Constant-pressure water supply system for water, electricity and gas system

Abstract

The invention relates to the technical field of constant-pressure water supply systems, and discloses a constant-pressure water supply system for a water, electricity and gas system, which comprises a central control unit, and the central control unit is integrated with a data acquisition and verification module, a data storage unit, an energy collaborative allocation module, a flow leakage module, a prediction regulation and control module and a block chain regulation and control module. Flow data of key nodes of a pipe network are collected, a water pump motor variable-frequency speed regulation control system is connected to obtain motor parameters so as to reversely deduce pipe network pressure and flow data, data collection abnormity is judged through data fusion and data comparison, and a troubleshooting module and a flow leakage module are started when the data collection abnormity is judged. Multi-source data are collected through the data collection and verification module by means of the high-precision flow sensor and the motor parameter monitoring unit, then the data fusion unit fuses, verifies and compares the data through the Kalman filtering algorithm, and the accuracy and reliability of the data are greatly improved through the multi-data-source fusion and real-time verification mechanism.

Description

Technical Field

[0001] The present invention relates to the technical field of constant pressure water supply systems, and more particularly to a constant pressure water supply system for water, electricity and gas systems. Background Art

[0002] In the field of constant pressure water supply systems, with the acceleration of urbanization and the continuous expansion of industrial production, higher requirements are placed on the stability, efficiency and intelligent management of water supply systems. However, existing constant pressure water supply systems have many technical problems: 1. Data collection and processing issues: Traditional water supply system data collection relies on a single data source, resulting in poor accuracy; 2. Pipeline leak detection and treatment issues: Existing technologies have difficulty accurately distinguishing between normal and abnormal flow changes, making it difficult to detect pipeline leaks in a timely manner. After a leak occurs, it is difficult to maintain stable water supply pressure. 3. Energy utilization issues: Low energy utilization efficiency. In traditional water supply systems, the water pump power source configuration is unreasonable, often without considering factors such as energy cost, stability, and water pump operating efficiency, resulting in energy waste and high operating costs. 4. Water and energy consumption forecasting and control issues: Existing technologies cannot accurately predict water and energy consumption trends; 5. Community water supply network management issues: Unscientific water pump operation management and lack of a reasonable alternating operation strategy have resulted in shortened water pump service life and increased maintenance costs; Based on this, the present invention provides a constant pressure water supply system for a water, electricity and gas system to solve the technical problems raised in the above background technology. Summary of the Invention

[0003] In order to overcome the shortcomings of the existing technology, the present invention provides a constant pressure water supply system for water, electricity and gas systems. The present invention uses a data acquisition and verification module, a high-precision flow sensor and a motor parameter monitoring unit to collect multi-source data, and then uses a Kalman filter algorithm to fuse, verify and compare the data in a data fusion unit. This multi-data source fusion and real-time verification mechanism greatly improves the accuracy and reliability of the data. Once the data is abnormal, the troubleshooting process can be started in time, providing a solid data foundation for the precise regulation of the water supply system, effectively avoiding regulation errors caused by inaccurate data, and ensuring the stable operation of the water supply system. This is unmatched by the existing technology.

[0004] To achieve the above objectives, the present invention provides the following technical solutions: a constant pressure water supply system for a water, electricity and gas system, comprising a central control unit, the central control unit integrating a data acquisition and verification module, a data storage unit, an energy coordination and allocation module, a flow leakage module, a prediction and control module, and a blockchain control module; The data acquisition and verification module collects flow data from key nodes in the pipeline network and connects to the water pump motor variable frequency speed control system to obtain motor parameters to infer pipeline network pressure and flow data. Through data fusion and data comparison, it determines data acquisition anomalies and initiates troubleshooting when anomalies occur. The flow leakage module collects pipe network data and water use pattern information, uses a recurrent neural network to build a prediction model, and distinguishes between normal and abnormal flow changes. When an anomaly is detected, it extracts multi-dimensional features and uses a decision tree model to determine whether the pipe network is leaking, thus achieving adaptive pipe network flow regulation and leak detection. The energy coordination module collects data on water, electricity, and gas, optimizes the configuration of water pump power sources, coordinates pressure control, and recovers excess pressure to generate electricity; The prediction and control module collects, processes, and stores multi-source data, uses technology and models to predict water and energy consumption trends in different regions and transmits the results. Based on the results, it builds pump operation plans and establishes model strategies to simulate pump status under different working conditions to optimize and adjust pump operation plans. The blockchain control module deploys smart contracts based on the Ethereum blockchain platform in the community-level water supply network to collect, process and utilize water demand, pump operation and pipe network structure data to achieve dynamic distribution of pump output, complementary pressure regulation, alternating operation management, data security processing and network rule monitoring.

[0005] As a preferred technical solution of the present invention, the data acquisition and verification module includes: High-precision flow sensors: deployed at key nodes in the pipeline network to collect pipeline flow data, convert analog signals into digital signals, and transmit them to the data fusion unit through redundant communication lines; Motor parameter monitoring unit: Connects to the water pump motor variable frequency speed control system to obtain motor current and speed parameters. Using a pressure estimation model based on the motor characteristic curve and motor electromagnetics and fluid mechanics principles, it infers the pipe network pressure and flow, and transmits the results to the data fusion unit. Data fusion unit: Receives data feedback from high-precision flow sensors and motor parameter monitoring units, uses intelligent algorithms to fuse, inspect and compare data in real time, initiates troubleshooting when data is abnormal, and feeds back abnormal information to the central control unit. The data collected and analyzed by the data fusion unit are backed up to the data storage unit in real time.

