Dynamic drainage system of municipal sewage pipe network and control method

Abstract

The invention relates to the technical field of urban drainage management, and discloses a municipal sewage pipe network dynamic drainage system and a control method, and the system comprises a sewage pipe network, a central controller, a pump station, a valve and an edge control terminal; the control method comprises the following steps that real-time data are obtained from a plurality of sensors arranged in a sewage pipe network, the plurality of sensors comprise a flow sensor, a water level sensor, a pressure sensor and a rainfall sensor, and the obtained real-time data comprise the sewage flow, the water level, the pipeline pressure and the external rainfall inflow in the pipe network; based on the collected real-time data, dynamic hydraulic modeling is carried out on the sewage pipe network through a central controller, a mathematical model for describing the hydraulic state change of the pipe network is established, and the mathematical model comprises spatio-temporal evolution of flow, water level and pressure. According to the invention, by constructing a drainage scheduling mechanism based on real-time data modeling and edge control linkage, dynamic adjustment and stable control of the running state of the sewage pipe network are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of urban drainage management, and in particular to a dynamic drainage system and a control method for a municipal sewage pipe network. Background Art

[0002] With the rapid expansion of cities and the frequent occurrence of extreme weather events, the operational pressure on municipal drainage systems continues to increase. Especially during heavy rainstorms, peak drainage times, and uneven mainline operation, pipeline networks are prone to problems such as overpressure, backwatering, and sewage overflows. In severe cases, these problems can even impact commuting and urban safety. To ensure smooth sewage discharge and stable drainage scheduling, an intelligent drainage control solution with real-time response and dynamic adjustment is urgently needed.

[0003] Existing technologies often implement drainage control by setting simple pump start sequences and regular valve openings, often based on empirical rules. These solutions offer simple structures, rapid deployment, and can meet basic drainage requirements under routine low-flow conditions. They also offer a certain degree of drainage efficiency in areas with light rainfall loads. Data collection during system operation is primarily based on manual inspections or scheduled monitoring, combined with low-frequency remote control equipment. This offers advantages in maintainability and low cost.

[0004] However, it must be pointed out that this type of control approach fails to account for the real-time evolution of hydraulic conditions within the system. Dispatching instructions lack specificity and lag in response. Pumping stations and valve operating units often operate independently, often operating independently. Sudden flow changes often result in delayed system response, making high-water backflow a common occurrence. Sparsely distributed sensors result in delayed information, making it difficult to detect local anomalies. Furthermore, if platform communication is interrupted, the executing equipment cannot receive instructions, and without on-site backup logic, drainage operations come to a standstill. Summary of the Invention

[0005] In response to the shortcomings of the existing technology, the present invention provides a dynamic drainage system and control method and system for municipal sewage pipe networks, which solves the problems of delayed scheduling response, discontinuous data collection, lack of control coordination and equipment failure caused by communication interruption in the existing drainage system.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a dynamic drainage system for a municipal sewage pipe network, comprising: A sewage pipe network is used to carry and transport urban sewage. The sewage pipe network is equipped with multiple sensors along its route. The multiple sensors include flow sensors, water level sensors, and pressure sensors, which are used to collect key parameters such as sewage flow, water level, pressure, and external rainfall inflow in real time; a central controller, respectively connected to the plurality of sensors for receiving and processing real-time data collected by the plurality of sensors, and constructing a dynamic hydraulic model of the sewage pipe network based on the real-time data, and further generating drainage scheduling control instructions according to the model analysis results; The pump station is deployed in the sewage pipe network and is used to receive control instructions sent by the central controller and adjust the operating status of the pump station accordingly to dynamically adjust the sewage flow rate and direction; Valves are installed at key nodes in the sewage network to receive opening control instructions from the central controller and adjust the valve opening to achieve precise control of the drainage capacity of the pipeline; The edge control terminal is connected to the pump station and the valve respectively, and is used to receive the dispatching control instructions issued by the central controller and execute them in real time.

