Sterilization system control method and related equipment

Abstract

The embodiment of the invention provides a sterilization system control method and related equipment. The sterilization system control method comprises the following steps: determining whether sterilization treatment is needed or not according to water consumption data of the water softener; if sterilization treatment needs to be carried out, corresponding sterilization parameters are determined, and the sterilization parameters comprise electrolysis time; and sterilizing the water softener according to the sterilization parameters. According to the technical scheme, whether sterilization treatment needs to be carried out or not is determined according to the water consumption data of the water softener, if sterilization treatment needs to be carried out, the corresponding sterilization parameters are determined according to the water consumption data of the water softener, and precise adjustment of the sterilization strength of the resin tank is achieved. And the water softener is sterilized according to the sterilization parameters, so that healthier and safer water quality can be provided.

Description

Technical Field

[0001] The present application relates to the field of computer and communication technology, and in particular to a sterilization system control method and related equipment. Background Art

[0002] Household water softening equipment uses ion exchange technology to exchange the functional ions on the resin with the calcium and magnesium ions in the water, thereby absorbing the excess calcium and magnesium ions in the water to achieve the purpose of removing scale. By using a water softener, the back-end water will not have scaling problems, including bathing water and drinking water.

[0003] However, the resin of the water softener is easily bred by bacteria due to long-term immersion in water, which will cause secondary pollution of the water. Therefore, the water softener introduces an electrolytic sterilization module to sterilize the resin tank. During the resin regeneration stage, the electrolytic sterilization module is started to electrolyze the brine, thereby electrolyzing the chloride ions in the brine into sodium hypochlorite and other sterilizing substances.

[0004] The bacterial growth of water softeners is different in different seasons and under different user habits, and the requirements for sterilization efficiency are also different. However, the current sterilization of water softeners is carried out once at a certain interval according to a predetermined program, without taking into account the different user habits. Summary of the invention

[0005] The embodiments of the present application provide a sterilization system control method and related equipment, which can at least to some extent overcome the problem that the water softener in the prior art has no way to accurately control the sterilization performance.

[0006] 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.

[0007] According to one aspect of an embodiment of the present application, a sterilization system control method is provided, including: determining whether sterilization treatment is required based on water usage data of the water softener; if sterilization treatment is required, determining corresponding sterilization parameters, the sterilization parameters including electrolysis time; and sterilizing the water softener according to the sterilization parameters.

[0008] In one implementation of the present application, the water usage data includes cumulative water output, the sterilization parameters also include a driving voltage pulse width ratio, and determining the corresponding sterilization parameters specifically includes: determining the electrolysis time based on the cumulative water output; determining the driving voltage pulse width ratio based on the electrolysis time.

[0009] In one implementation of the present application, the electrolysis time is specifically determined by the following formula:

[0010] T=f(V)=αV

[0011] Wherein, T is the electrolysis time, V is the cumulative water output, and α is the time conversion coefficient.

[0012] In one implementation of the present application, the driving voltage pulse width ratio is specifically determined by the following formula:

[0013] PWM=f(T)=aT+b

[0014] 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.

[0015] In one implementation of the present application, the water usage data includes standby time, the sterilization parameters also include current, and determining the corresponding sterilization parameters specifically includes: determining the electrolysis time based on the standby time; determining the current based on the electrolysis time.

[0016] In one implementation of the present application, the electrolysis time is specifically determined by the following formula:

[0017] T=f(t)=βt

[0018] Wherein, T is the electrolysis time, t is the standby time, and β is the time conversion coefficient.

[0019] In one implementation of the present application, the current is specifically determined by the following formula:

[0020] I=f(T)=cT+d

[0021] Where, I is the current, T is the electrolysis time, c is the current conversion factor, and d is the constant term coefficient.

[0022] In one implementation of the present application, the determining the corresponding sterilization parameters specifically includes: determining the corresponding sterilization mode according to the water usage data; and determining the corresponding sterilization parameters according to the sterilization mode.

[0023] In one implementation of the present application, the water usage data includes the cumulative water output and the standby time, the sterilization parameters also include the driving voltage pulse width ratio and the current, and the determination of the corresponding sterilization parameters specifically includes: determining the electrolysis time based on the cumulative water output and the standby time; determining the driving voltage pulse width ratio and the current based on the electrolysis time.

[0024] In one implementation of the present application, determining the electrolysis time based on the cumulative water output and the standby time specifically includes: inputting the cumulative water output and the standby time into an electrolysis time estimation model to obtain the electrolysis time.

