Sewage lifting prefabricated pump station and digital twin intelligent control system thereof

Abstract

This invention discloses a prefabricated sewage lifting pump station and its digital twin intelligent control system, relating to the field of sewage lifting. The prefabricated sewage lifting pump station includes a cylinder, ladder, bar screen guide rail, pump suspension chain, maintenance platform, comminutor screen, inlet, non-clogging sewage pump, fiberglass base, concrete base, sensor group, outlet, gate valve, check valve, pressure piping system, level controller, float level system, coupling guide rail, and coupling base. Digital twin technology is used to achieve equipment status monitoring and optimized management. This invention achieves operational monitoring and energy-saving operation optimization of the prefabricated pump station through a digital twin intelligent control system. Particle swarm optimization algorithm is used for timely fault diagnosis and early warning, reducing manual intervention, achieving intelligent control, and greatly improving the control accuracy and automation level of the pump station.

Description

Technical Field

[0001] This invention relates to the field of sewage lifting technology, and in particular to a prefabricated sewage lifting pump station and its digital twin intelligent control system. Background Technology

[0002] With the development of digital and intelligent technologies, digital twin technology has become one of the key research areas. Digital twin refers to the technology of creating a corresponding digital model of an actual physical system through digital means, and then simulating and optimizing it based on this model. Digital twin technology can achieve synchronous linkage between physical and digital systems, improving the accuracy and reliability of system control.

[0003] Prefabricated pumping stations are indispensable facilities in urban drainage systems and industrial wastewater treatment, and their automated control technology is receiving increasing attention. Traditional pumping station control methods mainly rely on manual operation, which suffers from low control accuracy, long response time, and susceptibility to errors. Therefore, it is crucial to utilize advanced digital technology to improve the control accuracy and automation level of prefabricated pumping stations. Summary of the Invention

[0004] To address the problems mentioned in the background art, the present invention provides a prefabricated sewage lifting pump station and its digital twin intelligent control system, which can improve the control accuracy and automation level of the pump station.

[0005] To achieve the above objectives, the present invention provides the following solution:

[0006] On one hand, the present invention provides a prefabricated sewage lifting pump station, comprising: a ladder, a bar screen guide rail, a pump suspension chain, a maintenance platform, a shredder, an inlet, a non-clogging sewage pump, a fiberglass base, a concrete base, a sensor group, an outlet, a gate valve, a check valve, a pressure piping system, a level controller, a float level system, a coupling guide rail, and a coupling base; the sensor group includes a flow sensor, a head sensor, a speed sensor, an efficiency sensor, and a temperature sensor;

[0007] The ladder is fixed to the inner wall of the prefabricated pump station cylinder and connected to the maintenance platform. The maintenance platform is located in the middle of the cylinder and has a support frame underneath. The level controller is welded to the lower part of the maintenance platform. The inlet is located on the cylinder and connected to the comminutor grid through a pipe. The outlet is connected to the gate valve and check valve through a pipe. The coupling guide rail is welded to the bottom of the maintenance platform. The coupling base is bolted to the bottom of the cylinder. The pump chain is connected to the top center of the cylinder and to the non-blocking sewage pump below. The coupling guide rail, coupling base, and pump chain together fix the non-blocking sewage pump. The non-blocking sewage pump is connected to the check valve through a pressure pipeline system. The fiberglass base sits on the concrete base and is used to fix the entire cylinder. The float level system is located inside the cylinder to detect the water level. The sensor group is installed on the non-blocking sewage pump to collect the operating parameters of the non-blocking sewage pump, including flow rate, head, speed, efficiency, motor temperature, and open / closed status.

[0008] Optionally, the prefabricated pump station cylinder is cylindrical; the cylinder wall material includes reinforced fiberglass and high-density polyethylene; the cylinder wall consists of an anti-corrosion layer, an anti-permeability layer, a structural layer and an outer protective layer, and the outer protective layer is made of a special UV-resistant material.

[0009] Optionally, the optimal effective volume V of the cylinder Ef The calculation formula is in Z represents the rated flow rate of a single non-clogging sewage pump in a prefabricated pumping station; max This indicates the maximum number of times a non-clogging sewage pump can be started and stopped per hour.

