Multi-parameter cooperative control method for non-excavation repair of drainage pipe network in urban updating

Abstract

The invention discloses a multi-parameter cooperative control method for non-excavation repair of a drainage pipe network in urban updating, and relates to the technical field of municipal engineering, and the method comprises the steps: firstly constructing a quantum entanglement sensing pipe network digital twinborn model, fusing multi-source data, monitoring micro-strain in real time through a nano sensor, deploying a self-organizing intelligent node and terahertz imaging equipment, and constructing a quantum entanglement sensing pipe network digital twinborn model; multi-dimensional features are extracted, repair parameters are dynamically regulated and controlled through technologies such as magnetofluid plugging and multi-robot cooperation based on digital twinning virtual simulation, finally, the repair effect is evaluated and the scheme is optimized in combination with cognitive calculation and microbial self-healing technologies, and full-process intelligent control is achieved. The intelligent level of non-excavation repair of the drainage pipe network is improved, the problem that traditional monitoring is one-sided is solved through high-precision data fusion, precise construction control is achieved through cooperation of magnetofluid leaking stoppage and the robot, durability is enhanced through the microorganism self-healing technology, repair quality and efficiency are improved, and urban updating and sustainable development are promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of municipal engineering, and in particular to a multi-parameter collaborative control method for trenchless repair of drainage pipe networks in urban renewal. Background Art

[0002] In the process of urban renewal, drainage networks, as an important component of urban infrastructure, have a direct impact on urban flood control and drainage, water resource utilization, and ecological environmental quality through their functional integrity. Traditional drainage network repair relies on excavation construction, which has problems such as long construction period, high cost, and significant impact on urban traffic and residents' lives. Trenchless repair technology has become the preferred option in urban renewal due to its advantages of high efficiency, environmental protection, and low interference. However, existing trenchless repair technologies have significant bottlenecks in data collection, decision optimization, and process control. Pipeline network disease diagnosis relies on single sensor data, which makes it difficult to fully reflect the structural defects and functional failures of complex pipeline networks; repair plan formulation is mostly based on empirical judgment, lacking systematic optimization of multiple objectives such as repair cost, construction safety, and environmental impact; parameter adjustment during the repair process relies on manual intervention and cannot respond to changes in pipeline network status in real time, resulting in uneven repair results and insufficient long-term reliability.

[0003] With the development of technologies such as the Internet of Things and big data, intelligent monitoring equipment and digital twin models are gradually being applied to pipeline network management. However, existing technologies still face the problem of inefficient fusion of multi-source heterogeneous data. Pipeline network data from different eras and standards have problems such as inconsistent formats and inconsistent spatiotemporal benchmarks. Traditional data processing methods are unable to effectively integrate multi-dimensional data such as laser scanning, sensor monitoring, and geological exploration, resulting in a low degree of match between the digital twin model and the actual pipeline network, and an inability to provide accurate support for repair decisions. In addition, multi-parameter collaborative control technology in complex pipeline network environments is not yet mature. The dynamic coupling relationship of key parameters such as pressure, flow, and material curing during the repair process has not been fully modeled. The collaborative operation between construction equipment lacks intelligent scheduling, which restricts the automation and precision level of the repair project.

[0004] In the context of sustainable development, urban renewal is placing higher demands on greener and smarter drainage network repair. Traditional repair solutions rarely consider factors such as carbon emissions, material durability, and ecological impacts. The selection of repair materials and construction schedules lack systematic evaluation, making it difficult to meet the urban governance needs under the "dual carbon" goals. Furthermore, repair effectiveness evaluation often relies on short-term monitoring data, lacking long-term tracking and prediction of network structural performance, hydraulic efficiency, and environmental benefits. This makes it impossible to form a closed-loop management system of "monitoring-repair-assessment-optimization," limiting the promotion and application of trenchless repair technology. Summary of the Invention

