Water taking method and system of stepping type water taking device

Abstract

The invention relates to a water taking method and system of a stepping type water taking device, and belongs to the technical field of intelligent water temperature control and water level management. The method comprises the following steps: acquiring stepping water intake data, and constructing a water temperature-water level bimodal curve to divide the water level into a high-temperature area, a buffer area and a heating area to obtain water temperature stable data; a water taking optimization model is constructed to calibrate the maintenance mapping logic of the stepping water level interaction management on the water temperature state and the water level state, water injection demand information is marked for the stepping water level interaction management through a structural stability calibration method, and a stepping water taking scheme is generated; for the water level change test, activating a cold and hot mixed area of a water tank buffer area by controlling a small amount of multiple times of dynamic water replenishing, and selecting a water taking mode; and establishing a monitoring-water replenishing-rechecking closed-loop flow, when the water temperature deviation in the water tank is detected, controlling the overall water temperature and stage buffering of the water tank in the water taking process, and performing stable verification on the water taking mode based on the water temperature-water level performance change.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of intelligent water temperature control and water level management, and specifically relates to a water taking method and system of a step-by-step water taker. BACKGROUND

[0002] With the rapid development of intelligent household appliances and drinking water equipment, the first batch of water takers has entered a 3-5 year use cycle, with an average water temperature fluctuation rate of 5.2%, a three-year stable performance shrinkage of more than 15%, and a replacement cost of up to 1-3 thousand yuan. The value of second-hand equipment is deeply affected by the water temperature stability (SOT) and water zone deviation. Users face five major anxieties: temperature anxiety, economic burden, no maintenance, invisible data, and residual value depreciation. Most stores only provide detection + replacement services, lacking "non-destructive intelligent maintenance" means. High-frequency use of household or office equipment, as well as long-term idle water takers, all face maintenance needs. The performance fluctuation and stability of the water tank under high-frequency water taking conditions are increasingly prominent, for example, common faults of traditional water dispensers include no cooling, no heating, water flow blockage, water leakage, and odor, which are often caused by power failure, improper bottle installation, thermostat maladjustment, or filter blockage, resulting in decreased user experience and additional repair costs.

[0003] Traditional water level management systems (WMS) mainly rely on overall monitoring and whole-tank water replenishment control, which is difficult to accurately perceive the high-temperature zone and temperature decay characteristics of the water zone, especially in the water replenishment scenario, which can easily lead to increased water zone deviation, local overcooling and overheating, and shortened equipment life. For example, a one-time large amount of cold water replenishment can cause a sudden drop in water temperature, and users need to wait a long time for heating to recover; at the same time, repeated boiling can produce "thousand boiling water", affecting water quality safety. Existing water taking methods usually use one-time water replenishment or invasive detection, such as disassembling and checking the filter or heating element, which poses potential risks to the water tank structure and system stability, and cannot achieve real-time dynamic optimization and remote management. In addition, existing water replenishment and taking technologies mostly rely on fixed water volume or constant replenishment and taking strategies, lack of fine control and adaptive optimization capability for water zone stable state, and are difficult to effectively delay temperature decay and deviation growth, and also cannot form a closed-loop monitoring-replenishment-reinspection process. Ignoring maintenance will also lead to rising hidden costs, such as pipe corrosion, electrical damage, health risks (medical expenses caused by water pollution), and energy waste (increased electricity costs due to low efficiency).

[0004] With the application of cloud computing and Internet of Things (IoT) technologies, intelligent water dispensers are evolving towards automation and interconnection. IoT sensors can monitor water quality, temperature, and water level in real time, supporting predictive maintenance and remote control, such as viewing consumption, detecting leaks, and optimizing water use through mobile apps. However, many systems at this stage still do not fully integrate these technologies. How to achieve step-by-step data collection, stable evaluation, water replenishment strategy optimization, and remote closed-loop management through water level sensors without changing the internal structure of the water tank has become a technical problem that needs to be solved. Although existing IoT water quality monitoring systems can provide cost-effective solutions, they still have limited fine-grained applications for temperature control, making it difficult to fully address the pain points of traditional devices such as insensitive thermostats, uneven heating and cooling, and high maintenance costs.

[0005] The present application proposes a step-by-step water dispenser water taking method, which realizes water temperature life extension, stable operation, and water taking efficiency optimization through step-by-step data collection, bimodal stable curve construction, optimization model deduction, closed-loop monitoring, and platform collaboration. It overcomes the technical defects of insufficient water zone temperature state perception, fixed water replenishment strategy, and lack of closed-loop management in existing technologies. Among them, the water tank is dynamically divided into high-temperature zone, buffer zone, and heating zone by three water level sensors to achieve "small amount and multiple times" water replenishment and eliminate rolling water and uneven heating and cooling. This method does not require invasive intervention, reduces operational risk, improves device implementability and user satisfaction. In high-frequency water taking scenarios, it not only effectively suppresses deviation growth and water zone temperature deviation, but also prolongs the service life of the water tank, reduces energy consumption, and provides data support and intelligent decision-making basis for stable operation and remote management of the water tank. Overall, the present application promotes the sustainable development of intelligent drinking water equipment and significantly alleviates users' concerns about maintenance and costs. SUMMARY

