316 results about "Drainage network" patented technology

The invention discloses an intelligent monitoring system for a municipal drainage pipe network, and particularly relates to the technical field of drainage pipe network monitoring. The node operation mode identification module carries out real-time classification and confidence evaluation on the operation state of the pipe network, constructs a multi-attribute pipe network weighted graph based on pipe diameter difference, gradient and confluence density, and extracts multi-scale features through graph Fourier transform. A hybrid anomaly detection link is constructed in combination with an LSTM self-encoder, an isolated forest model and chemical oxygen demand and turbidity water quality verification, and the problems that traditional single-index monitoring is prone to false alarm and missing alarm and inaccurate in positioning are solved; sensor data compensation is realized through cooperation with digital twinning, a rapid detection mode is started during rainstorm early warning, key nodes are processed preferentially, and drainage scheduling is controlled in a closed-loop mode; and target nodes which are easy to accumulate grease are screened based on pipe network topology connectivity, accumulation risks are predicted by fusing multi-sensor data, and a preventive clearing instruction is triggered.

This invention disclosed a full-space intelligent detection method and system for underground drainage networks, as well as storage media, including the following steps: image acquisition, intelligent image denoising, internal pipe defect segmentation, concealed defect detection around the pipe, 3D reconstruction with volume quantification, and pipeline life prediction. This invention introduced a bionic four-wheel-drive, all-terrain detection robot that can effectively navigate through mud and flowing water-challenges that hinder traditional detection devices. By leveraging deep learning algorithms as well as various techniques of computing vision, 3D reconstruction, and point cloud processing, the system thoroughly analyzed collected data to determine defect types and precise locations. Utilizing this analysis, precise location of different defect type and quantitative measurement of their dimensions can be realized. Based on the data analysis results, a deep-learning driven model was developed for predicting pipeline longevity to support maintenance staff with timely information on pipe defects and operational lifespan.

The invention discloses an intelligent discharge port dynamic regulation and control system and method based on multi-source time sequence fusion, and relates to the technical field of intelligent water affairs, and the system comprises a data collection module which is used for obtaining the multi-source data of a target area in real time; the space-time fusion module is used for mapping the meteorological radar data to the topological space of the drainage pipe network through a space-time alignment encoder, dynamically fusing the meteorological radar data, the surface runoff sensor data and the historical drainage data by adopting a multi-head attention mechanism, and generating a space-time fusion tensor; the prediction model module is used for constructing a TCN-LSTM hybrid model, taking the space-time fusion tensor as input and taking future drainage flow as output; and the dynamic regulation and control module is used for optimizing the gate opening degree and the pump station power control sequence in a rolling manner based on a model predictive control algorithm, and performing dual-target optimization by combining real-time electricity price data and overflow risks. According to the system, the prediction precision of the drainage flow can be improved, and double-target balance of the overflow risk and the energy consumption cost can be achieved.

The invention discloses an urban life body full-cycle monitoring system based on a digital twinborn technology, relates to the technical field of urban governance, integrates multi-source data such as GIS data, remote sensing information, surface permeability data and an underground drainage pipe network structure, quantifies a flood high-risk area, and provides an urban life body full-cycle monitoring system based on the digital twinborn technology. The AI flood prediction module deduces the ponding range and the drainage capacity under different rainfall situations by adopting extreme weather analogue simulation based on a historical rainfall trend, a current meteorological condition and a drainage network state, and dynamically adjusts a flood diffusion trend prediction model, so that the flood risk identification is more accurate; the intelligent emergency scheduling module automatically matches flood control resources, combines flood high-risk areas, ponding point locations and traffic flow analysis, optimizes a drainage pump station start-stop strategy, remotely regulates and controls an underground drainage gate, dynamically adjusts the overflow adjustment capability of a sewage treatment plant, and optimizes an emergency risk avoiding route in combination with an intelligent traffic management system. And the accuracy and the execution efficiency of the flood control scheduling scheme are improved.

