210 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.

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 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 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 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 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.

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 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 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 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 invention relates to the technical field of urban sewage discharge management, and discloses a time-of-flight mass spectrometry-based rain and sewage mixing detection and traceability method, system and equipment for a drainage pipe network, a storage medium and a program product, which are used for solving the technical problems of high detection and traceability difficulty and low speed in the prior art. Comprising the following steps: acquiring a first detection result of volatile organic compounds of an in-situ time-of-flight mass spectrum at a first detection position along a drainage pipe network, inputting the first detection result into a trained mixed connection judgment model, and determining whether a mixed connection condition exists or not; if yes, according to the path trend information of the drainage pipe network, each upstream drainage pipe network detection well is searched, and at least one second detection position is obtained; acquiring a second detection result of the volatile organic compound of the in-situ time-of-flight mass spectrum of each second detection position; and inputting the second detection results into the trained mixed connection judgment model according to the sequence from the downstream to the upstream to perform mixed connection judgment, and searching the detection well with the mixed connection condition at the most upstream to obtain a mixed connection point.

The application discloses a kind of municipal engineering technical field's multi-source data fusion's urban drainage pipe network evaluation method, for evaluating the drainage quality of drainage pipe network in target area, the method includes obtaining the water quantity data of each water treatment system in the first period of target area, water quality data, climate data, tidal data, water quantity corresponding permanent population data, pollution emission background value and low concentration external water three-dimensional fluorescence spectrum.The application is fused to multi-source data, and the water quality and quantity data of influent of sewage treatment plant or pump station are cleaned, the type of influent and seepage external water in sewage treatment plant is distinguished, the problem that current sewage treatment system quality improvement and efficiency evaluation method only focuses on external water quantity evaluation but external water type is not clear is solved, and then the improvement direction of drainage pipe network quality improvement and efficiency is clear, it is helpful to clear the priority of mixed error connection, damage and external water inflow problem in the quality improvement and efficiency range of drainage pipe network.

The invention provides an intelligent grading identification method for a potential infiltration risk area of a drainage pipe network, and relates to the technical field of risk identification of the drainage pipe network. Establishing spatial relation mapping between triangular grid units of the surface water-underground water coupling model and pipe sections of the drainage pipe network model, calculating hourly liquid level difference time sequence data by utilizing underground water level time sequence data and corresponding pipe section liquid level time sequence data which are obtained through simulation calculation, and constructing risk indexes according to the hourly liquid level difference time sequence data; and then constructing an uncertainty scene sample set and respectively inputting the two models to obtain corresponding simulation calculation results, calculating to obtain a risk index corresponding to each pipe section, and judging a grading result of a potential infiltration risk area according to the risk indexes. Simulation calculation and intelligent diagnosis analysis are fused, and efficient identification of the potential infiltration risk area of the drainage pipe network is achieved on the premise that large-scale sensor deployment is not needed.

The invention relates to the technical field of drainage networks, in particular to a drainage network siltation risk assessment method based on a random forest algorithm, and the method comprises the steps: obtaining pipeline basic data, siltation detection data, land utilization data and social economic data of a drainage network; constructing a pipeline siltation regression model based on a random forest algorithm and obtaining a pipeline siltation degree; calculating the importance degree of input factors by using an OOB sample during training of the pipeline siltation regression model; calculating a pipeline risk factor according to the importance degree of the input factor, the value of the input factor and the pipeline siltation degree; fitting is conducted on the pipeline siltation degree and the pipeline danger factors through a logistic curve, and a curve fitting result is obtained; and calculating a pipeline risk factor corresponding to a preset pipeline siltation degree based on a curve fitting result, and obtaining a pipeline siltation risk assessment result according to the pipeline risk factor and a preset siltation risk grade. According to the method, multi-dimensional comprehensive assessment of the sedimentation risk of the drainage pipeline is realized, and the efficiency and accuracy of risk assessment are greatly improved.