[0007] A method for dynamic drainage control of a municipal sewage network is also provided, comprising the following steps: Acquire real-time data from multiple sensors deployed in the sewage pipe network, including flow sensors, water level sensors, pressure sensors, and rainfall sensors. The acquired real-time data includes sewage flow, water level, pipe pressure, and external rainfall inflow within the pipe network; Based on the collected real-time data, the central controller conducts dynamic hydraulic modeling of the sewage pipe network and establishes a mathematical model that describes the changes in the hydraulic state of the pipe network. The mathematical model includes the temporal and spatial evolution of flow, water level and pressure. Analyzing the current hydraulic state of the pipe network based on the hydraulic modeling, and generating corresponding drainage scheduling control instructions, wherein the scheduling instructions include power adjustment instructions for the pump station and valve opening adjustment instructions; The generated drainage scheduling control instructions are transmitted to the pumping station and valves through the edge control terminal. The pumping station and valves adjust their own operating status according to the instructions, and adjust the sewage flow rate, flow direction and drainage capacity of the pipeline.

[0008] Preferably, the real-time data acquisition comprises the following steps: Multiple sensors are installed at typical operating nodes of the sewage network, including junctions, pump station forebays, trunk and branch pipe connections, and terminal outlets. Collect the instantaneous flow, water level and internal pressure values ​​of each node within the preset sampling period; Process the external rainfall intensity and duration information received by the rainfall sensor and convert it into rainfall intensity input per unit area; The collected data is sent to the central controller through the communication network, and timestamp synchronization and outlier filtering are performed.

[0009] Preferably, the dynamic hydraulic modeling comprises the following steps: The one-dimensional unsteady flow model of the sewage pipe network is carried out, and the shallow water equation is used to describe the continuity and momentum transfer relationship of the fluid in the pipe in the time and space dimensions; The modeling process adopts finite difference method or finite volume method for discrete solution, taking into account the influence of pipeline slope, cross-sectional shape and friction resistance; The dynamic hydraulic model satisfies the following continuity control equation: Among them, A(x,t) is the flow area at a certain cross section, Q(x,t) is the volume flow rate, q l (x,t) is the lateral inflow rate per unit length.

[0010] Preferably, the mathematical model comprises the following steps: The hydraulic response characteristics of different areas of the pipe network are represented by node state variables, including flow, water level and pressure. The above state variables are input into the controller to establish a state-response prediction relationship; The mathematical model uses a multivariable nonlinear state space expression to describe the sewage flow evolution process; The model includes the following momentum equation expression: Among them, h(x,t) is the water level, S f is the friction slope, g is the acceleration due to gravity, A(x, t) is the flow area at a certain cross section, and Q(x, t) is the volume flow rate.

[0011] Preferably, the hydraulic state includes the following steps: Comparison between the real-time water level height at each node of the sewage pipe network and the design critical water level; The deviation between the internal pressure of the pipe and the threshold pressure; The degree of synchronization between the drainage flow rate change trend and the flow regulation of the pumping station; The pressure loss response caused by the head difference at the valve and the opening adjustment.

[0012] Preferably, the drainage scheduling control instruction includes the following steps: Output pump frequency control signal for the pump station, increasing step by step according to power limit; Set the valve output opening percentage and make dynamic fine-tuning according to the current node pressure; Taking into account the overall drainage balance of the system, multiple pumping stations and valve nodes are coordinated and controlled to achieve balanced discharge of the entire system; when an overpressure trend is detected, the priority emptying command is automatically triggered and more discharge channels are opened locally.

[0013] Preferably, the opening adjustment instruction includes the following steps: Calculate the target valve opening according to the deviation between the current node water level and the target drainage capacity; Convert the calculation results into electronic control execution signals, taking into account the execution lag time and the mechanical inertia characteristics of the valve; If there are multiple adjacent valves in linkage, the opening of the most downstream valve shall be adjusted first; The valve response behavior is corrected through a continuous feedback mechanism.

[0014] Preferably, the edge control terminal includes: A data receiving module is used to receive control instructions from a central controller; An execution control module, used for converting control instructions into pump frequency adjustment signals and valve opening signals; Local data cache module, used to store the previous cycle instructions when communication is interrupted to ensure control continuity; The status reporting module is used to transmit the current pump station and valve execution status back to the central controller to achieve remote monitoring and diagnosis.

[0015] Preferably, the operating state includes the following steps: The operating status of the pump station includes current power output, start / stop status, and operating frequency; The operating status of the valve includes the current opening value, opening and closing direction and response delay; The running status is updated synchronously with the sensor acquisition status and used as the input variable of the scheduling strategy for the next period.

