Layered water taking tongue flap gate dual-mode driving control system and method

Abstract

The invention discloses a layered water taking tongue flap gate dual-mode driving control system and method, the system not only can quickly respond to complex hydrological conditions, but also can realize real-time dynamic adjustment in the system operation process, and the problem of excessive adjustment or lagging response is avoided. Through accurate data analysis and real-time control instruction generation, the system has remarkable advantages in the aspects of optimizing water flow control, improving response speed and reducing equipment loss. In addition, the learning module is added, so that the system can be continuously self-optimized, the precision of the control strategy is continuously improved through historical data and operation records, and the overall performance and adaptability of the system are further improved. Compared with a traditional control system, the intelligent and self-adaptive control method has the advantages that the stability, flexibility and accuracy of the system are greatly enhanced, and the management efficiency of water resources and the operation effect of water conservancy projects are remarkably improved.

Description

Technical Field

[0001] This application relates to the field of pump body processing equipment technology, and in particular to a dual-mode drive control system and method for a stratified water intake valve. Background Technology

[0002] Layered intake valves precisely control the inflow or outflow of water into a body by adjusting the opening of the valve, making them crucial equipment in water resource regulation. Therefore, the valve control system is not only a key component of hydraulic engineering but also a core technology for ensuring stable and precise water flow regulation in water resource management.

[0003] Traditional control systems lack sufficient flexibility and real-time response capabilities when faced with sudden hydrological changes. They cannot adapt to rapidly changing water levels or flow rates, resulting in response delays and failing to achieve ideal regulation effects. Traditional control systems typically rely on fixed thresholds and preset rules, lacking dynamic adaptability and predictive capabilities, making them unsuitable for complex and extreme hydrological conditions. Secondly, existing systems cannot quickly switch to appropriate drive modes when there are drastic fluctuations in flow or sudden rises in water levels, affecting regulation accuracy and response speed. These problems make it difficult for existing valve gate control systems to provide stable regulation effects in unpredictable water flow environments, impacting the accuracy of water resource management and the overall operational efficiency of the system. Summary of the Invention

[0004] The main objective of this application is to provide a dual-mode drive control system, device, equipment, and storage medium for a layered water intake valve, in order to solve the problem in the prior art where the transfer of workpieces between different workshops consumes a lot of time, resulting in excessively high time costs for the production of chemical pumps, which further restricts the production efficiency of the pump body.

[0005] To achieve the above objectives, this application provides the following technical solution: A dual-mode drive control system for a stratified water intake valve includes a data interaction module, a control demand analysis module, a drive switching module, a control execution module, and a learning module. The data interaction module is used to collect and preprocess multiple data sets. The control demand analysis module is used to process the data and generate basic demand coefficients and subsequent demand coefficients. The drive switching module is used to analyze the basic demand coefficient and the subsequent demand coefficient, thereby generating control commands and analyzing the timeliness of the control commands. The control execution module is used to switch the mode of the stratified water intake valve. The learning module is used to organize and record adjustment parameters and generate archives.

[0006] Preferably, the data interaction module includes a data acquisition unit and a data preprocessing unit; The data acquisition unit is used to collect parameters of the stratified water intake valve and its surrounding environment, and divides them into basic data group and real-time data group. The basic data components include the valve weight ZA, the maximum valve opening ZB, the minimum valve opening ZC, the basic resistance ZD, the basic water level ZE, the basic flow rate ZF, the basic flow velocity ZG, and the basic signal response time ZH. The real-time data components are real-time opening degree, real-time resistance, real-time water level, real-time flow rate, real-time flow velocity, and real-time information response time. The real-time opening and closing degree is recorded as A1, A2, A3, ..., An according to the timestamp; Real-time resistance is recorded as D1, D2, D3, ..., Dn according to timestamps; Real-time water levels are recorded as E1, E2, E3, ..., En according to timestamps; Real-time traffic is recorded as F1, F2, F3, ..., Fn according to timestamps; Real-time flow rates are denoted as G1, G2, G3, ..., Gn according to timestamps; Real-time information response times are recorded as H1, H2, H3, ..., Hn using timestamps; The data preprocessing unit is used to preprocess and dimensionless the parameters under the basic data set and the real-time data set.

[0007] Preferably, the control requirements analysis module includes a pre-requisite requirements analysis module and a post-requisite requirements analysis module; The pre-demand analysis module performs data integration calculations based on the basic data set, integrating the valve weight ZA, valve maximum opening ZB, valve minimum opening ZC, and basic signal response time ZH with basic resistance ZD, basic water level ZE, basic flow rate ZF, and basic flow velocity ZG to generate the mode selection coefficient MSX. The ratio of the difference between the maximum opening ZB and the minimum opening ZC of the valve reflects the load characteristics of the valve. The ratio between the signal response time ZH and the basic resistance ZD determines the response speed of the valve control system. The comprehensive analysis of water level ZE, flow rate ZF and velocity ZG can accurately reflect the actual water flow conditions. The post-demand analysis module performs data integration calculations based on real-time data, integrating real-time opening and closing degree and real-time information response time with real-time resistance, real-time water level, real-time flow rate and real-time flow velocity to generate the mode change coefficient MSG. The system calculates the average opening value of the valve at multiple time points to reflect its regulation state and trend. It also calculates the average response time of the control signal, which reflects the system's delayed response to the signal. The smaller the response time, the faster the system's regulation. By combining water level and flow rate, the system reflects the complexity of water regulation. The product of flow rate and water level determines the size of the regulation demand and is an important factor in determining the change of valve opening. Finally, it calculates the average flow rate, which affects the stability of the water flow and the speed of valve opening adjustment.

