A novel method and system for real-time monitoring of filter cartridge status in water dispensers

Abstract

This application relates to the field of separation technology, specifically to a novel method and system for real-time monitoring of the filter cartridge status of a water dispenser. The method includes: acquiring the current operating parameters and historical operating data of the novel water dispenser; determining the temperature influence coefficient of each type of water quality sensor based on the historical operating data; determining the target water flow rate and target data acquisition frequency of the novel water dispenser based on the current operating parameters; acquiring the current monitoring values ​​of each type of water quality sensor based on the target data acquisition frequency; and determining the current status evaluation index of the filter cartridge based on the temperature influence coefficient and the current monitoring values ​​of each type of water quality sensor. This current status evaluation index is used to evaluate the filter cartridge status. This method can improve the accuracy of filter cartridge monitoring.

Description

Technical Field

[0001] This application relates to the field of separation technology, specifically to a novel method and system for real-time monitoring of the filter cartridge status of a water dispenser. Background Technology

[0002] The current real-time monitoring of the filter status of new water dispensers mainly involves installing sensors before and after the filter to compare the data changes of drinking water after it passes through the filter, thereby assessing the filter status of the new water dispenser.

[0003] However, since existing new water dispensers are usually designed without a water tank, that is, they heat the water flow directly through the heating device. During this process, the sudden rise in temperature can cause abnormal sensor values, which in turn leads to poor monitoring results of the filter cartridge, and thus affects the health of the drinker. Summary of the Invention

[0004] To address the technical problem of unsatisfactory status monitoring results for filter cartridges in new water dispensers, this application aims to provide a method and system for real-time monitoring of filter cartridge status in new water dispensers. The specific technical solution adopted is as follows:

[0005] This application provides a novel method for real-time monitoring of the filter cartridge status of a water dispenser. The method includes: acquiring current operating parameters and historical operating data of the water dispenser; the current operating parameters include the current preset water temperature, current water flow rate, current water temperature, and current heating power; the historical operating data includes monitoring data from multiple water quality sensors at the multiple preset water temperatures and the average water flow rate at each preset water temperature; determining a temperature influence coefficient for each type of water quality sensor based on the historical operating data, whereby the temperature influence coefficient characterizes the degree of fluctuation in the monitoring data of that type of water quality sensor due to changes in water temperature; determining a target water flow rate and a target data acquisition frequency for the water dispenser based on the current operating parameters; acquiring the current monitoring value of each type of water quality sensor based on the target data acquisition frequency; and determining a current status evaluation index for the filter cartridge based on the temperature influence coefficient and the current monitoring value of each type of water quality sensor, whereby the current status evaluation index is used to evaluate the filter cartridge status.

[0006] Optionally, determining the temperature influence coefficient of each type of water quality sensor based on the historical operating data specifically includes: determining the initial influence coefficient of the first type of water quality sensor based on the monitoring data of the first water quality sensor at multiple preset water temperatures, wherein the first water quality sensor is the first type of water quality sensor at the outlet of the heating module, and the first type of water quality sensor is any one of multiple types of water quality sensors; determining the temperature influence coefficient of the first type of water quality sensor based on the initial influence coefficient, the monitoring data of the first water quality sensor and the second water quality sensor at the same preset water temperature, and the average water flow rate at each preset water temperature, wherein the second water quality sensor is the first type of water quality sensor at the inlet of the heating module.

[0007] Optionally, the above-mentioned determination of the initial influence coefficient of the first type of water quality sensor based on the monitoring data of the first water quality sensor at multiple preset water temperatures specifically includes: combining the multiple preset water temperatures in pairs to obtain M pairs of preset water temperatures, where M is an integer greater than or equal to 1; determining the difference in monitoring data of the first water quality sensor at each pair of preset water temperatures and the temperature difference between the preset water temperatures; and determining the initial influence coefficient of the first type of water quality sensor based on the difference in monitoring data of the first water quality sensor at each pair of preset water temperatures and the temperature difference between the preset water temperatures.

[0008] Optionally, the above-mentioned determination of the temperature influence coefficient of the first type of water quality sensor based on the initial influence coefficient, the monitoring data of the first water quality sensor and the second water quality sensor at the same preset water temperature, and the average water flow velocity at each preset water temperature specifically includes: determining the difference in monitoring data between the first and second water quality sensors at each preset water temperature and the historical temperature difference between the inlet and outlet ends at each preset water temperature; correcting the difference in monitoring data between the inlet and outlet ends at each preset water temperature based on the distance between the installation positions of the first and second water quality sensors, the average water flow velocity at each preset water temperature, and the initial influence coefficient to obtain the temperature rise difference of the monitoring data at the inlet and outlet ends at each preset water temperature; and determining the temperature influence coefficient of the first type of water quality sensor based on the temperature rise difference of the monitoring data at the inlet and outlet ends at each preset water temperature and the historical temperature difference between the inlet and outlet ends at each preset water temperature.

[0009] Optionally, the current water temperature includes the current water temperature at the inlet of the heating module and the current water temperature at the outlet of the heating module. The determination of the target water flow rate and target data acquisition frequency of the new water dispenser based on these current operating parameters specifically includes: determining the current heating efficiency of the heating module based on the current water temperature at the inlet of the heating module, the current water temperature at the outlet of the heating module, the current water flow rate, and the current heating power; determining the current temperature error index based on a first temperature difference between the current preset water temperature and the current water temperature at the inlet of the heating module, and a second temperature difference between the current water temperature at the outlet of the heating module and the current water temperature at the inlet of the heating module; adjusting the current water flow rate based on the current temperature error index and the current heating efficiency to obtain the target water flow rate; and adjusting the current data acquisition frequency based on the target water flow rate to obtain the target data acquisition frequency.

[0010] Optionally, the above-mentioned adjustment of the current water flow rate based on the current temperature error index and the current heating efficiency to obtain the target water flow rate specifically includes: when the current heating efficiency is greater than a first heating efficiency threshold, increasing the current water flow rate based on the current temperature error index and the current heating efficiency to obtain the target water flow rate; when the current heating efficiency is less than a second heating efficiency threshold, decreasing the current water flow rate based on the current temperature error index and the current heating efficiency to obtain the target water flow rate, wherein the second heating efficiency threshold is less than the first heating efficiency threshold.