The invention relates to the technical field of urban drainage network optimization design, and discloses a BIM model-based urban drainage network optimization design method and system, and the method comprises the steps: collecting multi-source hydrological data, and carrying out the preprocessing of the multi-source hydrological data; modeling the drainage system into a space-time diagram structure, and predicting the bearing capacity of the drainage system; an overflow risk assessment model is constructed, key influence factors are identified, node risk degrees are quantified, and high-risk areas are identified; constructing a fault model based on a causal graph, identifying a causal chain of an overflow event, and realizing crossing from correlation analysis to causality understanding; performing drainage system parameter optimization by using the BIM model; by fusing multi-source data analysis, a time-space diagram neural network and a causal inference technology, dynamic bearing capacity prediction, accurate risk assessment and abnormal source overflow diagnosis of the drainage system are realized.

The invention discloses an urban drainage network overflow risk intelligent regulation and control system and method based on the Internet of Things, and relates to the technical field of urban drainage network monitoring, and the system comprises an Internet of Things sensing collection module which is used for fusing sensing data and carrying out the preprocessing, and obtaining an original data flow; the real-time diagnosis and early warning module is used for calculating the original data flow based on a nonlinear dynamic algorithm to obtain a fluid chaos degree index, and performing judgment in combination with a preset early warning threshold to obtain an early warning signal; the risk causal deduction module is used for fusing a graph neural network and a causal discovery algorithm and analyzing a fluid chaos degree index and an early warning signal to obtain a risk propagation space-time atlas; and the cooperative game decision execution module is used for analyzing the risk propagation space-time atlas by using a multi-agent adaptive game algorithm to obtain and execute a cooperative control instruction. According to the method, the Internet of Things, nonlinear dynamics, causal reasoning and the game theory are fused, and the problem of urban drainage pipe network overflow regulation and control is effectively solved.

The invention discloses an urban distribution network and flood drainage water network risk-dependent rainstorm-induced accident situation prediction method, which comprises the following steps: S1, obtaining related data of an urban distribution network and a flood drainage water network at a t moment, and solving urban inland inundation ponding distribution in a rainstorm weather, based on the longitude and latitude information of the power equipment, mapping the solved urban inland inundation water distribution to the submerging depth of the power equipment; s2, judging whether the large-area power failure occurs or not according to the critical condition for causing the large-area power failure; and S3, considering uncertain parameters causing urban waterlogging and power outage, predicting the probability of occurrence of the power outage through a power outage probability density calculation model, and performing rolling correction on a model power outage risk distribution result by using a multi-source data driving method.

The invention provides an urban drainage pipe network flow prediction method based on an improved Transform neural network model, and the method comprises the steps: S1, simulating the rainfall processes under different conditions through constructing a rainfall parameterization engine, and generating a rainfall data set; and S2, calculating the corresponding discharge port flow according to the rainfall data by using the calibrated physical model to form a flow data set. S3, preprocessing the data, including constructing a data set, deleting invalid data, and supplementing features and labels to form a training and verification data set; and S4, an RO-former model is constructed, the model adopts an encoder-decoder architecture, and rainfall and flow data are processed through a dynamic mask and a cross attention mechanism. And S5, training and optimizing the model through the loss function to obtain a model which can be used for predicting the urban drainage network flow in real time. The method improves the accuracy and efficiency of urban drainage pipe network flow prediction, and is of great significance to urban waterlogging early warning and drainage management.

The invention discloses a regional waterlogging early warning method and device based on a multi-water professional model and a medium, and belongs to the technical field of hydrodynamic models. The method comprises the following steps: selecting a research area, and collecting meteorological data, geographic data and hydrological data of the research area; constructing four basic models of the research area based on the data, and coupling the four basic models to construct a waterlogging forecast simulation overall model; importing an input value of historical measured data of the research area into the waterlogging forecasting simulation overall model to output calculation data, and determining parameters of the waterlogging forecasting simulation overall model when the deviation between the calculation data and the output value of the historical measured data meets the requirement; and based on preset rainfall data, performing regional waterlogging forecasting simulation through the waterlogging forecasting simulation overall model, and outputting a drainage pipe network water flow condition, an open channel water flow condition and a waterlogging ponding submerging condition. According to the method, the multi-water professional model is integrated, and the technical effect of co-simulation of the waterlogging evolution process is achieved.