[0008] Preferably, the specific formula for calculating the mode selection coefficient MSX is as follows:

[0009] In the formula: ZA is the weight of the tongue valve, ZB is the maximum opening of the tongue valve, ZC is the minimum opening of the tongue valve, ZH is the basic signal response time, ZD is the basic resistance, ZE is the basic water level, ZF is the basic flow rate, and ZC is the basic velocity.

[0010] Preferably, the specific formula for calculating the mode change coefficient MSG is as follows:

[0011] In the formula: Ai, Hi, Di, Ei, Fi and Gi are the real-time opening degree, real-time resistance, real-time water level, real-time flow rate, real-time flow velocity and real-time information response time at time stamp i, respectively. n is the nth timestamp, and i is the ith timestamp.

[0012] Preferably, the drive switching module includes a command generation unit and a command calibration unit; The command generation unit is used to analyze the mode selection coefficient MSX to determine the activation mode of the stratified water intake valve under the initial condition. The command generation unit is also used to analyze the mode change coefficient MSG to determine whether the operation mode of the stratified water intake valve needs to be changed in the real-time state. The command calibration unit is used to analyze and calibrate the instructions output by the command generation unit.

[0013] Preferably, the command generation unit performs the following specific analysis of the mode selection coefficient MSX: when This indicates that the low-power mode is currently selected, the opening of the lingual valve is below the middle value, and the opening angle is kept within 50% of the maximum opening of the lingual valve. when This indicates that the high-power mode is currently selected, the lingual valve opening is set to the middle value or above, and the minimum opening angle is maintained at 50%-100% of the maximum opening of the lingual valve.

[0014] Preferably, the command generation unit is further used for the specific analysis of the mode change coefficient MSG as follows: If the low power mode is currently selected, when This means no mode adjustment is needed. This indicates that the mode needs to be switched to high power. If the high-power mode is currently selected, when This indicates that it needs to be switched to low power mode. This represents the minimum value of the opening angle that needs to be adjusted, and the new opening angle is greater than 10% of the initial value.

[0015] Preferably, the command calibration unit is used to analyze and verify the instructions output by the command generation unit as follows:

[0016] In the formula: Ai and An-1 are the real-time opening and closing degrees at different timestamps, and Ai is located before An-1. ZA is the weight of the tongue valve, ZB is the maximum opening degree of the tongue valve, ZC is the minimum opening degree of the tongue valve, ZH is the basic signal response time, ZD is the basic resistance, ZE is the basic water level, ZF is the basic flow rate, and ZC is the basic flow velocity. when This indicates that the value in the current window has low real-time performance, and the tongue flap gate will not be switched in mode. when This indicates that the value in the current window is highly real-time and requires mode switching for the tongue flap gate.

[0017] To achieve the above objectives, this application also provides the following technical solutions: A dual-mode drive control method for a stratified water intake valve, comprising the following steps: S1. Collect and preprocess multiple data sets through the data interaction module; S2. By controlling the demand analysis module, the data is processed to generate basic demand coefficients and subsequent demand coefficients; S3. Analyze the basic demand coefficient and the later demand coefficient through the drive switching module to generate control commands and analyze the timeliness of the control commands. S4. Switch the mode of the stratified water intake valve through the control execution module; S5. Organize and record adjustment parameters through the learning module, and generate an archive.

[0018] This system not only responds quickly to complex hydrological conditions but also enables real-time dynamic adjustments during operation, avoiding over-adjustment or delayed response. Through precise data analysis and real-time control command generation, the system demonstrates significant advantages in optimizing flow control, improving response speed, and reducing equipment wear. Furthermore, the addition of learning module 6 allows the system to continuously self-optimize, constantly improving the accuracy of control strategies through historical data and operational records, thereby further enhancing the overall performance and adaptability of the system. Compared to traditional control systems, this intelligent and adaptive control method greatly enhances the system's stability, flexibility, and accuracy, significantly improving water resource management efficiency and the operational effectiveness of water conservancy projects. Attached Figure Description

[0019] Figure 1 This is the system flowchart for this application.

[0020] Figure 2 This is a flowchart illustrating the steps of the method described in this application.

[0021] In the diagram: 1. Data interaction module; 11. Data acquisition unit; 12. Data preprocessing unit; 2. Control requirements analysis module; 21. Pre-requisite requirements analysis module; 22. Post-requisite requirements analysis module; 3. Drive switching module; 31. Command generation unit; 32. Command calibration unit; 4. Control execution module; 5. Learning module. Detailed Implementation

[0022] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0023] The terms "first," "second," and "third" in this application are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified. All directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of this application are only used to explain the relative positional relationships and movements between components in a specific orientation (as shown in the figures). If the specific orientation changes, the directional indications also change accordingly. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0024] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0025] Example 1: Please refer to Figure 1 A dual-mode drive control system for a layered water intake valve includes a data interaction module 1, a control demand analysis module 2, a drive switching module 3, a control execution module 4, and a learning module 5. Data interaction module 1 is used to collect and preprocess multiple data sets; The control demand analysis module 2 is used to process the data and generate basic demand coefficients and subsequent demand coefficients; The drive switching module 3 is used to analyze the basic demand coefficient and the later demand coefficient, thereby generating control commands and analyzing the timeliness of the control commands. Control execution module 4 is used to switch the mode of the stratified water intake tongue valve; Learning Module 5 is used to organize and record adjustment parameters and generate archives.

