Accurate water level electric control water supply system

Abstract

The invention provides a precise water level electric control water supply system, and relates to the technical field of water supply system water level control, and the method comprises the following steps: sensing the water level change and the water inlet flow dynamic state in real time through the cooperative work of a liquid level detection module, a flow monitoring module and a main control module, and determining the water level through the intelligent analysis and decision of the main control module. The opening degree of the water inlet valve is accurately adjusted, the common problems of water level overflow, water shortage and the like of a traditional system are effectively solved, and the stability and reliability of operation of the water supply system are remarkably improved. Meanwhile, the water level variation trend fuzzy rule base is established, the water level trend is pre-judged in combination with real-time data, the opening degree of the water inlet valve is adjusted in advance, the problems of overshoot and oscillation in the water level adjusting process are solved, and the control precision and the response speed under the complex working condition are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of water level control of water supply systems, and in particular to a precise water level electronically controlled water supply system. Background Art

[0002] In modern industrial production and civil water supply, precise water level control is a key link in ensuring stable system operation and efficient resource utilization. Traditional water level control systems mostly use simple devices such as float valves and mechanical switches. These devices rely on physical contact of mechanical structures to achieve control. After long-term use, they are easily affected by impurities, scale, and corrosion in the water, resulting in control contact failure and delayed operation, which in turn leads to problems such as water level loss, overflow, or insufficient water supply. Although some systems have been upgraded to a combination of electronic liquid level sensors and electric valves, there are still obvious shortcomings: the measurement accuracy of a single type of sensor (such as an ultrasonic liquid level sensor) is significantly reduced when faced with complex environmental interference such as steam and foam; the PID control algorithm based on fixed parameters is difficult to adapt to nonlinear and large hysteresis characteristics such as flow fluctuations and changes in pipeline resistance during the water supply process. Water level regulation overshoot and oscillation often occur, and it cannot meet the needs of high-precision water level control.

[0003] With the continuous expansion of industrial production and urban water supply, the limitations of traditional water level control systems have become increasingly apparent. Most current water supply systems still rely on single-point level detection and open-loop control, which cannot accurately capture the spatial distribution of liquid levels in large tanks or complex pipelines. For example, in industrial circulating water systems, flow disturbances and eddy currents can cause localized liquid level anomalies. Single-point detection can easily overlook these changes, making water level control inconsistent with actual demand. Furthermore, existing flow monitoring modules and control units lack deep coordination. When pressure in the water supply pipeline fluctuates or the inflow flow rate suddenly changes, the system cannot adjust valve openings in a timely manner, resulting in significant delays in water level regulation and severely impacting system stability and water supply efficiency. Furthermore, existing water level control systems are severely limited in adaptability under complex operating conditions such as switching between multiple water sources and extreme weather conditions. For example, in municipal water supply systems, when the main water source pressure drops and a switch to a backup source is required, traditional systems struggle to quickly calculate the pressure-flow relationship between the different sources, leading to significant water level fluctuations and even water supply interruptions during the switchover process. Environmental factors (such as temperature changes causing water volume expansion and air pressure fluctuations affecting liquid level measurement) can also significantly interfere with control accuracy, but existing systems generally lack mechanisms to compensate for these environmental parameters. Furthermore, these systems lack fault diagnosis capabilities, unable to predict potential problems such as sensor failure and valve sticking. Once these problems occur, they can easily cause equipment damage or production halts, making them unable to meet the urgent demand for intelligent and highly reliable water supply systems. Summary of the Invention

[0004] An embodiment of the present invention provides a precise water level electronically controlled water supply system, which aims to solve the problem that existing water supply systems are difficult to perceive water level changes and water inlet flow dynamics in real time, resulting in difficulty in accurately controlling the opening of the water inlet valve according to current water level and flow data.

