Regeneration control method and apparatus for water softener

Abstract

The application relates to a regeneration control method and device of a water softener, which comprises the following steps: calculating self-learning regeneration interval days according to the flow measured by a flow meter of the water softener within a predetermined time period; determining flow regeneration interval days according to the current flow measured by the flow meter in the case that the error rate of the flow meter is less than a preset value, and determining the regeneration interval days of the water softener according to the self-learning regeneration interval days and the flow regeneration interval days; and starting the regeneration process of the water softener in the case that the regeneration interval days of the water softener are reached. According to the scheme, on one hand, the regeneration interval days can be adjusted according to the water use habit of a user, so that the regeneration interval days are more suitable for actual needs, and on the other hand, the problem that the flow meter cannot regenerate in time due to failure after long-time use can be avoided.

Description

Technical Field

[0001] This application relates to the field of software control technology, and in particular to a regeneration control method and apparatus for a water softener. Background Technology

[0002] Currently, with the improvement of people's living standards, various water softener products have emerged on the market. Water softeners work by adsorbing calcium and magnesium ions in water through ion exchange resin to soften the water and reduce scale. When the ion exchange resin becomes saturated, it needs to be backwashed with brine to exchange the calcium and magnesium ions adsorbed on the resin with sodium ions, allowing the resin to regain its ability to soften water.

[0003] However, ensuring timely regeneration of the resin when it is saturated or near saturation is a crucial issue. Currently, traditional water softeners adjust the regeneration time based on user water consumption (flow-based regeneration), maximum regeneration interval days, and adjustable water volume according to the number of users. This method may have the following drawbacks:

[0004] (1) The calculation based on the user's water consumption is based on the flow meter of the water softener, but the flow meter may be attenuated and fail after long-term use;

[0005] (2) Adjusting based on the maximum regeneration interval days and the number of people is not very accurate and will affect the user's water experience. Summary of the Invention

[0006] To address the aforementioned problems, this application provides a water softener regeneration control scheme. In addition to traditional flow regeneration and maximum regeneration interval regeneration, it adds a periodic self-learning regeneration interval regeneration based on user water usage habits. This scheme can automatically determine the appropriate regeneration interval based on the error of the water softener flow meter among traditional flow regeneration, maximum regeneration interval regeneration, and self-learning regeneration interval regeneration.

[0007] According to a first aspect of this application, a regeneration control method for a water softener is provided, characterized in that it includes:

[0008] Calculate the self-learning regeneration interval days based on the flow rate measured by the flow meter of the water softener within the predetermined time period;

[0009] If the error rate of the flow meter is less than a preset value, the flow regeneration interval in days is determined based on the flow rate currently measured by the flow meter.

[0010] The regeneration interval days of the water softener are determined based on the self-learning regeneration interval days and the flow regeneration interval days; and

[0011] When the regeneration interval days of the water softener are reached, the regeneration process of the water softener is started.

[0012] According to a second aspect of this application, a regeneration control device for a water softener is provided, characterized in that it comprises:

[0013] The first calculation module is used to calculate the self-learning regeneration interval days based on the flow rate measured by the flow meter of the water softener within a predetermined time period.

[0014] The first determining module is used to determine the flow regeneration interval in days based on the flow rate currently measured by the flow meter when the error rate of the flow meter is less than a preset value.

[0015] The second determining module is used to determine the regeneration interval days of the water softener based on the self-learning regeneration interval days and the flow regeneration interval days; and

[0016] The regeneration module is used to initiate regeneration of the water softener when the regeneration interval days of the water softener are reached.

[0017] According to a third aspect of this application, a water softener is provided, characterized in that it includes a control valve assembly for performing the method described in the first aspect.

[0018] According to a fourth aspect of this application, an electronic device is provided, comprising:

[0019] Processor; and

[0020] A memory storing computer instructions that, when executed by the processor, cause the processor to perform the method described in the first aspect.