[0026] In this embodiment, the data interaction module 1 plays a core role in information acquisition and preliminary processing throughout the system. This module collects data in real-time from multiple data sources, covering various key parameters such as water flow, flow velocity, water level, and opening / closing degree, and preprocesses this data. By standardizing, filtering, and denoising the raw data, the accuracy and reliability of the data are ensured, eliminating interference caused by data fluctuations or errors. This module provides high-quality data support for subsequent modules, forming the foundation for precise adjustment and real-time response of the entire control system, and ensuring that the entire system maintains stable and efficient operation during data interaction.

[0027] The Control Demand Analysis Module 2 is a core component of the system's decision-making process, responsible for in-depth analysis and processing of various information collected from the data interaction module. Based on data such as water flow, flow opening, and flow velocity, this module generates basic and subsequent demand coefficients. These coefficients reflect the current and future demand conditions related to water flow changes, accurately guiding subsequent control decisions. Through the calculation and optimization of these demand coefficients, the Control Demand Analysis Module helps the system determine the optimal control strategy, providing a scientific basis for mode switching, thereby improving the accuracy and timeliness of water flow regulation.

[0028] The drive switching module 3 performs in-depth analysis based on the basic and subsequent demand coefficients generated by the control demand analysis module, thereby generating control commands and evaluating their timeliness. The key task of this module is to determine when to switch modes based on hydrological changes and demand fluctuations to optimize the operation of the valve. By analyzing the changing trends of the demand coefficients, the drive switching module can accurately select the most suitable control mode, ensuring that the valve is always in its most effective working state. This module greatly improves the system's adaptability under complex hydrological conditions and avoids the problems of mode switching lag and over-adjustment.

[0029] The control execution module 4 is responsible for actually switching the mode of the stratified intake valve according to the control commands generated by the drive switching module. This module accurately translates the control commands generated by the system into actual operations, adjusting the opening of the valve to ensure precise control of the water flow. Through rapid and accurate execution, the control execution module can respond in a very short time, ensuring that the system can adjust in a timely manner under dynamic hydrological conditions, thereby effectively avoiding control delays or misoperations caused by hydrological changes. The precise execution of this module ensures the efficient operation of the valve under different water flow conditions, enhancing the operational stability of the entire system.

[0030] Learning Module 5 is a key component of the system's intelligence and self-optimization. This module is responsible for organizing and recording the system's adjustment parameters, generating historical archives, and conducting long-term tracking and analysis. By accumulating various operational data and parameter change records, the learning module can continuously optimize control strategies, enabling the system to learn and evolve. Over time, the system can adjust control demand coefficients and operating modes through the analysis of historical data, thereby improving the system's accuracy and adaptability. This module not only enhances the system's intelligence but also provides valuable data support for subsequent technological upgrades and optimization.

[0031] Compared to traditional water flow regulation systems, this system not only responds quickly to complex hydrological conditions but also achieves real-time dynamic adjustments during system operation, avoiding over-regulation or delayed response. Through precise data analysis and real-time control command generation, the system demonstrates significant advantages in optimizing water flow control, improving response speed, and reducing equipment wear. Furthermore, the inclusion of learning module 6 enables the system to continuously self-optimize, constantly improving the accuracy of control strategies through historical data and operational records, thereby further enhancing the overall performance and adaptability of the system. Compared to traditional control systems, this intelligent and adaptive control method greatly enhances the system's stability, flexibility, and accuracy, significantly improving water resource management efficiency and the operational effectiveness of water conservancy projects.

[0032] Example 2: Please refer to Figure 1 The data interaction module 1 includes a data acquisition unit 11 and a data preprocessing unit 12; The data acquisition unit 11 is used to collect parameters of the stratified water intake valve and the surrounding environment, and divides them into basic data group and real-time data group. The basic data components include the valve weight ZA, the maximum valve opening ZB, the minimum valve opening ZC, the basic resistance ZD, the basic water level ZE, the basic flow rate ZF, the basic flow velocity ZG, and the basic signal response time ZH. The real-time data components are real-time opening degree, real-time resistance, real-time water level, real-time flow rate, real-time flow velocity, and real-time information response time. The real-time opening and closing degree is recorded as A1, A2, A3, ..., An according to the timestamp; Real-time resistance is recorded as D1, D2, D3, ..., Dn according to timestamps; Real-time water levels are recorded as E1, E2, E3, ..., En according to timestamps; Real-time traffic is recorded as F1, F2, F3, ..., Fn according to timestamps; Real-time flow rates are denoted as G1, G2, G3, ..., Gn according to timestamps; Real-time information response times are recorded as H1, H2, H3, ..., Hn using timestamps; The data preprocessing unit 12 is used to preprocess and dimensionless the parameters under the basic data set and the real-time data set.

[0033] In this embodiment, the data acquisition unit 11 collects various parameters of the stratified intake valve and its surrounding environment, including valve weight, maximum opening, minimum opening, water level, flow rate, and flow velocity. This allows for comprehensive monitoring and capture of key factors affecting water flow regulation. By dividing these parameters into basic data groups and real-time data groups, the system can clearly distinguish between static and dynamic data, ensuring the scientific organization and management of the data. This precise data acquisition aids in subsequent analysis and decision-making, ensuring that control errors do not occur during mode switching due to incomplete or inaccurate data acquisition.

[0034] The parameters of the real-time data set are recorded with timestamps, accurately reflecting the real-time changes of the system and the dynamic changes of the hydrological environment at different points in time. This time-series recording method provides important time dimension support for subsequent data analysis, enabling precise tracking of the operational history of the valve and any fluctuations in the water flow regulation process, thus ensuring timeliness and accuracy for control demand analysis and mode switching.