[0006] As a preferred technical solution of the present invention, the motor parameter monitoring unit also monitors the motor temperature and vibration parameters. When the motor parameter monitoring unit detects data abnormality, it promptly warns the data fusion unit.

[0007] The data fusion unit uses the Kalman filter algorithm to fuse data from different sources.

[0008] As a preferred technical solution of the present invention, the flow leakage module includes: The intelligent algorithm processing unit uses high-precision flow sensors to collect flow data from the historical period of the pipe network, simultaneously collects information related to water usage patterns, cleans the raw flow data, and smoothes it using methods such as moving averages to integrate it into a structured data set. The intelligent algorithm processing unit uses a recurrent neural network as the basic model, divides the structured data set into a training set, a validation set, and a test set, uses historical flow and water use pattern information as input to train the model, and optimizes model performance by adjusting the loss function, parameter update algorithm, and hyperparameters. The trained model receives high-precision flow sensor data in real time, predicts the normal flow range based on the real-time time series data and water use pattern information, and compares the real-time flow with the predicted range, using ±10% as the judgment standard; When the intelligent algorithm processing unit detects an abnormal flow change, it extracts the flow change amplitude, duration, and rate, uses a leakage determination model based on a decision tree algorithm and trained with actual leakage cases to determine whether a leak has occurred, and evaluates the degree of leakage in combination with the physical parameters of the pipeline network; The intelligent algorithm processing unit is provided with an alarm output interface. When a pipeline leak is detected, an alarm signal is promptly sent to the central control unit, which triggers the emergency response process. The water pump operation parameter control unit, after the intelligent algorithm processing unit generates an alarm signal, the water pump operation parameter control unit adjusts the water pump operation parameters, compensates for the pressure loss caused by leakage by adjusting the flow, and maintains a constant water supply pressure.

[0009] As a preferred technical solution of the present invention, the energy coordinated allocation module includes: The energy data acquisition unit is connected to the monitoring equipment at the water, electricity, and gas energy production end to collect real-time data on the generation of water, electricity, and gas energy, as well as the pressure data of the three water, electricity, and gas networks. After standardization, encryption, and transmission verification of the data, it is transmitted to the data analysis and decision-making unit and the pressure coordination control unit respectively; The data analysis and decision-making unit, with built-in optimization algorithms and intelligent models, receives energy generation data transmitted by the energy data acquisition unit, comprehensively considers energy cost, stability, pump operation efficiency and overall system energy consumption factors, calculates the power source combination plan suitable for water pump operation, and transmits the plan instructions to the power source switching control unit. It can also self-learn and adjust parameters based on the system operation history data and real-time feedback; The power source switching control unit controls the water pump power source switching device according to the instructions of the data analysis and decision-making unit, realizing fast and smooth switching of the water pump between different power sources, ensuring that the water pump operates under the optimal power source configuration, and is connected to the water pump power source switching device through a redundant communication line; The pressure coordination control unit receives the three-network pressure data transmitted by the energy data acquisition unit. When the water pressure fluctuates, it uses air pressure to compensate for the water pressure and coordinately adjusts the water pump operating parameters and energy allocation strategy according to the three-network pressure. The energy recovery unit is equipped with a residual pressure power generation device to detect the residual pressure in the pipeline network and use it to generate electricity, and then feed the recovered electric energy back to the electric energy system.

[0010] As an optimal technical solution of the present invention, the energy coordinated allocation module is provided with an energy allocation strategy adjustment interface, and the operator can manually adjust the energy allocation strategy according to actual needs through the external control terminal and intervene in the calculation results of the data analysis and decision-making unit.

[0011] As a preferred technical solution of the present invention, the prediction and control module includes: The multi-source data fusion acquisition unit is connected to the meteorological data interface, geographic information system, urban population flow monitoring system and regional economic activity monitoring platform respectively. It is used to collect weather conditions, topographic features, population flow density, commercial activity data and water supply system equipment energy consumption data in real time. The collected data is standardized and cleaned, and outliers and noise data are removed before classification and storage. The water and energy consumption prediction unit uses big data analysis technology and neural network models, combined with data provided by the multi-source data fusion acquisition unit and historical water and energy consumption data, to predict water demand changes and energy consumption trends in different regions, and transmit the prediction results to the control and prediction unit; The control and prediction unit constructs a predictive operation plan for the water pump based on the water demand forecast results provided by the water use and energy consumption forecast unit, which includes differences in water demand in different time periods and regions, and establishes a water pump operation model strategy to simulate the water pump operation status under predicted working conditions and extreme non-predicted working conditions, so as to optimize and adjust the water pump operation plan.