[0021] According to a fifth aspect of this application, a non-transitory computer storage medium is provided, which stores a computer program that, when executed by a plurality of processors, causes the processors to perform the method described in the first aspect.

[0022] According to the regeneration control method and device for a water softener provided in this application, considering the error of the water softener's flow meter, the regeneration interval is determined by comprehensively considering three regeneration methods: flow-based regeneration, self-learning regeneration interval regeneration, and maximum regeneration interval regeneration. Regeneration is then performed according to the determined regeneration interval. This allows the regeneration interval to be adjusted according to the user's water usage habits, making it more aligned with actual needs. Furthermore, it avoids the problem of delayed regeneration due to flow meter failure after prolonged use. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings, without exceeding the scope of protection claimed by this application.

[0024] Figure 1 This is a schematic diagram of the composition of a water softener according to an embodiment of this application.

[0025] Figure 2 This is a flowchart of a regeneration control method for a water softener according to an embodiment of this application.

[0026] Figure 3 This is a flowchart of a regeneration control method for a water softener according to another embodiment of this application.

[0027] Figure 4 This is a flowchart of a regeneration control method for a water softener according to yet another embodiment of this application.

[0028] Figure 5 This is a schematic diagram of a regeneration control device for a water softener according to an embodiment of this application.

[0029] Figure 6 This is a schematic diagram of a regeneration control device for a water softener according to another embodiment of this application.

[0030] Figure 7 This is a schematic diagram of a regeneration control device for a water softener according to yet another embodiment of this application.

[0031] Figure 8 This is a structural diagram of an electronic device provided in this application. Detailed Implementation

[0032] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0033] Figure 1 This is a schematic diagram of the structural composition of a water softener according to an embodiment of this application. Figure 1As shown, the water softener includes a control valve assembly, a resin tank assembly, a brine tank system, a flow meter, and an operation display module. The control valve assembly has a main control board, a flow detection module, and a water circuit switching module. Under programmed conditions, the control valve assembly can switch water circuits through flow triggering, time setting, and manual operation. The water circuit switching described in this invention refers to the need for changes in the water circuit system within the machine to meet functional requirements during normal water production and regeneration. The resin tank assembly is a tank that holds the regenerated resin; the water flow direction within the tank is opposite during regeneration and water production. The flow meter is located at the inlet or outlet end and is used to measure the water flow rate. The operation display module is the user interface, allowing users to input parameters and observe the machine's operating status. The brine tank system is a tank assembly that provides regenerated brine to the resin.

[0034] In the embodiments of this application, a regeneration control program runs in the control valve assembly. By capturing the flow rate measured by the flow meter, the regeneration interval days are obtained through periodic self-learning based on the user's water usage habits. Taking into account the flow meter's error rate, the regeneration interval days of the water softener are determined based on the self-learned regeneration interval days and the flow regeneration interval days, or the self-learned regeneration interval days and the preset maximum regeneration interval days. When the regeneration interval days of the water softener are reached, the regeneration process of the water softener is started.

[0035] For the regenerative control scheme operating in the control valve assembly, it will be based on Figure 2 The embodiments shown are described in detail below.

[0036] According to one aspect of this application, a regeneration control method for a water softener is provided. Figure 2 This is a flowchart of the regeneration control method for a water softener according to an embodiment of this application. For example... Figure 2 As shown, the method includes the following steps:

[0037] Step S201: Calculate the self-learning regeneration interval days based on the flow rate measured by the flow meter of the water softener within a predetermined time period.

[0038] Step S202: If the error rate of the flow meter is less than a preset value, determine the flow regeneration interval in days based on the flow rate currently measured by the flow meter, and determine the regeneration interval in days for the water softener based on the self-learning regeneration interval in days and the flow regeneration interval in days; and

[0039] Step S203: When the regeneration interval days of the water softener are reached, the regeneration process of the water softener is started.