[0035] The data preprocessing unit 12 effectively solves problems such as diverse data sources, different units, and inconsistent scales by preprocessing and dimensionlessizing the collected basic and real-time data sets. Dimensionless processing removes the dimensional differences between parameters, enabling comparison and analysis of different data under a unified standard. This not only enhances the comparability between data but also improves the accuracy of subsequent analysis and decision-making. Furthermore, preprocessing removes noise from the data, avoiding erroneous operations caused by data quality issues, further improving the system's stability and control accuracy.

[0036] Through the data acquisition unit 11 and data preprocessing unit 12 in the data interaction module 1, the system can efficiently acquire, preprocess, and dimensionlessly convert various types of water flow regulation-related data. This not only ensures the accuracy and consistency of the data but also provides reliable support for subsequent control analysis, decision-making, and mode switching. Compared to traditional control systems, the data interaction module offers more precise and flexible data processing capabilities, enabling the entire system to react quickly and accurately in dynamically changing hydrological environments, thus improving system stability, intelligence, and real-time response capabilities. These innovative technological improvements make water resource management more efficient and precise, ultimately achieving better water flow control results.

[0037] Example 3: Please refer to Figure 1 The control requirements analysis module 2 includes a pre-requisite requirements analysis module 21 and a post-requisite requirements analysis module 22. The pre-requirement analysis module 21 performs data integration calculations based on the basic data set, integrating the valve weight ZA, the maximum valve opening ZB, the minimum valve opening ZC, the basic signal response time ZH, the basic resistance ZD, the basic water level ZE, the basic flow rate ZF, and the basic flow velocity ZG to generate the mode selection coefficient MSX. The ratio of the difference between the maximum opening ZB and the minimum opening ZC of the valve reflects the load characteristics of the valve. The ratio between the signal response time ZH and the basic resistance ZD determines the response speed of the valve control system. The comprehensive analysis of water level ZE, flow rate ZF and velocity ZG can accurately reflect the actual water flow conditions. The post-demand analysis module 22 performs data integration calculations based on real-time data, integrating real-time opening and closing degree and real-time information response time with real-time resistance, real-time water level, real-time flow rate and real-time flow velocity to generate the mode change coefficient MSG. The system calculates the average opening value of the valve at multiple time points to reflect its regulation state and trend. It also calculates the average response time of the control signal, which reflects the system's delayed response to the signal. The smaller the response time, the faster the system's regulation. By combining water level and flow rate, the system reflects the complexity of water regulation. The product of flow rate and water level determines the size of the regulation demand and is an important factor in determining the change of valve opening. Finally, it calculates the average flow rate, which affects the stability of the water flow and the speed of valve opening adjustment.

[0038] In this embodiment: the pre-demand analysis module 21 generates the mode selection coefficient MSX by integrating and calculating various key parameters in the basic data set. By analyzing the load characteristics of the valve, the ratio between the signal response time ZH and the basic resistance ZD reflects the control response speed of the valve, providing a comprehensive assessment of the system load and response capability. The comprehensive analysis of water level, flow rate, and velocity accurately reflects the actual water flow conditions, providing a precise reference for subsequent mode selection. This module ensures the system's high efficiency adaptability and adjustment accuracy under basic conditions, making the control strategy more scientific and reasonable.

[0039] The post-demand analysis module 22 generates a mode change coefficient (MSG) by integrating and calculating real-time data. This coefficient reflects the adjustment state and trend of the valve, especially by calculating the average opening value at multiple time points, accurately describing the valve's adjustment process. By calculating the average response time of the control signal in real time, it reflects the system's delayed response to the control signal. The shorter the response time, the faster the system adjusts, and the more promptly the system can react to changes in water flow, improving the accuracy and timeliness of water flow regulation.

[0040] The synergistic effect of the pre- and post-modules enables the system to make precise control decisions at different stages. The pre-module demand analysis provides the system with a basis for mode selection based on fundamental data, while the post-module demand analysis provides the system with a basis for dynamic adjustment based on real-time data. By continuously analyzing factors such as the valve's adjustment status, response time, and flow characteristics, the system can make real-time and efficient adjustment decisions, ensuring that the valve can adjust to the most suitable opening in a timely manner under complex and sudden hydrological changes, avoiding problems of adjustment lag or over-adjustment.

[0041] The control demand analysis module 2 provides precise mode selection and switching criteria for the operation of the valve flap. Compared to traditional fixed-rule control systems, this module optimizes the system's regulation decisions through in-depth analysis of basic and real-time data, improving response speed and accuracy. Whether in a stable water flow environment or under sudden hydrological changes, the system can respond quickly and flexibly, significantly improving the efficiency of water flow regulation and the system's adaptability. Simultaneously, this module's design enhances the system's intelligence level, enabling it to continuously optimize control strategies based on historical data and real-time changes, driving water resource management towards a more efficient and precise direction.

[0042] Example 4: Please refer to Figure 1 The specific formula for calculating the mode selection coefficient MSX is as follows:

[0043] In the formula: ZA is the weight of the tongue valve, ZB is the maximum opening of the tongue valve, ZC is the minimum opening of the tongue valve, ZH is the basic signal response time, ZD is the basic resistance, ZE is the basic water level, ZF is the basic flow rate, and ZC is the basic velocity.

[0044] In this embodiment, the MSX calculation formula reflects the load characteristics of the lingual valve. By calculating this ratio, the adjustment capability of the lingual valve at different opening degrees can be accurately evaluated. The load characteristics of the lingual valve are a key factor determining its adjustment efficiency; the greater the load, the higher the complexity and difficulty of system adjustment. Therefore, calculating the load characteristics provides a scientific basis for system mode selection, ensuring that the system can adjust appropriately under high loads and avoiding slow or inaccurate adjustment due to excessive load.