[0010] Optionally, the required head H of the non-clogging sewage pump is calculated using the formula H = H1 + H2 + H3 + H4; where H1 represents the static head; H2 is the sum of friction loss and local resistance loss of the external pipeline of the prefabricated pumping station; H3 is the sum of friction loss and local resistance loss of the internal pipeline of the prefabricated pumping station; and H4 is the safety head.

[0011] Optionally, the shredding grid consists of biaxial spiral blades, with two sets of cutting blades and pads arranged on two parallel rotating axes in an alternating double spiral pattern.

[0012] On the other hand, the present invention also provides a digital twin intelligent control system for a prefabricated sewage lifting pump station, including: a digital model establishment module, a historical operating condition database establishment module, a data acquisition module, an operating status monitoring module, and a human-machine interface;

[0013] The digital model building module is used to construct a digital twin model of the prefabricated sewage lifting pump station based on the input CAD drawings, electrical diagrams, and process flow diagrams of the prefabricated pump station.

[0014] The historical operating condition database establishment module is used to process historical operating condition data using the particle swarm optimization algorithm to establish and update the historical operating condition database.

[0015] The data acquisition module is used to collect the operating status parameters of the prefabricated pumping station in real time through the sensor group and transmit them to the human-machine interface for display; the operating status parameters include the operating parameters of the non-blocking sewage pump, the water level in the cylinder, the opening and closing status of the pulverizing screen, and the opening and closing status of the valves.

[0016] The operation status monitoring module is used to process and analyze the collected operation status parameters to determine whether they belong to normal operating conditions. If they are normal operating conditions, the module compares them with the historical operating condition database and selects the best operating condition for energy-saving operation adjustment. If they are abnormal operating conditions, the module performs fault diagnosis and issues fault warnings based on the prediction results of the operation digital twin model, thereby guiding equipment operation and status adjustment.

[0017] Optionally, the digital twin intelligent control system further includes a communication module; the communication module provides support for multiple interfaces and protocols, including digital signals, analog signals, RS485, and MODBUS.

[0018] Optionally, the digital twin intelligent control system supports remote data acquisition and transmission, enabling APP control by uploading data to the cloud; the digital twin intelligent control system is also equipped with automatic recovery and backup mechanisms as well as mechanisms to prevent data loss.

[0019] Optionally, the operation status monitoring module is also used to control the inlet and the pulverizing screen to close and increase the speed of the non-blocking sewage pump when the float level system detects a rapid rise in the sewage level, until the prefabricated pumping station restores a safe water level.

[0020] Optionally, the operation status monitoring module is also used to monitor the operation status of the crushing grid; when it detects that the crushing grid is blocked by solid objects, it automatically sends a protection signal to control the blades to reverse and re-enter after exiting the obstacle.

[0021] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0022] The present invention provides a prefabricated sewage lifting pump station and its digital twin intelligent control system. The prefabricated pump station includes a cylinder, ladder, bar screen guide rail, pump suspension chain, maintenance platform, comminutor screen, inlet, non-clogging sewage pump, fiberglass base, concrete base, sensor group, outlet, gate valve, check valve, pressure piping system, level controller, float level system, coupling guide rail, and coupling base. Digital twin technology is used to achieve equipment status monitoring and optimized management. The present invention achieves operational monitoring and energy-saving operation optimization of the prefabricated pump station through the digital twin intelligent control system. Particle swarm optimization algorithm is used for timely fault diagnosis and early warning, reducing manual intervention, achieving intelligent control, and greatly improving the control accuracy and automation level of the pump station. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a schematic diagram of the prefabricated sewage lifting pump station of the present invention;

[0025] Figure 2 A schematic diagram of the digital twin intelligent control system equipped with the prefabricated sewage lifting pump station of the present invention;

[0026] Figure 3 This is a flowchart illustrating the process of training historical operating data using the particle swarm optimization algorithm in this invention.