[0040] Since the self-learning regeneration interval days are determined based on the flow rate measured by the flow meter of the water softener, according to some embodiments, it is first necessary to determine the time period during which the flow meter accuracy is reliable. During the time period when the flow meter accuracy is reliable, the regeneration interval days are continuously determined and adjusted based on the flow rate measured by the flow meter; outside of the time period when the flow meter accuracy is reliable, the regeneration interval days obtained during the period of reliable accuracy are used to determine the regeneration interval days of the water softener.

[0041] According to a specific embodiment, the reliable accuracy period of the flow meter is set at one year (corresponding to a preset regeneration learning time). Within that year, 21 consecutive days are defined as a period (corresponding to a first preset time period). The flow rate measured by the flow meter during these 21 consecutive days is determined, and the average daily flow rate (daily water consumption) is calculated. Then, the regeneration interval days (corresponding to a first self-learning regeneration interval day) are calculated based on the projected water production. Subsequently, the average daily water consumption for the previous 21 days is calculated daily (i.e., the flow rate measured by the flow meter of the water softener from the current point back to the first preset time period), and the regeneration interval days are calculated and adjusted. This process allows the machine to learn for one year (corresponding to the preset regeneration learning time). Within the reliable accuracy period of the flow meter, the regeneration interval days of the water softener are determined using the first self-learning regeneration interval days and the flow regeneration interval days.

[0042] According to a specific embodiment, outside of the period when the flow meter's accuracy is reliable, after a year, the flow rate measured by the water softener's flow meter for six months (corresponding to the second preset time period) is used to determine the average daily flow rate (daily water consumption). Then, the regeneration interval days (corresponding to the second self-learning regeneration interval days) are calculated based on the expected water production. The second preset time period is any time period within the preset regeneration learning period, and its length can be arbitrary, typically longer than the first preset time period. For example, on the 365th day (corresponding to the day the preset regeneration learning time is reached), the flow rate measured by the water softener's flow meter for six months (corresponding to the second preset time period) is traced back to determine the average daily flow rate (daily water consumption). Then, the regeneration interval days (corresponding to the second self-learning regeneration interval days) are calculated based on the expected water production. When selecting the second preset time period, a later period within the preset regeneration learning time can be chosen, as this period is closer to the user's current water usage habits. Outside of the period when the flow meter's accuracy is reliable, the regeneration interval days of the water softener are determined by the second self-learning regeneration interval days and the flow regeneration interval days.

[0043] Thus, step S201 may include:

[0044] Within a preset regeneration learning time, the first self-learning regeneration interval in days is calculated based on the flow rate measured by the flow meter of the water softener currently traced back to the first preset time period; and

[0045] When the preset regeneration learning time is reached, the second self-learning regeneration interval days are calculated based on the flow rate measured by the flow meter of the water softener within the second preset time period, wherein the second preset time period is longer than the first preset time period.

[0046] Step S202 may include:

[0047] Within the preset regeneration learning time, the regeneration interval days of the water softener are determined based on the first self-learning regeneration interval days and the flow regeneration interval days.

[0048] When the preset regeneration learning time is reached, the regeneration interval days of the water softener are determined based on the second self-learning regeneration interval days and the flow regeneration interval days.

[0049] In the above embodiments, learning is no longer performed based on the flow rate measured by the flow meter after the preset regeneration learning time has been reached. According to other embodiments, learning can continue based on the flow rate measured by the flow meter even after the preset regeneration learning time has been reached.

