Water softener and control method of sterilization module

Abstract

The embodiment of the invention provides a water softener and a control method of a sterilization module. According to the water softener, the sterilization module is arranged at the downstream of the jet device, so that diluted saline water (namely a mixed solution) mixed and diluted by the jet device is directly electrolyzed by the sterilization module, and the diluted saline water is electrolyzed by the sterilization module to generate a low-concentration sterilization solution (namely a target solution), so that the corrosion to each contact part in a pipeline is reduced. And meanwhile, the flow of the mixed solution is larger than that of strong brine, so that the influence of bubbles in the electrolysis process can be better reduced, and the current and the electrolysis effect are more stable.

Description

Technical Field

[0001] The present application relates to the field of water treatment technology, and in particular to a control method for a water softener and a sterilization module. Background Art

[0002] Household water softening equipment uses ion exchange technology to exchange functional ions on the resin with calcium and magnesium ions in the water to effectively remove scale, thereby improving the quality of bathing and drinking water. However, resins soaked in water for a long time are prone to breed bacteria, which may cause secondary pollution. In order to solve this problem, the water softener introduced an electrolytic sterilization module to sterilize the tank through sterilizing substances such as sodium hypochlorite generated by electrolyzing salt water.

[0003] Current water softeners all use sterilization modules to directly electrolyze concentrated brine, and the sterilization solution produced is also highly concentrated, which is highly corrosive to the contact parts in the pipeline. Summary of the invention

[0004] The embodiments of the present application provide a control method for a water softener and a sterilization module, thereby overcoming, at least to a certain extent, the problem that the sterilization module of a water softener in the prior art directly electrolyzes concentrated brine, resulting in the product being highly corrosive to the contact parts in the pipeline.

[0005] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by the practice of the present application.

[0006] According to one aspect of an embodiment of the present application, there is provided a water softener, the water softener comprising:

[0007] The ejector comprises a first water inlet, a second water inlet and a water outlet which are interconnected, wherein the first water inlet is connected to a concentrated brine pipeline, and the second water inlet is connected to a water source pipeline;

[0008] A sterilization module is arranged downstream of the ejector and is communicated with the water outlet of the ejector;

[0009] A tank body, disposed downstream of the sterilization module and communicated with the sterilization module;

[0010] The control system is connected with the sterilization module by electrical signals, and controls the sterilization module to electrolyze the mixed solution output from the water outlet of the ejector to produce a target solution.

[0011] According to one aspect of an embodiment of the present application, a control method for a sterilization module is provided, characterized in that the method is applied to the water softener as described above, and the control of the sterilization module includes:

[0012] Determining whether sterilization is required based on the water usage data of the water softener;

[0013] If sterilization is required, the corresponding sterilization parameters are determined, and the sterilization parameters include electrolysis time;

[0014] The water softener is sterilized according to the sterilization parameters.

[0015] In the technical solutions provided in some embodiments of the present application, by arranging the sterilization module downstream of the ejector, the sterilization module directly electrolyzes the diluted brine (i.e., the mixed solution) mixed and diluted by the ejector, and the diluted brine is electrolyzed by the sterilization module to produce a low-concentration sterilization solution (i.e., the target solution), thereby reducing the corrosiveness to the contact parts in the pipeline. At the same time, the flow rate of the mixed solution is also larger than that of the concentrated brine, which can better reduce the influence of bubbles during the electrolysis process and make the current and electrolysis effect more stable.

[0016] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present application, and together with the specification, are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0018] Figure 1 A structural schematic diagram of a water softener of the present application is shown.

[0019] Figure 2 A flow chart of a sterilization module control method provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0020] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more comprehensive and complete and fully convey the concept of the example embodiments to those skilled in the art.

[0021] In addition, described feature, structure or characteristic can be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present application. However, those skilled in the art will appreciate that the technical scheme of the present application can be put into practice without one or more of the specific details, or other methods, components, devices, steps, etc. can be adopted. In other cases, known methods, devices, realizations or operations are not shown or described in detail to avoid blurring the various aspects of the application.