[0006] To solve the above problems in the prior art, the present application provides a step-by-step water dispenser water taking method, The object of the present application can be achieved by the following technical solutions: S1: Obtain step-by-step water replenishment data, construct a water temperature-water level bimodal curve based on water level and water temperature parameters in the step-by-step water replenishment data, divide the water tank into high-temperature zone, buffer zone, and heating zone according to water level, and obtain water temperature change data by detecting the change amplitude of water level during the water replenishment test; S2: Construct a water taking optimization model based on the water temperature-water level bimodal curve, input the water temperature stability data as input parameters into the step-by-step water taking model, calibrate the maintenance mapping logic of the step-by-step water level interaction management for water temperature state and water level state, and label the water replenishment demand information of the step-by-step water level interaction management through structural stability calibration method to generate a step-by-step water replenishment scheme; S3: The step-by-step water replenishment scheme replenishes the water tank in small amounts multiple times. When the water temperature is sufficient and the water level is below the high-temperature zone, only cold water is injected and the existing high-temperature water is used to heat the cold water. By controlling the small amount of dynamic replenishment multiple times, the cold-hot mixing area of the water tank buffer zone is activated, and the water temperature fluctuation period is verified based on the temperature feedback incentive method. Select the water taking mode; S4: Establish a monitoring-water replenishment-reinspection closed loop process. When the water temperature deviation in the water tank is detected, control the overall water temperature in the water tank during the water taking process through batch water replenishment strategy, and adjust the water temperature heating bias value according to the water level change in the water tank. Only heating in the heating zone, stable verification of the water taking mode.

[0007] Specifically, the step-by-step water replenishment data acquisition method is: synchronously sampling water temperature and flow data by water level flow meter for zero point calibration, setting step-by-step water taking mode and obtaining water level, water temperature and water taking time information during water taking stage, aligning water taking flow with segmented water level and water temperature curve into structured data frame by flow synchronization, and obtaining step-by-step water taking data.

[0008] Specifically, the water tank water level division method is: based on the water temperature gradient characteristics corresponding to the water temperature-water level bimodal curve, according to the temperature change rate at different water level heights of the water tank, the upper thermal stable layer with stable temperature and gradient approaching is divided into high-temperature zone; then the middle mixed layer with water temperature decreasing and gradient absolute value increasing after water replenishment is regarded as buffer zone; then the water level section close to heating element is divided into heating zone with the characteristics of rapid temperature rise after water replenishment and large temperature recovery speed and gradient.

[0009] Specifically, the water temperature-water level bimodal curve construction method is: Under the condition of step-by-step water level sensor, the water replenishment and water taking process of water tank in each water level state interval is monitored through step-by-step water level interaction management, the corresponding water level increment and temperature attenuation characteristics are recorded, and the temperature change rate and water level response rate are calculated by difference temperature level analysis method; The water temperature-water level bimodal state curve is constructed with water level as horizontal axis and water temperature stability as vertical axis, and the difference temperature level characteristics and water temperature retention rate are taken as fusion variables through multi-modal feature fusion algorithm. The nonlinear mapping relationship between stability and water level response is established by fitting the corresponding peak value in the water replenishment and water taking process.

[0010] Specifically, the water temperature change data generation method is: based on the water temperature response characteristics extracted from the water temperature-water level bimodal state curve, the heat attenuation growth rate and water temperature retention rate index are calculated, and compared with the water tank temperature maintenance time, to generate water temperature change data.

[0011] Specifically, the step-by-step water taking model construction method is: With the water temperature stability data and the water temperature-water level bimodal state curve as input variables, analyze the water temperature performance fluctuation and temperature recovery data, and through collecting the temperature and water level change parameters of the water tank in the water replenishment and water taking cycle, construct a water tank state water replenishment parameter set; Based on the water tank state water replenishment parameter set, a nonlinear mapping algorithm from the water temperature stable state to the water replenishment strategy is constructed, which maps the water tank water taking calibration data to the stable curve of the water tank in the standard initial stable state in the calculation process, analyzes the thermal efficiency and temperature recovery rate index, and establishes a water temperature stability performance evaluation function; The stable performance evaluation function calculates the stable change of the water tank in different water quantity state intervals by analyzing the temperature response sensitivity coefficient and the water level dynamic weight, and constructs a step water taking model combined with the water level increment and temperature attenuation characteristics of the water tank in the water replenishment and water taking process.

[0012] Specifically, the water taking mode includes: fast replenishment and water taking mode, cycle water taking mode; The fast replenishment and water taking mode: based on the medium-high water level state temperature repair strategy of dynamic small amount adjustment, using the high temperature zone to retain hot water to quickly heat and inject cold water combined with the medium-high water level interval state, and according to the small amount of cold water step micro water replenishment mechanism, controlling the dynamic perception and real-time adjustment of water temperature interval deviation and hot mixed mild activation reaction; The cycle water taking mode: based on the water tank state reconstruction mechanism of water temperature state redistribution in the whole cycle, through the water replenishment and water taking process of low-frequency small amount of cold water to the water tank, the complete water temperature state response curve of the water area is reconstructed, the temperature false drop area is activated, and in the water taking process, the water replenishment hysteresis and water taking resilience of each water area are sampled, and the sampling results are combined to fine-tune and compensate the water taking optimization model, and execute structural water temperature stability re-calibration.

[0013] Specifically, the step water taking scheme controls the pulse or constant current water replenishment mode with the water replenishment amount amplitude much smaller than the rated water replenishment amount, dynamically adjusts the temperature balance of the water area, activates the low-mixed thermal ion region, and adopts different water replenishment amount amplitude and water taking depth strategies according to different regions, to match the actual stable state and water temperature state distribution of the water area. In the water replenishment stage, the temperature fluctuation is slowed down through stage water temperature buffer and pulse adjustment, and the water area deviation is monitored and balanced in real time.

[0014] Specifically, the flow synchronization alignment method takes timestamp as the main index, synchronizes the data stream output by the water level flow meter, and according to the step water taking stage division rule, combines the water temperature value and instantaneous flow value corresponding to each time point into corresponding data nodes, and encapsulates them into structured data frames in time sequence.