[0005] The present invention proposes a multi-parameter collaborative control method for trenchless repair of drainage pipe networks in urban renewal to solve the problems mentioned in the above-mentioned prior art.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions: A multi-parameter collaborative control method for trenchless restoration of drainage pipe networks in urban renewal, comprising the following steps: The steps for fusion modeling of multi-source heterogeneous data in the pipeline network are as follows: Build a digital twin model of the pipeline network based on quantum entanglement perception, and process data using the principle of quantum state superposition; Develop nanoscale pipeline network stress sensing technology, implant carbon nanotube sensor arrays to monitor microstrain, and combine molecular dynamics simulation to predict material aging processes; Multi-parameter real-time monitoring and feature extraction steps: deploy self-organizing neural network driven monitoring nodes, use biologically inspired swarm algorithm between nodes, according to the formula Realize data self-synchronization, is the node synchronization coefficient; γ is the inertia factor; is the set of neighboring nodes of node i; is the node connection weight; is the number of neighborhood nodes; develop terahertz wave pipeline imaging technology, penetrate the pipe wall to obtain three-dimensional information of internal defects, combine computer vision algorithm, according to the formula Identify crack types and trends, where F is the comprehensive characteristic value of the crack, L, W, and A are the length, width, and area of ​​the crack, respectively, and α, β, and δ are the characteristic weight coefficients; Multi-objective optimization and restoration decision-making steps: Establish a restoration decision-making model optimized by a quantum genetic algorithm, and use the superposition of quantum bits to search the solution space; comprehensively consider community impact, ecological restoration, and technical feasibility to construct a three-dimensional Pareto frontier; Dynamic repair process collaborative control steps: Design a repair parameter encoding method based on DNA computing, convert the construction parameter vector P into a DNA base sequence, and use the external magnetic field gradient to Control the trajectory of magnetic nanoparticles, and the two are coupled through a cross-scale model Collaboration, is the system state function, is the bio-physical synergy operator, is a DNA coding module, It is a magnetic fluid control module; Repair effect evaluation and continuous optimization steps: Build an evaluation system driven by cognitive computing, perceive public satisfaction through affective computing, and evaluate the repair effect in combination with knowledge graphs; develop pipeline self-healing enhancement technology, implant microbial flora in materials, and achieve autonomous repair and protection of cracks through biomineralization.

[0007] Furthermore, it also includes: in the pipeline network multi-source heterogeneous data fusion modeling step, developing a pipeline network feature extraction technology based on topological data analysis, capturing the topological invariants of the pipeline network structure through persistent homology theory; building a quantum secure communication channel, and using quantum key distribution technology to ensure data transmission security.

[0008] Furthermore, it also includes: in the said multi-parameter real-time monitoring and feature extraction step, developing a bionic intelligent Daphnia robot to simulate the movement and perception capabilities of Daphnia to achieve cable-free autonomous detection inside the pipeline network; designing a surface acoustic wave sensor array to achieve non-contact structural health monitoring by detecting the propagation characteristics of acoustic waves on the surface of the pipeline network.

[0009] Furthermore, it also includes: introducing quantum game theory into the multi-objective optimization and repair decision-making step to establish a multi-party interest coordination model to resolve conflicts of interest among owners, construction parties and regulatory authorities; developing a spatiotemporal value stream evaluation method to quantify the impact of different repair timings on the value of the entire life cycle of the pipeline network and achieve dynamic timing optimization.

[0010] Furthermore, it also includes: in the collaborative control step of the dynamic repair process, constructing a brain-computer interface assisted construction system to realize mind control of the repair equipment by reading the operator's brain wave signals; designing a shape memory alloy intelligent lining to realize self-repair of the pipeline by utilizing the shape memory effect of the material.

[0011] Furthermore, the pipeline network multi-source heterogeneous data fusion modeling step also includes: realizing quantum entanglement synchronization of the pipeline network digital twin model, so that the physical pipeline network and the virtual model status are associated in real time; developing molecular imprinting sensing technology, and specifically detecting pollutants in the pipeline network through customized molecular recognition materials.

[0012] Furthermore, the multi-parameter real-time monitoring and feature extraction steps also include: designing a pipeline material analysis system based on laser-induced breakdown spectroscopy to determine the composition and degree of corrosion of the pipe in real time; developing a microbial electrochemical sensor to monitor the health status of the pipeline using the current signal generated by the metabolic activity of microorganisms in the pipeline.

[0013] Furthermore, the multi-objective optimization and restoration decision-making steps also include: constructing a quantum annealing optimized restoration solution generator to solve high-dimensional combinatorial optimization problems; developing an ecological footprint assessment module to quantify the impact of restoration projects on urban ecosystems and achieve green restoration decisions.

[0014] Furthermore, the collaborative control step of the dynamic repair process also includes: realizing multi-robot collaborative repair based on swarm intelligence, coordinating robot cluster operations through pheromone simulation algorithms; developing an intelligent lighting control system for light-curing repair materials, and automatically adjusting lighting parameters according to material properties and environmental conditions.