[0025] In one implementation of the present application, the water usage data includes cumulative water output and standby time, and determining the corresponding sterilization parameters specifically includes: inputting the cumulative water output and the standby time into a sterilization parameter estimation model to obtain the sterilization parameters.

[0026] In one implementation of the present application, the cumulative water output and the standby time are input into a sterilization parameter estimation model, and the sterilization parameters also include a driving voltage pulse width ratio and a current. The sterilization parameter estimation model includes 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. The cumulative water output and the standby time are input into the sterilization parameter estimation model to obtain the sterilization parameters, which specifically includes: inputting the cumulative water output and the standby time into the electrolysis time estimation sub-model to obtain a rough estimate of the electrolysis time; inputting the cumulative water output and the electrolysis time into the driving voltage pulse width ratio estimation sub-model to obtain a rough estimate of the driving voltage pulse width ratio; inputting the standby time and the electrolysis time into the current estimation sub-model to obtain a rough estimate of the current; inputting the rough estimate of the electrolysis time, the rough estimate of the driving voltage pulse width ratio and the rough estimate of the current into the normalization sub-model to obtain the sterilization parameters.

[0027] In one implementation of the present application, determining whether sterilization treatment is required based on the water usage data of the water softener specifically includes: determining whether the water usage data meets predetermined sterilization conditions; if the water usage data meets the predetermined sterilization conditions, determining that sterilization treatment is required; if the water usage data does not meet the predetermined sterilization conditions, determining that sterilization treatment is not required.

[0028] In an implementation of the present application, the sterilization system control method further includes: if the water usage data reaches the clearing threshold interval, clearing the water usage data.

[0029] According to one aspect of an embodiment of the present application, a sterilization system control device is provided, which includes: a sterilization judgment module, used to determine whether sterilization treatment is required based on the water usage data of the water softener; a parameter judgment module, used to determine the corresponding sterilization parameters if sterilization treatment is required, and the sterilization parameters include electrolysis time; a sterilization execution module, used to sterilize the water softener according to the sterilization parameters.

[0030] In one implementation of the present application, the water usage data includes the cumulative water output, the sterilization parameters also include the driving voltage pulse width ratio, and the parameter judgment module specifically includes: a first time determination submodule, used to determine the electrolysis time according to the cumulative water output; a PWM determination submodule, used to determine the driving voltage pulse width ratio according to the electrolysis time.

[0031] In one implementation of the present application, the electrolysis time is specifically determined by the following formula:

[0032] T=f(V)=αV

[0033] Wherein, T is the electrolysis time, V is the cumulative water output, and α is the time conversion coefficient.

[0034] In one implementation of the present application, the driving voltage pulse width ratio is specifically determined by the following formula:

[0035] PWM=f(T)=aT+b

[0036] 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.

[0037] In one implementation of the present application, the water usage data includes standby time, the sterilization parameter also includes current, and the parameter judgment module specifically includes: a second time determination submodule, used to determine the electrolysis time according to the standby time; and a current determination submodule, used to determine the current according to the electrolysis time.

[0038] In one implementation of the present application, the electrolysis time is specifically determined by the following formula:

[0039] T=f(t)=βt

[0040] Wherein, T is the electrolysis time, t is the standby time, and β is the time conversion coefficient.

[0041] In one implementation of the present application, the current is specifically determined by the following formula:

[0042] I=f(T)=cT+d

[0043] Where, I is the current, T is the electrolysis time, c is the current conversion factor, and d is the constant term coefficient.

[0044] In one implementation of the present application, the parameter judgment module specifically includes: a sterilization mode determination submodule, used to determine the corresponding sterilization mode according to the water usage data; and a sterilization parameter determination submodule, used to determine the corresponding sterilization parameters according to the sterilization mode.

[0045] In one implementation of the present application, the water usage data includes the cumulative water output and the standby time, the sterilization parameters also include the driving voltage pulse width ratio and the current, and the parameter judgment module specifically includes: an electrolysis time determination submodule, used to determine the electrolysis time according to the cumulative water output and the standby time; a specific parameter determination submodule, used to determine the driving voltage pulse width ratio and the current according to the electrolysis time.

[0046] In one implementation of the present application, the electrolysis time determination submodule specifically includes: a time estimation unit, which is used to input the cumulative water output and the standby time into an electrolysis time estimation model to obtain the electrolysis time.

[0047] In one implementation of the present application, the water usage data includes cumulative water output and standby time, and the parameter judgment module specifically includes: a parameter estimation submodule, which is used to input the cumulative water output and the standby time into a sterilization parameter estimation model to obtain the sterilization parameters.