[0027] Figure 4 This is a flowchart illustrating the operation state adjustment using the particle swarm optimization algorithm in this invention. Detailed Implementation

[0028] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] Currently, relevant digital technologies are used for the control of prefabricated pumping stations, such as SCADA systems and PLC controllers. While these technologies have improved the control accuracy and automation level of pumping stations to some extent, their application scope is limited due to the lack of complete models and real-time feedback mechanisms. Therefore, the purpose of this invention is to provide a prefabricated sewage lifting pumping station and its digital twin intelligent control system. Based on digital twin technology, this system highly replicates the actual environment and provides real-time feedback on the pumping station's operating status through a digital model, thereby improving the control accuracy and automation level of the pumping station.

[0030] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0031] This invention discloses a prefabricated sewage lifting pump station that utilizes digital twin technology for status monitoring and optimized management. For example... Figure 1 As shown, the prefabricated sewage lifting pump station includes: a ladder 1, a bar screen guide rail 2, a pump suspension chain 3, a maintenance platform 4, a shredder bar 5, an inlet 6, a non-clogging sewage pump 7, a fiberglass base 8, a concrete base 9, a sensor group 10, an outlet 11, a gate valve 12, a check valve 13, a pressure piping system 14, a level controller 15, a float level system 16, a coupling guide rail 17, and a coupling base 18. The sensor group 10 includes a flow sensor, a head sensor, a speed sensor, an efficiency sensor, and a temperature sensor, etc.

[0032] The ladder 1 is fixed to the inner wall of the prefabricated pump station cylinder and directly connected to the maintenance platform 4. The maintenance platform 4 is located in the middle of the cylinder and has a support frame underneath. The level controller 15 is fixed to the lower part of the maintenance platform 4 by welding. The inlet 6 is opened on the cylinder and connected to the comminutor 5 through a pipe. The outlet 11 is connected to the gate valve 12 and the check valve 13 through pipes. The coupling guide rail 17 is fixed to the bottom of the maintenance platform 4 by welding. The coupling base 18 is fixed to the bottom of the cylinder by bolts. The pump suspension chain 3 is connected to the center of the top of the cylinder at the top and to the non-clogging sewage pump 7 at the bottom. The coupling guide rail 17, the coupling base 18, and the pump suspension chain 3 together serve to fix the non-clogging sewage pump 7. The non-clogging sewage pump 7 is connected to the check valve 13 through the pressure pipeline system 14. The fiberglass base 8 sits on the concrete base 9 and is used to fix the entire cylinder. When using the prefabricated pump station, a layer of concrete is first poured to form the concrete base 9. After leveling and solidification, the fiberglass base 8 is placed on top and secured with bolts, then another layer of concrete is poured. The suspension cable of the level controller 15 should be kept free from tangling and interference from obstacles. The float level system 16 is located inside the cylinder and is used to detect the water level height inside the cylinder. The sensor group 10 is installed on the non-clogging sewage pump 7 to collect the operating parameters of the non-clogging sewage pump, including flow rate, head, speed, efficiency, motor temperature, and open / closed status.

[0033] During operation, prefabricated pumping stations are typically located in low-lying areas to collect sewage and rainwater from the surrounding area. When a certain amount of sewage accumulates in the prefabricated pumping station, it flows into the station through inlet 6. At this time, the sensor of the float level system 16 sends a water level signal from the cylinder to the digital twin intelligent control system 19. The digital twin intelligent control system 19 then controls the start of the pulverizing screen 5 and the non-clogging sewage pump 7, and the sewage is pumped to outlet 11 through the pressure pipeline system 14. Based on the water level signal, the pumping station's control device should be able to adjust the operation of the non-clogging sewage pump 7 in a timely manner and dynamically display the pump operating parameters and the pumping station's operating status using the digital twin intelligent control system 19. When the sewage level rises rapidly, the digital twin intelligent control system 19 controls the inlet 6 and the pulverizing screen 5 to close, and the speed of the non-clogging sewage pump 7 increases until the prefabricated pumping station returns to a safe water level. When a malfunction occurs in the prefabricated pumping station, the digital twin intelligent control system 19 performs real-time fault diagnosis, analyzes the cause of the malfunction, and reports the solution to the operating personnel.

[0034] The prefabricated pump station cylinder is cylindrical, and its wall material includes lightweight, high-strength, and corrosion-resistant materials such as reinforced fiberglass and high-density polyethylene. The cylinder wall consists of an anti-corrosion layer, an anti-permeability layer, a structural layer, and an outer protective layer. The outer protective layer is reinforced with a special UV-resistant material to prevent aging when exposed to sunlight for extended periods.