[0045] The formula reflects the ratio between the basic signal response time and the basic resistance, which determines the system's response speed to control signals. A shorter signal response time indicates that the system can react more quickly to control signals, thus improving the regulating efficiency of the valve. This indicator is crucial for hydraulic engineering in dealing with rapidly changing hydrological conditions, ensuring timely responses at critical moments and preventing water loss or equipment damage due to delayed responses.

[0046] This part of the calculation reflects the relationship between water level, flow rate, and minimum opening, comprehensively considering the current actual flow conditions. The product of water level ZE and flow rate ZF accurately assesses the current water body's regulation needs, while the minimum opening ZC serves as the system's regulation limit, reflecting the lower limit of the valve's regulation. This part of the calculation helps the system determine the regulation needs under different flow conditions and select the appropriate regulation mode in a timely manner based on changes in water level and flow rate, thereby improving the water body's regulation accuracy and the system's stability.

[0047] By comprehensively considering factors such as the valve's load, signal response, resistance, water level, and flow rate, the MSX coefficient can accurately assess the system's regulatory capability and adaptability under basic conditions. This provides a quantitative basis for selecting the valve's control mode, ensuring efficient operation under different water flow conditions. Whether in a stable water flow environment or under conditions of significant water level fluctuations, the system can determine the effectiveness of the current operation based on the MSX coefficient, thereby achieving more flexible and precise water flow regulation.

[0048] Example 5: Please refer to Figure 1 The specific formula for calculating the mode change factor (MSG) is as follows:

[0049] In the formula: Ai, Hi, Di, Ei, Fi and Gi are the real-time opening degree, real-time resistance, real-time water level, real-time flow rate, real-time flow velocity and real-time information response time at time stamp i, respectively. n is the nth timestamp, and i is the ith timestamp.

[0050] In this embodiment, the formula calculates the average real-time opening and closing degree of the lingual valve over a period of time. By calculating the average opening and closing degree, the adjustment status and trend of the lingual valve can be accurately reflected, allowing us to understand whether the lingual valve is working stably or whether there is over- or under-adjustment. This information can provide a basis for subsequent mode switching, ensuring that the system makes corresponding adjustments based on the actual adjustment status of the lingual valve.

[0051] This represents the average real-time response time, measuring the degree of delay in the system's response to control signals. By calculating the average response time, the system can monitor signal response delays in real time, ensuring the real-time performance and sensitivity of the control system. A shorter response time allows for faster system adjustments, avoiding problems such as water runoff or adjustment lag caused by reaction delays.

[0052] The average real-time resistance was calculated in part. Resistance is a crucial factor affecting the flow rate regulation of the valve, and changes in real-time resistance can directly impact the flow velocity and the difficulty of regulation. By calculating the average resistance, the system can assess the current flow conditions and adjust the control strategy in a timely manner, ensuring that the valve always operates at high efficiency.

[0053] This section uses the product of real-time water level and real-time flow rate as a comprehensive indicator, reflecting the complexity of water flow regulation. The product of water level and flow rate determines the current regulation demand, accurately reflecting the system's workload and regulation intensity. Through this calculation, the system can determine whether to adjust the opening of the valve to meet current water flow regulation needs when water level and flow rate change.

[0054] The average real-time flow velocity was calculated. Flow velocity is a crucial factor affecting flow stability and the speed of valve opening adjustment. Excessive flow velocity can lead to flow instability, while insufficient flow velocity can result in a slow valve response. By calculating the average flow velocity, the system can assess the current flow conditions and adjust the valve opening accordingly, thereby ensuring flow stability and valve adjustment efficiency.

[0055] By calculating the Mode Change Coefficient (MSG), this formula enables a comprehensive assessment of the valve's regulation status. It comprehensively considers multiple factors, including real-time opening and closing degree, resistance, water level, flow rate, velocity, and response time, thus providing a scientific basis for adjusting the valve's operating mode. Compared to traditional control methods, MSG can reflect the system's regulation status and flow conditions in real time, allowing the control system to react quickly to rapid or sudden changes in flow, avoiding problems of regulation lag or over-regulation. This mechanism enhances the intelligence of the valve control system, strengthens its adaptability to complex hydrological conditions, and improves the accuracy and efficiency of water resource management. Example 6: Please refer to Figure 1 The drive switching module 3 includes a command generation unit 31 and a command calibration unit 32; Command generation unit 31 is used to analyze the mode selection coefficient MSX to determine the start-up mode of the stratified water intake valve under the initial condition. Command generation unit 31 is also used to analyze the mode change coefficient MSG to determine whether the operation mode of the stratified water intake valve needs to be changed in the real-time state. The command calibration unit 32 is used to analyze and calibrate the instructions output by the command generation unit 31.

[0056] The specific analysis of the mode selection coefficient MSX by command generation unit 31 is as follows: when This indicates that the low-power mode is currently selected, the opening of the lingual valve is below the middle value, and the opening angle is kept within 50% of the maximum opening of the lingual valve. when This indicates that the high-power mode is currently selected, the lingual valve opening is set to the middle value or above, and the minimum opening angle is maintained at 50%-100% of the maximum opening of the lingual valve.

[0057] In this embodiment, the command generation unit 31 analyzes the mode selection coefficient MSX to accurately determine the activation mode of the stratified intake valve in the initial state. The MSX coefficient provides a preliminary judgment basis for the system based on multiple factors such as the valve's load characteristics, response speed, and water flow regulation requirements. Through this analysis, the system can select an appropriate activation mode under different hydrological conditions, ensuring that the valve can quickly enter its optimal working state in the initial stage of activation, thereby reducing fluctuations and errors during system startup and improving startup stability and efficiency.