[0012] As a preferred technical solution of the present invention, the blockchain control module includes: Contract deployment and management unit: Deploy smart contracts based on the blockchain platform in the community-level water supply network, predefine data processing, water pump control, and reward and punishment rules, and monitor and manage network operations; Water demand collection and upload unit: The user side is equipped with a smart water meter, which collects, processes and encrypts water demand data and uploads it to the blockchain platform at set intervals; Pump output dynamic allocation unit: The system uses a particle swarm optimization algorithm to build a multi-objective optimization model based on water demand, pump operation, and pipe network structure data on the blockchain to dynamically allocate pump output to achieve regional pressure balance and optimal energy consumption; Water pressure complementary regulation unit: The blockchain platform records the pressure data of each node, and the smart contract analyzes the pressure deviation to generate adjustment instructions. The instructions are broadcast to the water pump control device via the blockchain. After the equipment executes the instructions, it feedbacks the operating status. The smart contract adjusts the instructions accordingly to maintain constant pressure. Water pump alternating operation management unit: The smart contract formulates the water pump alternating operation strategy, arranges the operation sequence according to the water pump operating time, maintenance cycle and water demand, records the number of starts and stops, issues maintenance reminders when the threshold is reached, and interacts with the equipment maintenance management platform to optimize the strategy.

[0013] As a preferred technical solution of the present invention, the water pressure complementary regulation unit has an emergency regulation mode for responding to sudden changes in water use or equipment failures. The smart water meter in the water demand collection and upload module can update the data collection and processing algorithm through remote firmware upgrades. The particle swarm optimization algorithm regards the output distribution plan of each water pump as a particle and searches for the optimal solution in the solution space. At the same time, combined with fuzzy control theory, the search parameters of the particle swarm are dynamically adjusted according to the water demand, water pump operation and pipeline structure data uploaded to the blockchain platform in real time. Fuzzy control theory uses fuzzy rules to fuzzy the regional pressure deviation and pressure change rate, and determines the adjustment amount of the inertia weight and acceleration constant based on fuzzy reasoning to achieve regional pressure balance and optimal water pump energy consumption.

[0014] As a preferred technical solution of the present invention, it also includes a three-dimensional dynamic monitoring platform with a two-way data connection with the central control unit. The three-dimensional dynamic monitoring platform constructs a 3D scene of the water supply network by accessing and integrating multi-module data, and displays the pipeline flow, pressure, equipment parameters and water, electricity and gas energy data information in real time and intuitively, realizing abnormal monitoring and early warning, prediction and control visualization, and realizing data interaction.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention collects multi-source data through a data acquisition and verification module using a high-precision flow sensor and a motor parameter monitoring unit, and then fuses, verifies and compares the data using a Kalman filter algorithm in a data fusion unit. This multi-data source fusion and real-time verification mechanism greatly improves the accuracy and reliability of the data. Once the data is abnormal, the troubleshooting process can be started in time, providing a solid data foundation for the precise regulation of the water supply system, effectively avoiding regulation errors caused by inaccurate data, and ensuring the stable operation of the water supply system. This is unmatched by existing technologies.

[0016] 2. The flow leakage module of the present invention uses a recurrent neural network to construct a prediction model, which can accurately distinguish between normal and abnormal flow changes. When an anomaly is detected, it extracts multi-dimensional features and uses a decision tree model to determine whether the pipeline network is leaking. It can also evaluate the degree of leakage. Once a leak is detected, the water pump operation parameter control unit will automatically adjust the water pump operation parameters to compensate for the pressure loss caused by the leakage, maintain a constant water supply pressure, effectively reduce water resource waste, reduce the impact of water supply accidents on residents' lives and production, and significantly improve the pipeline network leakage detection and processing capabilities.

[0017] 3. The energy coordination and allocation module of the present invention collects water, electricity, and gas energy data, optimizes the configuration of the water pump power source, calculates the optimal power source combination plan by comprehensively considering energy cost, stability, water pump operation efficiency and overall energy consumption factors of the system, and realizes fast and smooth switching. At the same time, it uses air pressure to compensate for water pressure fluctuations, recovers the excess pressure of the pipeline network to generate electricity, and feeds back the recovered electric energy to the electric energy system, which greatly improves energy utilization efficiency, reduces operating costs, and realizes efficient utilization and recycling of energy, which is difficult to achieve with traditional technologies.

[0018] 4. The prediction and control module of the present invention collects multi-source data such as meteorology, geography, population flow, commercial activities and equipment energy consumption through a multi-source data fusion acquisition unit, and uses big data analysis technology and neural network models to accurately predict changes in water demand and energy consumption trends in different regions. Based on the prediction results, a water pump operation plan is constructed, and the plan is optimized and adjusted by simulating different working conditions. The water pump operation is planned in advance to avoid insufficient or excessive water supply, reduce energy consumption, improve the stability and reliability of the water supply system, and ensure normal water use for residents and enterprises. It has obvious advantages in water use and energy consumption prediction and control.