[0011] Optionally, the above-mentioned adjustment of the current data acquisition frequency based on the target water flow velocity to obtain the target data acquisition frequency specifically includes: when the target water flow velocity is greater than or equal to the current water flow velocity, correcting the current data acquisition frequency based on the ratio of the current water flow velocity to the target water flow velocity to obtain the target data acquisition frequency; when the target water flow velocity is less than the current water flow velocity, determining the current data acquisition frequency as the target data acquisition frequency.

[0012] Optionally, the above-mentioned determination of the current state evaluation index of the filter element based on the temperature influence coefficient of each type of water quality sensor and the current monitoring value of each type of water quality sensor specifically includes: determining the individual deviation value of each type of water quality sensor based on the difference between the current monitoring value and the standard reference value of each type of water quality sensor; determining the fusion weight of the individual deviation value of each type of water quality sensor based on the temperature influence coefficient of each type of water quality sensor; and weighting and summing multiple individual deviation values ​​based on the fusion weight of the individual deviation values ​​of each type of water quality sensor to obtain the current state evaluation index of the filter element.

[0013] Optionally, the method further includes generating a filter replacement prompt message if the current status evaluation index of the filter element is greater than a first evaluation index threshold.

[0014] This application also provides a novel real-time monitoring system for the filter status of a water dispenser. The system includes a data acquisition unit, a data processing unit, and an evaluation unit. The data acquisition unit acquires the current operating parameters and historical operating data of the water dispenser. The current operating parameters include the current preset water temperature, current water flow rate, and current heating power. The historical operating data includes monitoring data from multiple water quality sensors at the preset water temperatures and the average water flow rate at each preset water temperature. The data processing unit determines the temperature influence coefficient of each type of water quality sensor based on the historical operating data. The temperature influence coefficient of a type of water quality sensor is used to characterize the degree of fluctuation of the monitoring data of a type of water quality sensor affected by changes in water temperature; the data processing unit is also used to determine the target water flow rate and target data acquisition frequency of the new water dispenser based on the current operating parameters; the data acquisition unit is also used to acquire the current monitoring value of each type of water quality sensor based on the target data acquisition frequency; the evaluation unit is used to determine the current state evaluation index of the filter element based on the temperature influence coefficient and the current monitoring value of each type of water quality sensor, and the current state evaluation index of the filter element is used to evaluate the state of the filter element.

[0015] This application has the following beneficial effects:

[0016] In this application, the heating effect of the heating module on drinking water is analyzed by current operating parameters, thereby dynamically adjusting the flow rate of drinking water passing through the heating module and the data acquisition frequency of the sensors. This ensures that the drinking water is fully heated while collecting sufficient monitoring data, guaranteeing the timeliness and accuracy of the data samples. At the same time, by analyzing the differences in sensor monitoring data under different preset temperatures and the differences in sensor data before and after heating at the same preset temperature, the temperature influence coefficient of each type of water quality sensor is extracted. Based on the temperature influence coefficient and the current monitoring value of each type of water quality sensor, the filter element status is evaluated, which can improve the accuracy of filter element status monitoring. Attached Figure Description

[0017] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart illustrating a novel method for real-time monitoring of the filter cartridge status of a water dispenser, provided in one embodiment of this application;

[0019] Figure 2This is a structural diagram of a novel real-time monitoring system for the filter status of a water dispenser, provided as an embodiment of this application. Detailed Implementation

[0020] To further illustrate the technical means and effects adopted by this application to achieve the intended inventive purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a novel water dispenser filter status real-time monitoring method and system proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0022] The filter cartridge (filtration device) is a core component of a new type of water dispenser. Its main functions are to remove physical impurities from drinking water, intercept chemical pollutants, and inhibit microbial contamination. It can even improve the quality of drinking water by selectively retaining minerals. The normal and stable operation of the filter cartridge greatly affects the health of the drinker. Therefore, users usually need to replace the filter cartridge regularly. However, in the actual use of new water dispensers, the lifespan of the filter cartridge is affected by many factors such as water consumption, raw water quality, and frequency of use. Therefore, replacing it at fixed intervals is not conducive to the health of the drinker. Thus, it is necessary to monitor the status of the filter cartridge in new water dispensers in real time through sensors.

[0023] The main feature of current new water dispensers is their instant heating technology. This technology uses rare-earth thick-film heating or nano-quartz tube heating to instantly raise the temperature of drinking water upon contact with the heating layer, achieving 24-hour real-time hot water. However, because they lack a storage tank, they also place extremely high demands on the real-time filtration capacity of the drinking water. Real-time monitoring of the filter status in current new water dispensers is primarily achieved by installing sensors before and after the filter cartridge. This allows for comparison of data changes in the drinking water after filtration, enabling the determination of the filter cartridge's purification capacity—that is, the filter status of the new water dispenser.

[0024] However, since existing new water dispensers are usually designed without a water tank, that is, they directly heat the water flowing through them through heating equipment. In this process, the dynamic water flow and the rapid rise in water temperature can cause certain errors in the data acquired by the sensors used for monitoring. That is, the water flow is too fast, which leads to untimely data monitoring; air bubbles and impurities in the water flow (instantaneous effects that cause inaccurate sensor data); or the temperature rise is a sudden increase, which causes abnormal sensor values. This results in poor monitoring of the filter cartridge's condition, affecting the determination of when to replace the filter cartridge, and thus affecting the health of the drinker.

[0025] The following description, in conjunction with the accompanying drawings, details the specific scheme of a novel water dispenser filter element real-time monitoring method and system provided in this application.

[0026] Please see Figure 1 The diagram illustrates a method flowchart for real-time monitoring of the filter status of a novel water dispenser according to an embodiment of this application.

[0027] like Figure 1 As shown, the real-time monitoring method for the filter status of this new type of water dispenser includes S101-S105.

[0028] S101. Obtain the current operating parameters and historical operating data of the new water dispenser.

[0029] The current operating parameters include the current preset water temperature, current water flow rate, current water temperature and current heating power. The historical operating data includes monitoring data from multiple water quality sensors at the multiple preset water temperatures and the average water flow rate at each preset water temperature.

[0030] It should be understood that the new water dispenser is equipped with a multi-dimensional sensor module, which includes multiple sensors deployed at key nodes of the water circuit of the new water dispenser to collect the operating parameters and operating data (including historical operating data and current operating data) of the new water dispenser.