[0048] In one implementation of the present application, the cumulative water output and the standby time are input into a sterilization parameter estimation model, and the sterilization parameters also include a driving voltage pulse width ratio and a current. The sterilization parameter estimation model includes 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. The parameter estimation sub-module specifically includes: a first rough estimation unit, used to input the cumulative water output and the standby time into the electrolysis time estimation sub-model to obtain a rough estimated electrolysis time; a second rough estimation unit, used to input the cumulative water output and the electrolysis time into the driving voltage pulse width ratio estimation unit to obtain a rough estimated driving voltage pulse width ratio; a third rough estimation unit, used to input the standby time and the electrolysis time into the current estimation sub-model to obtain a rough estimated current; a parameter normalization unit, used to input the rough estimated electrolysis time, the rough estimated driving voltage pulse width ratio and the rough estimated current into the normalization sub-model to obtain the sterilization parameters.

[0049] In one implementation of the present application, the sterilization judgment module specifically includes: a sterilization condition judgment submodule, used to determine whether the water use data meets the predetermined sterilization conditions; a first condition execution submodule, used to determine that sterilization treatment is required if the water use data meets the predetermined sterilization conditions; and a second condition execution submodule, used to determine that sterilization treatment is not required if the water use data does not meet the predetermined sterilization conditions.

[0050] In an implementation of the present application, the sterilization system control device further includes: a data clearing module, configured to clear the water usage data if the water usage data reaches the clearing threshold interval.

[0051] According to one aspect of an embodiment of the present application, a computer-readable medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the sterilization system control method as described in the above embodiment is implemented.

[0052] According to one aspect of an embodiment of the present application, a water softener is provided, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the sterilization system control method as described in the above embodiments.

[0053] According to one aspect of an embodiment of the present application, a computer program product is provided, including a computer program, characterized in that when the computer program is executed by a processor, the sterilization system control method as described in the above embodiment is implemented.

[0054] In the technical solutions provided in some embodiments 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 resin tank. Sterilizing the water softener based on the sterilization parameters can provide healthier and safer water quality.

[0055] 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

[0056] 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:

[0057] Figure 1 An exemplary implementation environment diagram is shown to which the technical solution of the embodiments of the present application can be applied.

[0058] Figure 2 Shown in Figure 1 An implementation environment diagram showing more details of the implementation environment diagram.

[0059] Figure 3 Shown in Figure 1 Another implementation environment diagram showing more details of the implementation environment diagram.

[0060] Figure 4 A flow chart of a sterilization system control method provided in an embodiment of the present application is shown.

[0061] Figure 5 A schematic structural diagram of a sterilization system control device provided in an embodiment of the present application is shown.

[0062] Figure 6A schematic structural diagram of a computer system of a water softener provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0063] 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.

[0064] 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.

[0065] 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.

[0066] 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.

[0067] Figure 1 FIG. 1 is an implementation environment diagram of a sterilization system control method provided in an embodiment, such as Figure 1 As shown, in this implementation environment, a salt box 100, a sterilization system 200, a resin tank 300 and a control system 400 are included, which are all arranged in the same water softener.

[0068] The salt box 100, the sterilization system 200 and the resin tank 300 are connected by pipelines, the salt box 100 is located upstream of the sterilization system 200, and the resin tank 300 is located downstream of the sterilization system 200. Concentrated brine is stored in the salt box 100, and after the concentrated brine flows into the sterilization system 200 through the pipeline, the sterilization system 200 electrolyzes to obtain a sodium hypochlorite solution. The sodium hypochlorite solution flows into the resin tank through the pipeline for sterilization.

[0069] The control system 400 is connected to the sterilization system 200 via electrical signals to control the sterilization system 200 to sterilize the resin tank 300 .

[0070] The control system 400 is used to control the sterilization system 200, which can be a single-chip microcomputer, a processor, a system on chip (System on Chip SoC) and other integrated circuits and circuit boards. During the operation of the water softener, the control system 400 will determine 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. Then the sterilization parameters are sent to the sterilization system 200 to control the sterilization system 200 to sterilize the water softener according to the sterilization parameters.

[0071] It should be noted that the sterilization system 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 system 200 can be connected via Bluetooth, USB or other communication connection methods, and the present invention is not limited thereto.

[0072] Please combine Figure 1 Read together Figure 2 , Figure 2 A more specific implementation environment diagram is shown.