[0005] In order to achieve the above objectives, the present invention provides a precise water level electronically controlled water supply system, comprising a liquid level detection module, a flow monitoring module, a water inlet valve control module and a main control module, wherein: The main control module is provided with a data processing unit for receiving real-time information fed back by the liquid level detection module and the flow monitoring module to control the waterway flow; The liquid level detection module is used to monitor the water level in the water tank in real time and transmit the detection signal to the main control module; the flow monitoring module is used to collect water inlet flow data in real time and transmit it to the main control module; the main control module is used to receive signals from the liquid level detection module and the flow monitoring module, and control the action of the water inlet valve according to the preset logic of the data processing unit; the water inlet valve control module is used to adjust the opening size of the water inlet valve according to the instructions of the main control module; The main control module has a built-in fuzzy prediction control unit, which has established a fuzzy rule library for water level change trends. It combines the current water level and flow data to predict the water level change trend within the next N seconds, and matches the prediction results with the fuzzy rule library to obtain control parameters to adjust the opening of the water inlet valve, where the value of N is 1 to 10 seconds.

[0006] Furthermore, the liquid level detection module adopts a distributed multi-point detection structure, arranges at least three liquid level sensors at different heights of the water tank, constructs a spatial distribution model of the water tank liquid level through a topological data analysis algorithm, identifies local liquid level anomalies caused by water flow disturbances and vortices in the water tank in real time, and corrects the errors caused by single-point detection.

[0007] Furthermore, the flow monitoring module is provided with a flow mutation detection mechanism. When it is detected that the water inlet flow rate changes by more than a set threshold within A seconds, the main control module activates the water hammer effect warning. The main control module combines the pipeline pressure sensor data and controls the water inlet valve to close slowly in stages through the water inlet valve control module, where the value range of A is 1 to 3 seconds.

[0008] Furthermore, the main control module is configured with a multi-water source intelligent switching strategy. When the water pressure of the main water source is lower than the set value or the water quality does not meet the standard, the flow-pressure matching of the backup water source is automatically calculated, and the dynamic programming algorithm is used to optimize the switching path to achieve seamless switching of the main and backup water sources.

[0009] Furthermore, the water inlet valve control module introduces a flexible control algorithm. When the water level approaches the target value, the water inlet valve control module switches the valve opening adjustment mode from fast adjustment to adaptive micro-step adjustment, and dynamically adjusts the adjustment step according to the real-time liquid level deviation. The minimum adjustment step can reach 0.1°.

[0010] Furthermore, the system is equipped with an environmental factor compensation module, which collects ambient temperature and air pressure data in real time, and automatically compensates for liquid level measurement errors caused by water volume expansion or contraction due to temperature changes and air pressure fluctuations by establishing an environmental parameter-water level correction model.

[0011] Furthermore, the main control module adopts a predictive maintenance algorithm. The main control module analyzes the historical data of the liquid level detection module and the flow monitoring module and the sensor working status parameters, uses the LSTM neural network to predict the probability of sensor failure, issues an early warning before the failure occurs, and automatically switches to a redundant sensor.

[0012] Furthermore, the flow monitoring module is equipped with a flow anomaly tracing function. When an abnormal flow data is detected, the main control module automatically retrieves the liquid level, pressure and valve opening data of T minutes before and after, and determines the cause of the anomaly through a predetermined causal analysis algorithm, where the value range of T is 1 to 5 minutes.

[0013] The above technical solution has the following technical effects: Through the collaborative work of the liquid level detection module, flow monitoring module, and main control module, water level changes and inlet flow dynamics are sensed in real time. Through intelligent analysis and decision-making by the main control module, the water inlet valve opening is precisely adjusted, effectively avoiding the common problems of water overflow and water shortage in traditional systems, and significantly improving the stability and reliability of the water supply system. At the same time, by establishing a fuzzy rule library for water level change trends, combined with real-time data to predict water level trends and adjust the water inlet valve opening in advance, the overshoot and oscillation problems in the water level regulation process are completely eliminated, significantly improving control accuracy and response speed under complex working conditions.

[0014] In further embodiments, through multi-sensor layout and topological data analysis, the system can accurately capture the differences in the spatial distribution of liquid levels in large water tanks or water flow disturbance scenarios, effectively eliminate measurement blind spots, ensure the acquisition of true and comprehensive liquid level information, and avoid control misjudgments due to local liquid level anomalies.