[0016] In summary, this application includes at least one of the following beneficial technical effects: 1. This invention utilizes dynamic hydraulic modeling technology based on shallow water equations to continuously simulate and predict the flow rate, water level, and pressure of the sewage network in real time, achieving proactive control over the system's operating status. Compared to existing control solutions that rely on fixed thresholds, this solves the problem of being unable to adapt to complex and changing drainage environments and improves the overall scheduling sensitivity.

[0017] 2. The present invention realizes digital perception of the global hydraulic status of the system by deploying multiple types of sensors in the sewage pipe network and realizing high-frequency real-time data collection. Compared with the existing collection method with sparse points and delayed data update, it effectively solves the pain points of delayed perception of pipe network status and difficulty in accurate modeling.

[0018] 3. This invention proposes a coordinated control mechanism for pump station power regulation and valve opening control. This mechanism generates and issues detailed control instructions, driving drainage equipment to respond and adjust accordingly, thereby achieving on-demand delivery and drainage. Traditional methods often rely on pre-set pump start-up schedules, which are unable to respond to flow fluctuations in real time. This invention addresses the issues of rigid scheduling and uncontrollable flow direction.

[0019] 4. This invention incorporates an edge control terminal for command parsing and execution buffering, enabling autonomous and stable operation in the event of communication anomalies, ensuring uninterrupted drainage. This offline fault-tolerant control structure significantly improves the system's shortcomings of poor anti-interference capabilities and slow fault recovery compared to existing control methods that rely on immediate responses from a central platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 Schematic diagram of the system architecture of the present invention; Figure 2 Schematic diagram of the method of the present invention. DETAILED DESCRIPTION

[0021] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the present specification. 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.

[0022] Please see the attached Figure 1 , an embodiment of the present invention provides a dynamic drainage system for a municipal sewage network, comprising: A sewage pipe network is used to carry and transport urban sewage. The sewage pipe network is equipped with multiple sensors along its route. The multiple sensors include flow sensors, water level sensors, and pressure sensors, which are used to collect key parameters such as sewage flow, water level, pressure, and external rainfall inflow in real time; a central controller, respectively connected to the plurality of sensors for receiving and processing real-time data collected by the plurality of sensors, and constructing a dynamic hydraulic model of the sewage pipe network based on the real-time data, and further generating drainage scheduling control instructions according to the model analysis results; The pump station is deployed in the sewage pipe network and is used to receive control instructions sent by the central controller and adjust the operating status of the pump station accordingly to dynamically adjust the sewage flow rate and direction; Valves are installed at key nodes in the sewage network to receive opening control instructions from the central controller and adjust the valve opening to achieve precise control of the drainage capacity of the pipeline; The edge control terminal is connected to the pump station and the valve respectively, and is used to receive the dispatching control instructions issued by the central controller and execute them in real time.

[0023] Specifically, the sewage pipe network is designed to form a branch-ring composite network structure through topological optimization. The internal pipe network is laid out with a slope gradient of 0.3%-0.5%, and is divided into several water catchment areas according to the characteristics of the urban terrain. In the main pipe section with a diameter of DN800-DN1500, a group of multi-parameter monitoring units are laid out every 200-300 meters. The unit integrates an electromagnetic flowmeter, an ultrasonic water level sensor and a piezoresistive pressure transmitter (0-1.6MPa range) to synchronously collect the volume flow, liquid level height and dynamic water pressure parameters of the fluid in the pipeline. In particular, a Doppler flowmeter is added at the intersection of the pipe network and the rainwater grate to accurately calculate the amount of exogenous rainwater intrusion through the velocity-area method.

[0024] The central controller uses the OPC UA communication protocol to exchange real-time data with 680 monitoring points. The system's core integrates the SWMM hydraulic calculation engine, which constructs a dynamic hydraulic model of the pipe network by solving the Saint-Venant equations. The data processing layer uses the Kalman filter algorithm to correct and compensate for abnormal data, and the feature extraction module automatically identifies abnormal operating conditions such as full pipe flow and backflow.

[0025] The pumping station utilizes variable-frequency submersible axial-flow pumps (55-160kW per unit). The impeller features a bidirectional flow path to accommodate both forward and reverse water delivery. The control system receives a 4-20mA analog control signal and uses PID closed-loop control to continuously adjust the pump speed between 980-1450rpm. A specially configured hydraulic quick-open / close mechanism allows for switching between operating states within 30 seconds, and combined with a pressure buffer tank, effectively suppresses water hammer.