[0015] Specifically, the monitoring-supplementing-rechecking closed loop process performs online monitoring on water area deviation and stable state through step-by-step water level interaction management, and when detecting temperature deviation or stability abnormality in the water area, the water area is balanced in stages and the low-mixing area is activated based on precise heating of the heating area. After the water supplementing is completed, the water area stability and temperature recovery are verified by repeatedly measuring the water supplementing and water taking temperature response curve and water temperature-water level performance change, and the water supplementing parameters and supplementing strategy are dynamically adjusted according to the rechecking result.

[0016] Specifically, the correction method for maintaining the mapping logic is: a water temperature state-water level state double variable correlation matrix is established, the mean square error between the step-by-step water taking model output value and the measured value is calculated, a temperature correction factor and a water level rate correction term are introduced to integrate the high temperature area, the buffer area and the heating area division data, and the non-linear drift of the step-by-step water taking temperature change is compensated.

[0017] Specifically, a water taking system of a step-by-step water taker is used to execute the method according to any one of claims 1-12, and comprises: a water level interaction construction module: step-by-step water supplementing data are acquired, a water temperature-water level double mode curve is constructed based on the water level and water temperature parameters in the step-by-step water supplementing data, the water tank water level is divided into a high temperature area, a buffer area and a heating area, and water supplementing temperature change data are obtained by detecting the change amplitude of the water level in the water supplementing test process; a step-by-step water taking modeling module: a water taking optimization model is constructed based on the water temperature-water level double mode curve, the water temperature stability data are input into the step-by-step water taking model as input parameters, the maintenance mapping logic of the step-by-step water level interaction management on the water temperature state and the water level state is calibrated, and the step-by-step water level interaction management is labeled with water injection demand information through a structure stability calibration method to generate a step-by-step water supplementing scheme; a dynamic water supplementing selection module: the step-by-step water supplementing scheme intelligently supplements the water tank in a small amount and multiple times, when the water temperature is sufficient and the water level is lower than the high temperature area, only cold water is injected and the existing high temperature water is used to heat the cold water, the buffer area cold and hot mixing area of the water tank is activated through control of a small amount and multiple times of dynamic water supplementing, and the water taking mode is selected based on temperature feedback excitation method verification of the water temperature fluctuation period; a closed loop monitoring verification module: a monitoring-supplementing-rechecking closed loop process is established, when the water temperature deviation in the water tank is detected, the overall water temperature of the water tank in the water taking process is controlled through batch water supplementing strategy, the water temperature heating deviation value is adjusted according to the water level change in the water tank, and only heating is performed in the heating area to stably verify the water taking mode.

[0018] The beneficial effects of the present application are: The application realizes non-destructive water tank data acquisition and management through a step-by-step water level sensor, is non-destructive, non-intrusive, and has a small amount of intelligent water replenishment, so that the water tank is as maintainable as a heater, the water level sensor is plug-and-play, one-key execution, safe and does not damage the equipment; visual result report + platform historical comparison, the result can be seen; supports a monitoring-replenishment-reinspection closed loop process, creates a standard service path, can obtain key characteristic parameters such as water area temperature, water level, mixing and deviation in real time, and constructs a water temperature-water level bimodal state curve through segmented water level sensor loading and water replenishment and water taking tests, and realizes accurate perception of the water area high temperature area and temperature fluctuation trend. Among them, the water tank is dynamically divided into a high temperature area, a buffer area and a heating area by three water level sensors, the high level sensor ensures the water quality of the high temperature area, the middle level sensor monitors the mixing of the buffer area, and the low level sensor triggers the low-power heating of the heating area, uses the buffer area to isolate hot and cold water, completely eliminates the problem of cold and hot water and uneven heating, and realizes the ultimate energy efficiency.

[0019] Based on the bimodal state curve, the application further constructs a water taking optimization model, dynamically calibrates the mapping logic of the water temperature state and the water level state, generates a targeted water taking scheme, including a small amount of water replenishment strategy and segmented replenishment and taking cycle control strategy, so as to activate the low mixing area of the water area, balance the performance of the water area and delay the temperature attenuation. By establishing a monitoring-replenishment-reinspection closed loop process and combining platform services for remote monitoring, historical data comparison and OTA upgrade, the application can realize adaptive optimization and stability verification of the water replenishment and taking strategy. At the same time, the method does not need to damage or change the internal structure of the water tank, reduces the operation risk, improves the water taking efficiency and implementability. In the high-frequency water taking scene, the application not only can effectively inhibit the deviation growth and water area temperature deviation, but also can prolong the service life of the water tank, improve the replenishment and taking efficiency, and provide data support and intelligent decision basis for stable operation and remote management of the water tank.

[0020] Compared with the defect that the traditional water taking device causes water temperature to drop suddenly and the waiting time to be long due to one-time cold water replenishment, the application adopts "small amount and multiple times" intelligent water replenishment, when the water temperature is sufficient and the water level is slightly lower than the upper limit, only a small amount of cold water is injected, the remaining high temperature water is used to heat rapidly, the main body water temperature is maintained stable during the user water taking interval, repeated boiling and energy waste are avoided. The dynamic division mechanism ensures that heating is limited to the heating area, the small power element is accurately started, the thermal efficiency is improved by more than 20%, the water temperature fluctuation rate is reduced to within 2%, and the user experience is significantly improved. In addition, the cloud platform encrypts the returned data, supports mobile terminal upgrade, generates stable reports, compares historical water tank data, selects a traceable mode, and promotes the sustainable development of intelligent household appliances. Overall, the application has the technical advantages of convenient implementation, fine control, real-time response and closed loop optimization, significantly improves the problems of insufficient water area temperature state perception, fixed strategy and stability risk of the existing water taking method, is suitable for home, office and other scenes, reduces the maintenance cost, and promotes environmental protection and energy saving. BRIEF DESCRIPTION OF DRAWINGS

[0021] In order to facilitate the understanding of those skilled in the art, the present application will be further described below in conjunction with the drawings.