[0022] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0023] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0024] See also Figure 1 The present disclosure provides a water softener, which includes a salt box 100, a sterilization module 200, a tank body 300, a control system 400, an ejector 600 and a water distributor 800.

[0025] The salt box 100, the ejector 600, the sterilization module 200, the water distributor 800 and the tank body 300 are connected in sequence through pipelines. The salt box 100 is located upstream of the ejector 600, the ejector 600 is located upstream of the sterilization module 200, and the water distributor 800 and the tank body 300 are located downstream of the sterilization module 200.

[0026] The ejector 600 includes two water inlets 601, 602 and a water outlet 603. The ejector 600 is connected to the salt box 100 through the water inlet 601, and is connected to the water source pipeline through the water inlet 602, so as to mix the concentrated brine from the salt box 100 and the softened water or tap water from the water source pipeline in a certain proportion to obtain a diluted brine (i.e., a mixed solution) of a certain concentration suitable for resin regeneration that meets the expected setting. The ejector 600 is connected to the sterilization module 200 through the water outlet 603, so as to input the aforementioned mixed solution into the sterilization module 200, so that the sterilization module 200 electrolyzes the mixed solution to produce a hypochlorous acid solution of a target concentration (i.e., a target solution). Finally, the target solution flows into the tank body 300 through the pipeline for sterilization and is discharged as wastewater.

[0027] The water distributor 800 is disposed on the tank body 300 , one end of which is connected to the tank body 300 , and the other end of which is connected to the sterilization module 200 , so as to evenly distribute the target solution generated by the sterilization module in the tank body 300 .

[0028] The tank body 300 may be a resin tank.

[0029] The control system 400 is connected to the sterilization module 200 via electrical signals to control the sterilization module 200 to electrolyze the mixed solution, thereby achieving control over the sterilization of the water softener.

[0030] In this embodiment, the sterilization module 200 electrolyzes diluted brine with a large flow rate, which can better reduce the impact of bubbles during the electrolysis process (hydrogen and chlorine will be produced during the electrolysis process), making the current and electrolysis effect more stable, and the sodium hypochlorite concentration is low, reducing corrosion to contact parts.

[0031] In some embodiments, the control system 400 may be a single chip microcomputer, a processor, a system on chip (System on Chip SoC) or other integrated circuits and circuit boards.

[0032] During the operation of the water softener, the control system 400 determines whether sterilization is required based on the water usage data of the water softener. If sterilization is required, the corresponding sterilization parameters are first determined, and the sterilization parameters include the electrolysis time. The sterilization parameters are then sent to the sterilization module 200 to control the sterilization module 200 to sterilize the water softener according to the sterilization parameters.

[0033] It should be noted that the sterilization module 200 can be a system for electrolyzing concentrated brine, such as a residual chlorine generator and an electrode sheet. The control system 400 can also be an air-cooled unit such as a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto. The control system 400 and the sterilization module 200 can be connected via Bluetooth, USB or other communication connection methods, and the present invention is not limited thereto.

[0034] Please refer to Figure 2 The control system 400 controls the sterilization module 200 to electrolyze the mixed solution output from the water outlet of the ejector, and the specific method of generating the target solution includes at least the following steps:

[0035] S100: Determine whether sterilization is required based on the water usage data of the water softener.

[0036] S200: If sterilization is required, corresponding sterilization parameters are determined, wherein the sterilization parameters include electrolysis time.

[0037] S300, sterilizing the water softener according to the sterilization parameters.

[0038] In the embodiment of the present application, it is first determined whether sterilization is required based on the water usage data of the water softener. If sterilization is required, the corresponding sterilization parameters are determined based on the water usage data of the water softener to achieve accurate adjustment of the sterilization intensity of the tank. Sterilizing the water softener based on the sterilization parameters can provide healthier and safer water quality.

[0039] In S100, since the sterilization module generally disinfects the water softener by electrolysis to produce a hypochlorous acid solution of the target concentration, in order to ensure normal use, the water softener needs to be disinfected at a specific time. Therefore, it is necessary to combine the water usage data to first determine whether it needs to be sterilized. If sterilization is required, then sterilization should be carried out.