[0026] Valves at key nodes utilize a redundant dual-valve manifold structure. The valve actuators feature built-in absolute encoders, enabling an opening resolution of 0.1° and a response time of less than 5 seconds. V-shaped ball valves are installed at pipe network intersections, and their parabolic flow path design enables linear regulation of flow and opening.

[0027] The edge control terminal utilizes the industrial-grade ARM Cortex-A72 processor architecture. It maintains μs-level clock synchronization with the upper-level system via Time-Sensitive Networking (TSN) and features local caching and resumable transmission. At the execution level, the terminal incorporates a built-in fuzzy control algorithm that automatically fine-tunes actuator movement based on pipeline pressure fluctuations. It also monitors device status parameters such as valve shaft torque and pump current, forming a closed-loop control verification mechanism.

[0028] The dynamic drainage control method of the municipal sewage network described below and the dynamic drainage system of the municipal sewage network described above can be referred to in correspondence with each other.

[0029] Please see the attached Figure 2 The present invention also provides a method for dynamic drainage control of a municipal sewage pipe network, comprising the following steps: S1. Acquire real-time data from multiple sensors deployed in the sewage pipe network, including flow sensors, water level sensors, pressure sensors, and rainfall sensors. The acquired real-time data includes sewage flow, water level, pipe pressure, and external rainfall inflow within the pipe network. S2. Based on the collected real-time data, a central controller is used to perform dynamic hydraulic modeling of the sewage pipe network and establish a mathematical model that describes the hydraulic state changes of the pipe network. The mathematical model includes the spatiotemporal evolution of flow, water level, and pressure. S3. Analyzing the current hydraulic state of the pipe network based on the hydraulic modeling, and generating corresponding drainage scheduling control instructions, wherein the scheduling instructions include power adjustment instructions for the pump station and valve opening adjustment instructions; S4. The generated drainage scheduling control instructions are transmitted to the pump station and valves through the edge control terminal. The pump station and valves adjust their own operating status according to the instructions, and adjust the sewage flow rate, flow direction and drainage capacity of the pipeline.

[0030] For step S1, pipe network hydraulic data is a key prerequisite for building an effective control model. Therefore, during implementation, it is necessary to prioritize the deployment of multiple types of highly adaptable and responsive sensors at typical nodes in the pipe network to achieve comprehensive monitoring of the sewage system's operating status.

[0031] In specific applications, data acquisition isn't performed in isolation; rather, it serves as a fundamental input for system modeling and control, forming a complete closed-loop control process alongside subsequent hydraulic model construction, scheduling strategy generation, and edge terminal execution. Therefore, the integrity, accuracy, and temporal consistency of collected data directly impact the reliability of subsequent hydrodynamic simulations and control instructions.

[0032] Real-time data is obtained from multiple sensors deployed in the sewage network, including but not limited to the following: In some embodiments, a flow sensor is installed at the confluence of a main or branch pipe to measure the volume of sewage passing through a specific section per unit time. This sensor typically uses electromagnetic induction or ultrasonic time-difference measurement principles, and the flow rate measured can be used to estimate instantaneous load changes.

[0033] Typically, water level sensors are installed in pump station forebays, near control valves, and at outlets. They employ pressure or float-type sensors to collect local water depth information within the pipe network. Water depth is a key indicator for assessing the degree of local congestion or siltation.

[0034] In one possible implementation, a pressure sensor is installed on the inner wall of the pipeline and can sense changes in static pressure to reflect the load strength of the pipeline and whether it is in a full pipe or backflow condition.

[0035] As an option, rainfall sensors are deployed at surface monitoring points in the pipe network service area to record local rainfall intensity and duration. The rainfall intensity per unit area can be converted based on the regional area and introduced as exogenous water input data into subsequent modeling modules.

[0036] Specifically, real-time data collection includes the following: In this embodiment, the flow collection value is used to characterize the volume passing through any measurement section per unit time, and combined with the pipeline cross-sectional area, the average flow velocity of the section can be inferred as one of the basic variables for velocity field modeling.

[0037] In this embodiment, the water level sensor data is processed through hydrostatic calibration and can be used to determine the instantaneous water head height at different nodes, and compared with the designed critical water level to determine whether there is an overflow risk in the local area.

[0038] In this embodiment, the pressure value is usually collected in kPa, which represents the static pressure per unit area generated by the liquid column in the pipeline. This value can be used to calculate the momentum term in the model, and the pressure gradient along the flow can be calculated by difference to further determine whether the flow state is stable.