[0031] Specifically, water quality sensors for monitoring water quality parameters are deployed at the inlet and outlet ends of the new water dispenser filter. These sensors include various types, such as TDS sensors for monitoring total dissolved solids (TDS) content, turbidity sensors for monitoring turbidity, residual chlorine sensors for monitoring residual chlorine content, and pressure sensors for monitoring pressure. Water quality sensors, such as TDS sensors and turbidity sensors, are also deployed at the inlet and outlet ends of the heating module. Temperature sensors for monitoring water temperature and power sensors for monitoring its operating status are also deployed. In addition, flow sensors for monitoring water flow are also deployed in the water circuit of the new water dispenser.

[0032] Optionally, when collecting the current operating condition parameters, the data can be collected based on a preset data collection frequency, and the collected data can be preprocessed in real time.

[0033] For example, the preset data acquisition frequency can be 0.1 times / second.

[0034] Understandably, when the new water dispenser is started and enters working mode (including standby heating and water dispensing), it receives the current preset water temperature set by the user through the operation interface. The multi-dimensional sensor module starts simultaneously, with the flow sensor collecting the current water flow rate in the water circuit of the new water dispenser in real time, the temperature sensor collecting the current water temperature at the inlet and outlet of the heating module in real time, and the power sensor collecting the current heating power of the heating module in real time, thus obtaining the current operating parameters.

[0035] It should be understood that the multiple preset water temperatures in the historical operation data of this new type of water dispenser are datasets collected during the historical operation of the new type of water dispenser when water is dispensed at different preset water temperatures. The number of multiple preset water temperatures refers to the number of multiple preset water temperature levels, and the number of multiple preset water temperature levels is at least two.

[0036] For example, assuming that the multiple preset water temperature settings include room temperature, 45°C, 85°C, and 100°C, then the number of the multiple preset water temperatures is 4.

[0037] It should be understood that there may be an error between the actual water temperature at the outlet of the water dispenser during operation and the preset water temperature. The current water temperature refers to the actual water temperature in the water dispenser at the moment. The current water temperature may include the current water temperature at the inlet of the heating module and the current water temperature at the outlet of the heating module.

[0038] In one alternative implementation, water may be dispensed multiple times at a preset water temperature. In this case, the average value of the monitoring data from multiple water dispenses at the same preset water temperature can be used as the representative value for that preset water temperature, and subsequent calculations can be performed based on this representative value.

[0039] Optionally, the historical operational data may include monitoring data from each sensor.

[0040] Optionally, the average water flow velocity can be determined as the mean water flow velocity by measuring the average water flow velocity during a single water discharge process.

[0041] S102. Determine the temperature influence coefficient of each type of water quality sensor based on historical operating data.

[0042] Among them, the temperature influence coefficient of a type of water quality sensor is used to characterize the degree of fluctuation of the monitoring data of a type of water quality sensor affected by changes in water temperature.

[0043] Based on the above description, it should be understood that water quality sensors are divided into multiple types. For any type of water quality sensor (such as TDS sensor), the monitoring data of all TDS sensors at each preset water temperature can be extracted from historical operating data, and then the temperature influence coefficient of the TDS sensor can be determined based on the monitoring data of all TDS sensors at all preset water temperatures.

[0044] In one implementation of this application, for a type of water quality sensor, the temperature influence coefficient of the water quality sensor can be determined based on the monitoring data of the water quality sensor at the same location under different preset water temperatures, and the monitoring data of the water quality sensor at different locations under the same preset water temperature.

[0045] Specifically, the initial influence coefficient of the first type of water quality sensor can be determined based on the monitoring data of the first water quality sensor at multiple preset water temperatures. Based on the initial influence coefficient, the monitoring data of the first water quality sensor and the second water quality sensor at the same preset water temperature, and the average water flow velocity at each preset water temperature, the temperature influence coefficient of the first type of water quality sensor can be determined.

[0046] The first water quality sensor is a first type of water quality sensor at the outlet of the heating module, and the second water quality sensor is a first type of water quality sensor at the inlet of the heating module. The first type of water quality sensor can be any one of multiple types of water quality sensors.

[0047] In one alternative implementation, the multiple preset water temperatures can be combined in pairs to obtain M pairs of preset water temperatures. Then, the differences in the monitoring data of the first water quality sensor under each pair of preset water temperatures and the temperature difference between the preset water temperatures are determined. Based on the differences in the monitoring data of the first water quality sensor under each pair of preset water temperatures and the temperature difference between the preset water temperatures, the initial influence coefficient of the first type of water quality sensor is determined.

[0048] Where M is an integer greater than or equal to 1.

[0049] It should be understood that the initial influence coefficient also represents the degree to which the monitoring data is affected by changes in water temperature. However, since different preset temperatures occur at different times, the filter cartridges themselves are different. Therefore, the difference in the monitoring data may be affected by the condition of the filter cartridge itself, resulting in a lower accuracy of the initial influence coefficient.

[0050] It is understandable that the first and second water quality sensors are water quality sensors before and after the heating module. Since there is no filter element, the water quality conditions at these two locations are the same. The difference in the monitoring data of the two water quality sensors is due to the error caused by temperature changes. By combining multiple preset water temperatures in pairs and comparing them, the data errors caused by various temperature differences can be analyzed.

[0051] Optionally, the normalized value of the absolute value of the difference in monitoring data can be determined as the monitoring data difference; the absolute value of the difference between two preset water temperatures can be determined as the temperature difference between the two preset water temperatures.

[0052] It should be understood that when the temperature difference is greater and the difference in monitoring data is also greater, it indicates that the monitoring data is more affected by changes in water temperature. Conversely, when the temperature difference is greater and the difference in monitoring data is smaller, it indicates that the monitoring data is less affected by changes in water temperature.

[0053] Optionally, the initial influence coefficient of a certain type of water quality sensor satisfies the following formula:

[0054]

[0055] in, Indicates the first Initial influence coefficient of water quality sensor; This indicates the number of preset water temperatures; This indicates the number of preset water temperatures for M. This represents the reciprocal of M with respect to the preset water temperature. Indicates the preset water temperature With preset water temperature The temperature difference between them; Represents the normalization factor, used for... Normalization is performed, and its value can be any of the following. The sum of; Indicates the water outlet of the heating module The Water quality sensor at preset water temperature Monitoring data and preset water temperature The monitoring data showed discrepancies.

[0056] In this formula, This represents the weighting coefficient, which is quantified by weighting the differences in monitoring data for each pair of water temperature combinations. The degree to which water quality sensors are affected by changes in water temperature. The larger the value, the more likely it is to be the first. The more drastic the fluctuations in the readings of a water quality sensor at different water temperatures, the stronger the temperature interference with its monitoring results, and the lower its reliability. The smaller the value, the better. The more stable the readings of a water quality sensor, the less susceptible it is to temperature interference, and the higher its reliability.