[0040] Specifically, in some embodiments, the specific implementation of step S100 can refer to the following embodiments. Figure 2 The detailed description of step S100 in the sterilization module control method shown in the corresponding embodiment, in the sterilization module control method, step S100 may include the following steps:

[0041] Determine whether the water usage data meets a predetermined sterilization condition.

[0042] If the water usage data meets the predetermined sterilization condition, it is determined that sterilization treatment is required.

[0043] If the water usage data does not meet the predetermined sterilization condition, it is determined that sterilization is not to be performed.

[0044] In this embodiment, the water usage data includes cumulative data such as standby time and cumulative water output, and may also include real-time data such as substance content and bacterial content in the water.

[0045] On the one hand, whether sterilization is needed can be determined based on whether the accumulated data reaches a sterilization threshold. When the accumulated data reaches a certain value, sterilization is needed.

[0046] In some embodiments, it can be determined whether sterilization is required based on the accumulated data to determine whether the sterilization threshold is reached for the first time. If the accumulated data reaches the sterilization threshold, it is determined that sterilization is required. If the accumulated data does not reach the sterilization threshold, it is determined that sterilization is not required. There can be multiple sterilization thresholds.

[0047] For example, the water usage data is the cumulative water output, and the sterilization thresholds correspond to 1000L, 2000L, and 3000L. When the standby time reaches 2000L, it reaches the sterilization threshold. At this time, it is determined that sterilization is required and the sterilization procedure is executed immediately; when the standby time reaches 1001L, although it exceeds the sterilization threshold of 1000L, it is not 1001L, so it does not reach the sterilization threshold. At this time, it is determined that sterilization is not required.

[0048] In other embodiments, it can be determined whether the accumulated data in the water usage data is within the sterilization threshold interval to determine whether sterilization treatment is required. If the accumulated data is within the sterilization threshold interval, it is determined that sterilization treatment is required, and if the accumulated data is not within the sterilization threshold interval, it is determined that sterilization treatment is not required.

[0049] For example, if the water usage data is the cumulative water output, the sterilization thresholds correspond to 1000L, 2000L, and 3000L. In this case, the sterilization threshold can be set to [1000L, 1000L+V d )、[2000L,2000L+V d )、[3000L,3000L+V d ). Among them, V d It is a correction parameter value, which is related to the user's usage habits. Its value is more than the water consumption of the user in one use, and less than the water consumption of the user in two uses, so as to ensure the accurate judgment of each sterilization time and avoid missing the correct sterilization time.

[0050] Correction parameter V d It can be set as a universal value by the manufacturer based on relevant data before leaving the factory, or it can be set by the user according to his or her own usage habits, or it can be automatically set according to the user's usage habits, and this application does not limit this.

[0051] V d =1L as an example, when the cumulative water output reaches 2000.5L, it falls into the sterilization threshold range [2000L, 2000L + V d ), sterilization treatment is required at this time; when the cumulative water output reaches 2001L, it does not fall into the sterilization threshold interval. At this time, it is determined that sterilization treatment is not required.

[0052] On the other hand, whether sterilization is needed can also be determined based on whether the real-time data exceeds the standard. When the real-time data reaches a certain value, the real-time data exceeds the standard, which means sterilization is needed. Otherwise, no treatment is required.

[0053] In S200, after it is determined that sterilization is required, corresponding sterilization parameters are determined according to the water usage data of the water softener to achieve accurate adjustment of the sterilization intensity of the tank.

[0054] Specifically, in some embodiments, the specific implementation of step S200 can refer to the following embodiments. Figure 2 The detailed description of step S200 in the sterilization module control method shown in the corresponding embodiment, in the sterilization module control method, the sterilization parameter also includes a driving voltage pulse width ratio, and step S200 may include the following steps:

[0055] The electrolysis time is determined according to the accumulated water output.

[0056] The driving voltage pulse width ratio is determined according to the electrolysis time.