[0015] Furthermore, the repair effect evaluation and continuous optimization steps also include: establishing an evaluation framework driven by a social-physical system, integrating the physical pipeline network status and social feedback information; developing a repair history database based on DNA storage, and utilizing the storage characteristics of DNA to achieve long-term data preservation.

[0016] Compared with the existing technology, the beneficial effects of the present invention are: In terms of data fusion and intelligent modeling, a quantum entanglement-aware digital twin model of the pipeline network was constructed. This model, integrating 3D laser scanning, sensor monitoring, and geological exploration data, combined with spatiotemporal kriging interpolation and graph neural network technology, achieved high-precision digital mapping of the pipeline network's status. Nanoscale carbon nanotube sensor arrays captured microstrain in the pipeline network in real time, while terahertz imaging technology penetrated the pipe wall to capture detailed damage. This provided multi-dimensional, lifecycle-wide data support for repair decisions, addressing the incompleteness of traditional data collection.

[0017] The multi-objective optimization decision-making system incorporates a quantum genetic algorithm and a socio-ecological-technical assessment framework, simultaneously considering factors such as repair cost, construction period, flow impact, and environmental disturbance to generate a Pareto-optimal solution set. The intelligent repair material selection model comprehensively considers mechanical properties, corrosion resistance, and ease of construction to recommend the optimal material combination. A spatiotemporal value stream assessment method quantifies the lifecycle value of the pipeline network at different repair opportunities, enabling dynamic optimization of repair options and significantly improving the scientific and economic efficiency of decision-making.

[0018] Dynamic repair process control utilizes a 5G+ edge computing architecture to achieve low-latency, precise control. A multi-robot collaborative algorithm simulates ant foraging behavior to optimize construction paths. Magnetic fluid intelligent leak-proofing technology utilizes an external magnetic field to adaptively fill complex cracks. An intelligent grouting pressure control system and light-curing material illumination control technology ensure uniform filling and curing of the repair material, addressing the issues of lag in parameter adjustment and insufficient coordination in traditional construction, significantly improving repair quality and efficiency.

[0019] The repair effectiveness evaluation and continuous optimization module builds an evaluation system driven by cognitive computing, combining knowledge graphs and sentiment analysis to achieve interpretable evaluation of repair results and public satisfaction surveys. Pipeline network self-healing enhancement technology embeds microbial flora into repair materials, enabling autonomous crack repair through biomineralization. DNA storage technology encodes and stores historical repair data, providing long-term data support for the full lifecycle management of the pipeline network.

[0020] Overall, the technology of this application has formed a complete technical chain of "data collection-intelligent decision-making-precision construction-long-term evaluation", which has significantly improved the intelligence level and sustainability of urban drainage network repair, and has significant economic, environmental and social benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a schematic block diagram of the multi-parameter collaborative control method for trenchless restoration of drainage pipe networks in urban renewal proposed by the present invention; Figure 2 A radar chart comparing the multi-objective optimization performance of the traditional solution and this solution; Figure 3 A bar chart comparing the prediction accuracy of repair effects for different model types. DETAILED DESCRIPTION

[0022] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0023] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like to indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0024] In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the said features. In the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined. In addition, the terms "installed", "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be a connection between the two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. The present invention will be further described in detail below with reference to the accompanying drawings.

[0025] Reference Figures 1 to 3 A multi-parameter collaborative control method for trenchless repair of drainage pipe networks in urban renewal, comprising the following steps: Pipeline network multi-source heterogeneous data fusion modeling steps: In this example, a quantum entanglement-aware digital twin model of the drainage network was constructed for a historic urban area drainage network renovation project. Using the IBM Qiskit quantum computing framework, quantum state superposition processing was achieved for spatial data (3D laser scanning point clouds), time series data (flow monitoring history), and uncertainty data (geological exploration errors). The uncertainty of the data was represented by the probability amplitude of quantum bits, and the properties of quantum entanglement were leveraged to ensure real-time correlation between the physical pipeline network and the virtual model.

[0026] To achieve nanoscale stress sensing of pipe network structures, an array of carbon nanotube sensors is implanted on the inner wall of the pipe. These sensors are grown using chemical vapor deposition and have diameters of approximately 1-2 nanometers and lengths up to tens of microns. The sensor array is connected via a dedicated circuit that converts stress changes into electrical signals, which are amplified by a low-noise amplifier and transmitted to a data acquisition system. Using LAMMPS molecular dynamics simulation software, combined with quantum mechanics / molecular mechanics (QM / MM) methods, the system predicts molecular structural changes in pipes under long-term stress, thereby assessing their aging evolution.