The invention discloses a multi-source data fusion urban drainage pipe network evaluation method in the technical field of municipal engineering, which is used for evaluating the drainage quality of a drainage pipe network in a target area. The method comprises the following steps: acquiring inflow water quantity data, inflow water quality data, climate data, tide data, permanent population data corresponding to inflow water quantity, a pollution emission background value and a low-concentration external water three-dimensional fluorogram of each water treatment system in a target area in a first period; according to the invention, through multi-source data fusion, inlet water quality and quantity data of the sewage treatment plant or the pump station are cleaned, the types of the inlet water and the seepage water in the sewage treatment plant are distinguished, and the problem that the current quality and efficiency improvement evaluation method of the sewage treatment system only focuses on external water quantity evaluation, but the types of the external water are not clear is solved; therefore, the quality-improving and efficiency-improving transformation direction of the drainage pipe network is determined, and the priority of the problems of misconnection, damage and external water inflow in the quality-improving and efficiency-improving range of the drainage pipe network can be determined.

The present invention discloses a digital management system for drainage pipe network operation and maintenance data, which relates to the field of digital management and includes an operation and maintenance management center, in which a pipe network management module, a data acquisition module, a data analysis module, a data collaboration module and an operation and maintenance management module are provided; the pipe network management module is used to construct a three-dimensional spatial model of the pipe network and set an operation and maintenance management node; the data acquisition module is used to collect pipeline drainage data; the data analysis module is used to obtain pipeline load data at various positions and set drainage pipe links; the data collaboration module is used to set collaborative drainage information at the operation and maintenance management node according to the pipeline load data and the drainage pipe link; the operation and maintenance management module is used to optimize the collaborative drainage information, obtain operation and maintenance decision information, and adjust the pipeline flow according to the operation and maintenance decision information; the present invention improves the collaboration and rationality in the operation and maintenance process of the drainage pipe network.

This invention relates to the diagnosis of sedimentation in drainage networks, specifically providing an unmanned underwater vehicle (UUV) based maintenance decision-making method for drainage pipeline sedimentation diagnosis and waterlogging warning. The UUV of this invention consists of an integrated hull inside the pipeline and a manhole box. The integrated hull inside the pipeline includes a Doppler ultrasound module, a three-axis gyroscope, a high-definition infrared camera, a main controller, a deep learning development board, baffles, a cabin cover, a cabin, fins, towing rings, and a navigation interface. The Doppler ultrasound module, three-axis gyroscope, high-definition infrared camera, navigation interface, and deep learning development board are each connected to the main controller. The fins, towing rings, cabin cover, and baffles are connected to the cabin.

The invention relates to a collaborative correction method for water quality monitoring data of a drainage pipe network, and belongs to the field of intelligent water affairs. The method comprises the following steps: constructing a water quality monitoring node network diagram and an incidence matrix of monitoring nodes based on a geographic position relationship of a drainage pipe network, and then respectively calculating the correlation degree of monitoring data of three correlation indexes among the nodes by utilizing the flow velocity of the monitoring nodes, the historical concentration variation of pollutants and the physical distance among the nodes; constructing a collaborative monitoring model of the monitoring nodes; based on the collaborative monitoring model, establishing an association index influence degree optimization model in combination with the characteristic that the total amount of pollutants among the monitoring nodes is unchanged, and calculating the comprehensive association degree among the monitoring nodes of the drainage pipe network in real time; and the server corrects the monitoring value of each monitoring node based on the real-time monitoring data of each monitoring node of the drainage pipe network in combination with the real-time comprehensive correlation degree among the nodes. The accuracy of water quality monitoring data of the drainage pipe network can be effectively improved.

The invention relates to the technical field of gas monitoring, and discloses an RFID-based drainage pipe network harmful gas monitoring device and method, the device comprises an RFID reader-writer and a passive RFID gas sensing tag arranged on a target drainage pipe; the passive RFID gas sensing tag is communicated with the RFID reader-writer through a wireless signal; the passive RFID gas sensing tag chip receives the detection coding signal and the electromagnetic wave energy, converts the electromagnetic wave energy into electric energy, converts the detection coding signal into a gas detection instruction, and performs harmful gas detection on a target drainage pipe network to obtain a harmful gas concentration value of the drainage pipe network; the concentration value of the harmful gas in the drainage pipe network is converted into a feedback coding signal, the feedback coding signal is sent to the RFID reader-writer, and the RFID reader-writer converts the feedback coding signal into a monitoring result of the harmful gas in the drainage pipe network and displays the monitoring result. According to the invention, the concentration of harmful gas is accurately measured, and the layout cost is reduced.