[0057] This formula, by iterating through all pairs of preset water temperatures and correlating the differences in water quality sensor monitoring data with their temperature differences under each pair, can comprehensively and without omission capture the overall trend and statistical regularity of water quality sensor readings as water temperature changes.

[0058] In one optional implementation, the differences in monitoring data between the first and second water quality sensors at each preset water temperature, as well as the historical temperature difference between the inlet and outlet at each preset water temperature, can be determined. Based on the distance between the installation locations of the first and second water quality sensors, the average water flow velocity at each preset water temperature, and the initial influence coefficient, the differences in monitoring data between the inlet and outlet at each preset water temperature are corrected to obtain the temperature rise difference of the monitoring data at the inlet and outlet at each preset water temperature. Based on the temperature rise difference of the monitoring data at the inlet and outlet at each preset water temperature and the historical temperature difference between the inlet and outlet at each preset water temperature, the temperature influence coefficient of the first type of water quality sensor is determined.

[0059] It should be understood that when comparing the monitoring data of water quality sensors at different locations, the flow of drinking water needs to be considered. Since the standards of filtered drinking water are similar, only the temperature changes during the transportation of drinking water need to be considered. Therefore, it is necessary to correct for the sensor reading changes caused by temperature changes (such as heat dissipation) during the flow of water from the first water quality sensor installation location to the second water quality sensor installation location. This will separate the reading changes caused purely by the instantaneous heating of the heating module. The corrected value can accurately reflect the differences in monitoring data caused by the sudden temperature rise.

[0060] Optionally, the historical operating data may also include the historical water temperature at the inlet and outlet of the heating module. Based on this historical water temperature, the historical temperature difference between the inlet and outlet at each preset water temperature can be determined.

[0061] It is understandable that a water dispenser may collect historical water temperatures from multiple inlet and outlet ports during a single operation. The historical water temperature at the moment when the heated drinking water first passes through the outlet sensor during this process can be used as the basis for determining the historical temperature difference between the inlet and outlet ports at a preset water temperature. Specifically, the absolute value of the difference between the historical water temperature at the inlet port and the historical water temperature at the outlet port of the heating module can be used as the basis for determining the historical temperature difference between the inlet and outlet ports at a preset water temperature. Alternatively, the average of the historical temperature differences between the inlet and outlet ports at multiple moments during the process can be used as the basis for determining the historical temperature difference between the inlet and outlet ports at a preset water temperature.

[0062] Optionally, the temperature rise difference of the monitoring data of a type of water quality sensor at a preset water temperature satisfies the following formula:

[0063]

[0064] in, Indicates the preset water temperature Next Water quality sensor at the water inlet of the heating module Water outlet of heating module The temperature rise differences between the monitoring data, Indicates the preset water temperature Next Water quality sensor at the water inlet of the heating module Water outlet of heating module The differences between the monitoring data, Indicates the first The initial influence coefficient of water quality sensors, Indicates the water inlet of the heating module Water outlet of heating module The distance between them Indicates the preset water temperature Water inlet of lower heating module Water outlet of heating module Historical temperature difference Indicates the preset water temperature The water flows from the inlet end of the heating module. to the water outlet of the heating module The average water flow velocity between This represents the normalization function, used to normalize... , as well as The value is mapped to the range [0, 1].

[0065] Optionally, preset distance reference values, temperature difference reference values, and water flow velocity reference values ​​can be used to... and Normalization is performed.

[0066] In this formula, The correction term represents the impact during the transportation process, where... This indicates that the water flows from the inlet end of the heating module. Flowing to the outlet of the heating module During the process, this involves estimating the changes in sensor readings that may occur due to heat dissipation (or temperature changes). The larger the distance, the greater the heating temperature difference, and the slower the water flow rate, the larger this correction term, indicating a more significant impact from the transport process. This is used to convert the estimated temperature change effect into a specific sensor reading change; since the original difference includes the effects of instantaneous heating and the effects of the transport process, therefore, from the original difference... Subtracting the correction term from the readings yields the sensor reading change caused by the sudden temperature rise during heating.

[0067] Based on this formula, the influence of the water flow process can be eliminated, resulting in a purer temperature rise effect.

[0068] Optionally, by weighted averaging the differences in temperature rise before and after heating at different preset water temperatures, the first... Temperature influence coefficient of water quality sensors.

[0069] Optionally, the historical total temperature difference between the outlet and inlet of the heating module at multiple preset water temperatures can be determined, and then the ratio between the historical temperature difference between the inlet and outlet at each preset water temperature and the historical total temperature difference can be determined as the weight.

[0070] Optionally, the temperature influence coefficient of a certain type of water quality sensor satisfies the following formula:

[0071]

[0072] in, Indicates the first Temperature influence coefficient of water quality sensors This indicates the number of preset water temperatures. Indicates the preset water temperature Water inlet of lower heating module Water outlet of heating module Historical temperature difference This represents the normalization factor, whose value is equal to the water inlet of the heating module at multiple preset water temperatures. Water outlet of heating module The sum of historical temperature differences, Used for Normalization is performed so that the sum of the weighting coefficients for multiple preset water temperatures is 1. Indicates the preset water temperature Next Water quality sensor at the water inlet of the heating module Water outlet of heating module The temperature rise differences between the monitoring data.

[0073] In this formula, The weighting coefficient is the larger the error. For any preset water temperature, the greater the difference in temperature rise after correction, the greater the final temperature influence coefficient.

[0074] It should be understood that the temperature influence coefficient obtained in this scheme is a comprehensive index for evaluating the reliability of sensor readings. The larger the temperature influence coefficient of a type of water quality sensor, the more significant the deviation in the monitoring data under the scenario of instantaneous temperature rise in the heating module, the stronger the interference from sudden temperature increases, and the lower the data reliability; conversely, the weaker the interference, the higher the data reliability. A large value means that the sensor's historical data exhibits significant inconsistency or fluctuation at different temperatures, therefore the reliability of any single reading (regardless of the current water temperature) is low.