[0027] In terms of data fusion, topological data analysis (TDA) technology is used to process the structural characteristics of the pipeline network. The persistent homology group of the pipeline network is calculated through the Dionysus library, and key topological invariants are extracted as the characteristic fingerprint of the pipeline network. At the same time, a quantum key distribution system based on the BB84 protocol is built to establish a quantum secure communication channel between the data center and the monitoring nodes to ensure that the data transmission process cannot be eavesdropped and tampered with. This step combines quantum computing and nanotechnology to achieve efficient processing and precise perception of pipeline network data. Quantum entanglement sensing technology enables the digital twin model to reflect real-time changes in the physical pipeline network's state, while nanoscale sensors provide unprecedented stress monitoring accuracy. Topological data analysis captures the essential structural characteristics of the pipeline network, and quantum secure communication ensures data reliability. The combined application of these innovative technologies provides a solid data foundation for subsequent repair decisions.

[0028] Multi-parameter real-time monitoring and feature extraction steps: First, deploy intelligent monitoring nodes driven by self-organizing neural networks (SONN). SONN has strong adaptability and learning capabilities, and can dynamically adjust monitoring strategies based on the actual operation status of the pipeline network. The nodes use a biologically inspired swarm intelligence algorithm to achieve data self-synchronization. This algorithm draws on the collaborative model of biological groups in nature, such as ant colonies foraging and bird flocks migrating. During the operation of this algorithm, the formula Accurately calculate the synchronization coefficient between nodes. is the synchronization coefficient between nodes i and j at time t, which reflects the closeness of data transmission and collaboration between nodes; γ is the inertia factor, which is used to balance the node's dependence on the historical synchronization state and the degree of response to the current neighbor node information; It is a set of neighborhood nodes of node i that has been strictly screened and defined; It is the connection weight between node i and neighboring node k, which is determined based on multiple factors such as the physical distance between nodes and signal strength; is the number of neighborhood nodes, which is determined based on an in-depth analysis of the pipe network topology and signal transmission characteristics. Secondly, develop advanced terahertz wave pipeline imaging technology. Terahertz waves have unique penetrating properties and can penetrate the pipe wall without damage. With this feature, three-dimensional information of internal defects in the pipeline can be effectively obtained. Afterwards, combined with high-precision computer vision algorithms, the acquired image data is deeply analyzed to accurately identify the type of cracks, including longitudinal cracks, transverse cracks, etc., and by comparing and modeling image data at different time points, the expansion trend of the cracks is scientifically predicted. Crack feature extraction is performed through the formula , where F represents the comprehensive characteristic value of the crack, L, W, and A represent the crack length, width, and area, respectively, and α, β, and δ are characteristic weight coefficients, all summed to 1. Their values ​​are determined based on actual operating conditions such as the pipe network material and operating pressure, and are determined through extensive experiments and data analysis to ensure that they can most realistically reflect the impact of each dimension of the crack on the comprehensive characteristic value.

[0029] Multi-objective optimization and repair decision-making: During the repair decision-making phase, a quantum genetic algorithm optimization decision model was constructed. Using a D-Wave quantum annealing processor, the four optimization objectives—repair cost, construction cycle, traffic impact, and environmental disturbance—were encoded into a quantum bit system. Quantum tunneling enabled parallel search of the solution space, significantly improving optimization efficiency. The algorithm employed the PennyLane quantum machine learning framework, combined with crossover and mutation operations from a classical genetic algorithm, to form a hybrid optimization strategy.

[0030] A social-ecological-technical (SET) assessment framework was introduced to construct a three-dimensional Pareto-optimal frontier. The social dimension considers the impact on community residents' travel and daily lives, quantified through questionnaires and sentiment analysis. The ecological dimension assesses environmental indicators such as carbon emissions and water consumption during construction. The technical dimension considers the durability and reliability of the restoration results. The developed ecological footprint assessment module, based on the Life Cycle Assessment (LCA) methodology, calculates the carbon, water, and material footprints of different restoration options.

[0031] To resolve conflicts of interest among multiple parties, a coordination model was established using quantum game theory. The owner, contractor, and regulatory authorities were considered participants in the game, with each participant's strategy set corresponding to a different repair plan. Quantum entanglement enabled information sharing and collaboration among participants, leveraging quantum advantage to identify the Pareto optimal equilibrium. A spatiotemporal value stream assessment method was developed, combining the frequency of use, importance, and disease development trends of the pipeline network to calculate value curves for different repair opportunities and determine the optimal repair sequence.