[0073] exist Figure 2 In the illustrated implementation environment, the water softener process includes a salt box 100 , a sterilization system 200 , a resin tank 300 , and a control system 400 , and may also include an ejector 600 and a water distributor 800 .

[0074] The water distributor 800 is disposed on the resin tank 300 , one end of which is connected to the resin tank 300 , and the other end of which is connected to the sterilization system 200 , so as to evenly distribute the sodium hypochlorite solution generated by the sterilization system in the resin tank 300 .

[0075] The ejector 600 includes two water inlets 601 and 602 and a water outlet 603. The ejector 600 is connected to the salt tank 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 tank 100 and the softened water or tap water from the water source pipeline in a certain proportion to obtain a diluted brine of a certain concentration suitable for resin regeneration that meets the expected setting. The ejector 600 is connected to the sterilization system 200 through the water outlet 603, so as to pass the aforementioned diluted brine into the sterilization system 200, so that the sterilization system 200 electrolyzes to produce a hypochlorous acid solution of a target concentration.

[0076] exist Figure 2In the illustrated embodiment, the sterilization system 200 electrolyzes diluted brine with a larger 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.

[0077] Please combine Figure 1 Read together Figure 3 , Figure 3 Another more specific implementation environment diagram is shown.

[0078] exist Figure 3 In the illustrated implementation environment, the water softener process includes a salt box 100 , a sterilization system 200 , a resin tank 300 , and a control system 400 , and may also include an ejector 600 and a water distributor 800 .

[0079] The water distributor 800 is disposed on the resin tank 300 , one end of which is connected to the resin tank 300 , and the other end of which is connected to the ejector 600 .

[0080] The ejector 600 includes two water inlets 601 and 602 and a water outlet 603. The ejector 600 is connected to the sterilization system 200 through the water inlet 601 to receive the high-concentration hypochlorous acid solution generated by electrolysis of the sterilization system 200. At the same time, it is connected to the water source pipeline through the water inlet 602 to mix the high-concentration hypochlorous acid solution of the sterilization system 200 with softened water or tap water from the water source pipeline in a certain proportion to obtain a sodium hypochlorite solution of a target concentration.

[0081] The ejector 600 is connected to the water distributor 800 through the water outlet 603 , so as to evenly distribute the aforementioned sodium hypochlorite solution of the target concentration in the resin tank 300 through the water distributor 800 .

[0082] exist Figure 3 In the illustrated embodiment, the sterilization system 200 directly electrolyzes high-concentration salt water, which has a higher electrolysis efficiency.

[0083] The implementation details of the technical solution of the embodiment of the present application are described in detail below:

[0084] Figure 4 A flowchart of a sterilization system control method according to an embodiment of the present application is shown. The sterilization system control method can be executed by a control system of a water softener. The control system can be Figure 1 The control system 400 shown in FIG. Figure 4 As shown, the sterilization system control method at least includes:

[0085] S100: Determine whether sterilization is required based on the water usage data of the water softener.

[0086] S200: If sterilization is required, corresponding sterilization parameters are determined, wherein the sterilization parameters include electrolysis time.

[0087] S300, sterilizing the water softener according to the sterilization parameters.

[0088] 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 resin tank. Sterilizing the water softener based on the sterilization parameters can provide healthier and safer water quality.

[0089] In S100, since the sterilization system 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.

[0090] Specifically, in some embodiments, the specific implementation of step S100 can refer to the following embodiments. Figure 4 The detailed description of step S100 in the sterilization system control method shown in the corresponding embodiment, in the sterilization system control method, step S100 may include the following steps:

[0091] Determine whether the water usage data meets a predetermined sterilization condition.

[0092] If the water usage data meets the predetermined sterilization condition, it is determined that sterilization treatment is required.

[0093] If the water usage data does not meet the predetermined sterilization condition, it is determined that sterilization is not to be performed.

[0094] 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.

[0095] 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.

[0096] 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.

[0097] For example, the water usage data is the standby time, and the corresponding sterilization thresholds are 40h, 80h, and 100h. When the standby time reaches 80h, 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 41h, although it exceeds the sterilization threshold of 40h, it is not 40h, so it does not reach the sterilization threshold. At this time, it is determined that sterilization is not required.

[0098] 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.

[0099] 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.

[0100] 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.

[0101] 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.

[0102] 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.

[0103] 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 resin tank.