[0057] In this embodiment, it is possible to flexibly adjust according to different water quality and requirements, improve the versatility of the system, realize the reasonable allocation of time and energy consumption in the electrolysis process, effectively reduce operating costs, and extend the service life of the equipment. At the same time, by accurately controlling the electrolysis time and the driving voltage pulse width ratio, the microbial killing rate in the water can be maximized to ensure water quality safety.

[0058] Specifically, the water outflow can be monitored in real time by a flow sensor to obtain the cumulative water output.

[0059] In some embodiments, the electrolysis time can be determined by querying a cumulative water output-electrolysis time mapping relationship table, or can be determined based on a mapping relationship in which the cumulative water output and the electrolysis time are positively correlated.

[0060] In other embodiments, the electrolysis time is specifically determined by the following formula:

[0061] T=f(V)=αV

[0062] Wherein, T is the electrolysis time, V is the cumulative water output, and α is the time conversion coefficient, which is determined according to the usage scenario and can be 0.00005.

[0063] In some embodiments, the electrolysis time can be determined by querying a driving voltage pulse width ratio-electrolysis time mapping relationship table, or can be determined based on a mapping relationship in which the driving voltage pulse width ratio-electrolysis time is positively correlated.

[0064] In some other embodiments, the driving voltage pulse width ratio is specifically determined by the following formula:

[0065] PWM=f(T)=aT+b

[0066] Wherein, PWM is the driving voltage pulse width ratio, T is the electrolysis time, a is the width ratio conversion coefficient, and b is the constant term coefficient. a and b are determined according to the usage scenario, and they can be a=500 and b=25.

[0067] Specifically, in some embodiments, the specific implementation of step S200 can refer to the following embodiments. Figure 2 The detailed description of step S200 in the sterilization module control method shown in the corresponding embodiment, in the sterilization module control method, step S200 may include the following steps:

[0068] According to the water usage data, a corresponding sterilization mode is determined.

[0069] According to the sterilization mode, corresponding sterilization parameters are determined.

[0070] In this embodiment, the corresponding sterilization mode can be determined according to the water usage data, and then the sterilization parameters can be determined according to the corresponding sterilization mode for sterilization. By introducing the sterilization mode, the sterilization parameters can be flexibly adjusted according to different environmental and water quality conditions to achieve the best sterilization effect. At the same time, the adaptability and efficiency of the system are improved by comprehensive adjustment, ensuring effective disinfection in various situations while reducing energy consumption and resource waste. Overall, it can better meet actual needs and improve user experience.

[0071] In some embodiments, taking the standby time as an example, a standby time of 120 hours corresponds to a strong sterilization mode, a standby time of 80 hours corresponds to a standard sterilization mode, and a standby time of 40 hours corresponds to a fast sterilization mode.

[0072] Taking the cumulative water output as an example, a cumulative water output of 3000L corresponds to a strong sterilization mode, a cumulative water output of 2000L corresponds to a standard sterilization mode, and a cumulative water output of 1000L corresponds to a rapid sterilization mode.

[0073] In the strong sterilization mode, the electrolysis time is 0.15h, the current is 1A, and the driving voltage pulse width ratio is 100%.

[0074] In the standard sterilization mode, the electrolysis time is 0.1h, the current is 0.75A, and the driving voltage pulse width ratio is 75%.

[0075] In the rapid sterilization mode, the electrolysis time is 0.05h, the current is 0.5A, and the driving voltage pulse width ratio is 50%.

[0076] Specifically, in some embodiments, the specific implementation of step S200 can refer to the following embodiments. Figure 2 The detailed description of step S200 in the sterilization module control method shown in the corresponding embodiment, in the sterilization module control method, step S200 may include the following steps:

[0077] Determine the electrolysis time based on the cumulative water output, standby time and concentration of the mixed solution.

[0078] According to the electrolysis time, the driving voltage pulse width ratio and the current are determined.