[0050] According to a specific embodiment, within a preset regeneration learning time (e.g., one year), multiple preset time periods (corresponding to a third preset time period), such as 60 days, are determined. The flow rate measured by the water softener's flow meter within each 60-day period is statistically analyzed, and the average daily flow rate (daily water consumption) is determined. Then, based on the expected water production, the regeneration interval days (corresponding to a third self-learning regeneration interval day) are calculated, thus obtaining multiple third self-learning regeneration interval days. The smallest interval day among these multiple third self-learning regeneration interval days is determined as the candidate interval day. Next, when the preset regeneration learning time is reached, based on the flow rate measured by the water softener's flow meter within the current 60-day period (corresponding to the third preset time period), the average daily flow rate (daily water consumption) is determined, and the regeneration interval days (corresponding to the current third self-learning regeneration interval day) are calculated based on the expected water production. Finally, the interval day with the smallest value between the candidate interval day and the current third self-learning regeneration interval day is determined as the self-learning regeneration interval day. In this way, during the preset regeneration learning period, the number of self-learning regeneration interval days obtained during the preset regeneration learning period is used to determine the regeneration interval days of the water softener; after the preset regeneration learning period expires, the number of self-learning regeneration interval days obtained after the expiration is used to determine the regeneration interval days of the water softener.

[0051] Thus, step S201 may also include:

[0052] Within a preset regeneration learning time, based on the flow rate measured by the flow meter of the water softener within multiple third preset time periods, multiple third self-learning regeneration interval days are calculated accordingly.

[0053] The smallest interval among the multiple self-learning regeneration intervals is determined as the candidate interval.

[0054] If the preset regeneration learning time is reached, calculate the current third self-learning regeneration interval in days based on the flow rate measured by the flow meter of the water softener within the currently traced third preset time period; and

[0055] The interval with the smallest value among the candidate interval days and the current third self-learning regeneration interval days is determined as the self-learning regeneration interval days.

[0056] In the above embodiments, the scenarios described are as follows: when the preset regeneration learning time is reached, learning is no longer performed based on the flow rate measured by the flow meter; and learning continues based on the flow rate measured by the flow meter. According to other embodiments, regardless of whether the preset regeneration learning time has been reached, the regeneration interval days are continuously learned over multiple preset time periods. When a new regeneration interval day is obtained, this new regeneration interval day is compared with the previously obtained regeneration interval day, and the minimum regeneration interval day is determined as the self-learning regeneration interval day.

[0057] According to a specific embodiment, a preset time period is 60 days (corresponding to a fourth preset time period). As the water softener starts operating, there are one or more fourth preset time periods. For each fourth preset time period, the flow rate measured by the water softener's flow meter within the 60 days can be statistically analyzed to determine the average daily flow rate (daily water consumption). Then, the regeneration interval days (corresponding to a fourth self-learning regeneration interval day) are calculated based on the expected water production. Thus, a fourth self-learning regeneration interval day can be determined for each fourth preset time period, resulting in one or more fourth self-learning regeneration interval days. Next, based on the flow rate measured by the water softener's flow meter over the past 60 days, the average daily flow rate (daily water consumption) is determined, and the regeneration interval days (corresponding to the current fourth self-learning regeneration interval day) are calculated based on the expected water production. Finally, the interval day with the smallest value among the one or more fourth self-learning regeneration interval days and the current fourth self-learning regeneration interval day is determined as the self-learning regeneration interval day. In this way, the self-learning regeneration interval days are continuously updated, and the most recently updated self-learning regeneration interval days are used to determine the regeneration interval days of the water softener.

[0058] Thus, step S201 may include:

[0059] Calculate the current fourth self-learning regeneration interval days based on the flow rate measured by the flow meter of the water softener from the current time to the fourth preset time period.

[0060] If one or more fourth self-learning regeneration interval days already exist corresponding to the fourth preset time period, the interval day with the smallest value among the one or more fourth self-learning regeneration interval days and the current fourth self-learning regeneration interval days is determined as the self-learning regeneration interval day.

[0061] It is understood that in the above embodiments, the lengths of the preset time periods, including the first preset time period, the second preset time period, the third preset time period, and the fourth preset time period, can be set arbitrarily, and the preset time periods can be isolated or overlapped.