[0032] For the selection of repair materials, a multi-attribute decision-making model was constructed. This model considered multiple attributes, including mechanical properties (compressive strength, elastic modulus), corrosion resistance (resistance to chemical and microbial corrosion), ease of construction (curing time, construction temperature range), and economic efficiency (material cost, service life). The analytic hierarchy process (AHP) was used to determine the weights of each attribute, and the TOPSIS method was combined to optimize material selection.

[0033] Dynamic repair process collaborative control steps: Design a repair parameter encoding method based on DNA computing. The construction parameter vector P includes key elements such as pressure, temperature, and rate. Through specific encoding rules, these parameters are accurately converted into DNA base sequences. DNA molecules have powerful information storage and parallel processing capabilities. Leveraging biological enzyme reactions, they can efficiently achieve parallel parameter calculation. In this process, different biological enzymes trigger corresponding chemical reactions according to the instructions of the base sequence, quickly and accurately processing a large amount of parameter information.

[0034] At the same time, we develop advanced magnetic fluid plugging technology. The magnetic fluid is formed by uniformly dispersing magnetic nanoparticles in a carrier fluid. The magnetic nanoparticles are precisely controlled. The strength and direction of the external magnetic field can be flexibly adjusted according to the actual situation of the pipeline crack, thereby accurately changing the movement trajectory of the magnetic nanoparticles. When the magnetic nanoparticles move under the action of the magnetic field, they can accurately reach the crack location. The two are coupled through a cross-scale model. Collaborative work, where It is the state function of the repair system at time t, reflecting the repair process in real time; It is a bio-physical synergistic operator that cleverly coordinates the interaction between DNA computing and magnetic fluid control; It is the DNA encoding module, responsible for parameter encoding and processing; The magnetic fluid control module controls the movement of magnetic nanoparticles. This synergy enables efficient transmission of repair parameters and precise positioning of plugging materials, enabling adaptive filling of complex cracks.

[0035] Restoration Evaluation and Continuous Optimization Steps: During the restoration evaluation phase, a cognitive computing-driven evaluation system was constructed. The IBM Watson cognitive platform, combined with knowledge graph technology, ensured interpretability of the evaluation process. The system collected multi-source data before and after the pipeline network restoration, including monitoring sensor data, construction records, and public feedback. Natural language processing (NLP) technology was used to analyze public satisfaction with the restoration project. A sentiment analysis model was developed, based on the BERT pre-trained language model and fine-tuned with pipeline network domain knowledge, to accurately identify public sentiment.

[0036] A socio-physical system (CPS)-driven evaluation framework was established to deeply integrate the physical status of the pipeline network with social feedback. A digital twin model was used to simulate the operational status of the pipeline network, incorporating agent-based modeling methods to simulate the behavior and feedback of community residents. The developed adaptive prediction model utilizes a gated recurrent unit (GRU) network to dynamically adjust model parameters based on real-time monitoring data. An attention mechanism was introduced to enable the model to focus on changes in key parameters, improving prediction accuracy.

[0037] The self-healing enhancement technology developed for pipeline networks incorporates Bacillus pasteurianus (Sporosarcina pasteurii) into the repair material. These microorganisms metabolize urea under aerobic conditions, producing calcium carbonate precipitates that fill tiny cracks. By manipulating the material formulation and microbial concentration, the repair layer is endowed with self-healing properties. A long-term monitoring database for repair effectiveness has been established, using DNA storage technology to preserve critical data. Binary data is encoded into DNA base sequences and stored in a laboratory cryogenic storage facility using synthetic biology techniques, with a theoretical storage lifespan of up to 1,000 years.

[0038] A multi-dimensional evaluation index system was designed. The hydraulic performance recovery rate was calculated by comparing the flow-pressure curves before and after repair. The structural integrity index was assessed based on finite element analysis results and actual strain monitoring data. The durability improvement factor was determined by combining material aging models and long-term monitoring data. The weighting of each indicator was determined using the analytic hierarchy process, forming a comprehensive evaluation system.

[0039] The present invention also includes developing a pipeline network feature extraction technology based on topological data analysis (TDA) during the pipeline network multi-source heterogeneous data fusion modeling step. With the help of persistent homology theory, the complex structure of the pipeline network can be deeply analyzed. Specifically, by abstracting and modeling the pipeline network nodes and connection relationships, algebraic topology methods are used to accurately capture the topological invariants of the pipeline network structure at different scales. At the same time, a quantum secure communication channel is constructed. Quantum key distribution technology is used to generate and distribute absolutely secure keys based on the principle of non-cloning of quantum states and the uncertainty principle. During data transmission, these keys are used to encrypt multi-source heterogeneous data, effectively resisting malicious attacks. Even if an attacker attempts to steal information, any measurement of the quantum state will inevitably disturb the quantum state, which will be detected by the sender and receiver, ensuring the security of data transmission and preventing decision-making errors caused by data leakage or tampering.