[0079] In this embodiment, by comprehensively considering the standby time, cumulative water output and mixed solution concentration, the system can adjust the sterilization parameters in real time to maintain a high efficiency sterilization effect under different water quality conditions, that is, it can accurately control the sterilization process according to demand, thereby reducing unnecessary energy consumption, reducing operating costs, and extending the service life of the equipment.

[0080] It should be noted here that the concentration of the mixed solution is obtained in real time. Since the present application is to electrolyze a diluted mixed solution, the concentration of its product, that is, the concentration of the target solution for sterilizing the tank body, can be accurately estimated based on the concentration of the mixed solution. Therefore, by controlling the electrolysis parameters according to the concentration of the mixed solution, more precise adjustment of the tank sterilization intensity can be achieved.

[0081] In one implementation, the electrolysis time can be calculated according to preset rules. For example, a corresponding electrolysis time is first determined according to the cumulative water output and the mixed solution concentration, the standby time and the mixed solution concentration, and then summation, weighted summation and normalization are performed to obtain the corresponding electrolysis time.

[0082] In another implementation, a neural network model may be used, that is, the cumulative water output, the standby time, and the mixed solution concentration are input into an electrolysis time estimation model to obtain the electrolysis time.

[0083] Specifically, the cumulative water output, the standby time and the mixed solution concentration may be vectorized to obtain a multi-dimensional water use data vector, and then the water use data vector may be input into an electrolysis time estimation model to obtain the electrolysis time.

[0084] Since the electrolysis time estimation model is obtained through training with a large number of samples, maintenance only requires adjustment through samples. Compared with other estimation methods, the maintenance cost is lower. Basically, it only requires maintenance of the water consumption data vector, which reduces maintenance costs and improves code stability.

[0085] Specifically, in some embodiments, the training method of the electrolysis time estimation model mainly includes:

[0086] Acquire a water use data vector sample set, wherein the water use data vector sample set includes a plurality of water use data vector samples, and each of the water use data vector samples is marked with a corresponding electrolysis time in advance;

[0087] Inputting all water use data vector samples in the water use data vector sample set into the electrolysis time estimation model one by one to obtain an output electrolysis time;

[0088] According to the output electrolysis time and the marked electrolysis time, the parameters of the electrolysis time estimation model are updated until a predetermined end condition is reached, and the training is terminated to obtain a trained electrolysis time estimation model.

[0089] Specifically, in some embodiments, the electrolysis time estimation model is updated with parameters according to the output electrolysis time and the marked electrolysis time until a predetermined end condition is reached, and the training is terminated. Obtaining the trained electrolysis time estimation model may specifically include:

[0090] If, in the water use data vector sample set, less than a predetermined number of water use data vector samples are input into the electrolysis time estimation model, and the output electrolysis time is consistent with the marked electrolysis time, then the encoder parameters are updated;

[0091] If in the water use data vector sample set, more than a predetermined number of water use data vector samples are input into the electrolysis time estimation model and the output electrolysis time is consistent with the marked electrolysis time, then the predetermined end condition is met, the training is terminated, and a trained electrolysis time estimation model is obtained.

[0092] Specifically, in other embodiments, the electrolysis time estimation model is updated with parameters according to the output electrolysis time and the marked electrolysis time until a predetermined end condition is reached, and the training is terminated. Obtaining the trained electrolysis time estimation model may specifically include:

[0093] Determining a loss function according to the output electrolysis time and the marked electrolysis time;

[0094] The parameters of the electrolysis time estimation model are updated according to the loss function until a predetermined end condition is reached, and the training is terminated to obtain a trained electrolysis time estimation model.

[0095] In this embodiment, the loss function reaching a predetermined end condition may be that the loss function converges or the loss function is less than a predetermined loss (eg, 0.001).

[0096] In the above embodiment, the electrolysis time is estimated by using a neural network model obtained through multiple trainings to obtain the corresponding electrolysis time. The neural network model is obtained through multiple trainings. The more samples it trains, the more accurate the result obtained. It basically does not require maintenance during operation, which also reduces maintenance costs and improves the efficiency and accuracy of electrolysis time estimation.