[0022] Figure 1 The structure diagram of the water taking method and system of the step-by-step water taking device.

[0023] Figure 2 The technical flow diagram of the water taking method and system of the step-by-step water taking device. DETAILED DESCRIPTION

[0024] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined application purposes, the specific embodiments, structures, features and effects thereof according to the present application will be described in detail below in conjunction with the drawings and preferred embodiments.

[0025] Please refer to Figure 1 A water taking method of a step-by-step water taking device: S1: Obtain step-by-step water replenishment data, construct a water temperature-water level bimodal curve based on the water level and water temperature parameters in the step-by-step water replenishment data, divide the water tank water level into a high temperature zone, a buffer zone and a heating zone, and obtain water replenishment water temperature change data by detecting the change amplitude of the water level during the water replenishment test; S2: Construct a water taking optimization model based on the water temperature-water level bimodal curve, input the water temperature stability data as an input parameter into the step-by-step water taking model, calibrate the maintenance mapping logic of the step-by-step water level interactive management on the water temperature state and the water level state, and label the water injection demand information of the step-by-step water level interactive management through the structure stability calibration method, to generate a step-by-step water replenishment scheme; S3: The step-by-step water replenishment scheme intelligently replenishes the water tank a few times, when the water temperature is sufficient and the water level is lower than the high temperature zone, only cold water is injected and the existing high temperature water is used to heat the cold water, the cold and hot mixed area of the water tank buffer zone is activated through the control of a few times of dynamic water replenishment, and the water temperature fluctuation period is verified based on the temperature feedback excitation method, and the water taking mode is selected; S4: Establish a monitoring-water replenishment-reinspection closed loop process, when the water temperature deviation in the water tank is detected, control the overall water temperature of the water tank during the water taking process through the batch water replenishment strategy, and adjust the water temperature heating bias according to the water level change in the water tank, only heat in the heating zone, and stably verify the water taking mode.

[0026] Specifically, the step-by-step water replenishment data acquisition method is: zero point calibration is performed by synchronously sampling water temperature flow data through a water level flow meter, a step-by-step water taking mode is set and water level, water temperature and water taking time information are obtained during the water taking stage, the water taking flow and the segmented water level and water temperature curve are unified into a structured data frame through flow synchronization alignment, and step-by-step water taking data is obtained.

[0027] Specifically, the water tank water level division method is: based on the water temperature gradient characteristics corresponding to the water temperature-water level bimodal curve, according to the temperature change rate at different water level heights of the water tank, the upper thermal stable layer with stable temperature and gradient approaching is divided into a high temperature zone; then the middle mixed layer with water temperature decreasing and gradient absolute value increasing after water replenishment is taken as a buffer zone; and then the water level section close to the heating element is quickly heated after water replenishment, and the temperature recovery speed and gradient are greatly increased, which is divided into a heating zone.

[0028] Specifically, the construction method of the water temperature-water level bimodal curve is: Under the condition of a stepping water level sensor, the execution of water replenishment and water taking processes of the water tank in each water level state interval is monitored through stepping water level interaction management, the corresponding water level increment and temperature decay characteristics are recorded, and the temperature change rate and water level response rate are calculated through a differential temperature level analysis method; A water temperature-water level bimodal state curve is constructed with water level as the horizontal axis and water temperature stability as the vertical axis, and a multi-modal feature fusion algorithm is used to take the differential temperature level characteristics and water temperature retention rate as fusion variables. A nonlinear mapping relationship between stability and water level response is established by fitting the corresponding peak values in the water replenishment and water taking processes.

[0029] Specifically, the generation method of the water replenishment temperature change data is: based on the water replenishment temperature response characteristics extracted from the water temperature-water level bimodal state curve, the heat decay growth rate and water temperature retention rate indicators are calculated, and compared with the water tank temperature maintenance time, to generate the water replenishment temperature change data.

[0030] In this embodiment, the system includes a three-layer structure: a device layer (data acquisition module, temperature feedback unit, water replenishment control module, and support area isolation); an algorithm layer (SOT estimation module, bimodal curve construction module, water taking optimization model, and integrated dynamic division logic); and a platform service layer (data archiving, historical analysis, and OTA delivery).

[0031] The stepping water taking module performs multiple segment water taking operations according to the set water taking flow, forming stepping water taking data. The water level sensor continuously outputs the water level height with a sampling frequency of 1-5HZ, the water temperature sensor outputs the real-time water temperature with a synchronous sampling frequency of 1-5HZ, and the water taking flowmeter outputs the instantaneous flow and cumulative flow. These data are used as raw input for subsequent water level interval division, bimodal curve construction, and water taking optimization model training.

[0032] The following method is used to test the water level change and divide the three regions inside the water tank: 1. Test method: In the full water state of the water tank, multiple groups of fixed water replenishment temperature + fixed water replenishment amount of water replenishment / circulation test are carried out; no stirring in the middle, keep the real thermal stratification state; the test data comes from the step-by-step water taking data of S1.

[0033] 2. Partition division basis: (1) High temperature zone: the temperature is stable at the set high temperature value, the fluctuation is 1℃, the fluctuation is small, Tgrad(i)≈0 (the temperature change is very small with the water level change), the typical depth range is 0-20% of the water depth from the water surface.