[0039] In some embodiments, the collected rainfall data is converted into a unit area rainwater inflow curve in the form of a time series by coupling with the runoff coefficient of the pipe network inlet, and is added to the flow conservation analysis as a lateral inflow term during the modeling stage.

[0040] During the data processing phase, a timestamp mechanism is used to align the collected data from various sensors to a unified time axis, preventing model mismatches caused by sampling delays. The sampling period can be set to 5 seconds, 10 seconds, or 1 minute, depending on the system's response requirements.

[0041] The data preprocessing process also includes logic for removing outliers. Typically, empirical thresholds are set, such as flow rates not exceeding 1.5 times the maximum design flow rate and water level fluctuations not exceeding 50 cm per cycle. Data exceeding these thresholds are automatically removed.

[0042] In addition, this embodiment can be further expanded to a multi-sensor fusion approach. For example, water level and flow sensors can be deployed simultaneously at some intersection nodes, and methods such as Kalman filtering can be used to estimate and correct state variables, thereby improving the stability and reliability of time series data.

[0043] In a typical implementation, the real-time data collected by each sensor can be encapsulated into a status packet in a structured format, including the data collection time, device number, parameter type, numerical unit and correction identification field, and uploaded to the central controller via the LoRa or NB-IoT network.

[0044] In step S2, based on the collected real-time data, the central controller dynamically models the hydraulic state of the sewage network. This modeling process not only describes the current state of the sewage network but also predicts its spatiotemporal evolution, providing an important basis for subsequent scheduling and control decisions. Through dynamic modeling, the central controller can understand the flow rate, water level, and pressure changes within the network in real time, thereby achieving precise control of the sewage network.

[0045] In the previous steps, sensors have captured real-time flow, water level, pipe pressure, and external rainfall inflow data within the sewage network. This real-time data serves as input to the system and is used by the central controller for dynamic hydraulic modeling. Specifically, dynamic hydraulic modeling involves accurately simulating the spatiotemporal evolution of parameters such as flow, water level, and pressure within the sewage network to predict future trends in the network's hydraulic state.

[0046] In this embodiment, the central controller processes collected real-time data and uses variables such as flow rate, water level, and pressure to build a mathematical model that describes the hydraulic state of the sewage network. This mathematical model updates the evolution of the network's water flow in real time by combining the hydraulic continuity equation with the momentum conservation equation.

[0047] In general, the dynamic hydraulic model satisfies the following continuity control equations: Among them, A(x,t) is the flow area at a certain cross section, Q(x,t) is the volume flow rate, q l (x,t) is the lateral inflow rate per unit length.

[0048] In order to more accurately describe the dynamic process of water flow, it is also necessary to combine the momentum conservation equation to simulate the evolution of pressure and flow velocity of sewage flow in the pipe. The momentum conservation equation takes into account factors such as water inertia, friction loss, and slope effects in the pipe, and can be expressed as: Among them, h(x,t) is the water level, S f is the friction slope, g is the acceleration due to gravity, A(x, t) is the flow area at a certain cross section, and Q(x, t) is the volume flow rate.

[0049] To build the spatiotemporal evolution model, the central controller dynamically adjusts model parameters by processing flow, water level, and pressure data, updating the system status in real time. Optionally, the flow momentum term in the model can be adjusted based on actual flow resistance and pipe network characteristics, improving the model's adaptability and accuracy.

[0050] In another possible implementation, the central controller can also discretize the above equations using numerical methods based on the finite difference method (FDM) or the finite element method (FEM). This enables the model to perform dynamic calculations at higher spatial and temporal resolutions, ensuring that the hydraulic state of each node in the pipe network and each time step is accurately simulated.

[0051] Specifically, in the hydraulic modeling process of the sewage pipe network, the hydraulic state inside the pipe network at a certain moment is calculated by performing spatiotemporal interpolation on the collected real-time flow, pressure and water level data. Then, the hydraulic continuity equation and momentum conservation equation are used, combined with the rainfall inflow q l (x, t), and through iterative calculations using a numerical solution algorithm, the hydraulic conditions such as water level, pressure, and flow at future moments are obtained. The results of each iteration serve as input for the next moment, forming a closed-loop feedback loop.

[0052] Real-time data not only provides the current hydraulic status but also, through dynamic modeling, predicts hydraulic evolution trends for several future moments. This process ensures that the sewage network control system can respond quickly to changing external conditions (such as rainfall and inflow), and provides a basis for subsequent scheduling decisions through accurate model output.