[0097] It should be noted that the determination method of the driving voltage pulse width ratio and the current can refer to the previous embodiment, and this application will not repeat it here.

[0098] Specifically, in some embodiments, the specific implementation of step S200 can refer to the following embodiments. Figure 2 The detailed description of step S200 in the sterilization module control method shown in the corresponding embodiment, in the sterilization module control method, step S200 may include the following steps:

[0099] The cumulative water output, the standby time and the concentration of the mixed solution are input into a sterilization parameter estimation model to obtain the sterilization parameter.

[0100] In this embodiment, by inputting the cumulative water output, standby time and mixed solution concentration into the sterilization parameter estimation model, the required sterilization parameters can be determined more accurately to ensure the effectiveness of the sterilization process. The sterilization parameter estimation model can analyze data in real time and generate sterilization parameters, reduce manual intervention and decision-making time, and improve system response speed and efficiency.

[0101] Specifically, the sterilization parameter estimation model may include an electrolysis time estimation sub-model, a driving voltage pulse width ratio estimation sub-model, a current estimation sub-model and a normalization sub-model. When estimating the sterilization parameters, the sterilization parameter estimation model specifically performs the following steps:

[0102] The accumulated water output, the standby time and the mixed solution concentration are input into the electrolysis time estimation sub-model to obtain a rough estimate of the electrolysis time.

[0103] The cumulative water output, the mixed solution concentration and the electrolysis time are input into the driving voltage pulse width ratio estimation sub-model to obtain a rough estimation of the driving voltage pulse width ratio.

[0104] The standby time, the mixed solution concentration and the electrolysis time are input into a current estimation sub-model to obtain a rough estimated current.

[0105] The roughly estimated electrolysis time, the roughly estimated driving voltage pulse width ratio, the roughly estimated current and the concentration of the mixed solution are input into a normalized sub-model to obtain sterilization parameters.

[0106] In this embodiment, through the combination of multiple sub-models, the estimation model is made more refined, multi-dimensional parameter adjustment is achieved, the adaptability of the system is improved, and the problem of unsatisfactory sterilization effect caused by traditional technology based on only a single parameter is overcome, and the accuracy and flexibility of the sterilization process are improved; it also solves the response delay problem caused by traditional manual adjustment and ensures real-time performance. At the same time, through normalization processing, it can ensure that different parameters are balanced during the control process, and optimize resource utilization efficiency.

[0107] Among them, the electrolysis time estimation sub-model roughly estimates the electrolysis time based on the cumulative water output and the standby time, and the electrolysis time is a reference value. The driving voltage pulse width ratio estimation sub-model obtains a more accurate voltage pulse width ratio estimation by combining the existing electrolysis time and the cumulative water output, thereby improving the electrolysis effect. The current estimation sub-model obtains a more accurate current estimation by combining the standby time and the electrolysis time, thereby ensuring the stability of the electrolysis process.

[0108] Since the rough estimated electrolysis time, rough estimated driving voltage pulse width ratio and rough estimated current are independently estimated by their respective sub-models, but the electrolysis time, driving voltage pulse width ratio and current are interrelated in terms of sterilization intensity, they need to be normalized to ensure that the sterilization intensity formed by each sterilization parameter as a whole is appropriate, that is, the normalized sub-model normalizes each parameter to ensure the synergistic effect of different parameters in the control process and reduce the efficiency loss caused by imbalance.

[0109] When the cumulative water output and standby time are input into the sterilization parameter estimation model, the cumulative water output and standby time can be first vectorized into a water use data vector. Since the sterilization parameter estimation model is obtained through training with a large number of samples, maintenance only requires adjustment through samples. Compared with other estimation methods, the maintenance cost is lower. Basically, it only needs to maintain the water use data vector, which reduces maintenance costs and improves code stability.