[0104] Specifically, in some embodiments, the specific implementation of step S200 can refer to the following embodiments. Figure 4 The detailed description of step S200 in the sterilization system control method shown in the corresponding embodiment, in the sterilization system control method, the sterilization parameter also includes the driving voltage pulse width ratio, and step S200 may include the following steps:

[0105] The electrolysis time is determined according to the accumulated water output.

[0106] The driving voltage pulse width ratio is determined according to the electrolysis time.

[0107] 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.

[0108] Specifically, the water outflow can be monitored in real time by a flow sensor to obtain the cumulative water output.

[0109] 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.

[0110] In other embodiments, the electrolysis time is specifically determined by the following formula:

[0111] T=f(V)=αV

[0112] 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.

[0113] 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.

[0114] In some other embodiments, the driving voltage pulse width ratio is specifically determined by the following formula:

[0115] PWM=f(T)=aT+b

[0116] 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.

[0117] Specifically, in some embodiments, the specific implementation of step S200 can refer to the following embodiments. Figure 4 The detailed description of step S200 in the sterilization system control method shown in the corresponding embodiment, in the sterilization system control method, the sterilization parameter also includes current, and step S200 may include the following steps:

[0118] The electrolysis time is determined according to the standby time.

[0119] The current is determined according to the electrolysis time.

[0120] In this embodiment, by monitoring the standby time, the system can be operated stably and the impact of water quality fluctuations can be reduced. At the same time, the electrolysis time and current can be accurately controlled according to the standby time, making the sterilization process more efficient, reducing damage to the equipment due to overload, and improving the durability and reliability of the equipment.

[0121] Specifically, the standby time can be obtained by a timer.

[0122] In some embodiments, the electrolysis time can be determined by querying a standby time-electrolysis time mapping relationship table, or can be determined based on a mapping relationship in which the standby time and the electrolysis time are positively correlated.

[0123] The electrolysis time is specifically determined by the following formula:

[0124] T=f(t)=βt

[0125] Wherein, T is the electrolysis time, t is the standby time, and β is the time conversion coefficient, which is determined according to the usage scenario and can be 0.0013.

[0126] In some embodiments, the electrolysis time can be determined by querying a current-electrolysis time mapping relationship table, or can be determined based on a mapping relationship in which the current and the electrolysis time are positively correlated.

[0127] The current is specifically determined by the following formula:

[0128] I=f(T)=cT+d

[0129] Wherein, I is the current, T is the electrolysis time, c is the current conversion coefficient, and d is the constant term coefficient. c and d are determined according to the usage scenario, and they can be c=5 and d=0.25.

[0130] It should be noted here that in some other embodiments, the electrolysis time, the driving voltage pulse width ratio and the current can also be directly determined according to the standby time or the cumulative water output, or the driving voltage pulse width ratio and the current can be first determined according to the standby time or the cumulative water output, and then the electrolysis time can be determined according to the driving voltage pulse width ratio and / or the current. This application does not limit this.

[0131] Specifically, in some embodiments, the specific implementation of step S200 can refer to the following embodiments. Figure 4 The detailed description of step S200 in the sterilization system control method shown in the corresponding embodiment, in the sterilization system control method, step S200 may include the following steps:

[0132] A corresponding sterilization mode is determined according to the water usage data.

[0133] According to the sterilization mode, corresponding sterilization parameters are determined.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] In the strong sterilization mode, the electrolysis time is 0.15h, the current is 1A, and the driving voltage pulse width ratio is 100%.

[0138] 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%.

[0139] 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%.

[0140] Specifically, in some embodiments, the specific implementation of step S200 can refer to the following embodiments. Figure 4The detailed description of step S200 in the sterilization system control method shown in the corresponding embodiment, in the sterilization system control method, step S200 may include the following steps:

[0141] The electrolysis time is determined according to the accumulated water output and the standby time.

[0142] According to the electrolysis time, the driving voltage pulse width ratio and the current are determined.

[0143] In this embodiment, by comprehensively considering the standby time and the cumulative water output, the system can adjust the sterilization parameters in real time so that it can 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.

[0144] In one implementation, the electrolysis time may be calculated according to a preset rule, for example, a corresponding electrolysis time may be determined according to the cumulative water output and the standby time, and then summation, weighted summation, and normalization may be performed to obtain the corresponding electrolysis time.

[0145] In another implementation, a neural network model may be used, that is, the cumulative water output and the standby time are input into an electrolysis time estimation model to obtain the electrolysis time.

[0146] Specifically, the accumulated water output and the standby time can be vectorized to obtain a multi-dimensional water consumption data vector, and then the water consumption data vector can be input into the electrolysis time estimation model to obtain the electrolysis time.