[0053] In step S3, after completing hydraulic modeling based on sensor data, the central controller dynamically analyzes the current hydraulic status of the sewage network based on the model output. This analysis not only determines the current operating status of the drainage system but also serves as the core basis for generating control instructions, enabling refined adjustments to drainage scheduling strategies.

[0054] Typically, drainage scheduling strategies require real-time decisions about pump station operating power and the opening status of key valves based on model-calculated flow, water level, and pressure distribution. Scheduling control instructions are sent to execution devices via edge control units, forming a complete "model-decision-execution" closed loop.

[0055] In this embodiment, after obtaining the instantaneous flow field based on the shallow water equation solution, the central controller determines the hydraulic index of multiple key nodes. This process generally includes: Determine whether a node is above the high water mark threshold; Determine whether there is a continuous overpressure section; Determine whether the flow in the main pipe is close to full flow.

[0056] As an option, a decision indicator function is introduced into the system to quantitatively evaluate the current operating status of the pipeline network. This function can be defined as: Where D(x,t) represents the comprehensive dispatch pressure index of node x at time t, h(x,t) is the water level, P(x,t) is the node water pressure, Q(x,t) is the volume flow, and H max (x) is the maximum water level, P crit (x) is the critical water pressure, Q design (x) is the design flow rate.

[0057] Specifically, when D(x, t) exceeds the preset threshold, the controller determines that the node is in a potential abnormal state and requires immediate drainage scheduling intervention.

[0058] In one possible implementation, the dispatch instruction includes adjusting the power of the pump station. The pump station control usually uses the frequency setting value of the inverter as the control parameter, and its output power P out The following relationship is established between P (t) and the motor speed n (t): out (t) = k p n(t) 3 ; Among them, P out (t) is the output power of the pump station, n(t) is the motor speed, k p is the pump power characteristic coefficient, unit is.

[0059] Generally, the controller will calculate the required flow increment based on the current flow rate and liquid level of the discharge section, and further reversely calculate the required pump speed and corresponding power adjustment instructions.

[0060] In this embodiment, if the model output shows that a certain trunk pipe section is about to enter a full flow state, the controller will select the upstream pump station to increase the power output to speed up the discharge rate and reduce the burden of water accumulation.

[0061] At the same time, the valve opening adjustment control is also driven by the model output data. In some embodiments, the system uses an electric control valve, whose opening θ(t) is related to the target flow rate Q target (t) The following relationship exists: Among them, θ(t) is the current opening of the regulating valve, C v is the valve flow capacity coefficient, ΔP(t) is the pressure difference between the two ends of the valve, f -1 It is the inverse function of the valve characteristic function and is usually set according to equal percentage, linear or fast opening characteristics.

[0062] Alternatively, when multiple nodes are experiencing concurrent overload trends, the controller can implement a regional coordination strategy. This strategy involves dispatching commands to balance regional flow, linking multiple pump stations and valves, and executing control commands sequentially according to priority.

[0063] In certain embodiments, to prevent excessive system fluctuations due to control response lag, the central controller incorporates a delay compensation mechanism. This mechanism involves evaluating the impact of each control instruction on the hydraulic model after it is generated using a dynamic verification module to ensure stable operation after adjustments.

[0064] To prevent communication interruptions from impacting the execution of dispatch instructions, this embodiment also introduces a buffering mechanism for edge control terminals. Control instructions are cached as instruction groups. If the central controller loses connection, the edge terminal can maintain stable operation based on the previous state and automatically update its state when communication is restored.

[0065] In step S4, the generated drainage scheduling control instructions are not transmitted directly to the pumping stations and valves. Instead, they are first transmitted to the corresponding execution devices via the edge control terminal. The edge control terminal acts as an intermediary in this process, receiving, storing, parsing, and executing instructions, ensuring the accurate issuance and execution of control instructions.

[0066] Generally speaking, the primary function of an edge control terminal is to receive, cache, parse, and execute pump station power adjustment and valve opening adjustment commands generated by the central controller. Specifically, the central controller generates pump station power adjustment and valve opening adjustment commands based on the pipeline network status calculated by the real-time hydraulic model. These commands include pump station power adjustment, valve opening adjustment, and flow rate change requirements. Upon receiving these commands, the edge control terminal stores them locally and distributes them as needed.

