechanics and statistical methods, combining historical data and real-time monitoring data, to predict the flow changes in the drainage network under different weather conditions: Q = A · C · R n ; where Q is the flow rate, A is the cross-sectional area, C is the Chezy coefficient, R is the hydraulic radius, and n is the flow regime index; Drainage network health assessment formula: Using GIS technology and big data analysis to assess the health of the drainage network: Among them, H is the health of the pipe network, w i is the weight, h i is the health of each index, and N is the total number of indexes; Early warning threshold setting formula: Combining historical data and real-time monitoring data, setting the early warning threshold: T = μ + k·σ; where T is the early warning threshold, μ is the average value, σ is the standard deviation, and k is the risk coefficient.

4. The resilient management and emergency response system for water supply and drainage pipe networks under extreme weather according to claim 1, wherein: The principle of the resilient water supply and drainage facilities and equipment and emergency support module is specifically calculated as follows: Real-time rain load calculation formula for transmission lines: Assuming that the raindrop diameters are the same, the real-time rain load L of the transmission line R is: L R = 29πd 3 ρd p n(d)V 2 ; where ρ is the density of raindrops, V is the velocity of raindrops acting on the structure, d is the outer diameter of the wire, and d p is the horizontal span of the pole tower; Total load calculation formula for transmission line: The load mainly considers rain load L R (t) and fixed load L G in two parts; the fixed load is the permanent load, mainly the self-weight of components; the rain load is a variable load related to time, and the rain load at a certain moment is a fixed value; considering the more severe situation, that is, the rain load and the fixed load are in the same direction: S(t) = L G + L R (t); where S(t) is the total load borne by the transmission line Calculation formula for the failure probability of transmission lines: The failure probability P(t) of a transmission line under rainstorm conditions is the probability that the line strength is less than the load: P(t) = P[Z(t) < 0] = P[R d - S(t) < 0]; where R d is the design strength of the transmission line.

5. The resilient management and emergency response system for water supply and drainage pipe networks under extreme weather according to claim 1, wherein: The principle of the post-disaster emergency rescue support and rapid recovery module specifically includes: Intelligent unmanned search and rescue technology: Utilize unmanned aerial vehicles and unmanned vehicles for rapid search and rescue in the air and on the ground, improving search and rescue efficiency and safety; UAV Path Planning Model: The problem of the rapid delivery path of UAVs in emergency rescue in complex mountainous areas is a multi-stage decision-making problem. A dynamic programming model is established, and the optimal rescue path of the UAV is calculated by solving the model. The formula of the dynamic programming model is: V(s) = max a∈A(s) [R(s, a) + γmin s′∈S V(s′)]; where V(s) is the value of state s, A(s) is all possible actions in state s, R(s, a) is the immediate reward obtained after executing action a, γ is the discount factor, and S is the set of all possible states; Underwater emergency rescue robot technology: Develop robots capable of performing rescue tasks in underwater environments, integrating advanced sensor technologies, artificial intelligence, and autonomous navigation capabilities; Underwater robot positioning and navigation algorithm: Utilize sonar detection technology combined with the GPS navigation system and marine battery energy technology to enable intelligent search and rescue equipment to quickly search for the vital information of victims; Positioning algorithm formula: Among them, P(x, y) is the optimal position of the robot, where (x i , y i ) is the point detected by the sonar, and d is the corresponding distance.

6. The resilient management and emergency response system for water supply and drainage pipe networks under extreme weather according to claim 1, wherein: The principle of the emergency dispatching platform for the collaborative linkage strategy is specifically calculated as follows: Task scheduling optimization model: Based on a multi-layer collaborative air-space-ground integrated task scheduling framework, achieve task resource matching, trajectory planning, edge computing, and multi-layer collaborative task scheduling problems through optimization algorithms; Optimized model formula: where, x ij indicates whether task i is assigned to resource j, c ij cj is the assignment cost, u i is the penalty cost of task i, b i is a binary variable indicating whether the task is completed; Resource allocation and optimization algorithm: Utilize multi-objective optimization algorithms such as NSGA-II to achieve optimization of resource allocation, considering various factors such as task priority, complexity, data volume, latency requirements, as well as the computing power, communication bandwidth, and load conditions of edge servers; Multi-objective optimization algorithm formula: Among them, g k (x) is the k-th objective function, and w k is the weight of the k-th objective.

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