[0110] During the model training process, the sterilization parameter estimation model can be taken as a whole, and all sub-models can be uniformly trained together through the same sample set, and finally a trained sterilization parameter estimation model can be obtained. In other embodiments, the electrolysis time estimation sub-model can use a pre-trained model, that is, before the sterilization parameter estimation model is trained, the electrolysis time estimation sub-model can be pre-trained first, and then the electrolysis time estimation sub-model can be included in the sterilization parameter estimation model and trained together with other sub-models. Among them, the specific training method of the electrolysis time estimation sub-model can refer to the training method of the above-mentioned electrolysis time estimation model, and this application will not repeat it here.

[0111] Specifically, the training method of the above-mentioned sterilization parameter estimation model specifically includes:

[0112] The water use data vector sample set is obtained, wherein the water use data vector sample set includes a plurality of water use data vector samples, and each water use data vector sample is marked with a corresponding sterilization parameter label.

[0113] The water use data vector samples are input into the sterilization parameter estimation model one by one to obtain the sterilization parameter results.

[0114] According to the output sterilization parameter results and the sterilization parameter labels, the parameters of the sterilization parameter estimation model are updated until a predetermined end condition is reached, and the training is terminated to obtain a trained sterilization parameter estimation model.

[0115] In an embodiment of the present application, during training, a water use data vector sample set including multiple water use data vector samples can be first obtained, and each water use data vector sample is marked with a corresponding sterilization parameter label; then the multiple water use data vector samples are divided into a training set, a validation set, and a test set according to a predetermined ratio, and then the parameters of the encoder and decoder in the sterilization parameter estimation model are adjusted and determined according to the water use data vector samples included in the training set, the validation set, and the test set to obtain a trained sterilization parameter prediction model.

[0116] When training the model, the water use data vector sample set can be divided into a training set, a validation set, and a test set, and then training is performed based on the training set, validation is performed based on the validation set, and testing is performed based on the test set to obtain a trained sterilization parameter estimation model.

[0117] Before training based on the training set, the water use data vector samples in the training set can be preprocessed. The preprocessing includes vector adjustment, normalization, data enhancement, category encoding and other processing.

[0118] After obtaining the enhanced training set, the sterilization parameter estimation model can be trained based on the enhanced training set to update the parameters and weights in the network.

[0119] Specifically, the water data vector samples in the training set are input into the sterilization parameter estimation model to obtain the sterilization parameter results output by the sterilization parameter estimation model. The sterilization parameter results are compared with the sterilization parameter labels to calculate the loss function. Then, the stochastic gradient descent method is used to minimize the loss function, and the parameters and weights in the sterilization parameter estimation model are updated by back propagation until the loss function meets the predetermined conditions, such as convergence or less than a predetermined threshold.

[0120] In some embodiments, the sterilization parameter result includes electrolysis time, driving voltage pulse width ratio and current, and the sterilization parameter label may include at least one of the electrolysis time label, the driving voltage pulse width ratio label and the current label. When calculating the loss function, the electrolysis time is compared with the electrolysis time label, the driving voltage pulse width ratio is compared with the driving voltage pulse width ratio label, and the current is compared with the current label.

[0121] After training, the sterilization parameter network after updating the parameters of the training set can be verified based on the validation set. Specifically, the sterilization parameter network is debugged based on the validation set data, and when the loss function meets the predetermined conditions, the model parameters of this stage are output. If the loss function does not meet the predetermined conditions, the hyperparameters such as the learning rate are automatically adjusted to train the next round of network model.

[0122] When the loss function calculated on the validation set meets the predetermined conditions, the parameters and weights can be retained, and then the retained parameters can be tested based on the test set. Specifically, the test set data is input so that the sterilization parameter network with retained parameters and weights can output the sterilization parameter results and model weights. The model loss and corresponding weights of multiple rounds are compared, and the model weight with the minimum loss is output to determine the sterilization parameter estimation model obtained by training.

[0123] After obtaining the trained sterilization parameter estimation model, the sterilization parameters can be completed based on the sterilization parameter estimation model.

[0124] In addition, no data augmentation is required for the data input in the validation set and the test set.

[0125] In S300, the previously determined sterilization parameters are applied to the water softener, and the sterilization process is started by controlling the device to achieve water purification. The embodiments of the present application can ensure that the sterilization effect matches the water quality state, avoid excessive or insufficient sterilization, reduce manual intervention, improve operational convenience, and reduce human errors.