[0035] Optimal effective volume V of the cylinder Ef The calculation formula is:

[0036]

[0037] in This indicates the rated flow rate of a single non-clogging sewage pump in a prefabricated pumping station, in cubic meters per second (m³). 3 / h;Z max This indicates the maximum number of start-stop cycles per hour for the non-clogging sewage pump. The optimal effective volume V of the cylinder... Ef Entering selections and calculation formulas helps calculate the effective volume of the cylinder, aiding in the design of the prefabricated pump station's cylinder. A suitable cylinder volume can help reduce production and operating costs. Inputting the daily processing capacity, based on the rated flow rate of a single pump and the maximum number of starts and stops per hour, allows calculation of the required cylinder size.

[0038] The non-clogging sewage pump 7 is a sewage pump equipped with a pre-cutting device and a pre-swirl basin to prevent solid phase deposition at the bottom of the prefabricated pumping station. The non-clogging sewage pump 7 is selected based on flow rate requirements, and the pump housing includes, but is not limited to, one non-clogging sewage pump 7. These pumps should preferably have the same model parameters.

[0039] The formula for calculating the required head H of the non-blocking sewage pump 7 is as follows:

[0040] H = H1 + H2 + H3 + H4 (2)

[0041] Where H1 represents static head, which is the difference between the bottom elevation of the outlet pipe of the non-blocking sewage pump and the water level when the pump stops, in meters; H2 is the sum of friction loss and local resistance loss of the external pipeline of the prefabricated pumping station, in meters; H3 is the sum of friction loss and local resistance loss of the internal pipeline of the prefabricated pumping station, in meters; and H4 is safety head, which is generally taken as 1.5 meters.

[0042] The formula for calculating friction loss is:

[0043]

[0044] The formula for calculating local resistance loss is:

[0045]

[0046] Where λ represents the friction coefficient; ξ i The parameters represent: local resistance coefficient; n represents the number of pipe segments; v represents the average flow velocity in the pipe; l represents the pipe length; d represents the pipe inner diameter; and g represents the acceleration due to gravity. Each segment's superposition and optimal volume are entered into the selection and calculation formula to help calculate the required head for an effective non-clogging sewage pump, avoiding pump selection failures due to head calculation errors, and preventing sewage from being smoothly lifted and discharged from the cylinder. Inputting the daily treatment capacity and the head of the non-clogging sewage pump allows for automatic selection of a suitable pump.

[0047] The crushing grid 5 consists of dual-axis spiral blades made of special alloy steel, which has high strength and wear resistance and can adapt to the crushing of different particles. The two sets of cutting blades and pads are arranged on two parallel rotating shafts in an alternating double spiral pattern, achieving a high-precision, high-force, and high-efficiency cutting effect.

[0048] The prefabricated sewage lifting pump station of this invention is equipped with a digital twin intelligent control system 19, which is installed inside the control cabinet. See also... Figure 2 The digital twin intelligent control system mainly includes: a digital model establishment module, a historical operating condition database establishment module, a data acquisition module, an operating status monitoring module, and a human-machine interface.

[0049] The digital model building module is used to construct a digital twin model of the prefabricated sewage lifting pump station based on the entered CAD drawings, electrical diagrams, and process flow diagrams of the prefabricated pump station.

[0050] The historical operating condition database establishment module is used to process historical operating condition data using the particle swarm optimization algorithm to establish and update the historical operating condition database.

[0051] The data acquisition module is used to collect the operating status parameters of the prefabricated pumping station in real time through the sensor group and transmit them to the human-machine interface for display. The operating status parameters include the operating parameters of the non-blocking sewage pump, the water level in the cylinder, the opening and closing status of the pulverizing screen, and the opening and closing status of the valves. The operating parameters of the non-blocking sewage pump include parameters such as flow rate, head, speed, frequency, efficiency, and temperature.