[0019] 5. The blockchain control module of the present invention deploys smart contracts based on the Ethereum blockchain platform in the community-level water supply network, uses blockchain technology to ensure data security and credibility, and realizes dynamic distribution of water pump output, pressure complementary adjustment, and alternating operation management. The reward and punishment rules formulated by the smart contract can also promote users' rational water use. Through these functions, the intelligence level and operating efficiency of the water supply system are improved, the service life of the water pump is extended, and the difficulties of traditional community water supply network management are solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a functional block diagram of the constant pressure water supply system for water, electricity and gas systems of the present invention; Figure 2 This is a principle block diagram of the data acquisition and verification module of the present invention; Figure 3 This is a principle block diagram of the flow leakage module of the present invention; Figure 4 This is a principle block diagram of the energy coordinated allocation module 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 accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0022] like Figures 1 to 4 As shown, the present invention provides a constant pressure water supply system for a water, electricity and gas system, including a central control unit, which integrates a data acquisition and verification module, a data storage unit, an energy coordinated allocation module, a flow leakage module, a prediction and control module, and a blockchain control module; The data acquisition and verification module collects flow data from key nodes in the pipeline network and connects to the water pump motor variable frequency speed control system to obtain motor parameters to infer pipeline network pressure and flow data. Through data fusion and data comparison, it determines data acquisition anomalies and initiates troubleshooting when anomalies occur. The data acquisition and verification module includes: High-precision flow sensors: deployed at key nodes in the pipeline network to collect pipeline flow data, convert analog signals into digital signals, and transmit them to the data fusion unit through redundant communication lines; Motor parameter monitoring unit: Connects to the water pump motor variable frequency speed control system to obtain motor current and speed parameters. Using a pressure estimation model based on the motor characteristic curve and motor electromagnetics and fluid mechanics principles, it infers the pipe network pressure and flow, and transmits the results to the data fusion unit. The motor parameter monitoring unit also monitors the motor temperature and vibration parameters. When the motor parameter monitoring unit detects abnormal data, it will promptly issue an early warning to the data fusion unit.

[0023] Data fusion unit: Receives data feedback from high-precision flow sensors and motor parameter monitoring units, uses intelligent algorithms to fuse, inspect and compare data in real time, initiates troubleshooting when data is abnormal, and feeds back abnormal information to the central control unit. The data collected and analyzed by the data fusion unit are backed up in real time to the data storage unit; The data fusion unit uses the Kalman filter algorithm to fuse data from different sources; The high-precision flow sensor uses the SN450 flow sensor, which has the characteristics of high precision and strong reliability and can accurately measure the flow data of the pipe network; This solution solves the technical problems of inaccurate data collection, low reliability of single data source, and untimely troubleshooting in traditional water supply systems; Compared with existing technologies, its outstanding beneficial effect is that through the fusion of multiple data sources and real-time verification mechanism, the accuracy and reliability of data are greatly improved, data anomalies can be discovered in a timely manner and the troubleshooting process can be quickly initiated, effectively ensuring the stability and reliability of water supply system data, and providing a solid data foundation for subsequent precise regulation.

[0024] In the water supply system of a large residential complex, a minor blockage in some pipes caused abnormal flow data. Traditional monitoring methods failed to detect it in time. However, this data acquisition and verification module, relying on the collaborative work of high-precision flow sensors and motor parameter monitoring units, quickly detected the data anomaly. Through the fusion analysis of the Kalman filter algorithm, not only the anomaly of the flow data was determined, but also the blockage location was accurately located by combining the motor parameters with reverse calculation, which quickly restored the water supply and ensured the normal water use of residents.

[0025] When the data fusion unit performs data verification, it not only compares the currently collected data, but also analyzes the historical data within a certain period of time; Set a time window of 1 hour. If multiple abnormal data fluctuations occur within this time period, even if the fluctuation amplitude does not exceed the threshold, a more in-depth troubleshooting process will be triggered to ensure data accuracy and system stability. The flow leakage module collects pipe network data and water use pattern information, uses a recurrent neural network to build a prediction model, and distinguishes between normal and abnormal flow changes. When an anomaly is detected, it extracts multi-dimensional features and uses a decision tree model to determine whether the pipe network is leaking, thus achieving adaptive pipe network flow regulation and leak detection. Traffic leakage module, including: The intelligent algorithm processing unit uses high-precision flow sensors to collect flow data from the historical period of the pipe network, simultaneously collects information related to water usage patterns, cleans the raw flow data, and smoothes it using methods such as moving averages to integrate it into a structured data set. The intelligent algorithm processing unit uses a recurrent neural network as its basic model, divides the structured data set into training, validation, and test sets, and uses historical flow and water usage pattern information as input for model training. Model performance is optimized by adjusting the loss function, parameter update algorithm, and hyperparameters. The trained model receives high-precision flow sensor data in real time, predicts the normal flow range based on real-time time series data and water usage pattern information, and compares the real-time flow with the predicted range, using ±10% as the judgment standard. When the intelligent algorithm processing unit detects an abnormal flow change, it extracts the flow change amplitude, duration, and rate, uses a leakage determination model based on a decision tree algorithm and trained with actual leakage cases to determine whether a leak has occurred, and evaluates the degree of leakage in combination with the physical parameters of the pipeline network; The intelligent algorithm processing unit is equipped with an alarm output interface. When a pipeline leak is detected, an alarm signal is promptly sent to the central control unit, which triggers the emergency response process. The water pump operation parameter control unit, after the intelligent algorithm processing unit generates an alarm signal, the water pump operation parameter control unit adjusts the water pump operation parameters, compensates for the pressure loss caused by leakage by adjusting the flow, and maintains a constant water supply pressure.