[0015] In a further embodiment, the flow monitoring module is provided with a flow mutation detection mechanism, which can quickly identify sudden changes in the water inlet flow, link the pressure sensor data to timely warn of the water hammer effect, and greatly reduce the water hammer impact force by slowly closing the water inlet valve in stages, effectively protecting the pipelines and equipment, extending the system service life, and reducing the risk of failure caused by water hammer impact.

[0016] In a further embodiment, when the main water source is abnormal, the system automatically evaluates the adaptability of the backup water source, optimizes the switching path, and achieves seamless connection between the main and backup water sources, completely solving the common water level fluctuations and water supply interruptions during the switching of multiple water sources, and ensuring the continuity and stability of water supply. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a structural diagram of a precise water level electronically controlled water supply system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0018] To further illustrate various embodiments, the present invention is provided with accompanying drawings. These drawings form part of the present disclosure and are primarily used to illustrate the embodiments and, in conjunction with the relevant description in the specification, to explain the operating principles of the embodiments. By referring to these drawings, one of ordinary skill in the art will understand other possible embodiments and the advantages of the present invention. The components in the figures are not drawn to scale, and similar reference numerals are generally used to represent similar components.

[0019] The present invention will now be further described with reference to the accompanying drawings and specific embodiments. Example 1:

[0020] Figure 1 This is a flow chart of a precise water level electronically controlled water supply system according to an embodiment of the present invention. Figure 1 As shown, the system of this embodiment includes a liquid level detection module, a flow monitoring module, a water inlet valve control module and a main control module, wherein: The main control module is equipped with a data processing unit, which is used to receive real-time information fed back by the liquid level detection module and the flow monitoring module, and control the water flow. Specifically, it controls the action of the water inlet valve according to the preset logic of the data processing unit; Liquid level detection module, used to monitor the water level in the water tank in real time and transmit the detection signal to the main control module; Flow monitoring module, used to collect water inlet flow data in real time and transmit it to the main control module; The water inlet valve control module is used to adjust the opening of the water inlet valve according to the instructions of the main control module; In a specific implementation, the main control module has a built-in fuzzy prediction control unit, which establishes a fuzzy rule library for water level change trends. It combines the current water level and flow data to predict the water level change trend within the next N seconds, and matches the prediction results with the fuzzy rule library to obtain control parameters to adjust the opening of the water inlet valve, where the value of N is 1 to 10 seconds.

[0021] In this embodiment, the precise water level electronically controlled water supply system utilizes a modular design, achieving precise water level control through the efficient collaboration of various functional units. The liquid level detection module, serving as the system's sensor layer, utilizes sensors to monitor the water level in the water tank in real time. The analog signal is converted into a digital signal and transmitted to the main control module, providing the system with essential data on water level changes. The flow monitoring module is responsible for collecting real-time flow data from the water inlet pipe and also provides digital feedback to the main control module. The main control module serves as the system's decision-making hub. Its built-in data processing unit receives this dual-source data and performs in-depth analysis based on pre-set logic algorithms. It determines key indicators such as the deviation between the current water level and the target level and the stability of the inlet flow rate, and then issues instructions to the inlet valve control module. The inlet valve control module, acting as the actuator, precisely adjusts the inlet valve opening according to the main control module's instructions, dynamically controlling the inlet flow rate. This complete closed-loop control system of "data acquisition - analysis and decision-making - execution and feedback" ensures that the water level remains within the target range.