The invention relates to the technical field of intelligent city management, in particular to an intelligent drainage pipe network management system which comprises a drainage pipe network data monitoring module, a local health assessment module, an intelligent flow adjustment module, an abnormal fault recognition module and an operation state optimization module. According to the method, through comprehensive monitoring and time sequence analysis of the water flow speed, the pipeline pressure, the fluid temperature, the pipe wall vibration frequency and the data transmission state, the accuracy of data integrity evaluation is improved, the stability and reliability of data are enhanced, and the analysis can accurately reflect the pipe network state; the early warning capability of the health state of a local pipeline is improved, the pertinence of flow regulation and control is optimized by calculating the flow distribution ratio and recognizing the flow difference ratio of adjacent pipelines, and meanwhile, the refinement of fault diagnosis is improved by comprehensively analyzing abnormal characteristics and fault data, so that the operation state of a pipe network is optimized, and the fault diagnosis efficiency is improved. And the overall management precision and the operation stability are enhanced.

The invention relates to the technical field of foundation pit drainage, and provides a deep foundation pit drainage system and a use method.The method comprises the steps that a1, an annular dewatering well is arranged on the periphery of a deep foundation pit, and underground water is collected and lowered through the annular dewatering well; a2, a drainage network in the foundation pit is established to eliminate surface rainfall and seepage water; a3, based on a preset water level control strategy, a drainage pumping device is started to drain the collected underground water away from the foundation pit; a4, hydrological changes inside and outside the deep foundation pit are monitored, and operation parameters of the dewatering well and the drainage system are adjusted in time so that the safe water level state in the deep foundation pit can be maintained; through the scheme of the embodiment of the invention, the problem of how to effectively prevent underground water from seeping into the foundation pit in a high-water-level area by the deep foundation pit drainage system can be solved.

The invention provides a method and system for determining the scale of an initial rain regulation and storage pond based on the rainfall session interception rate. The method comprises the following specific steps: screening out typical annual 5-minute step rainfall data; the method comprises the following steps: establishing a relation curve of rainfall capacity and a closure rainfall accumulated session frequency difference value, selecting an inflection point of the curve, and determining the rainfall capacity corresponding to the inflection point as a closure standard recommended value; according to typical annual 5-minute step rainfall data, typical session rainfall with representativeness is screened to serve as design rainfall; constructing a numerical model of the drainage network of the research area; simulating water catchment time t1 required for collecting all initial rainwater; and obtaining the design scale of the first rain storage pond. The technical defects existing in existing first rain storage pond scale argumentation are overcome, and the reasonability of first rain storage pond scale argumentation is improved.

The invention relates to the technical field of electronics, and discloses a drainage pipe network pollutant tracing method, device and equipment, a medium and a program product. According to the method, the map similarity between a first three-dimensional fluorescence spectrum map corresponding to a first water sample of a target node and a second three-dimensional fluorescence spectrum map corresponding to each upstream pipe network node is calculated; and determining at least one target upstream pipe network node in the plurality of upstream pipe network nodes based on the map similarity, and determining pollution source information of abnormal water in a target node according to first water quality data of the target upstream pipe network node and second water quality data on a sewage flowing path between the target upstream pipe network node and the target node, the advantages of high sensitivity, rapid detection and the like of the three-dimensional fluorescence spectrum technology are utilized in the pollutant traceability process, and efficient and accurate traceability of pipe network pollutants is achieved.