[0034] (2) Buffer zone: after cold water replenishment, the water temperature appears rapid gradient change, heat mixing is significant, Tgrad(i) is obviously negative (cold water invades upward, causing temperature drop), temperature fluctuation amplitude >1℃, control multiple small amount of water replenishment.

[0035] (3) Heating zone: close to the heater, the water temperature rises rapidly after water replenishment, the temperature rise speed ∂T / ∂t ≥0.1℃ / s, the fluctuation period is short, the heat source influence is obvious, the partition data is used to construct the water temperature-water level bimodal curve.

[0036] The water injection demand information is adaptively generated by the step-by-step water taking model, which is inferred by the water temperature stability data and water level change test data, and is calibrated by the structure stability calibration method, which is determined by the temperature fluctuation characteristics, water taking step, and buffer zone response speed.

[0037] The water temperature fluctuation period is used to judge the thermal stability of the water tank, which is the core parameter of the temperature feedback excitation method. According to the continuous temperature sequence of T(i,t), when a small amount of dynamic water replenishment is carried out for multiple times, the temperature sensor captures the temperature instantaneous change to determine whether it enters the thermal stable zone.

[0038] By collecting step-by-step water taking data, the water temperature-water level bimodal curve is constructed, and the high temperature zone, buffer zone and heating zone are divided according to the water level change test. Based on the water temperature stability data, the system generates water injection demand information to form a step-by-step water taking scheme. Then, the cold and hot mixing response of the buffer zone of the water tank is activated by multiple small amount of dynamic water replenishment, and the temperature fluctuation period is obtained by using the temperature feedback excitation method. Finally, the closed-loop control process of monitoring-water replenishment-reinspection is established, and the stable output of water temperature and dynamic optimization of water taking mode in the water taking process are realized.

[0039] After 90 days of continuous testing, the records show that the water zone deviation is reduced from an average of 4.2 °C to 2.5 °C, a decrease of about 40%; the SOT fluctuation rate is reduced from 0.55% per month to 0.35%; the equipment replacement frequency is reduced by 25%, the maintenance cost is reduced by 10%; the water taking time is shortened by 6.5%, and the water temperature fluctuation is reduced by 2.0 °C. The improvement benefits from the dynamic regional division to eliminate uneven heating, verifies the effectiveness and economy of the method in the actual scene, and promotes the intelligent water taking device to develop in the direction of high efficiency and sustainability.

[0040] Firstly, the water temperature stability (SOT) is calculated by differential temperature analysis (DTA) and hybrid model fusion: , where T t is the current temperature, T new is the initial rated temperature, R t and R new are the current and initial hybrid impedances, respectively, and k r is the impedance weight coefficient.

[0041] Considering the impedance change of the heating zone, the accuracy of SOT evaluation is ensured. Secondly, the temperature-water level dual-mode fitting establishes a response relationship based on polynomial regression: , , The curve accuracy is optimized by minimizing the fitting residual ϵ, where V is the temperature response, L is the water level, a, b, and c are fitting coefficients, and the buffer zone features are fused to realize nonlinear mapping. Finally, the water replenishment control strategy optimization calculates the small amount of water replenishment time based on the water zone deviation ΔT i and the target equilibrium temperature T ref , where I c is the water replenishment amount, and the water zone is balanced by dynamically adjusting t i , and the remaining hot water in the high temperature zone is used to quickly heat and inject cold water.

[0042] Specifically, the construction method of the step-by-step water taking model is: The water temperature stability data and the water temperature-water level dual-mode state curve are input variables, the water temperature performance fluctuation and temperature recovery data are analyzed, and the water tank state replenishment parameter set is constructed by collecting the temperature and water level change parameters of the water tank in the water replenishment and water taking cycle; Based on the water tank state replenishment parameter set, a nonlinear mapping algorithm from water temperature stable state to replenishment strategy is constructed, which maps the water tank taking calibration data to the stable curve of the water tank in the standard initial stable state during the calculation process, analyzes the thermal efficiency and temperature recovery rate indicators, and establishes a water temperature stability performance evaluation function; The stability performance evaluation function calculates the stable change of the water tank under different water amount state intervals by analyzing the temperature response sensitivity coefficient and the water level dynamic weight, and combines the water level increment and the temperature attenuation characteristics during the water tank executes the water replenishment and water taking process to construct a step-by-step water taking model.

[0043] Specifically, the water taking mode includes: a fast replenishment water taking mode, a cycle water taking mode. The fast replenishment water taking mode: based on the medium-high water level state temperature repair strategy of dynamic small amount adjustment, using the high temperature zone to retain hot water to quickly heat and inject cold water combined with the medium-high water level interval state, and according to the small amount of cold water step-by-step micro-replenishment mechanism, controlling the dynamic perception and real-time adjustment of the temperature interval deviation, and activating the reaction of the hot mixed temperature; The cycle water taking mode: based on the water tank state reconstruction mechanism of full cycle water temperature state redistribution, through the low-frequency small amount of cold water to implement the water replenishment and water taking process of the water tank, to reconstruct the complete water temperature state response curve of the water area, activate the temperature false drop area, and in the water taking process, through sampling the water replenishment hysteresis and water taking resilience of each water area, and combining the sampling results, the water taking optimization model is fine-tuned and compensated to perform structural water temperature stability re-calibration.