[0062] The water softener has a flow calculation module that can calculate the total actual water consumption L1 of the machine in real time, either when the machine is new or since the last regeneration. The water softener has an estimated water production capacity L0 based on the user's raw water hardness. Flow regeneration determines whether the machine needs to regenerate by checking if the actual water consumption L1 reaches the programmed estimated water production capacity L0. According to some embodiments, in determining the flow regeneration interval based on the current flow rate measured by the flow meter, the estimated water production capacity is used. If the current flow rate does not reach the estimated water production capacity, then the conditions for regeneration have not yet been met. For example, if the water softener has been producing water for 7 days since the last regeneration, and the current flow rate measured by the flow meter does not reach the estimated water production capacity, then the flow regeneration interval is greater than 7 days; if the current flow rate measured by the flow meter reaches the estimated water production capacity, then the flow regeneration interval is 7 days.

[0063] According to some embodiments, the preset maximum regeneration interval days are the regeneration isolation days set to ensure the normal operation of the water softener. The reasons for setting this maximum regeneration interval days include: (1) If the user does not use the water softener for a long time, bacteria will easily grow in the resin inside the machine and yellow water will be produced, requiring regular regeneration and rinsing; (2) If the machine resin is not regenerated for a long time, the resin performance will decline, and regular regeneration will activate the resin. According to a specific embodiment, the preset maximum regeneration interval days can be 14 days.

[0064] Regarding how to determine the regeneration interval days of a water softener based on the flow regeneration interval days, the preset maximum regeneration interval days, and the self-learning regeneration interval days, this application considers the error rate of the flow meter and sets a preset value, such as 20% or 25%. When the error rate of the flow meter is less than the preset value, the flow regeneration interval days are determined based on the flow rate currently measured by the flow meter. Then, the regeneration interval days of the water softener are determined based on the self-learning regeneration interval days and the flow regeneration interval days.

[0065] The flow meter's error rate and the reliable flow meter duration are different ways of evaluating flow meter performance. The reliable flow meter duration, such as one year, is an empirically determined length of time, while the flow meter's error rate is determined through measurement and calculation. According to some embodiments, the flow meter's error rate is calculated and determined during the water softener's regeneration process. The error rate determined during this regeneration process will serve as the basis for determining whether to include flow meter regeneration in the next regeneration interval. For determining the error rate of the flow meter in the first regeneration interval, it can be set to 0% or an error less than a preset value.

[0066] According to some embodiments, when the error rate of the flow meter is less than a preset value, after determining the self-learning regeneration interval days and the flow regeneration interval days, the interval days with the smaller value among the two are determined as the regeneration interval days of the water softener, and when the regeneration interval days of the water softener are reached, the regeneration process of the water softener is started.

[0067] Figure 3 This is a flowchart of a regeneration control method for a water softener according to another embodiment of this application. Figure 2 compared to, Figure 3 Steps S301 to S303 and Figure 2 Steps S201 to S203 are the same, except that... Figure 3 The method shown also includes:

[0068] Step S304: If the error rate is not less than the preset value, determine the regeneration interval days of the water softener based on the self-learning regeneration interval days and the preset maximum regeneration interval days.

[0069] According to some embodiments, when the flow meter's error rate is not less than a preset value, the regeneration interval days of the water softener are determined based on the self-learning regeneration interval days and the preset maximum regeneration interval days. When the flow meter's error rate is not less than the preset value, after determining the self-learning regeneration interval days and the preset maximum regeneration interval days, the interval day with the smaller of these two values ​​is determined as the regeneration interval days of the water softener. When the regeneration interval days of the water softener are reached, the regeneration process of the water softener is initiated.

[0070] Step S304 may include:

[0071] Within the preset regeneration learning time, the regeneration interval days of the water softener are determined based on the first self-learning regeneration interval days and the preset maximum regeneration interval days.

[0072] When the preset regeneration learning time is reached, the regeneration interval days of the water softener are determined based on the second self-learning regeneration interval days and the preset maximum regeneration interval days.

[0073] Figure 4 This is a flowchart of a regeneration control method for a water softener according to yet another embodiment of this application. Figure 2 compared to, Figure 4 Steps S401 to S403 and Figure 2 Steps S201 to S203 are the same, except that... Figure 4 The method shown also includes:

[0074] Step S404: During the regeneration process of the water softener, calculate the current error rate of the flow meter.