[0067] In this embodiment, command transmission utilizes a reliable communication protocol, such as MQTT, to ensure the timeliness and accuracy of control commands. These commands are issued not only to adjust the operating status of pump stations and valves, but also to adjust the drainage capacity of pipelines based on the hydraulic conditions of each node, thereby regulating the flow rate and direction of sewage and preventing overload or waterlogging in the pipeline network.

[0068] Alternatively, valve opening control commands are transmitted to the valve actuator via the edge control terminal. Valve opening control is based on flow demand and hydraulic conditions. The goal of regulating valve opening control is to adjust the direction and flow rate of water by adjusting the degree of valve opening. The relationship between valve opening and flow can be represented by the valve characteristic curve: Among them, Q(t) is the flow rate, C v is the valve flow capacity coefficient, ΔP(t) is the pressure difference at both ends of the valve, and f(θ(t)) is the flow coefficient function of the valve.

[0069] In this model, valves adjust their openings based on the current hydraulic conditions to ensure that water flow is not overloaded or unevenly distributed, thus avoiding excessive pressure or uneven flow in the pipe network. Based on sensor feedback and instructions from the central controller, edge control terminals adjust valve openings in real time to optimize wastewater flow rate and direction.

[0070] Specifically, the regulation of pump stations and valves is verified and adjusted through a real-time feedback mechanism. Whenever the operating status of a pump station or valve changes, sensors collect new hydraulic data (such as water level, flow, and pressure) in real time and feed this data back to the central controller. The central controller analyzes this feedback data to verify the validity of the current scheduling instructions and then readjusts the operating status of the pump stations and valves, ensuring that the drainage system always maintains optimal operation.

[0071] In one possible implementation, control instructions also include dynamic optimization of valve openings and pump station power. Specifically, within different travel sections, the controller coordinates multiple pump stations and valves based on water flow variations, pressure feedback, and flow demand. This approach enables more flexible and responsive dynamic adjustments, improving drainage system efficiency.

[0072] Edge control terminals accurately transmit drainage scheduling control commands to pump stations and valves, which adjust their operating status based on real-time commands to optimize the flow rate, direction, and drainage capacity of the sewage network. This mechanism ensures the flexibility and efficiency of the drainage system, enabling automated and intelligent scheduling and control in a variety of complex working conditions.

[0073] The method of this embodiment can be used to execute the above system embodiment. Its principles and technical effects are similar and will not be described in detail here.

[0074] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. Dynamic drainage system of municipal sewage network, characterized by: include: A sewage pipe network is used to carry and transport urban sewage. The sewage pipe network is equipped with multiple sensors along its route. The multiple sensors include flow sensors, water level sensors, and pressure sensors, which are used to collect key parameters such as sewage flow, water level, pressure, and external rainfall inflow in real time; a central controller, respectively connected to the plurality of sensors for receiving and processing real-time data collected by the plurality of sensors, and constructing a dynamic hydraulic model of the sewage pipe network based on the real-time data, and further generating drainage scheduling control instructions according to the model analysis results; The pump station is deployed in the sewage pipe network and is used to receive control instructions sent by the central controller and adjust the operating status of the pump station accordingly to dynamically adjust the sewage flow rate and direction; Valves are installed at key nodes in the sewage network to receive opening control instructions from the central controller and adjust the valve opening to achieve precise control of the drainage capacity of the pipeline; The edge control terminal is connected to the pump station and the valve respectively, and is used to receive the dispatching control instructions issued by the central controller and execute them in real time.

2. A method for controlling the dynamic drainage of a municipal sewage pipe network, applied to the dynamic drainage system of a municipal sewage pipe network according to claim 1, characterized in that: The following steps are involved: Acquire real-time data from multiple sensors deployed in the sewage pipe network, including flow sensors, water level sensors, pressure sensors, and rainfall sensors. The acquired real-time data includes sewage flow, water level, pipe pressure, and external rainfall inflow within the pipe network; Based on the collected real-time data, the central controller conducts dynamic hydraulic modeling of the sewage pipe network and establishes a mathematical model that describes the changes in the hydraulic state of the pipe network. The mathematical model includes the temporal and spatial evolution of flow, water level and pressure. Analyzing the current hydraulic state of the pipe network based on the hydraulic modeling, and generating corresponding drainage scheduling control instructions, wherein the scheduling instructions include power adjustment instructions for the pump station and valve opening adjustment instructions; The generated drainage scheduling control instructions are transmitted to the pumping station and valves through the edge control terminal. The pumping station and valves adjust their own operating status according to the instructions, and adjust the sewage flow rate, flow direction and drainage capacity of the pipeline.