[0022] To further enhance the system's control performance under complex operating conditions, the main control module integrates a fuzzy prediction control unit. This unit constructs a fuzzy rule base for water level change trends based on historical operating data and expert experience. The rule base uses "IF-THEN" conditional statements to divide parameters such as liquid level, flow rate, and liquid level change rate into multiple fuzzy language variables such as "low," "medium," and "high," and establishes a logical mapping relationship between different operating condition combinations and water level change trends. During operation, the fuzzy prediction control unit collects current water level and flow rate data in real time, combines the time series prediction algorithm to calculate the water level change trend within the next N seconds, and matches the prediction results with the fuzzy rule base to select the rules that best fit the current operating conditions. Based on the matching results, the system automatically obtains the corresponding control parameters, such as the adjustment range and adjustment timing of the water inlet valve opening, to achieve early intervention on the water inlet valve. Compared with the traditional PID control method that only relies on the current error for adjustment, this fuzzy prediction mechanism can proactively respond to water level fluctuations and effectively avoid problems such as overshoot and oscillation. Especially in complex scenarios such as sudden changes in water inlet flow and switching of multiple water sources, it greatly improves the dynamic response speed and steady-state accuracy of water level control.

[0023] In one specific implementation, the liquid level detection module adopts a distributed multi-point detection structure, arranges at least three liquid level sensors at different heights in the water tank, and constructs a spatial distribution model of the water tank liquid level through a topological data analysis algorithm. It can identify local liquid level anomalies caused by water flow disturbances and vortices in the water tank in real time, and correct the errors caused by single-point detection.

[0024] In this embodiment, the traditional single-point liquid level detection method can only obtain the liquid level data of a certain position in the water tank, which is difficult to reflect the actual distribution of the liquid level in the water tank. Especially in large water tanks or scenarios with unstable water flow, factors such as water flow disturbance and vortexes can cause local liquid level abnormalities. Single-point detection is prone to measurement deviations and even form detection blind spots, which in turn affects the accuracy of water level control.

[0025] The liquid level detection module in this solution adopts a distributed multi-point detection structure, with at least three liquid level sensors arranged at different heights in the water tank to collect liquid level data in real time from multiple dimensions. These sensors can capture information on liquid level changes in all directions. On this basis, a topological data analysis algorithm is used to deeply process the data from each sensor, converting the discrete liquid level data into a visual spatial distribution model of the water tank liquid level. This model not only intuitively presents the overall situation of the liquid level, but also accurately identifies local liquid level anomalies caused by factors such as water flow disturbances and vortices. By analyzing and correcting these abnormal data, the errors that may be caused by single-point detection are effectively eliminated, making the liquid level data obtained by the system more real and reliable, providing solid data support for the precise decision-making of the subsequent main control module, and significantly improving the adaptability and measurement accuracy of the entire water level control system under complex working conditions.

[0026] In a specific implementation, the flow monitoring module sets a flow mutation detection mechanism. When it is detected that the water inlet flow rate changes by more than a set threshold within A seconds, the main control module activates the water hammer effect warning. Combined with the pipeline pressure sensor data, the water inlet valve control module controls the water inlet valve to close slowly in stages, where the value range of A is 1 to 3 seconds.

[0027] In traditional water supply systems, sudden changes in inflow flow, such as rapid valve opening and closing, or pump startup and shutdown, can easily trigger water hammer. The resulting high-pressure shockwave can severely impact pipelines, valves, and related equipment, leading to pipe ruptures, loose joints, and even equipment damage, posing a significant threat to the safe and stable operation of the system. Conventional flow monitoring methods only record flow values ​​and are unable to respond promptly to sudden flow changes.

[0028] In this embodiment, the flow monitoring module introduces a flow mutation detection mechanism that monitors the inlet flow data in real time. When it detects that the flow rate changes by more than a pre-set threshold within a very short period of A seconds, it is immediately determined to be a flow mutation event and quickly sends an early warning signal to the main control module. After receiving the early warning, the main control module links the pipeline pressure sensor data to accurately assess the potential risk level of the water hammer effect. Subsequently, the main control module issues a command to the water inlet valve control module to initiate a graded slow closing strategy: the water inlet valve is no longer closed once as in the traditional way, but is closed slowly in stages and proportionately, gradually buffering the inertial impact of the water flow and effectively weakening the water hammer pressure peak. Compared with traditional passive response methods, this linkage mechanism based on real-time monitoring, intelligent early warning and precise control can proactively prevent water hammer hazards, significantly reduce the risk of water hammer damage to system equipment, significantly improve the safety and reliability of water supply system operation, and extend the service life of pipelines and equipment.