The invention discloses an urban drainage network optimization design system, and relates to the technical field of urban drainage optimization, a data collection and preprocessing module is utilized to collect basic data, a parameter determination module is utilized to determine the rainfall intensity, the ground permeability, the sewage concentration and the pipeline cleanliness, and a comprehensive evaluation optimization module is utilized to optimize the urban drainage network. The drainage efficiency and cost effectiveness of rainwater and sewage are calculated and output respectively, a comprehensive evaluation result reflecting the sustainability of the whole drainage system is calculated and output in combination with the drainage efficiency and cost effectiveness of rainwater and sewage, and a detailed drainage network optimization design scheme is analyzed and formulated in combination with the drawn line graph. According to the method, innovative means of refined parameters, comprehensive cost-benefit analysis, systematic comprehensive evaluation and an intelligent feedback mechanism are introduced, and a more scientific, comprehensive and efficient solution is provided for planning, design, operation and maintenance of the urban drainage network.

The invention provides a drainage pipe network water quality prediction method based on deep learning, and belongs to the technical field of drainage pipe network water quality monitoring and prediction. The technical problems of poor real-time performance, high labor cost and low efficiency due to the fact that the conventional manual sampling and measuring method is still adopted for daily monitoring and management of the water quality of the urban drainage pipe network at present are solved. According to the technical scheme, the method comprises the steps of S1, determining input data and output data of a drainage pipe network water quality prediction model; s2, data preprocessing; s3, a prediction model is selected, model parameters are set and adjusted, the pump station-sewage treatment plant pipe network water quality process is simulated, and the prediction performance of the model is evaluated; s4, speculating key pump station water quality indexes influencing the biodegradability of the inflow water of the sewage treatment plant. The method has the beneficial effects that the key nodes influencing the inflow water quality of the sewage treatment plant are screened out through deep learning, and suggestions are provided for urban drainage monitoring management subsequently.

The invention discloses a dynamic control method and platform for intelligent intercepting and discharging equipment, and relates to the technical field of intercepting and discharging control, and the method comprises the steps: analyzing drainage parameters of multi-stage drainage equipment, and constructing a multi-stage drainage network; connecting a multi-source acquisition channel; based on the multi-stage drainage network, drainage demand prediction is carried out through multi-source collection data, and predicted drainage information is obtained; according to the prediction information, self-adaptive demand parameters are extracted through self-adaptive index parameters; taking the self-adaptive demand parameter as an index, inputting the self-adaptive search model to carry out control parameter search, and obtaining a dynamic control parameter; and utilizing the dynamic control parameters to carry out closure and drainage control on the multi-stage drainage equipment. The technical problems that a closure drainage system is poor in adaptability to complex environment changes and inaccurate in drainage demand prediction are solved, and the technical effects that drainage control is dynamically conducted according to weather changes, drainage demand prediction accuracy is improved, and waterlogging of farmland is avoided are achieved.

The invention relates to the field of urban drainage, and discloses an urban drainage pipe network operation safety assessment method and system, and the method comprises the steps: obtaining pipe network operation state data and pipe network physical structure data, and constructing a drainage pipe network GIS database; acquiring a pipeline defect detection image based on CCTV television detection and QV video detection technologies, and importing the pipeline defect detection image into a GIS system; performing model calibration dynamic simulation on the constructed drainage hydraulic model based on the data in the GIS and the real-time operation monitoring data of the drainage pipe network to obtain drainage pipe hydraulic data; performing defect evaluation on the sewage pipe network, the rainwater pipe network and the confluence pipe network by adopting different safety level models based on the drainage pipe hydraulic data; based on the corresponding defect probability, the risk is divided into a first-level risk, a second-level risk and a third-level risk; analyzing the pairwise variable relationship to find key indexes influencing the risk; and matching a corresponding coping strategy based on the key index influencing the risk, and displaying the coping strategy.

A monitoring point layout method for defect diagnosis of a drainage pipe network comprises the following steps: based on pipe network geographic information system data, constructing a grouping topology table through topological structure extraction and connectivity analysis, layering nodes according to a flow collection path to form a flow-closed upstream and downstream hierarchical relationship, and combining point backtracking, collection and upstream and downstream query in a group to obtain a flow-closed upstream and downstream hierarchical relationship; point locations in each layer of node group are adjusted to ensure the flow closeness; and with the fewest monitoring points and the longest covered pipe diameter as targets, an optimal node group combination is screened through an optimization model, and a final monitoring point position is generated by fusing a pipe diameter threshold value and environmental factors. According to the method, through a flow closing algorithm and a hierarchical optimization mechanism, the problems of low efficiency, insufficient coverage and flow closing deficiency of traditional manual layout are solved, automatic and high-precision point location layout is realized, the timeliness and accuracy of defect diagnosis are remarkably improved, meanwhile, the monitoring cost is reduced, and systematic technical support is provided for operation and maintenance of the urban drainage network.