[0075] Understandably, since new water dispensers are set with different preset water temperatures during operation, by combining historical operational data with the water quality sensor monitoring results at different preset water temperatures, the impact of different preset water temperatures on the sensor data can be analyzed. Furthermore, by quantifying the differences in sensor data at different locations under the same preset water temperature, the influence of minute temperature changes caused by heat loss or transfer during the water flow from the inlet to the outlet of the heating module can be identified. This allows for the extraction of sensor reading changes purely caused by the core action of "instantaneous heating by the heating module" (i.e., "temperature surge difference"). This makes the final determined temperature influence coefficient more accurate and precise, improving its applicability and correction effectiveness under actual dynamic operating conditions.

[0076] Based on the method provided in S102 above, the initial influence coefficient is first calculated using historical operating data from the outlet of the heating module, which initially reflects the performance of each type of water quality sensor under stable high temperature. Then, the temperature change interference during the water flow process is further removed, so that the final temperature influence coefficient can more accurately characterize the actual degree of influence of the sensor on the transient process of "sudden temperature rise", laying a more reliable foundation for subsequent high-precision status assessment.

[0077] S103. Determine the target water flow rate and target data acquisition frequency of the new water dispenser based on the current operating parameters.

[0078] It should be understood that in the process of obtaining the current operating parameters, the new water dispenser is already operating at a preset water flow rate, and the sensors are also collecting data based on a preset data acquisition frequency. In order to heat the drinking water to different temperatures, it is necessary to dynamically adjust the water flow rate of the drinking water passing through the heating module according to the current real-time water pressure, the current heating efficiency, etc. At the same time, since the drinking water is collected for different durations, in order to achieve the goal of real-time monitoring of the filter status, it is necessary to adjust the data acquisition frequency in real time according to the adjusted target water flow rate.

[0079] It is understandable that the target water flow rate and target data acquisition frequency are the adjusted water flow rate and data acquisition frequency. When the current heating efficiency is high, the current water flow rate (i.e., the current water flow rate of the new water dispenser) needs to be increased; when the current heating efficiency is low, the current water flow rate needs to be decreased; and when the current water flow rate is increased, the current data acquisition frequency (i.e., the current data acquisition frequency of the sensor) should also be increased.

[0080] In one implementation of this application, the current heating efficiency of the heating module can be determined based on the current water temperature at the inlet of the heating module, the current water temperature at the outlet of the heating module, the current water flow rate, and the current heating power. Then, based on the first temperature difference between the current preset water temperature and the current water temperature at the inlet of the heating module, and the second temperature difference between the current water temperature at the outlet of the heating module and the current water temperature at the inlet of the heating module, the current temperature error index is determined. The current water flow rate is adjusted based on the current temperature error index and the current heating efficiency to obtain the target water flow rate. The current data acquisition frequency is adjusted based on the target water flow rate to obtain the target data acquisition frequency.

[0081] Optionally, the current water temperature at the inlet of the heating module and the current water temperature at the outlet of the heating module can be determined at the moment when the heated drinking water passes through the outlet sensor. Then, the second temperature difference between the inlet and outlet of the heating module at that moment can be determined. Based on the second temperature difference at that moment, the current water flow rate, and the heating power of the heating module, the current heating efficiency can be determined.

[0082] Optionally, the current water flow rate may be unstable, and the current water flow rate can be determined by the water flow rate at the moment when the heated drinking water passes through the outlet sensor.

[0083] It is understandable that the data (including water temperature and flow rate) corresponding to the moment when heated drinking water passes through the sensor at the outlet is the earliest complete data that can be obtained. Based on the data at this moment, the current heating efficiency can be determined, and the water flow rate and data acquisition frequency can be adjusted more quickly and timely.

[0084] Optionally, the current heating efficiency of the heating module satisfies the following formula:

[0085]

[0086] in, express Current heating efficiency at any given moment. This indicates the specific heat capacity of water. This indicates the density of water. express The water flow rate at any given time express The second temperature difference between the inlet and outlet water temperatures of the constant heating module express The heating power of the heating module at all times.

[0087] It should be noted that if the heating power of the heating module is not in watts (e.g., in kilowatts), the unit of heating power needs to be converted to W before being used in the formula calculation.

[0088] In this formula, The time indicates the current moment, that is, the moment when the heated drinking water passes through the outlet sensor. This represents the heat power absorbed by water flow per unit time, and its unit is watt (W). The unit is watt. This is a dimensionless coefficient. The closer the value is to 1, the more heat the drinking water absorbs when flowing through the heating module, and the better the heating effect. The closer the value is to 0, the more insufficient the heating or the greater the heat loss.

[0089] It should be understood that the current temperature error index represents the degree and direction of deviation between the actual heating effect of the heating module at the current moment and the expected target.

[0090] Optionally, the current temperature error index satisfies the following formula:

[0091]

[0092] in, express The current temperature error index at any given moment. Indicates the expected water temperature. express The current water temperature at the inlet of the heating module is constantly monitored. express The second temperature difference between the inlet and outlet water temperatures of the heating module.

[0093] In this formula, This indicates the deviation between the target water temperature and the water temperature before heating, i.e., the first temperature difference. This represents the actual heating temperature difference, i.e., the second temperature difference. Based on this formula, it should be understood that when... When the actual heating effect is exactly as expected, it means that the heating effect has just reached the expected target; when If the water flow rate is too high, it indicates that the actual heating effect is insufficient and the water temperature has not reached the target. In this case, the current water flow rate can be appropriately reduced. If the flow rate is too high, it indicates that the actual heating effect is too great and there is overheating. In this case, the current water flow rate can be appropriately increased.

[0094] In this embodiment of the application, when If the heating module is not working, the temperature error index will not be calculated for this time.

[0095] In one alternative implementation, if the current heating efficiency is greater than a first heating efficiency threshold, the current water flow rate is increased based on the current temperature error index and the current heating efficiency to obtain the target water flow rate.

[0096] Optionally, a normal heating efficiency range can be set, which consists of a first heating efficiency threshold and a second heating efficiency threshold. When the current heating efficiency is within this normal heating efficiency range, no adjustment is needed; when the current heating efficiency is outside this range, the current heating efficiency is adjusted. This avoids over-adjustment.

[0097] For example, the first heating efficiency threshold can be 0.95, the second heating efficiency threshold can be 0.8, and the normal heating efficiency range can be [0.8, 0.95].

[0098] It is understandable that if the current heating efficiency is greater than the first heating efficiency threshold, it means that the heating capacity is excessive and the current flow rate is too slow, which may lead to overheating or wasted efficiency. In this case, the current water flow rate can be appropriately increased.

[0099] Optionally, the drinking water flow anomaly index can be determined based on the current temperature error index and the current heating efficiency, and then the product of the drinking water flow anomaly index and the current water flow rate can be determined as the target water flow rate.