[0147] 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.

[0148] Specifically, in some embodiments, the training method of the electrolysis time estimation model mainly includes:

[0149] 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;

[0150] Input 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;

[0151] 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.

[0152] 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:

[0153] 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;

[0154] 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.

[0155] 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:

[0156] Determining a loss function according to the output electrolysis time and the marked electrolysis time;

[0157] 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.

[0158] 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).

[0159] 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.

[0160] It should be noted that the method for determining the driving voltage pulse width ratio and the current can refer to the previous embodiments, and this application will not go into details here.

[0161] Specifically, in some embodiments, the specific implementation of step S200 can refer to the following embodiments. Figure 4 The detailed description of step S200 in the sterilization system control method shown in the corresponding embodiment, in the sterilization system control method, step S200 may include the following steps:

[0162] The cumulative water output and the standby time are input into a sterilization parameter estimation model to obtain the sterilization parameter.

[0163] In this embodiment, by inputting the cumulative water output and standby time 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.

[0164] 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:

[0165] The accumulated water output and the standby time are input into the electrolysis time estimation sub-model to obtain a rough estimate of the electrolysis time.

[0166] The accumulated water output 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.

[0167] The standby time and the electrolysis time are input into a current estimation sub-model to obtain a rough estimated current.

[0168] The roughly estimated electrolysis time, the roughly estimated driving voltage pulse width ratio and the roughly estimated current are input into a normalized sub-model to obtain sterilization parameters.

[0169] 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.

[0170] 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.

[0171] 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.

[0172] 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.

[0173] 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.

[0174] Specifically, the training method of the above-mentioned sterilization parameter estimation model specifically includes:

[0175] 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.

[0176] The water use data vector samples are input into the sterilization parameter estimation model one by one to obtain the sterilization parameter results.

[0177] 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.

[0178] 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.

[0179] 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.

[0180] 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.

[0181] 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.

[0182] 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.

[0183] In some embodiments, the sterilization parameter result includes a driving voltage pulse width ratio and a current, and the sterilization parameter label may include at least one of a driving voltage pulse width ratio label and a current label. When calculating the loss function, the driving voltage pulse width ratio is compared with the driving voltage pulse width ratio label and / or the current is compared with the current label.

[0184] 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.

[0185] 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.

[0186] After obtaining the trained sterilization parameter estimation model, the sterilization parameters can be completed based on the sterilization parameter estimation model.

[0187] In addition, no data augmentation is required for the data input in the validation set and the test set.

[0188] 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.

[0189] In some embodiments, the sterilization system control method further includes:

[0190] If the water usage data reaches the clearing threshold interval, the water usage data is cleared.

[0191] 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.

[0192] 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.

[0193] The following describes an embodiment of the device of the present application, which can be used to execute the sterilization system control method in the above embodiment of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the sterilization system control method in the above embodiment of the present application.

[0194] Figure 5 A block diagram of a sterilization system control device according to an embodiment of the present application is shown.

[0195] Reference Figure 5 As shown, a sterilization system control device 500 according to an embodiment of the present application includes: a sterilization judgment module 510, a parameter judgment module 520 and a sterilization execution module 530.

[0196] Among them, the sterilization judgment module 510 is used to determine whether sterilization treatment is required based on the water usage data of the water softener; the parameter judgment module 520 is used to determine the corresponding sterilization parameters if sterilization treatment is required, and the sterilization parameters include electrolysis time; the sterilization execution module 530 is used to sterilize the water softener according to the sterilization parameters.

[0197] In one implementation of the present application, the water usage data includes the cumulative water output, the sterilization parameters also include the driving voltage pulse width ratio, and the parameter judgment module specifically includes: a first time determination submodule, used to determine the electrolysis time according to the cumulative water output; a PWM determination submodule, used to determine the driving voltage pulse width ratio according to the electrolysis time.

[0198] In one implementation of the present application, the electrolysis time is specifically determined by the following formula:

[0199] T=f(V)=αV

[0200] Wherein, T is the electrolysis time, V is the cumulative water output, and α is the time conversion coefficient.

[0201] In one implementation of the present application, the driving voltage pulse width ratio is specifically determined by the following formula:

[0202] PWM=f(T)=aT+b

[0203] 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.

[0204] In one implementation of the present application, the water usage data includes standby time, the sterilization parameter also includes current, and the parameter judgment module specifically includes: a second time determination submodule, used to determine the electrolysis time according to the standby time; and a current determination submodule, used to determine the current according to the electrolysis time.