[0075] According to some embodiments, the flow meter can be located at the inlet of the water softener. During the regeneration process, the water path of the water softener is: inlet → flow meter → control valve assembly → resin tank → control valve assembly → wastewater outlet. Since the control valve assembly has a flow-limiting module, and the water softener program has corresponding wastewater flow rates for different water pressures (e.g., different water pressures have corresponding wastewater flow rates per unit time), the wastewater flow rate during regeneration can be obtained. Furthermore, different water pressures also have corresponding flow rates for the amount of salt absorbed from the brine tank. Simultaneously, the water softener program can capture the flow meter flow rate and compare the captured flow meter flow rate Q with the difference between the wastewater flow rate Q1 and the brine absorption rate Q2, for example, [Q - (Q1 - Q2)] / (Q1 - Q2), to calculate the flow meter error rate.

[0076] According to other embodiments, the flow meter can also be located at the outlet of the water softener. In one specific embodiment, an electrically controlled switch valve can be added between the flow meter at the outlet of the water softener and the wastewater outlet. The switch valve is closed by default and opens when the machine needs to regenerate. When the water softener needs to regenerate, the switch valve opens, and the flow rate passing through the flow meter is the wastewater flow rate Q. The water softener program has corresponding wastewater flow rates for different water pressures, thus the wastewater flow rate Q1 during regeneration can be obtained. By comparing the captured flow meter flow rate Q with the wastewater flow rate Q1, for example, (Q-Q1) / Q1, the error rate of the flow meter can be calculated.

[0077] Thus, step S404 may include:

[0078] With the flow meter located at the inlet of the water softener, the current error rate of the flow meter is calculated based on the flow rate detected by the flow meter, the flow rate at the wastewater outlet of the water softener, and the salt intake corresponding to the brine tank.

[0079] When the flow meter is located at the outlet of the water softener, the current error rate of the flow meter is calculated based on the flow rate detected by the flow meter and the flow rate at the wastewater outlet of the water softener.

[0080] According to some embodiments, when the error rate of the flow meter is detected to exceed a preset value, an alarm message can be issued, such as issuing an alarm sound or displaying an alarm message on the operation display module of the water softener, or notifying the R&D and after-sales departments for handling.

[0081] Based on the above-mentioned regeneration control method for water softeners, according to another aspect of this application, a regeneration control device for water softeners is provided. Figure 5 This is a schematic diagram of a regeneration control device for a water softener according to one embodiment of this application. Figure 5 As shown, the device includes a first calculation module 501, a first determination module 502, and a regeneration processing module 503. The first calculation module 501 calculates the self-learning regeneration interval in days based on the flow rate measured by the flow meter of the water softener within a predetermined time period. The first determination module 502 determines the flow regeneration interval in days based on the current flow rate measured by the flow meter when the error rate of the flow meter is less than a preset value, and determines the regeneration interval in days for the water softener based on the self-learning regeneration interval and the flow regeneration interval. The regeneration processing module 503 initiates regeneration processing for the water softener when the regeneration interval for the water softener is reached.

[0082] According to some alternative embodiments, the first computing module 501 can be used for:

[0083] Within a preset regeneration learning time, the first self-learning regeneration interval in days is calculated based on the flow rate measured by the flow meter of the water softener currently traced back to the first preset time period; and

[0084] When the preset regeneration learning time is reached, the second self-learning regeneration interval days are calculated based on the flow rate measured by the flow meter of the water softener within the second preset time period, wherein the second preset time period is longer than the first preset time period.

[0085] The first determining module 502 can be used for:

[0086] Within the preset regeneration learning time, the regeneration interval days of the water softener are determined based on the first self-learning regeneration interval days and the flow regeneration interval days.

[0087] When the preset regeneration learning time is reached, the regeneration interval days of the water softener are determined based on the second self-learning regeneration interval days and the flow regeneration interval days.