The invention provides a dredging and blocking combined salinized soil roadbed novel composite liner separation layer and a roadbed structure. The composite liner separation layer comprises a first layer of non-woven geotextile, an upper layer of three-dimensional geotextile drainage network, a second layer of non-woven geotextile, a polymer modified bentonite particle layer, a third layer of non-woven geotextile, a lower layer of three-dimensional geotextile drainage network and a fourth layer of non-woven geotextile which are sequentially arranged from top to bottom; the roadbed structure comprises a pavement structure layer, a roadbed, a composite liner partition layer and an embankment which are sequentially laid from top to bottom, and slope protection ways and drainage ditches are arranged on the two sides of the roadbed structure. Through the bentonite particle impermeable layer in the composite liner separation layer, infiltration of surface water can be prevented, and rising of capillary water and migration of water and salt under the action of temperature gradient can also be blocked; slope protection and drainage ditches are designed on the two sides of the roadbed, smooth salt and water drainage of the roadbed is guaranteed, and the risk of roadbed settlement caused by migration and uneven distribution of water and salt in the salinized soil roadbed is reduced.

The invention relates to the technical field of data processing, and discloses a drainage pipe network rain and sewage mixed connection tracing and spatial positioning method for a micro monitoring station network, which comprises the following steps: defining an upstream convergence pipe network range of each micro monitoring station according to a flow direction connection relationship of a drainage pipe network and layout nodes of the micro monitoring stations, establishing a unique mapping relation library between each pipe section and the corresponding multi-stage monitoring topological sequence; obtaining water quality and water level data of a monitoring station, intercepting an analysis time period, and identifying a target monitoring topological sequence which generates a response currently in the mapping relation library based on a time-space propagation association attribute of data between stations; locking an isomorphic mapping candidate pipe section set corresponding to the sequence, and constructing a pollutant source emission inversion model of each candidate pipe section according to a pipe network fluid transport diffusion mechanism; and calculating the fitting deviation degree of the source hypothesis of each candidate pipe section to the monitoring data by using the model, and selecting the pipe section with the minimum deviation degree as a positioning result.

The present invention proposes a method and system for automatically building a digital twin model of a drainage network based on UE5, which relates to the field of digital twin application technology of municipal drainage network. The method includes: obtaining drainage network census data and converting the drainage network census data format; the drainage network census data includes pipeline JSON data and pipe point JSON data; using the converted data to establish a drainage network model library and a drainage network material library in UE5; creating a pipeline blueprint class and a pipe point blueprint class in UE5; creating an editor tool blueprint in UE5, and using the editor tool blueprint script to automatically build pipeline and pipe point digital twin models. The present invention realizes the seamless connection between drainage network modeling and business applications, and has the advantage of high-fidelity visualization; it provides a method for realizing hot update of model data on the application platform through interface calls, which is conducive to the application and development of digital twin technology in the field of municipal drainage network.

The invention provides a drainage well lid bidirectional positioning matching method and system based on target detection and spatial feature index, and aims to solve the problems that unnumbered well lids are difficult in field positioning and low in file association efficiency. The method comprises the following steps: acquiring a manhole cover image and inertial sensor data through a mobile terminal; an improved lightweight target detection model MobileMC-Net is utilized to realize high-precision identification and visual feature extraction of a well lid area; synchronously fusing GPS coordinates and inertial sensor data to construct a dynamic spatial feature index; on the basis, the method is realized through a two-way matching algorithm: forward matching: associating electronic archive information according to visual features and real-time positions of field unnumbered well lids; and reverse positioning: according to the historical coordinates in the electronic file, navigating to the position of the target well lid in combination with the real-time inertial data. The method breaks through a traditional manual verification mode, remarkably improves the operation and maintenance efficiency of the well lid, and is particularly suitable for rapid recognition and file management of hidden well lids of an urban drainage pipe network.