[0100] Optionally, in When the current heating efficiency at any given time is greater than the first heating efficiency threshold, the drinking water flow anomaly index satisfies the following formula:

[0101]

[0102] in, express The abnormal index of drinking water flow at any given time. express Current heating efficiency at any given moment. express The current temperature error index at any given moment. This represents a normalization function, such as maximum-minimum normalization, used to normalize... The value is mapped to [0, 1].

[0103] Based on this formula, it should be understood that the lower the current heating efficiency and the greater the current temperature difference error index (greater than 1), the smaller the drinking water flow anomaly index and the smaller the adjustment range; conversely, the larger the drinking water flow anomaly index, the greater the adjustment range and the faster the target water flow rate after adjustment.

[0104] In another alternative implementation, if the current heating efficiency is less than the second heating efficiency threshold, the current water flow rate is reduced based on the current temperature error index and the current heating efficiency to obtain the target water flow rate.

[0105] The second heating efficiency threshold is less than the first heating efficiency threshold.

[0106] It is understandable that if the current heating efficiency is less than the second heating efficiency threshold, it means that the heating module's heating capacity is insufficient and the current water flow rate is too fast, causing the water temperature to not reach the required level. In this case, the current water flow rate can be appropriately reduced.

[0107] Similarly, the drinking water flow anomaly index can be determined based on the current temperature error index and the current heating efficiency, and then the product of the drinking water flow anomaly index and the current water flow rate can be determined as the target water flow rate.

[0108] Optionally, in When the current heating efficiency is less than the second heating efficiency threshold, the drinking water flow anomaly index satisfies the following formula:

[0109]

[0110] in, express The abnormal index of drinking water flow at any given time. express Current heating efficiency at any given moment. express The current temperature error index at any given moment. This represents a normalization function, such as maximum-minimum normalization, used to normalize... The values ​​are mapped to [0, 1]. This indicates the second heating efficiency threshold.

[0111] Based on this formula, it should be understood that since the current heating efficiency is less than the first heating efficiency threshold, therefore... A value greater than 0 indicates a significantly lower heating efficiency compared to the first heating efficiency threshold, signifying a more severe problem. This indicates the severity of poor heating; the more severe the poor heating, the lower the drinking water flow abnormality index.

[0112] Based on the above optional implementation method, two scenarios are distinguished: the current heating efficiency is too high and the current heating efficiency is too low. More refined and reasonable adaptive control logic is provided. When the current heating efficiency is too high, appropriately increasing the flow rate can prevent the water from being overheated, save energy, and extend the life of the heating element; when the current heating efficiency is too low, reducing the flow rate can ensure that the water is fully heated and that the drinking water temperature meets the standard.

[0113] In one alternative implementation, if the target water flow velocity is greater than or equal to the current water flow velocity, the current data acquisition frequency is corrected based on the ratio of the current water flow velocity to the target water flow velocity to obtain the target data acquisition frequency; if the target water flow velocity is less than the current water flow velocity, the current data acquisition frequency is determined as the target data acquisition frequency.

[0114] Understandably, if the target water flow velocity is greater than or equal to the current water flow velocity, the current data acquisition frequency may be too low, resulting in a small amount of data collected. In this case, the current data acquisition frequency can be increased.

[0115] Optionally, the target data acquisition frequency satisfies the following formula:

[0116]

[0117] in, express The target data acquisition frequency at any given time. express The current data acquisition frequency at any given moment. express The target water flow rate at any given time express The current water flow velocity at any given moment.

[0118] In this formula, when the target water flow velocity is greater than the current water flow velocity, If the value is greater than 1, the current data acquisition frequency is increased proportionally to the increase in water flow velocity to obtain the target data acquisition frequency.

[0119] Understandably, when the target water flow velocity is lower than the current water flow velocity, maintaining the current data collection frequency can avoid the problem of too few collection points due to instantaneous flow velocity fluctuations.

[0120] Understandably, the aforementioned method for adjusting the target data acquisition frequency achieves an adaptive balance between data acquisition load and information density. Adjusting the flow rate controls the residence time of drinking water in the heating module. When the target water flow rate increases, the acquisition frequency is increased proportionally, ensuring that a sufficient number of data points are collected per unit time to accurately capture water quality characteristics under high-speed water flow, improving the real-time performance of data acquisition and avoiding information loss. When the target water flow rate decreases, the original acquisition frequency is maintained, avoiding unnecessary and frequent adjustments to the data acquisition frequency, and reducing the system's data processing burden and energy consumption.

[0121] S104. Collect the current monitoring values ​​of each type of water quality sensor based on the target data acquisition frequency.

[0122] It is understandable that from the moment the target data acquisition frequency is determined, all sensors (including water quality sensors) acquire data based on the target data acquisition frequency.

[0123] Optionally, the target data acquisition frequency can be adjusted in real time based on the acquired data.

[0124] S105. Based on the temperature influence coefficient of each type of water quality sensor and the current monitoring value of each type of water quality sensor, determine the current status evaluation index of the filter element.

[0125] The current condition evaluation index of the filter element is used to evaluate the condition of the filter element.

[0126] It should be understood that the higher the current condition evaluation index of the filter element, the worse the condition of the filter element.

[0127] In one implementation of this application, the individual deviation value of each type of water quality sensor can be determined based on the difference between the current monitoring value and the standard reference value of each type of water quality sensor; the fusion weight of the individual deviation value of each type of water quality sensor can be determined based on the temperature influence coefficient of each type of water quality sensor; and the multiple individual deviation values ​​can be weighted and summed based on the fusion weight of the individual deviation values ​​of each type of water quality sensor to obtain the current state evaluation index of the filter element.

[0128] It should be understood that the standard reference value for each type of water quality sensor is the value monitored by that type of water quality sensor when the filter cartridge is in brand new condition.

[0129] Optionally, the current monitoring value of the water quality sensor at the outlet of the filter cartridge can be used as the current monitoring value of this type of water quality sensor.

[0130] Alternatively, the average of the current monitoring values ​​of all water quality sensors under each type of water quality sensor can be determined as the current monitoring value of that type of water quality sensor.

[0131] Optionally, the normalized value of the absolute value of the difference between the current monitoring value and the standard reference value of each type of water quality sensor can be determined as the individual deviation value of each type of water quality sensor.

[0132] Optionally, the absolute value of the difference can be normalized based on the maximum and minimum values ​​in the historical readings of each type of water quality sensor.