[0205] In one implementation of the present application, the electrolysis time is specifically determined by the following formula:

[0206] T=f(t)=βt

[0207] Wherein, T is the electrolysis time, t is the standby time, and β is the time conversion coefficient.

[0208] In one implementation of the present application, the current is specifically determined by the following formula:

[0209] I=f(T)=cT+d

[0210] Where, I is the current, T is the electrolysis time, c is the current conversion factor, and d is the constant term coefficient.

[0211] In one implementation of the present application, the parameter judgment module specifically includes: a sterilization mode determination submodule, used to determine the corresponding sterilization mode according to the water usage data; and a sterilization parameter determination submodule, used to determine the corresponding sterilization parameters according to the sterilization mode.

[0212] In one implementation of the present application, the water usage data includes the cumulative water output and the standby time, the sterilization parameters also include the driving voltage pulse width ratio and the current, and the parameter judgment module specifically includes: an electrolysis time determination submodule, used to determine the electrolysis time according to the cumulative water output and the standby time; a specific parameter determination submodule, used to determine the driving voltage pulse width ratio and the current according to the electrolysis time.

[0213] In one implementation of the present application, the electrolysis time determination submodule specifically includes: a time estimation unit, which is used to input the cumulative water output and the standby time into an electrolysis time estimation model to obtain the electrolysis time.

[0214] In one implementation of the present application, the water usage data includes cumulative water output and standby time, and the parameter judgment module specifically includes: a parameter estimation submodule, which is used to input the cumulative water output and the standby time into a sterilization parameter estimation model to obtain the sterilization parameters.

[0215] In one implementation of the present application, the cumulative water output and the standby time are input into a sterilization parameter estimation model, and the sterilization parameters also include a driving voltage pulse width ratio and a current. The sterilization parameter estimation model includes 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. The parameter estimation sub-module specifically includes: a first rough estimation unit, used to input the cumulative water output and the standby time into the electrolysis time estimation sub-model to obtain a rough estimated electrolysis time; a second rough estimation unit, used to input the cumulative water output and the electrolysis time into the driving voltage pulse width ratio estimation unit to obtain a rough estimated driving voltage pulse width ratio; a third rough estimation unit, used to input the standby time and the electrolysis time into the current estimation sub-model to obtain a rough estimated current; a parameter normalization unit, used to input the rough estimated electrolysis time, the rough estimated driving voltage pulse width ratio and the rough estimated current into the normalization sub-model to obtain the sterilization parameters.

[0216] In one implementation of the present application, the sterilization judgment module specifically includes: a sterilization condition judgment submodule, used to determine whether the water use data meets the predetermined sterilization conditions; a first condition execution submodule, used to determine that sterilization treatment is required if the water use data meets the predetermined sterilization conditions; and a second condition execution submodule, used to determine that sterilization treatment is not required if the water use data does not meet the predetermined sterilization conditions.

[0217] In an implementation of the present application, the sterilization system control device further includes: a data clearing module, configured to clear the water usage data if the water usage data reaches the clearing threshold interval.

[0218] Figure 6 A schematic diagram of the structure of a computer system suitable for implementing a water softener according to an embodiment of the present application is shown.

[0219] It should be noted that Figure 6 The computer system of the water softener shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0220] like Figure 6 As shown, the computer system includes a central processing unit (CPU) 1801, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 1802 or the program loaded from the storage part 1808 to the random access memory (RAM) 1803, such as executing the method described in the above embodiment. In RAM 1803, various programs and data required for system operation are also stored. CPU 1801, ROM 1802 and RAM 1803 are connected to each other through bus 1804. Input / output (I / O) interface 1805 is also connected to bus 1804.

[0221] The following components are connected to the I / O interface 1805: an input section 1806 including a keyboard, a mouse, etc.; an output section 1807 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 1808 including a hard disk, etc.; and a communication section 1809 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 1809 performs communication processing via a network such as the Internet. A drive 1810 is also connected to the I / O interface 1805 as needed. A removable medium 1811, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 1810 as needed so that a computer program read therefrom is installed into the storage section 1808 as needed.

[0222] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 1809, and / or installed from a removable medium 1811. When the computer program is executed by a central processing unit (CPU) 1801, various functions defined in the system of the present application are executed.

[0223] It should be noted that the computer-readable medium shown in the embodiment of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by an instruction execution system, device or device or used in combination with it. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a computer-readable computer program is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate, or transmit programs for use by or in conjunction with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0224] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. Wherein, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0225] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0226] As another aspect, the present application also provides a computer-readable medium, which may be included in the water softener described in the above embodiment; or may exist independently without being assembled into the water softener. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by the water softener, the water softener implements the method described in the above embodiment.