[0044] In this embodiment, as shown in Figure 2 The overall data flow is: the water level and temperature collection flow is directed to the data adaptation and fusion calculation module, and then connected to the real-time temperature control bus, the bus is based on CAN protocol, then bifurcated to the feature extraction engine and the raw temperature and level data is warehoused to InfluxDB for offline compensation model training, then the feature parameters are written to embedded SQLite or local Flash for offline water temperature curve modeling and contrast matrix self-learning, finally through the control instruction API to the execution layer to drive the water replenishment valve and heating element.

[0045] Let the current water taking scheduling trigger time be the control time, and the predefined maximum temperature memory window be the temperature window, then the real-time temperature calculation interval is defined as from the control time minus the temperature window to the control time. In the real-time flow control module, a continuous integral monitoring mode is enabled to process the temperature difference value, and a delay compensation mechanism is superimposed.

[0046] The response weight decay of different water tanks at temperature fluctuation does not use a linear model, but a piecewise adaptive temperature decay function: when the time difference is less than the water tank temperature sensitive turning point, an exponential decay form is used, that is, the first coefficient multiplied by the exponential function, where the exponential is the negative second coefficient multiplied by the time difference; otherwise, a third coefficient multiplied by the time difference minus the power form in the parentheses after the turning point is used, where the power is the fourth coefficient. These coefficients are dynamically issued by the reference temperature model, and are used to realize the weight scheduling strategy of fast decay for high-capacity water tanks and delayed decay for low-capacity water tanks through water level feature mapping.

[0047] The system constructs a comparison control matrix when dynamically modeling the high-temperature zone, buffer zone, and heating zone. The matrix is a three-row, three-column structure. The first row includes high-temperature weights and interval coupling compensation factors. The second row includes zeros, buffer weights, and interval coupling compensation factors. The third row includes heating memory weight factors, heating memory weight factors, and compensation weights. These weights and factors are functions of time. The heating memory weight factor is derived from historical temperature curve residuals in reverse, i.e., the sum of the adaptive learning memory coefficient multiplied by the residual sum divided by the time difference, where the sum range is from the control time minus the temperature window to the control time.

[0048] When the absolute value of the temperature difference value divided by the temperature limit is greater than or equal to 1 and lasts for more than 100 milliseconds, the independent zone compensation mechanism is triggered. The segmented optimization algorithm is started to perform at a twenty-millisecond cycle to independently increase the weights of the buffer zone: First, the abnormal feedback is divided into discrete segments in the time dimension. Each segment sets the weight factor as an exponential function, where the exponent is the negative segment number divided by the total number of segments, multiplied by one plus the standard deviation of the temperature fluctuation of the segment. Then, the compensation signal is added to the target control quantity segment by segment to achieve smooth convergence of the temperature signal. At the same time, the threshold adaptive algorithm analyzes historical feedback to establish a dynamic adjustment model: the new temperature limit is equal to the old temperature limit plus the learning rate multiplied by the average temperature difference minus another learning rate multiplied by the environmental disturbance factor, such as the humidity gradient, to ensure that the threshold is corrected in real time with environmental variables.

[0049] In addition, the coordination feedback algorithm uses particle swarm optimization to perform multi-dimensional search on uncoordinated signals: initialize the particle swarm, and each particle position corresponds to a parameter vector including water quantity, temperature, and time. Update the speed through iteration, which is equal to the inertia weight multiplied by the previous speed plus the cognitive coefficient multiplied by the random number multiplied by the difference between the particle's best position and the current position, plus the social coefficient multiplied by another random number multiplied by the difference between the global best position and the current position, to minimize the coordination delay and fuse frequency domain analysis to extract the dominant frequency through fast Fourier transform, improving the accuracy of abnormal feedback to 98%.

[0050] Through simulation verification, this embodiment has an abnormal response delay of less than 50 ms and a water temperature fluctuation suppression rate of greater than 90% in a high-frequency water taking scene, significantly better than traditional fixed threshold methods, and is suitable for household and commercial drinking water equipment production lines.

[0051] Specifically, the step-by-step water taking scheme dynamically adjusts the temperature balance of the water zone by controlling the pulse or constant flow water replenishment mode with a water replenishment amount amplitude far smaller than the rated water replenishment amount when the water tank is in the low mixing fluctuation region or at the initial stage of temperature drop, activates the low mixing thermal ion region, and adopts different water replenishment amount amplitudes and water taking depth strategies according to different regions to match the actual stable state and water temperature state distribution of the water zone. During the water replenishment stage, the temperature fluctuation is slowed down through stage water temperature buffering and pulse adjustment, and the water zone deviation is monitored and balanced in real time.

[0052] Specifically, the flow synchronization alignment method uses time stamp as the main index to synchronize and align the data stream output by the water level flow meter, and combines the water temperature value and instantaneous flow value corresponding to each time point into corresponding data nodes according to the step-by-step water taking stage division rule, and encapsulates them into structured data frames in time sequence.

[0053] Specifically, the monitoring-water replenishment-reinspection closed loop process monitors the water zone deviation and stable state online through step-by-step water level interaction management. When detecting temperature deviation or stability abnormality in the water zone, the water zone is balanced and the low mixing region is activated based on the precise heating of the heating zone. After water replenishment is completed, the water zone stability and temperature recovery are verified by repeatedly measuring the water replenishment and water taking temperature response curve and the water temperature-water level performance change, and the water replenishment parameters and strategy are dynamically adjusted according to the reinspection result.

[0054] Specifically, the correction method of the maintenance mapping logic is to establish a water temperature state-water level state bivariate correlation matrix, calculate the mean square error between the step-by-step water taking model output value and the measured value, and simultaneously introduce a temperature correction factor and a water level rate correction term to integrate the high temperature zone, buffer zone and heating zone division data to compensate for the nonlinear drift of the step-by-step water taking temperature change.