[0052] The operational status monitoring module processes and analyzes collected operational status parameters to determine whether they fall under normal operating conditions. If normal, it compares the data with a historical operating condition database, selects the optimal operating condition for energy-saving adjustments, and continuously records historical operating conditions using digital twin technology. This data is then processed using a particle swarm optimization algorithm to enrich the historical operating condition database. If abnormal, it diagnoses faults and issues early warnings based on the predictions of the operational digital twin model, guiding equipment operation and condition adjustments. Normal operating status parameters may include: water level in the tank, number of pumps operating, pump status, pump stop status, inlet valve status, inlet valve status, outlet valve status, outlet valve status, comminutor screen status, comminutor screen status, motor temperature, etc. Abnormal operating conditions include: motor overheating, low water level, and comminutor screen blockage by foreign objects. Normal and abnormal operating condition parameters are uploaded to a cloud server, and the data can be viewed via mobile phone or other terminals. The digital twin intelligent control system 19 enables the start-up, stop-up, and speed regulation of the non-blocking sewage pump 7. The liquid level in the cylinder is an important basis for the start-up, stop-up, or frequency conversion speed regulation of the non-blocking sewage pump 7.

[0053] See Figure 2 The digital twin intelligent control system also includes a communication module; this module provides support for various interfaces and protocols, including but not limited to digital signals, analog signals, RS485, and MODBUS. Furthermore, the digital twin intelligent control system is equipped with automatic recovery and backup mechanisms, as well as mechanisms to prevent data loss, ensuring data security and stable system operation. In situations where the deployment environment is limited, the digital twin intelligent control system can support remote data acquisition and transmission, enabling APP control by uploading data to the cloud. Specifically, the relevant APP can send control commands based on the PLC, including electrical signals, digital signals, or wireless signals, thereby adjusting valve opening (0-100%), non-blocking sewage pump frequency (0-50Hz), and the start and stop of the non-blocking sewage pump.

[0054] The operation status monitoring module is also used to control the inlet and the crushing screen to close when the float level system 16 detects a rapid rise in the sewage level, and to increase the speed of the non-blocking sewage pump until the prefabricated pumping station returns to a safe water level.

[0055] The operation status monitoring module is also used to monitor the operation status of the crushing grid 5; when the crushing grid 5 is detected to be blocked by solid objects, it automatically sends a protection signal to control the blades to reverse and re-enter after exiting the obstacle, thereby realizing intelligent control and protection of the entire operation process.

[0056] The digital twin intelligent control system also includes: a model data input module, an operation data training module, an operation status adjustment module, and a fault early warning module.

[0057] The model data entry module is used to input information about prefabricated pump station components, such as the pump station cylinder, comminutor, pipes, valves, and non-clogging sewage pumps, into the prefabricated pump station model library, in accordance with the requirements of relevant standards such as the "Technical Specification for Application of Integrated Prefabricated Pump Stations" (CECS407:2015), as well as the connection methods between these components. This information is entered using CAD drawings, electrical diagrams, and process flow diagrams.

[0058] The operational data training module is used to collect historical operating condition data, including pump start / stop status, water level, valve opening / closing status, and corresponding water level change data. It processes and cleans the data to ensure its quality and integrity. It is also used to continuously enrich the historical operating condition database based on the particle swarm optimization algorithm to achieve operation monitoring and energy-saving operation optimization of prefabricated pumping stations.

[0059] Figure 3 This is a flowchart for training the particle swarm optimization algorithm. This invention retains the most efficient pumps from the collected historical operating data and uses their corresponding operating settings as the control strategy for the water pumps. The operating settings include the flow rate, head, speed, and efficiency of the non-blocking sewage pump, as well as the valve opening at the pipeline outlet. Each set of pump operating strategy data is treated as a particle, and the particle swarm optimization algorithm is used to find the optimal particle as the best control strategy for the corresponding operating condition. Simultaneously, the flow rate, head, speed, and valve opening at the pipeline outlet corresponding to the most efficient non-blocking sewage pump are recorded as a corresponding operating condition in the historical operating condition database.

[0060] Specifically, the particle swarm optimization algorithm process is as follows.

[0061] Initialize the particle swarm: Set the number of particles to N, with each particle representing a water pump control strategy. The position of each particle is represented as X = [x1, x2, ..., x...]. N ], where x n This represents the parameters of the nth pump control strategy. The velocity of each particle is represented as V = [v1, v2, ..., v].N ], where v n This represents the speed of the nth parameter.