[0227] The present specification also provides a computer program product, which stores at least one instruction, and the at least one instruction is loaded and executed by the processor as described above. Figure 1 to Figure 4 The method of the embodiment shown in the figure can be specifically executed by referring to Figure 1 to Figure 4 The specific description of the illustrated embodiment will not be repeated here.

[0228] It should be noted that, although several modules or units of the equipment for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being embodied by multiple modules or units.

[0229] Through the description of the above implementation methods, it is easy for those skilled in the art to understand that the example implementation methods described here can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the implementation methods of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the implementation methods of the present application.

[0230] Those skilled in the art will readily come up with 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.

[0231] 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 sterilization system control method, characterized in that: Applied to a water softener, the sterilization system control method 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.

2. The sterilization system control method according to claim 1, 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.

3. The sterilization system control method according to claim 2, 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.

4. The sterilization system control method according to claim 2, 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.

5. The sterilization system control method according to claim 1, characterized in that: The water use data includes standby time, the sterilization parameter also includes current, and the determining of the corresponding sterilization parameter specifically includes: Determining the electrolysis time according to the standby time; The current is determined according to the electrolysis time.

6. The sterilization system control method according to claim 5, characterized in that: The electrolysis time is specifically determined by the following formula: T=f(t)=βt Wherein, T is the electrolysis time, t is the standby time, and β is the time conversion coefficient.

7. The sterilization system control method according to claim 5, characterized in that: The current is specifically determined by the following formula: I=f(T)=cT+d Where, I is the current, T is the electrolysis time, c is the current conversion factor, and d is the constant term coefficient.

8. The sterilization system control method according to claim 1, 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 sterilization system control method according to claim 1, characterized in that: The water use data includes the cumulative water output and the standby time, the sterilization parameters also include the driving voltage pulse width ratio and the current, and the determination of the corresponding sterilization parameters specifically includes: Determining electrolysis time according to the accumulated water output and the standby time; According to the electrolysis time, the driving voltage pulse width ratio and the current are determined.

10. The sterilization system control method according to claim 9, characterized in that: Determining the electrolysis time according to the accumulated water output and the standby time specifically includes: The accumulated water output and the standby time are input into an electrolysis time estimation model to obtain the electrolysis time.

11. The sterilization system control method according to claim 1, characterized in that: The water use data includes the cumulative water output and the standby time, and the determination of the corresponding sterilization parameters specifically includes: The cumulative water output and the standby time are input into a sterilization parameter estimation model to obtain the sterilization parameter.

12. The sterilization system control method according to claim 11, characterized in that: The cumulative water output and the standby time are input into a sterilization parameter estimation model, the sterilization parameters also include a driving voltage pulse width ratio and a current, the sterilization parameter estimation model includes 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, and the cumulative water output and the standby time are input into the sterilization parameter estimation model to obtain the sterilization parameters, specifically including: Inputting the accumulated water output and the standby time into an electrolysis time estimation sub-model to obtain a rough estimate of the electrolysis time; Inputting the accumulated water output and the electrolysis time into a driving voltage pulse width ratio estimation sub-model to obtain a rough estimation of the driving voltage pulse width ratio; Inputting the standby time and the electrolysis time into a current estimation sub-model to obtain a rough estimated current; The roughly estimated electrolysis time, the roughly estimated driving voltage pulse width ratio and the roughly estimated current are input into a normalized sub-model to obtain sterilization parameters.

13. The sterilization system control method according to claim 1, 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.

14. The sterilization system control method according to claim 1, characterized in that: The sterilization system control method also includes: If the water usage data reaches the clearing threshold interval, the water usage data is cleared.

15. A sterilization system control device, characterized in that: The sterilization system control device comprises: A sterilization judgment module, used to determine whether sterilization is required based on the water usage data of the water softener; A parameter determination module, used to determine corresponding sterilization parameters if sterilization is required, wherein the sterilization parameters include electrolysis time; A sterilization execution module is used to sterilize the water softener according to the sterilization parameters.

16. A computer readable medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the sterilization system control method according to any one of claims 1 to 14 is implemented.

17. A water softener, characterized in that: include: one or more processors; A storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, enables the one or more processors to implement the sterilization system control method as described in any one of claims 1 to 14.

18. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the sterilization system control method according to any one of claims 1 to 14 is implemented.

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