[0040] The present invention also includes: in the multi-parameter real-time monitoring and feature extraction step, developing a bionic intelligent Daphnia robot to simulate the movement and perception capabilities of Daphnia to achieve cable-free autonomous detection inside the pipe network; designing a surface acoustic wave (SAW) sensor array to achieve non-contact structural health monitoring by detecting the propagation characteristics of acoustic waves on the pipe network surface; designing a pipeline material analysis system based on laser-induced breakdown spectroscopy (LIBS). Using a high-energy pulsed laser (energy density >10 10 W / cm²) to generate plasma, and analyze the spectrum of the plasma emission to determine the elemental composition and content of the pipe. The developed microbial electrochemical sensor utilizes the metabolic activity of microorganisms such as sulfate-reducing bacteria within the pipeline to convert chemical energy into electrical energy, and monitors pipeline corrosion by detecting changes in current.

[0041] The present invention also includes: introducing quantum game theory into the multi-objective optimization and remediation decision-making step to establish a multi-party interest coordination model to resolve conflicts of interest between owners, construction parties, and regulatory authorities; developing a spatiotemporal value stream assessment method to quantify the impact of different remediation timings on the full lifecycle value of the pipeline network and achieve dynamic timing optimization. Constructing a quantum annealing-optimized remediation solution generator. Transforming the remediation decision-making problem into a quadratic unconstrained binary optimization (QUBO) problem and solving it using the D-Wave quantum annealing processor. Developing an ecological footprint assessment module, using the input-output lifecycle analysis (IO-LCA) method, quantifies the impact of remediation projects on urban ecosystems, including resource consumption, pollution emissions, and other aspects.

[0042] The present invention also includes: constructing a brain-computer interface (BCI)-assisted construction system during the collaborative control step of the dynamic repair process, enabling mind-controlled repair equipment by reading the operator's brainwave signals; designing a shape memory alloy intelligent lining that utilizes the material's shape memory effect to achieve self-repair of the pipeline, reducing manual intervention; and implementing multi-robot collaborative repair based on swarm intelligence. By simulating the foraging behavior of ant colonies and designing a pheromone update algorithm, robots can dynamically adjust their operating paths based on environmental changes. The developed intelligent light control system for light-curing repair materials uses photosensitive resin materials and controls the material's curing process by adjusting light intensity, wavelength, and duration to ensure repair quality.

[0043] In the present invention, the multi-source heterogeneous data fusion modeling step of the pipeline network also includes: realizing quantum entanglement synchronization of the digital twin model of the pipeline network is a key link. By utilizing the unique quantum mechanics phenomenon of quantum entanglement, a close connection is established between the physical pipeline network and the virtual model. For entangled quanta, no matter how far apart they are, the measurement of one quantum state will instantly affect the other, thereby ensuring that the physical pipeline network and the virtual model state are associated in real time. At the same time, molecular imprinting sensing technology is developed. By carefully designing customized molecular recognition materials that are complementary to the molecular structure of specific pollutants, when specific pollutants in the pipeline network pass through, they can be specifically bound like a "lock-key" match to achieve precise detection.

[0044] In the present invention, the multi-parameter real-time monitoring and feature extraction step also includes designing a pipeline material analysis system based on laser-induced breakdown spectroscopy (LIBS). This system emits high-energy laser pulses focused on the surface of the pipeline material, instantaneously generating a high-temperature plasma. As the plasma cools, different elements emit characteristic spectra. The system collects and analyzes these spectra with high precision, accurately determining the composition of the pipe material in real time based on the position and intensity of the characteristic spectral peaks. Furthermore, by analyzing changes in the content of specific elements and the spectral characteristics of corrosion products, the system can effectively assess the extent of pipeline corrosion.

[0045] Furthermore, a microbial electrochemical sensor has been developed. This sensor cleverly utilizes the current signals generated by the metabolic activity of microorganisms within pipelines. During their metabolic processes, microorganisms within the pipeline transfer electrons, which interact with electrodes to generate a current. By monitoring, amplifying, and analyzing this current signal, accurate information on microbial activity and species can be obtained, effectively monitoring pipeline health.