[0029] In one specific implementation, the main control module configures a multi-water source intelligent switching strategy. When the water pressure of the main water source is lower than the set value or the water quality does not meet the standard, the flow-pressure matching of the backup water source is automatically calculated, and a dynamic programming algorithm is used to optimize the switching path to achieve seamless switching between the main and backup water sources.

[0030] In traditional water level control systems, switching between primary and backup water sources often relies on manual judgment or simple threshold triggering. When the primary water source experiences insufficient water pressure or deteriorating water quality, the backup water source's suitability cannot be quickly assessed. The switching process is prone to significant water level fluctuations and water supply interruptions, severely impacting water supply stability and user experience. Furthermore, traditional switching methods lack comprehensive analysis of water source parameters and path optimization, making it difficult to ensure efficient system operation.

[0031] In this embodiment, the system monitors key indicators such as the water pressure and water quality of the main water source in real time. Once the water pressure of the main water source is lower than the set threshold or the water quality test results do not meet the standards, the main control module immediately starts the intelligent switching process. First, the flow-pressure matching degree of each backup water source is automatically calculated through the built-in algorithm, and its adaptability to the current water demand is comprehensively evaluated; then, a dynamic programming algorithm is used to globally optimize the activation sequence of the backup water sources, the pipeline switching path, etc., and formulate the optimal switching plan. During the execution process, the main control module accurately controls the opening of the water inlet valve, smoothly adjusts the water flow, and ensures seamless switching between the main and backup water sources. The entire process does not require human intervention, which not only avoids water level fluctuations and water supply interruptions during switching, but also minimizes energy loss.

[0032] In one specific implementation, a flexible control algorithm is introduced into the water inlet valve control module. When the water level approaches the target value, the water inlet valve control module switches the valve opening adjustment mode from fast adjustment to adaptive micro-step adjustment, and dynamically adjusts the adjustment step size according to the real-time liquid level deviation. The minimum adjustment step size can reach 0.1°.

[0033] In traditional water level control systems, the inlet valve's regulation is crude, typically employing a single, rapid adjustment strategy. When the water level approaches the target, this one-size-fits-all approach can easily lead to over- or under-regulation. This can cause the water level to overshoot the target due to excessive adjustment, leading to overshoot oscillation. Alternatively, lags in regulation can prevent the water level from reaching the target for extended periods, severely impacting control accuracy and system stability.

[0034] In this embodiment, the water inlet valve control module introduces a flexible control algorithm. Based on an in-depth analysis of the water level control process, when the water level is far from the target value, the fast adjustment mode is preferentially adopted to reduce the liquid level deviation in the shortest time and improve the system response efficiency. When the water level approaches the target value, the system automatically triggers the mode switching mechanism and switches to adaptive micro-step adjustment. In this mode, the water inlet valve control module dynamically adjusts the adjustment step of the valve opening based on the real-time collected liquid level deviation data, with a minimum accuracy of 0.1°. This refined adjustment method effectively avoids overshoot or undershoot problems during the adjustment process, and improves the water level control accuracy by an order of magnitude. It is especially suitable for scenarios such as laboratories and medical equipment that have extremely high requirements for water level stability, greatly improving the reliability and applicability of the water supply system.

[0035] In a specific implementation, the system adds an environmental factor compensation module, which collects ambient temperature and air pressure data in real time. By establishing an environmental parameter-water level correction model, it automatically compensates for the liquid level measurement error caused by water volume expansion or contraction due to temperature changes and air pressure fluctuations.

[0036] In traditional water level control systems, environmental factors often present an invisible interference that impacts control accuracy. Temperature fluctuations cause water to expand and contract, for example, expanding during summer heat and contracting during winter cooler temperatures. If uncorrected, this can lead to significant deviations in level measurements based on fixed volume scales. Air pressure fluctuations also alter the surface pressure of the liquid, affecting the level sensor's results. This interference is particularly pronounced at high altitudes or during drastic weather changes. However, conventional systems often ignore the impact of environmental factors, significantly reducing actual water level control accuracy.