[0088] According to some optional embodiments, the first computing module 501 can also be used for:

[0089] Within a preset regeneration learning time, based on the flow rate measured by the flow meter of the water softener within multiple third preset time periods, multiple third self-learning regeneration interval days are calculated accordingly.

[0090] The smallest interval among the multiple self-learning regeneration intervals is determined as the candidate interval.

[0091] If the preset regeneration learning time is reached, calculate the current third self-learning regeneration interval in days based on the flow rate measured by the flow meter of the water softener within the currently traced third preset time period; and

[0092] The interval with the smallest value among the candidate interval days and the current third self-learning regeneration interval days is determined as the self-learning regeneration interval days.

[0093] According to some optional embodiments, the first computing module 501 can also be used for:

[0094] Calculate the current fourth self-learning regeneration interval days based on the flow rate measured by the flow meter of the water softener from the current time to the fourth preset time period.

[0095] If one or more fourth self-learning regeneration interval days already exist corresponding to the fourth preset time period, the interval day with the smallest value among the one or more fourth self-learning regeneration interval days and the current fourth self-learning regeneration interval days is determined as the self-learning regeneration interval day.

[0096] Figure 6 This is a schematic diagram of a regeneration control device for a water softener according to another embodiment of this application. Figure 5 compared to, Figure 6 Modules 601 to 603 and Figure 5 Modules 501 to 503 are the same, the difference being that... Figure 6 The device shown also includes:

[0097] The second determining module 604 is used to determine the regeneration interval days of the water softener based on the self-learning regeneration interval days and the preset maximum regeneration interval days, provided that the error rate is not less than the preset value.

[0098] According to some alternative embodiments, the second determining module 604 can be used to:

[0099] Within the preset regeneration learning time, the regeneration interval days of the water softener are determined based on the first self-learning regeneration interval days and the preset maximum regeneration interval days.

[0100] When the preset regeneration learning time is reached, the regeneration interval days of the water softener are determined based on the second self-learning regeneration interval days and the preset maximum regeneration interval days.

[0101] Figure 7 This is a schematic diagram of the regeneration control device of a water softener according to yet another embodiment of this application. Figure 5 compared to, Figure 7 Modules 701 to 703 and Figure 5 Modules 501 to 503 are the same, the difference being that... Figure 7 The device shown also includes:

[0102] The second calculation module 704 is used to calculate the current error rate of the flow meter during the regeneration process of the water softener.

[0103] According to some optional embodiments, the second computing module 704 can also be used for:

[0104] With the flow meter located at the inlet of the water softener, the current error rate of the flow meter is calculated based on the flow rate detected by the flow meter, the flow rate at the wastewater outlet of the water softener, and the salt intake corresponding to the brine tank.

[0105] When the flow meter is located at the outlet of the water softener, the current error rate of the flow meter is calculated based on the flow rate detected by the flow meter and the flow rate at the wastewater outlet of the water softener.

[0106] According to the regeneration control method and device for a water softener provided in this application, considering the error of the water softener's flow meter, the regeneration interval is determined by comprehensively considering three regeneration methods: flow-based regeneration, self-learning regeneration interval regeneration, and maximum regeneration interval regeneration. Regeneration is then performed according to the determined regeneration interval. This allows the regeneration interval to be adjusted according to the user's water usage habits, making it more aligned with actual needs. Furthermore, it avoids the problem of delayed regeneration due to flow meter failure after prolonged use.

[0107] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0108] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0109] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be an electrical connection or other forms.

[0110] See Figure 8 , Figure 8 An electronic device is provided, including a processor and a memory. The memory stores computer instructions, which, when executed by the processor, cause the processor to perform the computer instructions to achieve the following: Figures 2 to 4 The method and its detailed scheme are shown.

[0111] It should be understood that the above-described device embodiments are merely illustrative, and the device disclosed in this invention can be implemented in other ways. For example, the division of units / modules described in the above embodiments is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units, modules, or components may be combined, integrated into another system, or some features may be ignored or not executed.