[0062] The speed update formula is:

[0063]

[0064] Introducing the inertia factor, we get:

[0065]

[0066] The position update formula is:

[0067]

[0068] In the formula, ω represents the update rate of particle i in the d-th iteration; ω represents the inertia weight of the particle update rate, which is reduced by 10% every 100 iterations to improve the particle's local optimization ability; c1 and c2 represent the individual learning factor and population learning factor of the particle, respectively. This represents the optimal position experienced by particle i up to the d-th iteration; gbest d This represents the optimal position reached by the population up to the d-th iteration; This represents the position of particle i in the d-th iteration. r1, r2, r i,l r i2,l The value of is in the range [0,1], and it is a pseudo-random number uniformly distributed within this interval. The individual extreme value of the particle in the t-th iteration is denoted as . The historical best position of all particles, also known as the global extremum of a particle in the th iteration, is... v represents the update rate of particle i in the d-th iteration; id (t) represents the velocity of particle i during the t-th iteration. The d-th dimension indicates that the particle has the ability to explore and develop new regions, giving the algorithm the ability to perform a global search. It is often used to balance the global and local search capabilities of the particle. x represents the position of particle i in the d-th iteration; id (t) represents the position of the particle at iteration time t. The d-th dimension.

[0069] Using linearly decreasing weights:

[0070]

[0071] In the formula, ω max The maximum value of ω, ω min Let ω be the minimum value, t be the current iteration number, and T be the minimum value.max The maximum number of iterations is given. The inertia weight ω describes the influence of particle inertia on the current velocity; the magnitude of ω balances the algorithm's global search capability and local optimization capability. At the beginning of the algorithm, to enrich the historical operating condition database and to ensure each particle has a good ability to explore new areas, ω is assigned a large value. In the later stages of the search, when seeking the optimal operating conditions, ω is preferred to be smaller, so that particles can accurately search around the global optimum with a higher probability. The running data training module needs to continuously update the model parameters and algorithm based on the data in the pre-built pump station model library to improve the model's accuracy and reliability. Improving model performance through data means continuously enriching the data source and historical operating condition database, and performing positive data recommendation, data augmentation, data removal, and search expansion based on the actual prediction results after model deployment, ultimately supplements the historical operating condition database, thus forming a continuously optimized historical operating condition database.

[0072] Define the objective function: Define the fitness function as the objective function to measure the optimization effect of energy-saving operation of the water pump. The objective function considers factors such as pump start-up and shutdown frequency, pump operating time, and power consumption to achieve the goal of energy-saving operation. The objective function is set as follows:

[0073]

[0074] Where E i Q represents the total daily energy consumption of the i-th non-blocking sewage pump; i,j H represents the flow rate of pump i at time step j; i,j Let e ​​be the pump head of pump i at time step j, and the pump head is related to the total displacement at time step j; i,j The efficiency of pump i at time step j; Δt j The time step on the demand-duration curve; IQ j Let ρ be the total demand at time step j; ρ be the density of water; and g be the acceleration due to gravity.

[0075] Water level and valve opening are used as constraints for starting and stopping multiple pumps. These constraints include:

[0076]

[0077] Q maxi Q represents i,j The maximum value of H; maxi and H mini H respectively i,j The maximum and minimum values.

[0078] The operation status adjustment module uses various types of sensors, including ultrasonic sensors, pressure sensors, and temperature sensors, to detect the status of each component. Pressure sensors are installed at the inlet and outlet to monitor changes in water pressure. Ultrasonic sensors and float level gauges are installed in the pipeline to detect parameters such as water flow velocity and water level. Digital twin technology is applied to intelligently adjust the operating conditions of variable components during operation to meet energy-saving requirements. Specifically, the module calculates the fitness value of the current position based on actual operating conditions, compares it with the optimal fitness and position of an individual component in the historical operating condition database, and adjusts the pump start / stop status and inlet valve opening / closing according to the water level to maintain the water level within a reasonable range, achieving energy-saving operation. Typically, one pump is in operation and one is on standby. If the water level is high, the outlet valve is opened wider. If the outlet valve is opened to its maximum and the water level drop is still slow, both pumps are started simultaneously. If the drop is still slow, the inlet valve is closed.