[0026] This solution solves the technical problems in existing technologies such as difficulty in accurately distinguishing normal and abnormal flow changes, inability to detect pipe network leaks in a timely manner, and difficulty in maintaining stable water supply pressure after a leak occurs. Compared with traditional methods, its outstanding beneficial effect is that it can accurately detect pipe network leaks, issue alarms in time and automatically adjust water pump operating parameters, so as to quickly compensate for pressure loss caused by leakage, effectively reduce water resource waste, and reduce the impact of water supply accidents on residents' lives and production.

[0027] In a certain city's old urban area, the water supply system had multiple potential leakage risks due to aging pipes. Previously, manual inspections made it difficult to detect small leaks in a timely manner. However, after using the flow leakage module, multiple small leaks were successfully detected. The energy coordination module collects data on water, electricity, and gas, optimizes the configuration of water pump power sources, coordinates pressure control, and recovers excess pressure to generate electricity; Energy coordinated deployment module, including: The energy data acquisition unit is connected to the monitoring equipment at the water, electricity, and gas energy production end to collect real-time data on the generation of water, electricity, and gas energy, as well as the pressure data of the three water, electricity, and gas networks. After standardization, encryption, and transmission verification of the data, it is transmitted to the data analysis and decision-making unit and the pressure coordination control unit respectively; The data analysis and decision-making unit, with built-in optimization algorithms and intelligent models, receives energy generation data transmitted by the energy data acquisition unit, comprehensively considers energy cost, stability, pump operation efficiency and overall system energy consumption factors, calculates the power source combination plan suitable for water pump operation, and transmits the plan instructions to the power source switching control unit. It can also self-learn and adjust parameters based on the system operation history data and real-time feedback; The power source switching control unit controls the water pump power source switching device according to the instructions of the data analysis and decision-making unit, realizing fast and smooth switching of the water pump between different power sources, ensuring that the water pump operates under the optimal power source configuration, and is connected to the water pump power source switching device through a redundant communication line; The power source switching control unit and the water pump power source switching device are connected via RS-485 communication interface and Modbus communication protocol for redundant communication; The pressure coordination control unit receives the three-network pressure data transmitted by the energy data acquisition unit. When the water pressure fluctuates, it uses air pressure to compensate for the water pressure and coordinately adjusts the water pump operating parameters and energy allocation strategy according to the three-network pressure. The energy recovery unit is equipped with a residual pressure power generation device to detect the residual pressure in the pipeline network and use it to generate electricity, and then feed the recovered electric energy back to the electric energy system.

[0028] The energy coordinated allocation module is equipped with an energy allocation strategy adjustment interface. Operators can manually adjust the energy allocation strategy according to actual needs through the external control terminal and intervene in the calculation results of the data analysis and decision-making unit.

[0029] The residual pressure power generation device may be a small hydroelectric power generation device; This solution solves technical problems in traditional water supply systems, such as low energy utilization efficiency, unreasonable power source configuration, uncoordinated pressure regulation, and waste of excess pressure energy; Compared with existing technologies, its outstanding beneficial effect is that it realizes the coordinated deployment of multiple energy sources such as water, electricity and gas, optimizes the configuration of water pump power source, improves energy utilization efficiency, reduces operating costs, and realizes energy recovery and reuse through waste pressure power generation; In the water supply system of a certain industrial park, energy consumption and costs were high in the past; After adopting this energy coordinated allocation module, the water pump power source can be reasonably switched according to the energy price and production demand in different time periods; During periods of low electricity prices, electric power is preferred for driving water pumps; Switch to natural gas power source when natural gas supply is stable and price is low; At the same time, air pressure is used to compensate for water pressure fluctuations, reducing energy waste; Through the waste pressure power generation device, the electricity recovered every month can meet the power needs of some auxiliary equipment, greatly reducing the energy costs of the park.

[0030] The prediction and control module collects, processes, and stores multi-source data, uses technology and models to predict water and energy consumption trends in different regions and transmits the results. Based on the results, it builds pump operation plans and establishes model strategies to simulate pump status under different working conditions to optimize and adjust pump operation plans. Prediction and control module, including: The multi-source data fusion acquisition unit is connected to the meteorological data interface, geographic information system, urban population flow monitoring system and regional economic activity monitoring platform respectively. It is used to collect weather conditions, topographic features, population flow density, commercial activity data and water supply system equipment energy consumption data in real time. The collected data is standardized and cleaned, and outliers and noise data are removed before classification and storage. The water and energy consumption prediction unit uses big data analysis technology and neural network models, combined with data provided by the multi-source data fusion acquisition unit and historical water and energy consumption data, to predict water demand changes and energy consumption trends in different regions, and transmit the prediction results to the control and prediction unit; The control and prediction unit constructs a predictive operation plan for the water pump based on the water demand forecast results provided by the water and energy consumption forecast unit, which includes differences in water demand in different time periods and regions. It also establishes a water pump operation model strategy to simulate the operating status of the water pump under predicted conditions and extreme non-predicted conditions, so as to optimize and adjust the water pump operation plan.

[0031] This solution solves the technical problems of existing technologies, such as the inability to accurately predict water and energy consumption trends, and the lack of scientific planning and reasonable regulation of water pump operation; Compared with traditional methods, its outstanding beneficial effect is that it can accurately predict water demand and energy consumption trends in advance, provide scientific and reasonable plans for water pump operation, optimize water pump operation strategies, reduce energy consumption, improve the stability and reliability of the water supply system, and ensure normal water use for residents and enterprises.