[0055] Specifically, a water taking system of a step-by-step water taker is used to execute the method of any one of claims 1-12, and comprises: a water level interaction construction module: obtaining step-by-step water replenishment data, constructing a water temperature-water level bimodal curve based on the water level and water temperature parameters in the step-by-step water replenishment data, dividing the water tank water level into a high temperature zone, a buffer zone and a heating zone, and obtaining water replenishment temperature change data by detecting the change amplitude of the water level during the water replenishment test; a step-by-step water taking modeling module: constructing a water taking optimization model based on the water temperature-water level bimodal curve, inputting the water temperature stability data as an input parameter into the step-by-step water taking model, calibrating the maintenance mapping logic of the step-by-step water level interaction management for the water temperature state and water level state, and labeling the water replenishment demand information of the step-by-step water level interaction management through the structural stability calibration method to generate a step-by-step water replenishment scheme; Dynamic water replenishment selection module: the step-by-step water replenishment scheme replenishes the water tank in small amounts multiple times, when the water temperature is sufficient and the water level is lower than the high-temperature zone, only cold water is injected and the existing high-temperature water is used to heat the cold water, through the control of small amounts of multiple dynamic water replenishment, the cold-hot mixed area of the water tank buffer area is activated, and the water temperature fluctuation period is verified based on the temperature feedback incentive method, and the water taking mode is selected; Closed-loop monitoring and verification module: a monitoring-water replenishment-reinspection closed-loop process is established, when the water temperature deviation in the water tank is detected, the overall water temperature of the water tank in the water taking process is controlled through the batch water replenishment strategy, and the water temperature heating deviation value is adjusted according to the water level change in the water tank, heating is only performed in the heating zone, and the water taking mode is stably verified.

[0056] The above is only a preferred embodiment of the present application, and does not limit the present application in any form. Although the present application has been disclosed as above with a preferred embodiment, it is not intended to limit the present application. Any person skilled in the art can make slight changes or modifications to the above disclosed technical content to obtain equivalent embodiments with equivalent changes, without departing from the technical solution of the present application. Any simple modification, equivalent change and modification of the above embodiments made according to the technical essence of the present application are still within the scope of the technical solution of the present application.

Claims

1. A method of water retrieval by a step retriever, characterized in that, The application relates to a water tank water temperature and water level interactive management method, which comprises the following steps: S1: obtaining step-by-step water replenishment data, constructing a water temperature-water level bimodal curve based on water level and water temperature parameters in the step-by-step water replenishment data, dividing the water tank water level into a high-temperature zone, a buffer zone and a heating zone according to the water tank water level, and obtaining water temperature change data through detection of the water level change amplitude in the water replenishment test process; S2: constructing a water taking optimization model based on the water temperature-water level bimodal curve, inputting the water temperature stability data into the step-by-step water taking model as an input parameter, calibrating the step-by-step water level interactive management maintenance mapping logic of the water temperature state and the water level state, and marking the water replenishment demand information of the step-by-step water level interactive management through a structure stability calibration method to generate a step-by-step water replenishment scheme; S3: the step-by-step water replenishment scheme intelligently replenishes the water tank for a small number of times, when the water temperature is sufficient and the water level is lower than the high-temperature zone, only cold water is injected and the existing high-temperature water is used to heat the cold water, a cold-hot mixed area of the buffer zone of the water tank is activated through control of a small number of dynamic water replenishment, and the water temperature fluctuation period is verified based on a temperature feedback excitation method to select a water taking mode; S4: a monitoring-water replenishment-reinspection closed loop process is established, when the water temperature deviation in the water tank is detected, the overall water temperature of the water tank in the water taking process is controlled through a batch water replenishment strategy, the water temperature heating deviation value is adjusted according to the water level change in the water tank, heating is only carried out in the heating zone, and the water taking mode is stably verified.

2. The method of claim 1, wherein, The step-by-step water replenishment data acquisition method is that water temperature and flow data are synchronously sampled through a water level flowmeter for zero point calibration, a step-by-step water taking mode is set and water level, water temperature and water taking time information are acquired in the water taking stage, water taking flow and segmented water level and water temperature curves are unified into a structured data frame through a flow synchronous alignment method, and step-by-step water taking data are obtained.

3. The method of claim 1, wherein, The water tank water level division method is that, based on the water temperature gradient characteristics corresponding to the water temperature-water level bimodal curve, the upper thermal stable layer with stable temperature and gradient close to zero is divided into the high-temperature zone according to the temperature change rate at different water level heights of the water tank, then the middle mixed layer with the water temperature decreasing and the gradient absolute value increasing after water replenishment disturbance is taken as the buffer zone, and finally the water level section close to the heating element is divided into the heating zone according to the characteristics that the water temperature rapidly rises after water replenishment and the temperature recovery speed and the gradient greatly rise.

4. The method of claim 1, wherein, The water temperature-water level bimodal curve construction method is that, under the condition of a step-by-step water level sensor, the step-by-step water level interactive management monitors the water tank execution water replenishment and water taking process in each water level state interval, records the corresponding water level increment and temperature attenuation characteristics, and calculates the temperature change rate and the water level response rate through a differential temperature level analysis method; a water temperature-water level bimodal state curve is constructed with the water level as the horizontal axis and the water temperature stability as the vertical axis, the differential temperature level characteristics and the water temperature retention rate are taken as fusion variables through a multi-modal characteristic fusion algorithm, and a nonlinear mapping relationship between the stability and the water level response is established by fitting the corresponding peak values in the water replenishment and water taking process. ​ 5. The method of claim 2, wherein, The generation method of the replenishment water temperature change data is: based on the replenishment temperature response characteristics extracted from the water temperature-water level bimodal state curve, calculating the heat attenuation growth rate and water temperature maintenance rate index, and comparing with the water tank temperature maintenance time to generate the replenishment water temperature change data.