[0079] The historical operating condition database obtained using the particle swarm optimization algorithm is continuously iterated and optimized based on actual operating results, adjusting parameters such as particle number, inertia weight, and acceleration factor to obtain better operating conditions. This improves the model's overall capabilities through algorithm tuning and data fusion. Once sufficient datasets are acquired, comparing data from the historical operating condition database allows for the rapid selection of appropriate operating conditions. Figure 4 As shown. Particle swarm optimization (PSO) searches for the global optimum using multiple parameters. Each particle with memory obtains its own historical best position during its search, also known as the individual extreme value; the historical best positions of all particles during the iteration process are called the global extreme values. The speed and direction of PSO optimization are adjusted based on the optimal position of the current operating condition and the optimal positions of all particles, thus approaching the suitable operating condition better and faster. This invention compares the actual operating condition with operating conditions of the same flow rate and head in the historical operating condition database, finding operating conditions close to the current condition as settings to maintain high operating efficiency. This allows the operating condition to be closer to the high-efficiency operating range of the non-clogging sewage pump while meeting safe operation requirements, thereby reducing energy consumption and improving efficiency. For example, it determines whether the efficiency of the non-clogging sewage pump is greater than the efficiency under the same flow rate and head in the historical operating condition database. If it is greater, operation continues; otherwise, the particle swarm algorithm is used to find suitable operating settings.

[0080] The fault early warning module is used to diagnose and warn of potential faults in a timely manner. Its main goal is to diagnose faults and respond to them to ensure the safe operation of components. Therefore, it is necessary to guide and adjust the operation of equipment based on the prediction results of the digital twin model. This generally includes data preprocessing, feature extraction, threshold judgment and result verification.

[0081] The fault early warning module primarily issues warnings based on abnormal operating status data transmitted from sensors. Input data includes water level, motor temperature, current, speed, pressure and flow rate of the non-clogging sewage pump, etc. Output predictions include: water level warnings (too high, too low), motor faults (too high, too low, excessive motor vibration, excessive motor current), pump faults (low flow rate, low pressure), etc. By comparing data, it identifies abnormal operating data, extracts characteristic parameters, determines the degree to which these parameters exceed safety thresholds, and verifies whether the problem lies with the sensors or the equipment.

[0082] In practical applications, the digital twin intelligent control system 19 automatically generates and stores a real-time operating database, generates data reports, and produces various operating status diagrams. It can also predict the operating status of the pumping station through human-machine interfaces and remote control systems, displaying the model prediction results to operators. Upon detecting an anomaly, it can connect to the superior network, automatically issuing alarms to operators. It can also receive dispatch commands from the superior network, allowing operators to monitor the pumping station's operating status at any time via mobile phones, computers, and other devices, and perform operations such as starting / stopping the pump and adjusting water flow, thus achieving remote monitoring and management. The prefabricated pumping station and its digital twin intelligent control system of this invention can be widely applied in urban drainage systems and other fields, offering significant economic and social benefits.

[0083] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A prefabricated sewage lifting pump station, characterized in that, include: Ladder, bar screen guide rail, water pump suspension chain, maintenance platform, shredder, inlet, non-clogging sewage pump, fiberglass base, concrete base, sensor group, outlet, gate valve, check valve, pressure piping system, level controller, float level system, coupling guide rail and coupling base; the sensor group includes flow sensor, head sensor, speed sensor, efficiency sensor and temperature sensor. The ladder is fixed to the inner wall of the prefabricated pumping station cylinder and connected to the maintenance platform. The maintenance platform is located in the middle of the cylinder and has a support frame underneath. The level controller is fixed to the lower part of the maintenance platform by welding. The inlet is opened on the cylinder and connected to the comminutor grid through a pipe. The outlet is connected to the gate valve and check valve through a pipe. The coupling guide rail is fixed to the bottom of the maintenance platform by welding. The coupling base is fixed to the bottom of the cylinder by bolts. The pump suspension chain is connected to the center of the top of the cylinder above and to the non-blocking sewage pump below. The coupling guide rail, coupling base, and pump suspension chain together serve to fix the non-blocking sewage pump. The non-blocking sewage pump is connected to the check valve through a pressure pipeline system. The fiberglass base sits on the concrete base and is used to fix the entire cylinder. The float level system is located in the cylinder to detect the water level. The sensor group is installed on the non-blocking sewage pump to collect the operating parameters of the non-blocking sewage pump, including flow rate, head, speed, efficiency, motor temperature, and open / closed status. The non-clogging sewage pump is a sewage pump with a pre-cutting device and is equipped with a pre-swirl basin to prevent solid phase from depositing at the bottom of the prefabricated pump station. The prefabricated sewage lifting pump station uses digital twin technology to achieve status monitoring and optimized management.