The utility model discloses a rain and sewage mixing detection experiment device applicable to a drainage network. The rain and sewage mixing detection experiment device comprises a first water storage tank, a second water storage tank, a third water storage tank and a drainage network header pipe, the drainage network header pipe is provided with a plurality of inspection wells; a plurality of first water inlet branch pipes corresponding to the inspection wells are formed on the first water inlet pipe; a plurality of second water inlet branch pipes corresponding to the inspection wells are formed on the second water inlet pipe; and a plurality of third water inlet branch pipes corresponding to the inspection wells are formed on the third water inlet pipe. According to the rain and sewage mixing detection experiment device suitable for the drainage network, by simulating different water inlet situations, the change rule of operation of a main pipe of the drainage network is obtained, and the change rule detected and summarized by the experiment device is applied to actual water quality detection and hydraulic condition detection of the main pipe of the drainage network; therefore, whether the mixed connection condition exists in the main pipeline of the drainage network or not can be more accurately judged, and then corresponding measures are taken in time according to the detection result to ensure smooth operation of urban rainwater pipelines and sewage pipelines.

The invention provides a short-distance coal seam group Y-shaped ventilation gas extraction method, which belongs to the technical field of coal mining, and comprises the following steps: firstly, arranging a main drill hole vertical to a coal seam and branch drill holes extending to upstream and downstream at an angle of 45 degrees to form a Y-shaped three-dimensional extraction network; installing a gas concentration monitoring sensor network, and setting monitoring points to collect real-time data; constructing a gas concentration adjusting buffer system and an intelligent mixed gas distribution device, and maintaining the concentration of extracted gas to be 30-45%; establishing a predictive control model based on a long short-term memory neural network, predicting a gas emission rule in advance and dynamically adjusting extraction parameters; a gas concentration grading utilization system is implemented, and gas with different concentrations is guided into the corresponding utilization system; a gas extraction intelligent monitoring platform is deployed to realize remote monitoring and fault early warning; the technical problems that in the coal seam group gas extraction process, the extraction concentration is unstable, and prediction control is difficult are solved.

The invention belongs to the technical field of building design, and particularly discloses a school building design method capable of converting space attributes, which comprises the following steps: designing a structure-equipment integrated core tube and a corresponding modular space, and constructing a space division system; a subsystem design strategy is utilized to construct a modular water treatment unit, an elastic drainage network, a distributed microclimate unit, an energy routing center, structure-equipment integration, an intelligent skin system and a core tube structure monitoring system; an adaptive transformation mechanism is constructed to ensure the flexible conversion capability of the building space in the whole life cycle; an integrated intelligent control center is designed, intelligent management and optimization of the building space are achieved, and finally school building design is completed. The method solves the problems that an existing building design method can only meet planning at the initial stage of design and lacks elasticity of later-stage transformation, so that when new requirements of use functions occur, the building cannot be transformed according to needs or cannot be transformed by considering existing fire protection specifications and the like.

The invention relates to the technical field of soil treatment, in particular to an integrated saline grainfield soil improvement and remediation method. According to the method, precise irrigation, concealed pipe drainage, salt-tolerant crop planting and bioremediation technologies are comprehensively applied, and systematic treatment of the salinized soil is achieved. Precise irrigation dynamically regulates and controls the leaching depth and frequency on the basis of real-time soil salinity and moisture data, the underground water level is intelligently controlled in combination with an underground pipe drainage network, salt accumulation is effectively reduced, and water resource waste is avoided; according to the salt-tolerant crop and green manure rotation mode, salt damage is reduced through plant salt absorption and root system nitrogen fixation, soil organic matter accumulation and microbial community reconstruction are promoted through application of a microbial agent and biochar, and a sustainable soil improvement mechanism is formed. The intelligent monitoring system integrates multiple types of sensors, collects key indexes such as salinity, nutrients and pH values in real time, predicts the salinization trend and regulates and controls irrigation, fertilization and drainage equipment in a linkage mode, full-process automatic management is achieved, and the management precision and efficiency are remarkably improved.