This invention relates to an underground pipeline drainage monitoring system and method based on distributed fiber optic acoustic sensing. The system includes sensing optical fibers deployed along the underground water pipeline, distributed fiber optic acoustic sensing equipment, a preprocessing module for preprocessing received signals, a feature extraction module, a status recognition module, an anomaly tracing module, and a display and early warning module. This invention utilizes sensing optical fibers deployed along drainage manholes and pipe sections to acquire acoustic and vibration responses under different operating conditions during pipeline network operation. It automatically identifies and locates abnormal discharge behavior under rainless conditions, enabling long-distance distributed sensing along the drainage network and is suitable for long-term online monitoring of urban drainage networks.

The present application relates to sewage treatment technical field, especially sewage treatment intelligent monitoring method and system, including: through sensor obtains rainwater collection drainage node's sewage discharge, water quality parameter and drainage point coordinate, and carries out pretreatment. Based on real-time sewage discharge and pipeline design maximum flow rate, the real-time load rate is calculated, the water quality difference between adjacent nodes and the pipeline water quality difference are analyzed, the path distance is calculated combined with the drainage point coordinates, the exponential function is used to comprehensively evaluate the discharge suitability index, the comprehensive dynamic weight is formed by fusing the real-time load rate, and the A algorithm is used to obtain the optimal path. Based on the comprehensive dynamic weight processing conflict, the intelligent selection of the drainage path is realized, and the operation of the drainage network is optimized. The present application optimizes the selection of the discharge path by calculating the water quality difference between the drainage nodes and the pipeline water quality difference, thereby reducing the risk of pollutant diffusion, improving the sewage treatment efficiency and suitability.

1. The name of the design product: grab car (small). 2. The use of the design product: the design product is used for dredging and desilting of vertical shaft in urban drainage network. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view. 5. The bottom view of the design product is not easy to see or not visible when in use, omit the bottom view.

The application discloses a kind of urban drainage network optimization design systems, it is related to urban drainage optimization technical field, utilize data collection and pretreatment module, collect basic data, utilize parameter determination module, determine the intensity of rainfall, ground permeability, sewage concentration and the cleanliness of pipeline, utilize comprehensive evaluation optimization module, respectively calculate the drainage efficiency and cost benefit of output rainwater and sewage, combine the drainage efficiency and cost benefit of rainwater and sewage, total calculation and output the comprehensive evaluation result reflecting the sustainability of overall drainage system, and combined with the line graph drawn, detailed drainage network optimization design scheme is analyzed and formulated, the present application introduces the innovative means of fine parameter, comprehensive cost benefit analysis, systematized comprehensive evaluation and intelligent feedback mechanism, provides more scientific, comprehensive and efficient solution for the planning, design, operation and maintenance of urban drainage network.

The utility model discloses a water conservancy slope protection component, and particularly relates to the technical field of water conservancy slope protection, which comprises rhombic frames and connecting pieces for connecting two adjacent rhombic frames, a plurality of diversion trenches are formed in the bottom wall of the rhombic frame, a plurality of plugs are fixed to the bottom wall of the rhombic frame, connecting plates are fixed to the four corners of the outer side of the rhombic frame, and through holes are formed in the connecting plates; the connecting piece comprises a connecting base, two parallel inserting rods are fixed to the lower side of the connecting base, and the inserting rods penetrate through the corresponding through holes. A plurality of diversion trenches are formed in the bottom wall of the rhombic frame, a plurality of drainage ports are formed in the side wall of the rhombic frame, and the drainage ports and the diversion trenches form a three-dimensional drainage network, so that slope runoff can be quickly dispersed, the problem of soil loosening caused by rainwater accumulation is solved, and meanwhile, the risk of rotting of vegetation roots caused by local water accumulation of a traditional slope protection can be avoided.