[0058] The command generation unit 31 also analyzes the mode change coefficient (MSG) under real-time conditions to determine whether the operation mode of the valve needs to be changed. The MSG coefficient combines real-time data such as the valve's opening degree, resistance, water level, flow rate, and velocity, accurately reflecting the current flow conditions and the valve's adjustment requirements. When the system detects a change in flow conditions or adjustment requirements, the command generation unit determines whether the valve's operation mode needs adjustment. This dynamic adjustment mechanism ensures that the valve can quickly switch to the optimal operating mode based on real-time hydrological changes, improving control flexibility and adaptability.

[0059] Through precise analysis by the command generation unit 31, the system can flexibly adjust the activation method and operating mode of the valve according to actual needs in both initial and real-time states. This allows the system to quickly adapt to changes in water flow, reducing control response delays and improving the overall response speed and adjustment accuracy. Whether under stable water flow conditions or in the face of sudden hydrological changes, the system can react rapidly, ensuring the valve is always in its optimal adjustment state.

[0060] The command calibration unit 32 analyzes and verifies the commands output by the command generation unit 31 to ensure the accuracy and effectiveness of the commands. This calibration process can correct command deviations that may be caused by data errors or external interference, and avoid improper operation of the valve valve due to command errors. By calibrating the commands, the system can reduce misoperations and avoid problems such as over-adjustment or adjustment lag, thereby improving control accuracy and system stability.

[0061] The drive switching module 3, through the coordinated operation of the command generation unit 31 and the command calibration unit 32, ensures that the valve can make rapid and precise adjustments under different water flow environments. Compared with traditional control systems, this module not only performs refined analysis of water flow regulation through the mode selection coefficient MSX and mode change coefficient MSG, but also reduces misoperation and delayed response through the command calibration mechanism, thereby improving the working stability and accuracy of the valve. Overall, this module makes the system more flexible and intelligent in response to sudden hydrological changes, improving the efficiency of water resource regulation and the operational reliability of water conservancy projects.

[0062] Example 7: Please refer to Figure 1 The command generation unit 31 is also used for the specific analysis of the mode change coefficient MSG as follows: If the low power mode is currently selected, when This means no mode adjustment is needed. This indicates that the mode needs to be switched to high power. If the high-power mode is currently selected, when This indicates that it needs to be switched to low power mode. This represents the minimum value of the opening angle that needs to be adjusted, and the new opening angle is greater than 10% of the initial value.

[0063] In this embodiment, the command generation unit 31 determines whether the operating mode of the valve needs to be adjusted based on the value of MSG. In low-power mode, when MSG ≤ R, the system determines that no mode adjustment is needed in the current state, and can maintain stable operation in low-power mode. This mechanism avoids unnecessary mode switching, reduces energy consumption, and improves the system's energy efficiency. Only when MSG > R will the system switch to high-power mode to meet higher adjustment requirements. This intelligent judgment and mode switching can help the system optimize power usage in real time according to water flow changes, avoiding over-adjustment or unnecessary power waste.

[0064] In high-power mode, command generation unit 31 further optimizes the control strategy of the valve based on the MSG value. When MSG > R, the system adjusts the opening angle of the valve to ensure more precise water flow regulation. At this time, the system increases the valve opening angle, with the new angle being more than 10% greater than the initial value. This strategy ensures that in high-power mode, the system can more efficiently respond to sudden changes in water flow or higher regulation demands, avoiding insufficient regulation or lag due to an excessively small opening angle.

[0065] By comparing MSG with a threshold R, the command generation unit 31 can determine whether a mode switch is needed. This mechanism ensures that the system can dynamically adjust its operating mode under different hydrological conditions, avoiding unnecessary energy consumption when mode switching is not required. For example, when MSG ≤ R, the system determines that the current mode is sufficient to meet the requirements, eliminating the need to switch to a high-power mode, thereby effectively reducing energy consumption and extending the lifespan of the equipment. This optimization mechanism improves the system's energy efficiency, ensuring water flow regulation while reducing energy waste.

[0066] In high-power mode, when MSG>R, the system achieves more precise regulation by increasing the opening angle of the valve. The new opening angle is 10% larger than the initial value, enabling the system to respond and regulate more sensitively in high-power mode. This adjustment can cope with larger changes in water flow, improve the valve's regulation accuracy, and thus ensure effective control of water level and flow under complex hydrological conditions, avoiding over-regulation or under-regulation.

[0067] The command generation unit 31 can adaptively switch between the low-power mode and the high-power mode based on real-time data through intelligent analysis of the mode change coefficient MSG, ensuring that the system always operates in the best state. Whether it is energy optimization in the low-power mode or precise adjustment of the flap gate opening in the high-power mode, the system can achieve flexible dynamic responses according to the water flow regulation requirements. This mechanism enables the flap gate control system to cope with various water flow changes, improving the energy utilization efficiency, regulation accuracy, and response speed. Compared with traditional control methods, it enhances the intelligence level and overall performance of the system, especially showing higher flexibility and stability under complex and sudden hydrological change conditions.