[0032] In the water supply system of a large city, due to the inability to accurately predict water demand during hot summer weather, water pumps often under- or over-supply water, resulting in water outages and energy waste in some areas. After adopting this forecasting and control module, by collecting meteorological data, population flow data and commercial activity data, combined with historical water use data, it can accurately predict the changes in water demand in different regions; The water pump operation plan was adjusted in advance based on the forecast results, and the operating frequency and power of the water pump were increased before the peak water usage period, ensuring stable water supply while avoiding energy waste.

[0033] When collecting data, the multi-source data fusion acquisition unit will perform time synchronization processing on data from different data sources; Meteorological data is updated every hour, and population mobility data is updated every 15 minutes. Time synchronization ensures data fusion and analysis on the same time dimension, improving forecast accuracy. At the same time, when constructing the water pump operation plan, the control and prediction unit will not only consider the normal changes in water demand, but also set a certain safety margin; Based on the predicted water demand, add a 10%-20% margin as a reference for water pump operation to cope with sudden increases in water demand and ensure the reliability of water supply.

[0034] The blockchain control module deploys smart contracts based on the Ethereum blockchain platform in the community-level water supply network to collect, process and utilize water demand, pump operation and pipe network structure data to achieve dynamic distribution of pump output, complementary pressure regulation, alternating operation management, data security processing and network rule monitoring.

[0035] Blockchain control module, including: Contract deployment and management unit: Deploy smart contracts based on the blockchain platform in the community-level water supply network, predefine data processing, water pump control, and reward and punishment rules, and monitor and manage network operations; Water demand collection and upload unit: The user side is equipped with a smart water meter, which collects, processes and encrypts water demand data and uploads it to the blockchain platform at set intervals; Smart water meters collect and upload data through the LoRa wireless communication protocol; Pump output dynamic allocation unit: The system uses a particle swarm optimization algorithm to build a multi-objective optimization model based on water demand, pump operation, and pipe network structure data on the blockchain to dynamically allocate pump output to achieve regional pressure balance and optimal energy consumption; Water pressure complementary regulation unit: The blockchain platform records the pressure data of each node, and the smart contract analyzes the pressure deviation to generate adjustment instructions. The instructions are broadcast to the water pump control device via the blockchain. After the equipment executes the instructions, it feedbacks the operating status. The smart contract adjusts the instructions accordingly to maintain constant pressure. Water pump alternating operation management unit: The smart contract formulates the water pump alternating operation strategy, arranges the operation sequence according to the water pump operating time, maintenance cycle and water demand, records the number of starts and stops, issues maintenance reminders when the threshold is reached, and interacts with the equipment maintenance management platform to optimize the strategy.

[0036] The water pressure complementary regulation unit has an emergency regulation mode to deal with sudden changes in water use or equipment failures. The smart water meter in the water demand collection and upload module can update the data collection and processing algorithm through remote firmware upgrades. The particle swarm optimization algorithm regards the output distribution plan of each water pump as a particle and searches for the optimal solution in the solution space. At the same time, combined with fuzzy control theory, the search parameters of the particle swarm are dynamically adjusted according to the water demand, water pump operation and pipeline structure data uploaded to the blockchain platform in real time. Fuzzy control theory uses fuzzy rules to fuzzy the regional pressure deviation and pressure change rate, and determines the adjustment amount of inertia weight and acceleration constant based on fuzzy reasoning to achieve regional pressure balance and optimal water pump energy consumption.

[0037] This solution addresses the technical issues of low data security, unscientific water pump operation management, inaccurate pressure regulation, and lack of effective incentive mechanisms in traditional community water supply networks. Compared with existing technologies, its outstanding beneficial effect lies in the use of blockchain technology to ensure the security and credibility of data, realize scientific management and precise pressure regulation of water pumps, improve the intelligence level and operation efficiency of the water supply system, and at the same time promote users' rational water use through reward and punishment rules.

[0038] In the water supply system of a newly built smart community, the blockchain control module enables scientific management of water pumps and precise pressure regulation; During peak water consumption periods, the dynamic water pump output allocation unit allocates water pump output appropriately based on water demand data on the blockchain, ensuring stable water supply pressure in each area. At the same time, the smart contract rationally arranges the alternating operation of the water pumps based on their operating hours and maintenance cycles, thus extending their service life. When abnormal pressure occurs in a certain area, the water pressure complementary regulation unit quickly starts emergency regulation; It also includes a three-dimensional dynamic monitoring platform with a two-way data connection to the central control unit. The three-dimensional dynamic monitoring platform constructs a 3D scene of the water supply network by accessing and integrating multi-module data, and displays the pipeline flow, pressure, equipment parameters and water, electricity and gas energy data information in real time and intuitively, realizing abnormal monitoring and early warning, prediction and control visualization, and realizing data interaction.