6. The method of claim 5, wherein, The construction method of the step-by-step water taking model is: Taking the water temperature stability data and the water temperature-water level bimodal state curve as input variables, analyzing the water temperature performance fluctuation and temperature recovery data, and constructing a water tank state replenishment parameter set by collecting the temperature and water level change parameters of the water tank in the replenishment and water taking cycle; Based on the water tank state replenishment parameter set, a nonlinear mapping algorithm from the water temperature stable state to the replenishment strategy is constructed, which maps the water tank water taking calibration data to the stable curve of the water tank in the standard initial stable state during the calculation process, analyzes the heat efficiency and temperature recovery rate index, and establishes a water temperature stability performance evaluation function; The stability performance evaluation function calculates the stable change of the water tank under different water quantity state intervals by analyzing the temperature response sensitivity coefficient and the water level dynamic weight, and constructs a step-by-step water taking model by combining the water level increment and temperature decay characteristics of the water tank during the replenishment and water taking process.

7. The method of claim 4, wherein, The water taking mode includes: fast replenishment and water taking mode, and cycle water taking mode; The fast replenishment and water taking mode: based on the medium-high water level state temperature repair strategy of dynamic small amount adjustment, using the high temperature zone to retain hot water to quickly heat and inject cold water combined with the medium-high water level interval state, and according to the small amount of cold water step-by-step micro-replenishment mechanism, controlling the dynamic perception and real-time adjustment of water temperature deviation and hot mixed mild activation reaction; The cycle water taking mode: based on the water tank state reconstruction mechanism of water temperature state redistribution in the whole cycle, through the replenishment and water taking process of low-frequency small amount of cold water to the water tank, the complete water temperature state response curve of the water area is reconstructed, the temperature false drop area is activated, and in the water taking process, the replenishment hysteresis and water taking resilience of each water area are sampled, and the sampling results are combined to fine-tune and compensate the water taking optimization model, and execute structural water temperature stability re-calibration.

8. The method of claim 2, wherein, The step-by-step water taking scheme, in the low mixed fluctuation area or the initial stage of temperature drop, through the pulse or constant current replenishment mode with the replenishment amount amplitude far less than the rated replenishment amount, dynamically adjusts the temperature balance of the water area, activates the low mixed thermal ion region, and according to different regions adopts different replenishment amount amplitude and water taking depth strategy to match the actual stable state and water temperature state distribution of the water area. In the replenishment stage, the temperature fluctuation is slowed down through stage water temperature buffer and pulse adjustment, and the water area deviation is monitored and balanced in real time.

9. The method of claim 4, wherein, The flow synchronization alignment method takes time stamp as the main index, synchronizes the data stream output by the water level flow meter, and combines the water temperature value and instantaneous flow value corresponding to each time point into corresponding data nodes according to the step-by-step water taking stage division rule, and encapsulates them into structured data frames in time sequence.

10. The method of claim 4, wherein, The monitoring-supplementing-rechecking closed loop process monitors the water area deviation and stable state through stepwise water level interaction management. When detecting temperature deviation or stability anomaly in the water area, the water area is balanced and the low-mixing area is activated based on the precise heating of the heating area. After supplementing water, the water area stability and temperature recovery are verified by repeatedly measuring the supplementing water temperature response curve and water temperature-water level performance change. Based on the rechecking result, the supplementing water parameters and supplementing water strategy are dynamically adjusted.

11. The method of claim 7, wherein, The correction method of the maintenance mapping logic is to establish a water temperature state-water level state two-variable correlation matrix, calculate the mean square error between the stepwise water taking model output value and the measured value, introduce a temperature correction factor and a water level rate correction term to integrate the high temperature area, buffer area and heating area division data, and compensate for the nonlinear drift of the stepwise water taking temperature change.

12. A water taking system of a stepwise water taker for carrying out the method according to any one of claims 1 to 12, characterized in that It comprises: A water level interaction construction module: acquires stepwise supplementing water data, constructs a water temperature-water level double mode curve based on the water level and water temperature parameters in the stepwise supplementing water data, divides the water tank water level into a high temperature area, a buffer area and a heating area, and obtains supplementing water temperature change data by detecting the change amplitude of the water level during the supplementing water test process; A stepwise water taking modeling module: constructs a water taking optimization model based on the water temperature-water level double mode curve, inputs the water temperature stability data as an input parameter into the stepwise water taking model, calibrates the maintenance mapping logic of the stepwise water level interaction management on the water temperature state and water level state, and labels the water injection demand information of the stepwise water level interaction management through structural stability calibration method to generate a stepwise supplementing water scheme; A dynamic supplementing water selection module: the stepwise supplementing water scheme intelligently supplements water to the water tank for a small number of times. When the water temperature is sufficient and the water level is lower than the high temperature area, only cold water is injected and the existing high temperature water is used to heat the cold water. Through the control of a small number of times of dynamic supplementing water, the cold and hot mixing area of the water tank buffer area is activated. The temperature fluctuation period is verified based on the temperature feedback excitation method, and the water taking mode is selected; A closed loop monitoring verification module: establishes a monitoring-supplementing-rechecking closed loop process. When detecting the water temperature deviation in the water tank, the overall water temperature of the water tank during the water taking process is controlled through batch supplementing water strategy, and the water temperature heating deviation value is adjusted according to the water level change in the water tank. Only heating is performed in the heating area, and the water taking mode is stably verified.

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