[0068] Example 8: Please refer to Figure 1 , the command calibration unit 32 is used to analyze and proofread the instructions output by the command generation unit 31 as follows:;

[0069] In the formula: Ai and An-1 are the real-time opening and closing degrees at different timestamps, and Ai is before An-1. ZA is the weight of the flap gate, ZB is the maximum opening of the flap gate, ZC is the minimum opening of the flap gate, ZH is the basic signal response time, ZD is the basic resistance, ZE is the basic water level, ZF is the basic flow rate, and ZC is the basic flow velocity; When , it represents that the value in the current window has low real-time performance, and no mode switching is performed on the flap gate; When , it represents that the value in the current window has high real-time performance, and mode switching needs to be performed on the flap gate In this embodiment: The calibration unit 32 calculates the instruction effectiveness coefficient ECC to evaluate the real-time performance of the data in the current time window, and then determines whether to perform mode switching on the flap gate. The calculation of ECC is based on the change of real-time opening and closing degrees and other basic parameters, which can accurately measure the speed and accuracy of the system response. When the ECC value is low, the system can identify that the current data has insufficient real-time performance, avoiding premature mode switching, and ensuring that adjustments are only made when the data changes significantly and meets the actual requirements, thereby improving the accuracy of the system response.

[0070] Through dynamic analysis of ECC, when ECC < S, the system determines that the current data change is small or the real-time performance is low, avoiding unnecessary mode switching. This mechanism helps the system reduce frequent mode switching, prevent over-regulation and system instability. For example, when the water level change is small or the opening and closing degree of the flap gate changes little, the system determines that no mode switching is required, thereby effectively reducing the energy consumption of the system and avoiding over-operation.

[0071] When ECC ≥ S, it indicates that the value within the current window has high real-time performance. The system can promptly identify significant changes in water flow and substantial changes in the adjustment requirements of the valve, and then make a decision on whether to switch modes. This allows the valve to quickly switch to a suitable adjustment mode based on changes in water flow and water level, ensuring that the system can make rapid and accurate adjustments under complex hydrological conditions.

[0072] The ECC calculation formula involves various parameters of the valve, such as load characteristics, resistance, water level, and flow rate. The comprehensive calculation of these factors allows the system to fully assess the current adjustment needs of the valve. The command calibration unit 32 uses these parameters to determine whether the valve needs mode switching, thus optimizing control decisions. This mechanism ensures that the valve operates in the optimal control mode, avoiding water loss or resource waste due to inappropriate mode selection.

[0073] Through the ECC analysis and calibration mechanism of the command calibration unit 32, the system can intelligently determine whether to switch modes under different water flow changes, optimizing the regulation effect of the valve. This mechanism avoids unnecessary mode switching, reduces system energy consumption, and improves the accuracy and response speed of water flow regulation. When the system faces complex or sudden hydrological changes, ECC calculation and analysis ensure that the valve can adjust quickly, ensuring stable and efficient water flow regulation. Compared with traditional control systems, the command calibration unit makes the water resource management system more intelligent and energy-efficient, enabling it to quickly and accurately respond to dynamically changing water flow and water level conditions, improving the reliability and operating efficiency of the entire system.

[0074] This application also includes a dual-mode drive control method for a stratified water intake tongue valve gate; please refer to [link / reference needed]. Figure 2 The specific steps are as follows: S1. Collect and preprocess multiple data points through data interaction module 1; S2. By controlling the demand analysis module 2, the data is processed to generate basic demand coefficients and subsequent demand coefficients; S3. The basic demand coefficient and the later demand coefficient are analyzed through the drive switching module 3 to generate control commands and analyze the timeliness of the control commands. S4. Switch the mode of the stratified water intake valve through the control execution module 4; S5. Organize and record the adjustment parameters through learning module 5, and generate an archive.

[0075] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units described above can be implemented in hardware or as software functional units. The above are merely embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made based on the description and drawings of this application, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

[0076] The specific embodiments of the invention have been described in detail above, but they are only examples, and this application is not limited to the specific embodiments described above. For those skilled in the art, any equivalent modifications or substitutions to the invention are also within the scope of this application. Therefore, all equivalent changes, modifications, and improvements made without departing from the spirit and principles of this application should be covered within the scope of this application.

Claims

1. A dual-mode drive control system for a stratified water intake valve, characterized in that: The module consists of a data interaction module (1), a control requirements analysis module (2), a drive switching module (3), a control execution module (4), and a learning module (5). The data interaction module (1) is used to collect and preprocess multiple data. The control demand analysis module (2) is used to process the data and generate basic demand coefficients and subsequent demand coefficients; The drive switching module (3) is used to analyze the basic demand coefficient and the later demand coefficient, thereby generating control commands and analyzing the timeliness of the control commands; The control execution module (4) is used to switch the mode of the stratified water intake valve. The learning module (5) is used to organize and record adjustment parameters and generate archives.

2. The stratified water intake valve dual-mode drive control system according to claim 1, characterized in that, The data interaction module (1) includes a data acquisition unit (11) and a data preprocessing unit (12). The data acquisition unit (11) is used to collect parameters of the stratified water intake valve and the surrounding environment, and divides them into basic data group and real-time data group. The basic data components include the valve weight ZA, the maximum valve opening ZB, the minimum valve opening ZC, the basic resistance ZD, the basic water level ZE, the basic flow rate ZF, the basic flow velocity ZG, and the basic signal response time ZH. The real-time data components are real-time opening degree, real-time resistance, real-time water level, real-time flow rate, real-time flow velocity, and real-time information response time. The real-time opening and closing degree is recorded as A1, A2, A3, ..., An according to the timestamp; Real-time resistance is recorded as D1, D2, D3, ..., Dn according to timestamps; Real-time water levels are recorded as E1, E2, E3, ..., En according to timestamps; Real-time traffic is recorded as F1, F2, F3, ..., Fn according to timestamps; Real-time flow rates are denoted as G1, G2, G3, ..., Gn according to timestamps; Real-time information response times are recorded as H1, H2, H3, ..., Hn using timestamps; The data preprocessing unit (12) is used to preprocess and dimensionless the parameters under the basic data group and the real-time data group.