[0133] Understandably, the larger the temperature influence coefficient of a type of water quality sensor, the lower the reliability of that type of water quality sensor, and the smaller the fusion weight should be.

[0134] Optionally, the reciprocal of the temperature influence coefficient of each type of water quality sensor can be determined as the fusion weight of the individual deviation value of each type of water quality sensor.

[0135] Optionally, maximum and minimum value normalization can be performed based on the maximum and minimum values ​​of the reciprocals of the temperature influence coefficients of various types of water quality sensors.

[0136] Optionally, the current condition evaluation index of the filter element satisfies the following formula:

[0137]

[0138] in, express The current condition evaluation index of the filter element. This indicates the number of different types of water quality sensors. Indicates the first Temperature influence coefficient of water quality sensors Indicates the water outlet end of the filter element The Individual deviation values ​​of water quality sensors.

[0139] In this formula, The fusion weight is determined based on the temperature influence coefficient. The individual deviation values ​​of each type of water quality sensor are weighted and averaged based on the fusion weight of each type of water quality sensor. The resulting current state evaluation index can more accurately measure the filter cartridge status.

[0140] In one implementation of this application, if the current status evaluation index of the filter element is greater than the first evaluation index threshold, a filter element replacement prompt message can also be generated.

[0141] Understandably, if the current status evaluation index of the filter element is greater than the first evaluation index threshold, it indicates that the filter element is in poor condition and cannot filter effectively. In this case, a filter element replacement prompt message can be generated to remind the filter element that it needs to be replaced.

[0142] Optionally, the filter replacement reminder may also include a filter evaluation index and the monitoring values ​​of each water quality sensor.

[0143] Optionally, multiple evaluation index thresholds can be defined by combining industry standards and rated parameters of filter element types (such as RO filter elements and activated carbon filter elements), such as a first evaluation index threshold and a second evaluation index threshold.

[0144] For example, the first evaluation index threshold can be 0.6, and the second evaluation index threshold can be 0.3. For instance, when the current status evaluation index of the filter element is less than or equal to the first evaluation index threshold and greater than the second evaluation index threshold, the filtration effect of the filter element is considered to have entered the warning range and requires close monitoring. At this time, a warning message can be generated, and the monitoring cycle can be shortened (e.g., from 7 days / time to 2 days / time). This warning message is used to remind users to pay close attention to the status of the filter element. When the current status evaluation index of the filter element is less than or equal to the second evaluation index threshold, the filter element is considered to be in good condition and the filtration effect is normal. At this time, a good condition message can be generated, indicating that the filter element does not need to be replaced.

[0145] Alternatively, the multiple prompts can be displayed on the new water dispenser screen or pushed to the user's device.

[0146] Combining the methods provided in S110-S105 above, the heating effect of the heating module on drinking water is analyzed by current operating parameters, thereby dynamically adjusting the flow rate of drinking water passing through the heating module and the data acquisition frequency of the sensors. This ensures that sufficient monitoring data is collected while ensuring that the drinking water is fully heated, guaranteeing the timeliness and accuracy of the data samples. At the same time, by analyzing the differences in sensor monitoring data under different preset temperatures and the differences in sensor data before and after heating at the same preset temperature, the temperature influence coefficient of each type of water quality sensor is extracted. Based on the temperature influence coefficient and the current monitoring value of each type of water quality sensor, the filter element status can be evaluated, which can improve the accuracy of filter element status monitoring.

[0147] Please see Figure 2 The diagram shows a structural diagram of a real-time monitoring system for the filter status of a novel water dispenser provided in one embodiment of this application.

[0148] like Figure 2 As shown, the real-time monitoring system 20 for the filter status of this new type of water dispenser includes a data acquisition unit 201, a data processing unit 202, and an evaluation unit 203.

[0149] The data acquisition unit 201 is used to acquire the current operating parameters and historical operating data of the new water dispenser.

[0150] The current operating parameters include the current preset water temperature, current water flow rate, current water temperature and current heating power. The historical operating data includes monitoring data from multiple water quality sensors at the multiple preset water temperatures and the average water flow rate at each preset water temperature.

[0151] The data processing unit 202 is used to determine the temperature influence coefficient of each type of water quality sensor based on historical operating data.

[0152] Among them, the temperature influence coefficient of a type of water quality sensor is used to characterize the degree of fluctuation of the monitoring data of a type of water quality sensor affected by changes in water temperature.

[0153] The data processing unit 202 is also used to determine the target water flow rate and target data acquisition frequency of the new water dispenser based on the current operating parameters.

[0154] The data acquisition unit 201 is also used to acquire the current monitoring values ​​of each type of water quality sensor based on the target data acquisition frequency.

[0155] Evaluation unit 203 is used to determine the current status evaluation index of the filter element based on the temperature influence coefficient of each type of water quality sensor and the current monitoring value of each type of water quality sensor.

[0156] The current condition evaluation index of the filter element is used to evaluate the condition of the filter element.

[0157] It should be noted that the real-time filter status monitoring system 20 of this new type of water dispenser can realize any of the above-mentioned optional real-time filter status monitoring methods of the new type of water dispenser.

[0158] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0159] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A novel method for real-time monitoring of the filter cartridge status in a water dispenser, characterized in that, include: The current operating parameters and historical operating data of the water dispenser are obtained. The current operating parameters include the current preset water temperature, the current water flow rate, the current water temperature, and the current heating power. The historical operating data includes the monitoring data of multiple water quality sensors at multiple preset water temperatures and the average water flow rate at each preset water temperature. The current water temperature includes the current water temperature at the inlet of the heating module and the current water temperature at the outlet of the heating module. Based on the historical operating data, the temperature influence coefficient of each type of water quality sensor is determined. The temperature influence coefficient of a type of water quality sensor is used to characterize the degree of fluctuation of the monitoring data of a type of water quality sensor affected by water temperature changes. The current heating efficiency of the heating module is determined based on the current water temperature at the inlet of the heating module, the current water temperature at the outlet of the heating module, the current water flow rate, and the current heating power. Based on the first temperature difference between the current preset water temperature and the current water temperature at the inlet of the heating module, and the second temperature difference between the current water temperature at the outlet of the heating module and the current water temperature at the inlet of the heating module, the current temperature error index is determined. The target water flow rate is obtained by adjusting the current water flow rate based on the current temperature error index and the current heating efficiency. The target data acquisition frequency is obtained by adjusting the current data acquisition frequency based on the target water flow velocity; The current monitoring values ​​of each type of water quality sensor are collected based on the target data acquisition frequency; Based on the difference between the current monitoring value and the standard reference value of each type of water quality sensor, determine the individual deviation value of each type of water quality sensor; Based on the temperature influence coefficient of each type of water quality sensor, the fusion weight of the individual deviation value of each type of water quality sensor is determined; The current state evaluation index of the filter element is obtained by weighting and summing multiple individual deviation values ​​based on the fusion weight of the individual deviation values ​​of each type of water quality sensor. The current state evaluation index of the filter element is used to evaluate the state of the filter element.