[0112] Furthermore, unless otherwise specified, the functional units / modules in the various embodiments of the present invention can be integrated into one unit / module, or each unit / module can exist physically separately, or two or more units / modules can be integrated together. The integrated units / modules described above can be implemented in hardware or as software program modules.

[0113] If the integrated unit / module is implemented in hardware, the hardware can be digital circuits, analog circuits, etc. The physical implementation of the hardware structure includes, but is not limited to, transistors, memristors, etc. Unless otherwise specified, the processor or chip can be any suitable hardware processor, such as a CPU, GPU, FPGA, DSP, and ASIC, etc. Unless otherwise specified, the on-chip cache, off-chip memory, and storage can be any suitable magnetic or magneto-optical storage medium, such as resistive random access memory (RRAM), dynamic random access memory (DRAM), static random access memory (SRAM), enhanced dynamic random access memory (EDRAM), high-bandwidth memory (HBM), hybrid memory cube (HMC), etc.

[0114] If the integrated unit / module is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer electronic device (which may be a personal computer, server, or network electronic device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this disclosure. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0115] This application embodiment also provides a non-transitory computer storage medium storing a computer program, which, when executed by multiple processors, causes the processors to perform actions such as... Figures 2 to 4 The method and its detailed scheme are shown.

[0116] The embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this application. Furthermore, any changes or modifications made by those skilled in the art based on the ideas of this application, and on the specific implementation methods and application scope of this application, are all within the scope of protection of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A regeneration control method for a water softener, characterized in that, include: Calculate the self-learning regeneration interval days based on the flow rate measured by the flow meter of the water softener within the predetermined time period; If the error rate of the flow meter is less than a preset value, the flow regeneration interval days are determined based on the flow rate currently measured by the flow meter, and the regeneration interval days of the water softener are determined based on the self-learning regeneration interval days and the flow regeneration interval days. When the regeneration interval days of the water softener are reached, the regeneration process of the water softener is started. as well as If the error rate is not less than the preset value, the regeneration interval days of the water softener are determined according to the self-learning regeneration interval days and the preset maximum regeneration interval days. The step of calculating the self-learning regeneration interval days based on the flow rate measured by the flow meter of the water softener within a predetermined time period includes: Within a preset regeneration learning time, the first self-learning regeneration interval in days is calculated based on the flow rate measured by the flow meter of the water softener currently traced back to the first preset time period; and When the preset regeneration learning time is reached, the second self-learning regeneration interval days are calculated based on the flow rate measured by the flow meter of the water softener within the second preset time period, wherein the second preset time period is longer than the first preset time period; Determining the regeneration interval days of the water softener includes: Within the preset regeneration learning time, the regeneration interval days of the water softener are determined based on the first self-learning regeneration interval days and the flow regeneration interval days, or based on the first self-learning regeneration interval days and the preset maximum regeneration interval days. When the preset regeneration learning time is reached, the regeneration interval days of the water softener are determined based on the second self-learning regeneration interval days and the flow regeneration interval days, or based on the second self-learning regeneration interval days and the preset maximum regeneration interval days.

2. The method as described in claim 1, characterized in that, Also includes: During the regeneration process of the water softener, the current error rate of the flow meter is calculated.

3. The method as described in claim 2, characterized in that, The calculation of the current error rate of the flow meter includes: With the flow meter located at the inlet of the water softener, the current error rate of the flow meter is calculated based on the flow rate detected by the flow meter, the flow rate at the wastewater outlet of the water softener, and the salt intake corresponding to the brine tank. When the flow meter is located at the outlet of the water softener, the current error rate of the flow meter is calculated based on the flow rate detected by the flow meter and the flow rate at the wastewater outlet of the water softener.

4. A water softener, characterized in that, Includes a control valve assembly for performing the method as described in any one of claims 1 to 3.

5. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the method of any one of claims 1 to 3 when executing the computer program in the memory.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 3.

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