[0046] In the present invention, the multi-objective optimization and repair decision-making step also includes the construction of a quantum annealing-optimized repair solution generator, which is a key step. Quantum annealing utilizes the quantum tunneling effect to rapidly explore high-dimensional solution spaces. When faced with high-dimensional combinatorial optimization problems such as trenchless drainage network repair, which involve numerous parameters (such as repair material selection, construction sequence, and resource allocation), traditional algorithms often take too long or become stuck in local optimal solutions. However, the quantum annealing-optimized repair solution generator, based on the superposition and entanglement properties of quantum states, can simultaneously evaluate a large number of possible solution combinations and quickly find a repair solution close to the global optimal solution.

[0047] At the same time, an ecological footprint assessment module will be developed. This module comprehensively considers factors such as resource consumption (e.g., energy and materials) and waste emissions (e.g., construction waste and chemical residues) involved in restoration projects. Using a specific quantitative model, these factors are converted into ecological footprint indicators, clearly demonstrating the impact of restoration projects on land, water resources, and biodiversity in urban ecosystems. This will help decision-makers weigh the ecological costs of restoration options and achieve green restoration decisions.

[0048] In the present invention, the collaborative control step of the dynamic repair process also includes implementing multi-robot collaborative repair based on swarm intelligence. Drawing on the mechanism by which ant colonies transmit information through pheromones in nature, a pheromone simulation algorithm was designed. During the operation, each robot "releases" virtual pheromones in real time based on its own task progress and environmental feedback. The simulated pheromone concentration reflects information such as task urgency and the quality of the path. Other robots, sensing pheromone concentrations, dynamically adjust their own paths and task priorities, achieving efficient swarm collaboration and avoiding conflicts and duplication of effort during repair operations.

[0049] At the same time, an intelligent lighting control system for light-curing restorative materials has been developed. This system incorporates multiple sensors to collect real-time data on ambient temperature, humidity, restoration material thickness, and cure level. This data is fed into a pre-built mathematical model for material curing, where it is analyzed and calculated. Based on the material's curing characteristics under different environments, the system automatically and precisely adjusts parameters such as light intensity, duration, and angle. This ensures that light-curing restoration materials cure quickly and fully under all conditions, improving both repair efficiency and quality.

[0050] In this invention, the restoration effectiveness evaluation and continuous optimization steps also include establishing a socio-physical system (CPS)-driven evaluation framework. Using the Internet of Things (IoT), pipeline network sensor data is integrated with social media and urban planning data to construct a multidimensional network model. Complex network analysis methods are used to quantitatively assess the impact of restoration projects on public quality of life and urban development. Furthermore, a DNA-based restoration history database is developed, utilizing the principle of complementary base pairing to encode key data such as construction parameters and material properties, and PCR technology is used to selectively access this data.

[0051] The above are only preferred specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with this technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solutions and inventive concepts of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A multi-parameter collaborative control method for trenchless repair of drainage pipe networks in urban renewal, characterized by: The following steps are involved: The steps for fusion modeling of multi-source heterogeneous data in the pipeline network are as follows: Build a digital twin model of the pipeline network based on quantum entanglement perception, and process data using the principle of quantum state superposition; Develop nanoscale pipeline network stress sensing technology, implant carbon nanotube sensor arrays to monitor microstrain, and combine molecular dynamics simulation to predict material aging processes; Multi-parameter real-time monitoring and feature extraction steps: deploy self-organizing neural network driven monitoring nodes, use biologically inspired swarm algorithm between nodes, according to the formula Realize data self-synchronization, is the node synchronization coefficient; γ is the inertia factor; is the set of neighboring nodes of node i; is the node connection weight; is the number of neighborhood nodes; develop terahertz wave pipeline imaging technology, penetrate the pipe wall to obtain three-dimensional information of internal defects, combine computer vision algorithm, according to the formula Identify crack types and trends, where F is the comprehensive characteristic value of the crack, L, W, and A are the length, width, and area of ​​the crack, respectively, and α, β, and δ are the characteristic weight coefficients; Multi-objective optimization and restoration decision-making steps: Establish a restoration decision-making model optimized by a quantum genetic algorithm, and use the superposition of quantum bits to search the solution space; comprehensively consider community impact, ecological restoration, and technical feasibility to construct a three-dimensional Pareto frontier; Dynamic repair process collaborative control steps: Design a repair parameter encoding method based on DNA computing, convert the construction parameter vector P into a DNA base sequence, and use the external magnetic field gradient to Control the trajectory of magnetic nanoparticles, and the two are coupled through a cross-scale model Collaboration, is the system state function, is the bio-physical synergy operator, is a DNA coding module, It is a magnetic fluid control module; Repair effect evaluation and continuous optimization steps: Build an evaluation system driven by cognitive computing, perceive public satisfaction through affective computing, and evaluate the repair effect in combination with knowledge graphs; develop pipeline self-healing enhancement technology, implant microbial flora in materials, and achieve autonomous repair and protection of cracks through biomineralization.