2. The method for real-time monitoring of filter cartridge status in a novel water dispenser according to claim 1, characterized in that, The determination of the temperature influence coefficient for each type of water quality sensor based on the historical operating data includes: The initial influence coefficient of the first type of water quality sensor is determined based on the monitoring data of the first water quality sensor under multiple preset water temperatures. The first type of water quality sensor is the first type of water quality sensor at the outlet of the heating module. The first type of water quality sensor is any one of multiple types of water quality sensors. Based on the initial influence coefficient, the monitoring data of the first water quality sensor and the second water quality sensor at the same preset water temperature, and the average water flow rate at each preset water temperature, the temperature influence coefficient of the first type of water quality sensor is determined, and the second water quality sensor is the first type of water quality sensor at the water inlet of the heating module.

3. The method for real-time monitoring of filter cartridge status in a novel water dispenser according to claim 2, characterized in that, The determination of the initial influence coefficient of the first type of water quality sensor based on monitoring data from multiple preset water temperature sensors includes: The multiple preset water temperatures are combined in pairs to obtain M pairs of preset water temperatures, where M is an integer greater than or equal to 1. Determine the differences in monitoring data from the first water quality sensor at each pair of preset water temperatures, as well as the temperature difference between preset water temperatures; The initial influence coefficient of the first type of water quality sensor is determined based on the difference in monitoring data of the first water quality sensor at each pair of preset water temperatures and the temperature difference between preset water temperatures.

4. The method for real-time monitoring of filter cartridge status in a novel water dispenser according to claim 2, characterized in that, The determination of the temperature influence coefficient of the first type of water quality sensor based on the initial influence coefficient, the monitoring data of the first water quality sensor and the second water quality sensor at the same preset water temperature, and the average water flow velocity at each preset water temperature includes: Determine the difference in monitoring data between the first and second water quality sensors at each preset water temperature, as well as the historical temperature difference between the inlet and outlet at each preset water temperature; Based on the distance between the installation positions of the first and second water quality sensors, the average water flow rate at each preset water temperature, and the initial influence coefficient, the difference in monitoring data at the inlet and outlet at each preset water temperature is corrected to obtain the temperature rise difference of the monitoring data at the inlet and outlet at each preset water temperature. Based on the temperature rise difference of the monitoring data at the inlet and outlet ends under each preset water temperature and the historical temperature difference at the inlet and outlet ends under each preset water temperature, the temperature influence coefficient of the first type of water quality sensor is determined.

5. The method for real-time monitoring of filter cartridge status in a novel water dispenser according to claim 1, characterized in that, The step of adjusting the current water flow rate based on the current temperature error index and the current heating efficiency to obtain the target water flow rate includes: If the current heating efficiency is greater than the first heating efficiency threshold, the current water flow rate is increased based on the current temperature error index and the current heating efficiency to obtain the target water flow rate. If the current heating efficiency is less than the second heating efficiency threshold, the current water flow rate is reduced based on the current temperature error index and the current heating efficiency to obtain the target water flow rate, where the second heating efficiency threshold is less than the first heating efficiency threshold.

6. The method for real-time monitoring of filter cartridge status in a novel water dispenser according to claim 1, characterized in that, The process of adjusting the current data acquisition frequency based on the target water flow velocity to obtain the target data acquisition frequency includes: If the target water flow velocity is greater than or equal to the current water flow velocity, the current data acquisition frequency is corrected based on the ratio of the current water flow velocity to the target water flow velocity to obtain the target data acquisition frequency; If the target water flow velocity is less than the current water flow velocity, the current data acquisition frequency is determined as the target data acquisition frequency.

7. The method for real-time monitoring of filter cartridge status in a novel water dispenser according to claim 1, characterized in that, The method further includes: If the current status evaluation index of the filter element is greater than the first evaluation index threshold, a filter element replacement prompt message is generated.

8. A novel real-time monitoring system for the filter cartridge status of a water dispenser, characterized in that, It includes a data acquisition unit, a data processing unit, and an evaluation unit: The data acquisition unit is used to acquire the current operating parameters and historical operating data of the water dispenser. The current operating parameters include the current preset water temperature, the current water flow rate, the current water temperature and the current heating power. The historical operating data includes the monitoring data of multiple water quality sensors at multiple preset water temperatures and the average water flow rate at each preset water temperature. The data processing unit is used to determine the temperature influence coefficient of each type of water quality sensor based on the historical operating data. The temperature influence coefficient of a type of water quality sensor is used to characterize the degree of fluctuation of the monitoring data of a type of water quality sensor affected by water temperature changes. The data processing unit is further configured to: The current heating efficiency of the heating module is determined based on the current water temperature at the inlet of the heating module, the current water temperature at the outlet of the heating module, the current water flow rate, and the current heating power. Based on the first temperature difference between the current preset water temperature and the current water temperature at the inlet of the heating module, and the second temperature difference between the current water temperature at the outlet of the heating module and the current water temperature at the inlet of the heating module, the current temperature error index is determined. The target water flow rate is obtained by adjusting the current water flow rate based on the current temperature error index and the current heating efficiency. The target data acquisition frequency is obtained by adjusting the current data acquisition frequency based on the target water flow velocity; The data acquisition unit is also used to acquire the current monitoring value of each type of water quality sensor based on the target data acquisition frequency; The evaluation unit is used for: Based on the difference between the current monitoring value and the standard reference value of each type of water quality sensor, determine the individual deviation value of each type of water quality sensor; Based on the temperature influence coefficient of each type of water quality sensor, the fusion weight of the individual deviation value of each type of water quality sensor is determined; The current state evaluation index of the filter element is obtained by weighting and summing multiple individual deviation values ​​based on the fusion weight of the individual deviation values ​​of each type of water quality sensor. The current state evaluation index of the filter element is used to evaluate the state of the filter element.

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