[0039] During operation, the 3D dynamic monitoring platform accesses and integrates data from multiple modules to construct a 3D scene of the water supply network, displaying pipe network flow, pressure, equipment parameters, and water, electricity, and energy data in real time; This solution solves the technical problems that traditional monitoring methods cannot intuitively and comprehensively display the operating status of the water supply system, and that abnormal monitoring, early warning, and predictive control lack visualization. Compared with existing technologies, its outstanding benefit lies in its ability to present water supply system operation data in an intuitive 3D scene, making it easier for operators to understand the system status in real time and detect abnormal situations in a timely manner; By realizing the visualization of abnormal monitoring, early warning, and predictive control, the efficiency of fault handling and the accuracy of control are greatly improved, which helps to improve the overall management level of the water supply system; At the city water supply dispatching center, staff use a three-dimensional dynamic monitoring platform to quickly locate areas with abnormal pipe network pressure and take timely control measures to ensure stable and safe water supply. It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0040] 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. Constant pressure water supply system for water, electricity and gas system, characterized by: It includes a central control unit, which integrates a data acquisition and verification module, a data storage unit, an energy coordination and allocation module, a flow leakage module, a prediction and control module, and a blockchain control module; The data acquisition and verification module collects flow data from key nodes in the pipeline network and connects to the water pump motor variable frequency speed control system to obtain motor parameters to infer pipeline network pressure and flow data. Through data fusion and data comparison, it determines data acquisition anomalies and initiates troubleshooting when anomalies occur. The flow leakage module collects pipe network data and water use pattern information, uses a recurrent neural network to build a prediction model, and distinguishes between normal and abnormal flow changes. When an anomaly is detected, it extracts multi-dimensional features and uses a decision tree model to determine whether the pipe network is leaking, thus achieving adaptive pipe network flow regulation and leak detection. The energy coordination module collects data on water, electricity, and gas, optimizes the configuration of water pump power sources, coordinates pressure control, and recovers excess pressure to generate electricity; The prediction and control module collects, processes, and stores multi-source data, uses technology and models to predict water and energy consumption trends in different regions and transmits the results. Based on the results, it builds pump operation plans and establishes model strategies to simulate pump status under different working conditions to optimize and adjust pump operation plans. The blockchain control module deploys smart contracts based on the Ethereum blockchain platform in the community-level water supply network to collect, process and utilize water demand, pump operation and pipe network structure data to achieve dynamic distribution of pump output, complementary pressure regulation, alternating operation management, data security processing and network rule monitoring.

2. The constant pressure water supply system for water, electricity and gas systems according to claim 1, characterized in that: The data acquisition and verification module includes: High-precision flow sensors: deployed at key nodes in the pipeline network to collect pipeline flow data, convert analog signals into digital signals, and transmit them to the data fusion unit through redundant communication lines; Motor parameter monitoring unit: Connects to the water pump motor variable frequency speed control system to obtain motor current and speed parameters. Using a pressure estimation model based on the motor characteristic curve and motor electromagnetics and fluid mechanics principles, it infers the pipe network pressure and flow, and transmits the results to the data fusion unit. Data fusion unit: Receives data feedback from high-precision flow sensors and motor parameter monitoring units, uses intelligent algorithms to fuse, inspect and compare data in real time, initiates troubleshooting when data is abnormal, and feeds back abnormal information to the central control unit. The data collected and analyzed by the data fusion unit are backed up to the data storage unit in real time.

3. The constant pressure water supply system for water, electricity and gas systems according to claim 2, characterized in that: The motor parameter monitoring unit also monitors the motor temperature and vibration parameters. When the motor parameter monitoring unit detects abnormal data, it will promptly issue an early warning to the data fusion unit. The data fusion unit uses the Kalman filter algorithm to fuse data from different sources.

4. The constant pressure water supply system for water, electricity and gas systems according to claim 1, characterized in that: The flow leakage module includes: The intelligent algorithm processing unit uses high-precision flow sensors to collect flow data from the historical period of the pipe network, simultaneously collects information related to water usage patterns, cleans the raw flow data, and smoothes it using methods such as moving averages to integrate it into a structured data set. The intelligent algorithm processing unit uses a recurrent neural network as the basic model, divides the structured data set into a training set, a validation set, and a test set, uses historical flow and water use pattern information as input to train the model, and optimizes model performance by adjusting the loss function, parameter update algorithm, and hyperparameters. The trained model receives high-precision flow sensor data in real time, predicts the normal flow range based on the real-time time series data and water use pattern information, and compares the real-time flow with the predicted range, using ±10% as the judgment standard; When the intelligent algorithm processing unit detects an abnormal flow change, it extracts the flow change amplitude, duration, and rate, uses a leakage determination model based on a decision tree algorithm and trained with actual leakage cases to determine whether a leak has occurred, and evaluates the degree of leakage in combination with the physical parameters of the pipeline network; The intelligent algorithm processing unit is provided with an alarm output interface. When a pipeline leak is detected, an alarm signal is promptly sent to the central control unit, which triggers the emergency response process. The water pump operation parameter control unit, after the intelligent algorithm processing unit generates an alarm signal, the water pump operation parameter control unit adjusts the water pump operation parameters, compensates for the pressure loss caused by leakage by adjusting the flow, and maintains a constant water supply pressure.