2. The prefabricated sewage lifting pump station according to claim 1, characterized in that, The prefabricated pump station cylinder is cylindrical in shape; the cylinder wall material includes reinforced fiberglass and high-density polyethylene; the cylinder wall consists of an anti-corrosion layer, an anti-permeability layer, a structural layer and an outer protective layer, and the outer protective layer is made of a special UV-resistant material.

3. The prefabricated sewage lifting pump station according to claim 2, characterized in that, The optimal effective volume of the cylinder The calculation formula is ;in This indicates the rated flow rate of a single non-clogging sewage pump in a prefabricated pumping station; This indicates the maximum number of times a non-clogging sewage pump can be started and stopped per hour.

4. The prefabricated sewage lifting pump station according to claim 1, characterized in that, The formula for calculating the required head H of the non-blocking sewage pump is H = H1 + H2 + H3 + H4; where H1 represents the static head; H2 is the sum of friction loss and local resistance loss of the external pipeline of the prefabricated pumping station; H3 is the sum of friction loss and local resistance loss of the internal pipeline of the prefabricated pumping station; and H4 is the safety head.

5. The prefabricated sewage lifting pump station according to claim 1, characterized in that, The crushing grid consists of dual-axis spiral blades, with two sets of cutting blades and pads arranged on two parallel rotating axes in an alternating double spiral pattern.

6. A digital twin intelligent control system for a prefabricated sewage lifting pump station, characterized in that, include: The system includes a digital model building module, a historical operating condition database building module, a data acquisition module, an operating status monitoring module, and a human-machine interface. The digital model building module is used to construct a digital twin model of the prefabricated sewage lifting pump station as described in claim 1 based on the input CAD drawings, electrical diagrams, and process flow diagrams of the prefabricated pump station. The historical operating condition database establishment module is used to process historical operating condition data using the particle swarm optimization algorithm to establish and update the historical operating condition database. The data acquisition module is used to collect the operating status parameters of the prefabricated pumping station in real time through the sensor group and transmit them to the human-machine interface for display; the operating status parameters include the operating parameters of the non-blocking sewage pump, the water level in the cylinder, the opening and closing status of the pulverizing screen, and the opening and closing status of the valves. The operation status monitoring module is used to process and analyze the collected operation status parameters to determine whether they belong to normal operating conditions. If they belong to normal operating conditions, the module compares them with the historical operating condition database and selects the best operating condition for energy-saving operation adjustment. If the condition is abnormal, fault diagnosis and early warning will be made based on the prediction results of the running digital twin model, thereby guiding equipment operation and condition adjustment. The operation status monitoring module is also used to control the inlet and the pulverizing screen to close when the float level system detects a rapid rise in the sewage level, and to increase the speed of the non-blocking sewage pump until the prefabricated pumping station returns to a safe water level.

7. The digital twin intelligent control system according to claim 6, characterized in that, The digital twin intelligent control system also includes a communication module; the communication module provides support for multiple interfaces and protocols, including digital signals, analog signals, RS485, and MODBUS.

8. The digital twin intelligent control system according to claim 6, characterized in that, The digital twin intelligent control system supports remote data acquisition and transmission, enabling APP control by uploading data to the cloud; the digital twin intelligent control system is also equipped with automatic recovery and backup mechanisms as well as mechanisms to prevent data loss.

9. The digital twin intelligent control system for the prefabricated sewage lifting pump station according to claim 6, characterized in that, The operation status monitoring module is also used to monitor the operation status of the crushing grid; when it detects that the crushing grid is blocked by solid objects, it automatically sends a protection signal to control the blades to reverse and re-enter after exiting the obstacle.

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