The invention relates to the technical field of hydraulic engineering, and discloses a drainage pipe network data detection method and device based on a graph theory, and the method comprises the steps: constructing a target drainage pipe network directed graph based on the connection information of pipe sections; performing pipe section missing node completion on the known pipe section node data by using the target drainage pipe network directed graph; constructing a current drainage pipe network directed graph by using the known pipe section node data after the completion of the pipe section missing nodes; performing pipe section topology detection on the current drainage pipe network directed graph to obtain pipe section topology detection data; performing reverse slope pipe section classification identification on the current drainage pipe network directed graph to obtain reverse slope pipe section detection data; and determining a drainage pipe network data detection result based on the topology detection data and the reverse slope pipe section detection data. According to the invention, the accuracy and efficiency of target drainage pipe network data quality inspection are greatly improved, and the situation of missing detection or false detection of drainage pipe network data is avoided.

The invention discloses an intelligent vertical shaft anti-floating pile system and a construction technology thereof, and belongs to the field of vertical shaft drainage, and the intelligent vertical shaft anti-floating pile system comprises a vertical shaft anti-floating pile system which is used for bearing pulling resistance generated by underground water and internal and external access of the underground water; the sensing monitoring system is used for anti-floating pile stress strain monitoring, anti-floating pile displacement monitoring and underground water level monitoring; the water pumping and draining system is used for pumping and draining underground water; the data system is used for carrying out data acquisition, transmission and processing on the shaft anti-floating pile system and underground water; the control system is used for controlling the water pumping and draining system to pump and drain water. According to the hollow anti-floating pile, the condition of the pile body is monitored in real time through various sensors, the drainage pipe and the anti-floating pile are communicated to form a drainage network, underground water is pumped and drained in time through the cooperation of the water pump, and it is guaranteed that the vertical shaft meets the anti-floating requirement under the condition that the space utilization rate of the vertical shaft is increased.

The invention discloses a simulation forecasting method suitable for urban rainstorm waterlogging in areas lacking pipe network data, which is characterized in that for areas without pipe network data, rainwater inspection well information is acquired by calling a Baidu map, pipeline drainage flow is generalized based on a rainwater well equivalent drainage method, and for areas with pipe network data, pipeline drainage flow is generalized by calling a Baidu map. Constructing a drainage pipe network model based on a one-dimensional Saint-View equation by adopting a finite difference method; then, constructing a hydrodynamic model, coupling a rainwater well equivalent drainage method and a drainage pipe network model with an FVCOM model, simulating an earth surface ponding evolution process, and obtaining a rainstorm waterlogging data set; and training and establishing a water depth prediction model based on the obtained data, then predicting the water depth of each prediction point after a specific time in an actual rainfall event, and giving an alarm in advance when a waterlogging early warning range is reached. According to the method, the submerged water depth of a waterlogging-prone point can be predicted in advance, waterlogging forecasting of a city lacking pipe network data can be achieved, and rainstorm disaster loss is greatly reduced.

The present invention belongs to the technical field of urban drainage network generation, and discloses a method and system for generating an urban drainage network based on remote sensing images, including: obtaining multi-source information of a target area; using a drainage network visual model to identify the satellite remote sensing image to obtain a network topology structure diagram of the drainage network; wherein, the vertices in the network topology structure diagram of the drainage network represent well points in the drainage network, and the edges represent pipelines connected between the well points; associating the multi-source information and the network topology structure diagram through geographical coordinates, and storing the associated multi-source information and network topology structure diagram in a GIS database; calculating the pipe crown cover depth, slope and diameter of each pipeline in the network topology structure diagram, and storing the calculation results in the GIS database as the attribute information of the corresponding pipeline, thereby completing the generation of the drainage network. The present invention realizes the rapid, efficient and low-cost acquisition of the layout and attributes of the drainage network.