3. The dynamic drainage system and control method of municipal sewage pipe network according to claim 2, characterized in that: Acquiring real-time data includes the following steps: Multiple sensors are installed at typical operating nodes of the sewage network, including junctions, pump station forebays, trunk and branch pipe connections, and terminal outlets. Collect the instantaneous flow, water level and internal pressure values ​​of each node within the preset sampling period; Process the external rainfall intensity and duration information received by the rainfall sensor and convert it into rainfall intensity input per unit area; The collected data is sent to the central controller through the communication network, and timestamp synchronization and outlier filtering are performed.

4. The municipal sewage network dynamic drainage system and control method according to claim 2, characterized in that: The dynamic hydraulic modeling includes the following steps: The one-dimensional unsteady flow model of the sewage pipe network is carried out, and the shallow water equation is used to describe the continuity and momentum transfer relationship of the fluid in the pipe in the time and space dimensions; The modeling process adopts finite difference method or finite volume method for discrete solution, taking into account the influence of pipeline slope, cross-sectional shape and friction resistance; The dynamic hydraulic model satisfies the following continuity control equation: Among them, A(x,t) is the flow area at a certain cross section, Q(x,t) is the volume flow rate, q l (x,t) is the lateral inflow rate per unit length.

5. The municipal sewage network dynamic drainage system and control method according to claim 2, characterized in that: The mathematical model comprises the following steps: The hydraulic response characteristics of different areas of the pipe network are represented by node state variables, including flow, water level and pressure. The above state variables are input into the controller to establish a state-response prediction relationship; The mathematical model uses a multivariable nonlinear state space expression to describe the sewage flow evolution process; The model includes the following momentum equation expression: Among them, h(x,t) is the water level, S f is the friction slope, g is the acceleration due to gravity, A(x, t) is the flow area at a certain cross section, and Q(x, t) is the volume flow rate.

6. The municipal sewage network dynamic drainage system and control method according to claim 2, characterized in that: The hydraulic state includes the following steps: Comparison between the real-time water level height at each node of the sewage pipe network and the design critical water level; The deviation between the internal pressure of the pipe and the threshold pressure; The degree of synchronization between the drainage flow rate change trend and the flow regulation of the pumping station; The pressure loss response caused by the head difference at the valve and the opening adjustment.

7. The municipal sewage network dynamic drainage system and control method according to claim 2, characterized in that: The drainage scheduling control instruction includes the following steps: Output pump frequency control signal for the pump station, increasing step by step according to power limit; Set the valve output opening percentage and make dynamic fine-tuning according to the current node pressure; Considering the overall drainage balance of the system, multiple pumping stations and valve nodes are coordinated and controlled to achieve balanced discharge of the entire system; When an overpressure trend is detected, the priority emptying command is automatically triggered and more discharge channels are opened locally.

8. The dynamic drainage system and control method of municipal sewage pipe network according to claim 2, characterized in that: The opening adjustment instruction includes the following steps: Calculate the target valve opening according to the deviation between the current node water level and the target drainage capacity; Convert the calculation results into electronic control execution signals, taking into account the execution lag time and the mechanical inertia characteristics of the valve; If there are multiple adjacent valves in linkage, the opening of the most downstream valve shall be adjusted first; The valve response behavior is corrected through a continuous feedback mechanism.

9. The municipal sewage network dynamic drainage system and control method according to claim 2, characterized in that: The edge control terminal includes: A data receiving module is used to receive control instructions from a central controller; An execution control module, used for converting control instructions into pump frequency adjustment signals and valve opening signals; Local data cache module, used to store the previous cycle instructions when communication is interrupted to ensure control continuity; The status reporting module is used to transmit the current pump station and valve execution status back to the central controller to achieve remote monitoring and diagnosis.

10. The municipal sewage network dynamic drainage system and control method according to claim 2, characterized in that: The operating state includes the following steps: The operating status of the pump station includes current power output, start / stop status, and operating frequency; The operating status of the valve includes the current opening value, opening and closing direction and response delay; The running status is updated synchronously with the sensor acquisition status and used as the input variable of the scheduling strategy for the next period.

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