2. The multi-parameter collaborative control method for trenchless repair of drainage pipe networks in urban renewal according to claim 1 is characterized in that: Also includes: In the pipeline network multi-source heterogeneous data fusion modeling step, a pipeline network feature extraction technology based on topological data analysis is developed to capture the topological invariants of the pipeline network structure through persistent homology theory; Build a quantum secure communication channel and use quantum key distribution technology to ensure the security of data transmission.

3. The multi-parameter collaborative control method for trenchless repair of drainage pipe networks in urban renewal according to claim 1 is characterized in that: Also includes: In the multi-parameter real-time monitoring and feature extraction step, a bionic intelligent Daphnia robot is developed to simulate the movement and perception capabilities of Daphnia to achieve cable-free autonomous detection inside the pipeline network; a surface acoustic wave sensor array is designed to achieve non-contact structural health monitoring by detecting the propagation characteristics of acoustic waves on the surface of the pipeline network.

4. The multi-parameter collaborative control method for trenchless repair of drainage pipe networks in urban renewal according to claim 1 is characterized in that: Also includes: In the multi-objective optimization and repair decision-making step, quantum game theory is introduced to establish a multi-party interest coordination model to resolve the conflicts of interest among the owner, the construction party and the regulatory authorities; Develop a spatiotemporal value stream assessment method to quantify the impact of different repair timings on the value of the pipeline network throughout its life cycle and achieve dynamic timing optimization.

5. The multi-parameter collaborative control method for trenchless repair of drainage pipe networks in urban renewal according to claim 1 is characterized in that: Also includes: In the collaborative control step of the dynamic repair process, a brain-computer interface assisted construction system is constructed to realize the mind control of the repair equipment by reading the operator's brain wave signals; Design a shape memory alloy smart lining and use the shape memory effect of the material to achieve self-repair of the pipeline.

6. The multi-parameter collaborative control method for trenchless repair of drainage pipe networks in urban renewal according to claim 1 is characterized in that: The pipeline network multi-source heterogeneous data fusion modeling step also includes: realizing quantum entanglement synchronization of the pipeline network digital twin model, so that the physical pipeline network and the virtual model status are associated in real time; developing molecular imprinting sensing technology, and specifically detecting pollutants in the pipeline network through customized molecular recognition materials.

7. The multi-parameter collaborative control method for trenchless repair of drainage pipe networks in urban renewal according to claim 1 is characterized in that: The multi-parameter real-time monitoring and feature extraction steps also include: designing a pipeline material analysis system based on laser-induced breakdown spectroscopy to determine the composition and degree of corrosion of the pipe in real time; developing a microbial electrochemical sensor to monitor the health status of the pipeline using the current signal generated by the metabolic activity of microorganisms in the pipeline.

8. The multi-parameter coordinated control method for trenchless repair of drainage pipe networks in urban renewal according to claim 1 is characterized in that: The multi-objective optimization and restoration decision-making steps also include: constructing a quantum annealing optimized restoration solution generator to solve high-dimensional combinatorial optimization problems; developing an ecological footprint assessment module to quantify the impact of restoration projects on urban ecosystems and achieve green restoration decisions.

9. The multi-parameter collaborative control method for trenchless repair of drainage pipe networks in urban renewal according to claim 1 is characterized in that: The collaborative control step of the dynamic repair process also includes: realizing multi-robot collaborative repair based on swarm intelligence, coordinating robot cluster operations through pheromone simulation algorithms; developing an intelligent lighting control system for light-curing repair materials, and automatically adjusting lighting parameters according to material properties and environmental conditions.

10. The multi-parameter coordinated control method for trenchless repair of drainage pipe networks in urban renewal according to claim 1, characterized in that: The repair effect evaluation and continuous optimization steps also include: establishing an evaluation framework driven by a social-physical system, integrating the physical pipeline network status with social feedback information; developing a repair history database based on DNA storage, and utilizing the storage characteristics of DNA to achieve long-term data preservation.

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