[0126] In some embodiments, the sterilization module control method further includes:

[0127] If the water usage data reaches the clearing threshold interval, the water usage data is cleared.

[0128] In the embodiments of the present application, water use data needs to be cleared during long-term use. If it is not cleared, the accumulated data may exceed the system processing capacity and cause failures. Expired water use data may also lead to unnecessary sterilization treatment, increase energy consumption and costs, and affect user health. Regularly clearing water use data can avoid misleading caused by data accumulation, improve data accuracy and real-time performance, and prevent system processing delays caused by excessive data, ensuring efficient operation of the control system.

[0129] The clearing step may be performed before S100 or after S300. If the clearing step is performed before S100, the water usage data is cleared if it exceeds the clearing threshold. If the clearing step is performed after S300, the water usage data is cleared if it reaches the clearing threshold.

[0130] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the embodiments disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not disclosed in the present application.

[0131] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A water softener, characterized in that: The water softener comprises: The ejector comprises a first water inlet, a second water inlet and a water outlet which are interconnected, wherein the first water inlet is connected to a concentrated brine pipeline, and the second water inlet is connected to a water source pipeline; A sterilization module is arranged downstream of the ejector and is communicated with the water outlet of the ejector; A tank body, disposed downstream of the sterilization module and communicated with the sterilization module; The control system is connected with the sterilization module by electrical signals, and controls the sterilization module to electrolyze the mixed solution output from the water outlet of the ejector to produce a target solution.

2. The water softener according to claim 1, characterized in that: The water softener also includes: The water distributor is arranged on the tank body, one end of which is connected to the tank body and the other end of which is connected to the sterilization module, so as to evenly distribute the target solution generated by the sterilization module in the tank body.

3. The water softener according to claim 1, characterized in that: The water softener also includes: The salt box is arranged upstream of the ejector and is communicated with the first water inlet of the ejector for storing concentrated salt water.

4. A control method for a sterilization module, characterized in that: Applied to the water softener according to any one of claims 1 to 3, the control of the sterilization module includes: Determining whether sterilization is required based on the water usage data of the water softener; If sterilization is required, the corresponding sterilization parameters are determined, and the sterilization parameters include electrolysis time; The water softener is sterilized according to the sterilization parameters.

5. The sterilization module control method according to claim 4, characterized in that: The water use data includes the cumulative water output, the sterilization parameter also includes the driving voltage pulse width ratio, and the determination of the corresponding sterilization parameter specifically includes: Determining the electrolysis time according to the accumulated water output; The driving voltage pulse width ratio is determined according to the electrolysis time.

6. The sterilization module control method according to claim 5, characterized in that: The electrolysis time is specifically determined by the following formula: T=f(V)=αV Wherein, T is the electrolysis time, V is the cumulative water output, and α is the time conversion coefficient.

7. The sterilization module control method according to claim 5, characterized in that: The driving voltage pulse width ratio is specifically determined by the following formula: PWM=f(T)=aT+b Among them, PWM is the driving voltage pulse width ratio, T is the electrolysis time, a is the width ratio conversion coefficient, and b is the constant term coefficient.

8. The control method of the sterilization module according to claim 4, characterized in that: The determining of the corresponding sterilization parameters specifically includes: Determining a corresponding sterilization mode according to the water use data; According to the sterilization mode, corresponding sterilization parameters are determined.

9. The control method of the sterilization module according to claim 4, characterized in that Determining whether sterilization is required based on the water usage data of the water softener specifically includes: Determining whether the water use data meets a predetermined sterilization condition; If the water usage data meets the predetermined sterilization condition, it is determined that sterilization treatment is required; If the water usage data does not meet the predetermined sterilization condition, it is determined that sterilization is not to be performed.

10. The control method of the sterilization module according to claim 4, characterized in that: The sterilization module control method also includes: If the water usage data reaches the clearing threshold interval, the water usage data is cleared.

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