[0037] In this embodiment, the added environmental factor compensation module solves this problem by building an intelligent perception and correction system. This module collects ambient temperature and air pressure data in real time. Based on a large amount of experimental data and thermodynamic principles, the system establishes an accurate environmental parameter-water level correction model, which can quantify the relationship between temperature and air pressure changes and liquid level errors. For example, when a temperature rise is detected, the model will automatically calculate the liquid level change based on the water body expansion coefficient and reversely correct the measurement data; if the air pressure fluctuates, the model will adjust the liquid level value based on the corresponding relationship between pressure and liquid level. Through this dynamic compensation mechanism, the system controls the liquid level measurement error caused by environmental factors to an extremely small range. Even under extreme conditions such as a temperature difference of 20°C or drastic changes in air pressure, it can still ensure high accuracy of water level measurement and control, significantly improving the adaptability and reliability of the system in complex environments.

[0038] In one specific implementation, the main control module adopts a predictive maintenance algorithm. The main control module analyzes the historical data of the liquid level detection module and the flow monitoring module and the sensor working status parameters, uses the LSTM neural network to predict the probability of sensor failure, issues an early warning before the failure occurs, and automatically switches to a redundant sensor.

[0039] In traditional water level control systems, sensor failures often occur suddenly. Once a level or flow sensor fails, the system loses accurate data and falls out of control, potentially leading to abnormal water levels, equipment damage, and even production accidents. Conventional post-fault repairs or scheduled inspections either fail to detect potential failures in advance or lead to excessive and costly maintenance, making it difficult to ensure stable system operation.

[0040] In this embodiment, the main control module incorporates a predictive maintenance algorithm. Leveraging the powerful time-series data analysis capabilities of a long short-term memory (LSTM) neural network, it continuously collects historical data from the liquid level detection and flow monitoring modules. This includes multi-dimensional status information such as sensor output signals, operating hours, and environmental parameters. Through deep learning of this data, the LSTM neural network uncovers potential patterns of sensor performance degradation and potential precursors to failure. For example, if analysis reveals a continuously increasing fluctuation in the measured values ​​of a liquid level sensor and an abnormal data update frequency, the system can accurately predict the probability of its future failure. Once the predicted failure probability exceeds a set threshold, the main control module immediately issues an alert, prompting operations and maintenance personnel to intervene. Simultaneously, it automatically triggers a redundant sensor switching mechanism, seamlessly taking over the work of the faulty sensor, ensuring uninterrupted operation of the water level control system.

[0041] In a specific implementation, the flow monitoring module is equipped with a flow anomaly tracing function. When an abnormal flow data is detected, the main control module automatically retrieves the liquid level, pressure and valve opening data of T minutes before and after, and determines the cause of the anomaly through a predetermined causal analysis algorithm, where the value range of T is 1 to 5 minutes.

[0042] In traditional water supply systems, once flow data anomalies occur, maintenance personnel often rely on manual, inefficient, and time-consuming troubleshooting of pipelines and equipment due to a lack of systematic fault analysis methods. For example, a sudden drop in flow could be caused by a variety of factors, including a pipeline leak, valve failure, or pump anomaly. However, traditional methods make it difficult to quickly identify the root cause, often delaying problem resolution and impacting system performance.

[0043] In this embodiment, the flow monitoring module is equipped with a flow anomaly tracing function, significantly improving fault diagnosis efficiency. When the flow monitoring module detects abnormal flow data fluctuations, such as a sudden increase or decrease, or a sustained deviation from the normal range, the main control module immediately initiates a tracing process, automatically retrieving multi-dimensional operational data such as liquid level, pressure, and valve opening within T minutes before and after the anomaly, thereby building a complete information chain for the system's operating status. The system then applies a causal analysis algorithm to deeply mine and analyze this data. By quantifying the strength of the causal relationships between various parameters, this algorithm identifies the factors most strongly associated with the flow anomaly, accurately pinpointing the root cause of the anomaly. For example, if the analysis reveals a decrease in flow accompanied by a sudden drop in pipeline pressure and no change in valve opening, a pipeline leak is quickly identified. If the pressure remains stable but the valve opening feedback is abnormal, a valve fault is identified. Compared to traditional manual troubleshooting methods, this function reduces fault location time from hours to minutes, significantly improving system fault response time and effectively reducing production losses and safety risks caused by flow anomalies.