This invention relates to the field of intelligent detection technology, and more specifically, to a method for detecting leakage in trenchless underground water supply and drainage pipe networks based on multi-data fusion. The method includes: Step 1: Deploying acoustic sensors at equal intervals along the pipe network; each acoustic sensor collects the acoustic time-domain signal generated by pipe leakage, and then calculating the spectral intensity of the acoustic time-domain signal at the pipe's characteristic frequency; Step 2: Calculating the cross-correlation function between two different acoustic sensors based on the spectral intensity; determining the acoustic delay of the acoustic time-domain signal between different acoustic sensors by finding the peak position of the cross-correlation function; Step 3: Calculating the location of the leakage point based on the acoustic delay and the principle of sound wave propagation; and assessing the leakage volume based on the location of the leakage point and combined with pipe usage data. This method, through multi-data fusion and intelligent analysis, effectively combines trenchless operation, high sensitivity, precise positioning, and scientific quantitative assessment.

The method comprises the steps that a basement structure roof area is comprehensively checked, cracks of all leakage points are accurately positioned and marked, a water seepage distribution diagram is drawn according to the leakage position, range and severity, and meanwhile a system connection plane graph is planned; secondly, a flow guide hole is drilled in the leakage crack according to the plane graph, and a channel is cut in a steel bar protection layer at the bottom of the structural top plate; then, a water absorption flow guide body is inserted into the flow guide hole, connected with a water diversion thin pipe through a quick connector, laid in the channel and communicated with a basement drainage system after gathering, and a concealed drainage network is formed; and finally, filling the flow guide hole and the channel with a blocking material, and recovering the top plate surface decoration layer after the material is cured. According to the method, active guiding and hidden discharging of leakage water are achieved, a leakage diffusion path is effectively cut off, structural damage and secondary leakage are avoided, and the durability and attractiveness of a waterproof system are improved.

The utility model discloses a zero direct discharge treatment device for sewage and wastewater of an urban rail transit station, which comprises a regulating reservoir connected with a station sewage and wastewater pipe and used for regulating the water quality and the water quantity of the station sewage and wastewater and conveying the regulated station sewage and wastewater to circulating biochemical treatment equipment; the circulating biochemical treatment equipment is arranged at the downstream of the adjusting tank and is used for carrying out nitrogen and phosphorus removal and impurity removal treatment on the sewage conveyed by the adjusting tank and respectively conveying the treated sewage and sludge to a clean water tank and a sludge storage tank; the clean water tank is arranged at the downstream of the circulating biochemical treatment equipment and is connected with a recycling pipe network system and a municipal rainwater drainage pipe network system through a reclaimed water recycling device; and the sludge storage tank is connected with the circulating biochemical treatment equipment and the regulating tank. The sewage treatment device has the beneficial effects that the sewage treatment efficiency is improved, and the sewage treatment rate reaches more than 95%; the treated water body is stable in performance, and the water resource utilization efficiency is high.

1. Name of the product in this design: Drainage Pipeline Monitoring Instrument. 2. Application of this design: This design is used for real-time water quality measurement, flood prevention and early warning, water pollution monitoring, and investigation of mixed rainwater and sewage connections. 3. The key design elements of this product are its shape, pattern, and their combination. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The invention discloses a deep tailing pit one-time filling vacuum preloading collaborative consolidation system and a construction method. The system is composed of a multi-layer rigid horizontal drainage network, a vacuum preloading sealing treatment device and a drainage network dynamic intelligent adjusting device in a cooperative mode. The drainage network is composed of geogrids and drainage plates fixed to the geogrids, and an anti-deformation horizontal drainage framework is formed. The dynamic adjusting device can monitor and actively adjust the elevation and form of each layer of drainage network in real time in the whole process of one-time filling of tailing mud and subsequent vacuum preloading through a vertical rod, a pull rope motor, a tension sensor and a lifting rope, and it is ensured that a drainage channel is always unblocked. The problems that after the deep pit is filled at a time, a drainage system is prone to failure, and consolidation is slow are solved, rapid, uniform and controllable efficient consolidation is achieved, the period is remarkably shortened, and the stability of a backfill body is improved.