3. The stratified water intake valve dual-mode drive control system according to claim 2, characterized in that, The control requirements analysis module (2) includes a pre-requisite requirements analysis module (21) and a post-requisite requirements analysis module (22). The pre-demand analysis module (21) performs data integration calculations based on the basic data group, integrating the tongue valve weight ZA, the tongue valve maximum opening ZB, the tongue valve minimum opening ZC, the basic signal response time ZH, the basic resistance ZD, the basic water level ZE, the basic flow rate ZF, and the basic flow velocity ZG to generate the mode selection coefficient MSX. The ratio of the difference between the maximum opening ZB and the minimum opening ZC of the valve reflects the load characteristics of the valve. The ratio between the signal response time ZH and the basic resistance ZD determines the response speed of the valve control system. The comprehensive analysis of water level ZE, flow rate ZF and velocity ZG can accurately reflect the actual water flow conditions. The post-demand analysis module (22) performs data integration calculations based on real-time data, integrating real-time opening and closing degree and real-time information response time with real-time resistance, real-time water level, real-time flow rate and real-time flow velocity to generate the mode change coefficient MSG. The system calculates the average opening value of the valve at multiple time points to reflect its regulation state and trend. It also calculates the average response time of the control signal, which reflects the system's delayed response to the signal. The smaller the response time, the faster the system's regulation. By combining water level and flow rate, the system reflects the complexity of water regulation. The product of flow rate and water level determines the size of the regulation demand and is an important factor in determining the change of valve opening. Finally, it calculates the average flow rate, which affects the stability of the water flow and the speed of valve opening adjustment.

4. The stratified water intake valve dual-mode drive control system according to claim 3, characterized in that, The specific formula for calculating the mode selection coefficient MSX is as follows: In the formula: ZA is the weight of the tongue valve, ZB is the maximum opening of the tongue valve, ZC is the minimum opening of the tongue valve, ZH is the basic signal response time, ZD is the basic resistance, ZE is the basic water level, ZF is the basic flow rate, and ZC is the basic velocity.

5. The stratified water intake valve dual-mode drive control system according to claim 4, characterized in that, The specific formula for calculating the mode change coefficient MSG is as follows: In the formula: Ai, Hi, Di, Ei, Fi and Gi are the real-time opening degree, real-time resistance, real-time water level, real-time flow rate, real-time flow velocity and real-time information response time at time stamp i, respectively. n is the nth timestamp, and i is the ith timestamp.

6. The stratified water intake tongue valve dual-mode drive control system according to claim 4, characterized in that, The drive switching module (3) includes a command generation unit (31) and a command calibration unit (32). The command generation unit (31) is used to analyze the mode selection coefficient MSX to determine the start-up mode of the stratified water intake valve in the initial state. The command generation unit (31) is also used to analyze the mode change coefficient MSG to determine whether the operation mode of the stratified water intake valve needs to be changed in the real-time state. The command calibration unit (32) is used to analyze and calibrate the instructions output by the command generation unit (31).

7. The stratified water intake tongue valve dual-mode drive control system according to claim 6, characterized in that, The specific analysis of the pattern selection coefficient MSX by the command generation unit (31) is as follows: when This indicates that the low-power mode is currently selected, the opening of the lingual valve is below the middle value, and the opening angle is kept within 50% of the maximum opening of the lingual valve. when This indicates that the high-power mode is currently selected, the lingual valve opening is set to the middle value or above, and the minimum opening angle is maintained at 50%-100% of the maximum opening of the lingual valve.

8. The stratified water intake tongue valve dual-mode drive control system according to claim 6, characterized in that, The command generation unit (31) is also used for the specific analysis of the mode change coefficient MSG as follows: If the low power mode is currently selected, when This means no mode adjustment is needed. This indicates that the mode needs to be switched to high power. If the high-power mode is currently selected, when This indicates that it needs to be switched to low power mode. This represents the minimum value of the opening angle that needs to be adjusted, and the new opening angle is greater than 10% of the initial value.

9. The stratified water intake tongue valve dual-mode drive control system according to claim 6, characterized in that, The command calibration unit (32) is used to analyze and calibrate the instructions output by the command generation unit (31) as follows: In the formula: Ai and An-1 are the real-time opening and closing degrees at different timestamps, and Ai is located before An-1. ZA is the weight of the tongue valve, ZB is the maximum opening degree of the tongue valve, ZC is the minimum opening degree of the tongue valve, ZH is the basic signal response time, ZD is the basic resistance, ZE is the basic water level, ZF is the basic flow rate, and ZC is the basic flow velocity. when This indicates that the value in the current window has low real-time performance, and the tongue flap gate will not be switched in mode. when This indicates that the value in the current window is highly real-time and requires mode switching for the tongue flap gate.

10. A dual-mode drive control method for a stratified water intake valve, characterized in that, When the stratified water intake valve dual-mode drive control method is executed, it can realize the stratified water intake valve dual-mode drive control system as described in any one of claims 1 to 9. The specific steps are as follows: S1. Collect and preprocess multiple data points through the data interaction module (1); S2. The data is processed by the control demand analysis module (2) to generate basic demand coefficients and later demand coefficients; S3. The basic demand coefficient and the later demand coefficient are analyzed by the drive switching module (3) to generate control instructions and analyze the timeliness of the control instructions. S4. The stratified water intake valve mode is switched by the control execution module (4); S5. Organize and record adjustment parameters through learning module (5) and generate archive.

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