5. The constant pressure water supply system for water, electricity and gas systems according to claim 1, characterized in that: The energy coordinated allocation module includes: The energy data acquisition unit is connected to the monitoring equipment at the water, electricity, and gas energy production end to collect real-time data on the generation of water, electricity, and gas energy, as well as the pressure data of the three water, electricity, and gas networks. After standardization, encryption, and transmission verification of the data, it is transmitted to the data analysis and decision-making unit and the pressure coordination control unit respectively; The data analysis and decision-making unit, with built-in optimization algorithms and intelligent models, receives energy generation data transmitted by the energy data acquisition unit, comprehensively considers energy cost, stability, pump operation efficiency and overall system energy consumption factors, calculates the power source combination plan suitable for water pump operation, and transmits the plan instructions to the power source switching control unit. It can also self-learn and adjust parameters based on the system operation history data and real-time feedback; The power source switching control unit controls the water pump power source switching device according to the instructions of the data analysis and decision-making unit, realizing fast and smooth switching of the water pump between different power sources, ensuring that the water pump operates under the optimal power source configuration, and is connected to the water pump power source switching device through a redundant communication line; The pressure coordination control unit receives the three-network pressure data transmitted by the energy data acquisition unit. When the water pressure fluctuates, it uses air pressure to compensate for the water pressure and coordinately adjusts the water pump operating parameters and energy allocation strategy according to the three-network pressure. The energy recovery unit is equipped with a residual pressure power generation device to detect the residual pressure in the pipeline network and use it to generate electricity, and then feed the recovered electric energy back to the electric energy system.

6. The constant pressure water supply system for water, electricity and gas systems according to claim 5, characterized in that: The energy collaborative allocation module is provided with an energy allocation strategy adjustment interface, and the operator can manually adjust the energy allocation strategy according to actual needs through the external control terminal, and intervene in the calculation results of the data analysis and decision-making unit.

7. The constant pressure water supply system for water, electricity and gas systems according to claim 1, characterized in that: The prediction and control module includes: The multi-source data fusion acquisition unit is connected to the meteorological data interface, geographic information system, urban population flow monitoring system and regional economic activity monitoring platform respectively. It is used to collect weather conditions, topographic features, population flow density, commercial activity data and water supply system equipment energy consumption data in real time. The collected data is standardized and cleaned, and outliers and noise data are removed before classification and storage. The water and energy consumption prediction unit uses big data analysis technology and neural network models, combined with data provided by the multi-source data fusion acquisition unit and historical water and energy consumption data, to predict water demand changes and energy consumption trends in different regions, and transmit the prediction results to the control and prediction unit; The control and prediction unit constructs a predictive operation plan for the water pump based on the water demand forecast results provided by the water use and energy consumption forecast unit, which includes differences in water demand in different time periods and regions, and establishes a water pump operation model strategy to simulate the water pump operation status under predicted working conditions and extreme non-predicted working conditions, so as to optimize and adjust the water pump operation plan.

8. The constant pressure water supply system for water, electricity and gas systems according to claim 5, characterized in that: The blockchain control module includes: Contract deployment and management unit: Deploy smart contracts based on the blockchain platform in the community-level water supply network, predefine data processing, water pump control, and reward and punishment rules, and monitor and manage network operations; Water demand collection and upload unit: The user side is equipped with a smart water meter, which collects, processes and encrypts water demand data and uploads it to the blockchain platform at set intervals; Pump output dynamic allocation unit: The system uses a particle swarm optimization algorithm to build a multi-objective optimization model based on water demand, pump operation, and pipe network structure data on the blockchain to dynamically allocate pump output to achieve regional pressure balance and optimal energy consumption; Water pressure complementary regulation unit: The blockchain platform records the pressure data of each node, and the smart contract analyzes the pressure deviation to generate adjustment instructions. The instructions are broadcast to the water pump control device via the blockchain. After the equipment executes the instructions, it feedbacks the operating status. The smart contract adjusts the instructions accordingly to maintain constant pressure. Water pump alternating operation management unit: The smart contract formulates the water pump alternating operation strategy, arranges the operation sequence according to the water pump operating time, maintenance cycle and water demand, records the number of starts and stops, issues maintenance reminders when the threshold is reached, and interacts with the equipment maintenance management platform to optimize the strategy.

9. The constant pressure water supply system for water, electricity and gas systems according to claim 8, characterized in that: The water pressure complementary regulation unit has an emergency regulation mode for responding to sudden changes in water use or equipment failures. The smart water meter in the water demand collection and upload module can update the data collection and processing algorithm through remote firmware upgrades. The particle swarm optimization algorithm regards the output distribution plan of each water pump as a particle and searches for the optimal solution in the solution space. At the same time, combined with fuzzy control theory, it dynamically adjusts the search parameters of the particle swarm based on the water demand, water pump operation and pipe network structure data uploaded to the blockchain platform in real time. Fuzzy control theory uses fuzzy rules to fuzzify the regional pressure deviation and pressure change rate, and determines the adjustment amount of the inertia weight and acceleration constant based on fuzzy reasoning to achieve regional pressure balance and optimal water pump energy consumption.

10. The constant pressure water supply system for water, electricity and gas systems according to claim 1, characterized in that: It also includes a three-dimensional dynamic monitoring platform with a two-way data connection to the central control unit. The three-dimensional dynamic monitoring platform constructs a 3D scene of the water supply network by accessing and integrating multi-module data, and displays the pipeline flow, pressure, equipment parameters and water, electricity and gas energy data information in real time and intuitively, realizing abnormal monitoring and early warning, prediction and control visualization, and realizing data interaction.

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