[0044] Although the present invention has been particularly shown and described in conjunction with preferred embodiments, it will be understood by those skilled in the art that various changes in form and details may be made to the present invention without departing from the spirit and scope of the invention as defined in the appended claims, and all such changes are within the scope of protection of the present invention.

Claims

1. A precise water level electronically controlled water supply system, characterized in that: It includes liquid level detection module, flow monitoring module, water inlet valve control module and main control module, among which, The main control module is provided with a data processing unit for receiving real-time information fed back by the liquid level detection module and the flow monitoring module, and controlling the water flow, specifically controlling the action of the water inlet valve according to the preset logic of the data processing unit; The liquid level detection module is used to monitor the water level in the water tank in real time and transmit the detection signal to the main control module; the flow monitoring module is used to collect water flow data in real time and transmit it to the main control module; the water inlet valve control module is used to adjust the opening size of the water inlet valve according to the instructions of the main control module; The main control module has a built-in fuzzy prediction control unit, which has established a fuzzy rule library for water level change trends. It combines the current water level and flow data to predict the water level change trend within the next N seconds, and matches the prediction results with the fuzzy rule library to obtain control parameters to adjust the opening of the water inlet valve, where the value of N is 1 to 10 seconds.

2. The precise water level electronically controlled water supply system according to claim 1 is characterized in that: The liquid level detection module adopts a distributed multi-point detection structure, arranges at least three liquid level sensors at different heights of the water tank, and constructs a spatial distribution model of the water tank liquid level through a topological data analysis algorithm.

3. The precise water level electronically controlled water supply system according to claim 1 is characterized in that: The flow monitoring module is equipped with a flow mutation detection mechanism. When it is detected that the water inlet flow rate changes by more than a set threshold within A seconds, the main control module activates the water hammer effect warning. The main control module combines the pipeline pressure sensor data and controls the water inlet valve to close slowly in stages through the water inlet valve control module, where the value range of A is 1 to 3 seconds.

4. The precise water level electronically controlled water supply system according to claim 1 is characterized in that: The main control module is configured with a multi-water source intelligent switching strategy. When the water pressure of the main water source is lower than the set value or the water quality does not meet the standard, the flow-pressure matching degree of the backup water source is automatically calculated and the switching path is optimized using a dynamic programming algorithm.

5. The precise water level electronically controlled water supply system according to claim 1 is characterized in that: The water inlet valve control module introduces a flexible control algorithm. When the water level approaches the target value, the water inlet valve control module switches the valve opening adjustment mode from fast adjustment to adaptive micro-step adjustment, and dynamically adjusts the adjustment step size according to the real-time liquid level deviation.

6. The precise water level electronically controlled water supply system according to claim 1 is characterized in that: An environmental factor compensation module is also provided, which collects ambient temperature and air pressure data in real time, and automatically compensates for liquid level measurement errors caused by water volume expansion or contraction due to temperature changes and air pressure fluctuations by establishing an environmental parameter-water level correction model.

7. The precise water level electronically controlled water supply system according to claim 1 is characterized in that: The main control module adopts a predictive maintenance algorithm. By analyzing the historical data and sensor working status parameters of the liquid level detection module and flow monitoring module, it uses the LSTM neural network to predict the probability of sensor failure, issues an early warning before a failure occurs, and automatically switches to a redundant sensor.

8. The precise water level electronically controlled water supply system according to claim 1 is characterized in that: The flow monitoring module is equipped with a flow anomaly tracing function. When an abnormal flow data is detected, the main control module automatically retrieves the liquid level, pressure and valve opening data of T minutes before and after, and determines the cause of the anomaly through a predetermined causal analysis algorithm, where the value range of T is 1 to 5 minutes.

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