Intelligent element replacement control method and device based on water purification capacity of filter element

Abstract

The invention discloses an intelligent filter element replacement control method and device based on the water purification capacity of a filter element, and the method comprises the steps: determining the purification capacity expression data of the filter element, and obtaining the purification capacity expression data through analyzing the data, corresponding to a TDS value, of the filter element; according to the purification capacity expression data, judging whether the filter element meets a water purification performance abnormal condition or not; if yes, filtering application influence information of the filter element is determined, and the filtering application influence information comprises at least one of a water use scene, equipment operation conditions, filter element filtering configuration and inflow water quality; according to the filtering application influence information, determining an abnormal type causing abnormal water purification performance of the filter element, the abnormal type including a first abnormal type or a non-first abnormal type of which the filter element is an abnormal factor; and according to the filtering application influence information, performing core replacement processing operation matched with the abnormal type on the filter core. Therefore, intelligent analysis of the performance of the filter element can be carried out based on the multi-dimensional data, and the operation pertinence and accuracy of filter element replacement are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, and in particular to an intelligent core replacement control method and device based on filter core water purification capacity. BACKGROUND

[0002] In the daily use of water purification equipment, as the core filter component, the performance state of the filter core directly determines the water quality and the safety of the user's drinking water. Therefore, effective management and timely replacement of the filter core are the key to ensuring the efficient and reliable operation of the water purification system.

[0003] At present, the traditional filter core management method commonly used in the industry has many limitations, mainly in the following two aspects: First, relying on subjective experience to replace the filter core. Most solutions rely on user manual recording or simple device timing, and roughly judge the service life of the filter core based on fixed time periods (such as usage time) or cumulative water flow. This method completely deviates from the actual working state and application environment of the filter core, and fails to comprehensively consider the dynamic fluctuations of the incoming water quality, the differences in actual water consumption, and key operating parameters such as household water pressure and water temperature. As a result, if the incoming water quality is poor and the water consumption is large, the filter core may fail prematurely without timely replacement, causing water quality risks; if the incoming water quality is good and the water consumption is small, the filter core may be replaced too early when it still has filtering capacity, resulting in resource waste and increased user costs. There is a problem of low accuracy and timeliness of filter core replacement.

[0004] Second, single parameter determination replacement. Although some solutions in the prior art attempt to monitor water quality parameters (such as filter water TOC (total organic carbon) values) to determine the filter core state, such methods are usually only used to identify whether the filter core is a "newly replaced filter core", or only rely on a single isolated parameter for threshold alarm. They lack comprehensive, multi-dimensional analysis of the actual application parameters of the filter core, for example, they fail to include the matching degree of the filter core type and its processing capacity, abnormal water usage scenarios, and device operating conditions, and other key factors affecting the performance of the filter core into a unified evaluation system. Therefore, it is impossible to accurately diagnose the root cause of the decline in filter core performance, and it is also impossible to propose differentiated treatment strategies accordingly, resulting in insufficient intelligence.

[0005] In summary, in view of the above technical problems in the prior art in the management of filter cores, it is particularly important to provide a corresponding solution. SUMMARY

[0006] The present application provides an intelligent core replacement control method and device based on filter core water purification capacity, which can perform intelligent analysis of filter core performance based on multi-dimensional data, and improve the operation accuracy of filter core replacement.

[0007] The first aspect of the present application discloses an intelligent core replacement control method based on filter core water purification capacity, the method comprises: determining the purification capacity performance data corresponding to the filter core currently analyzed, the purification capacity performance data is obtained by analyzing the data corresponding to the TDS value of the filter core; According to the purification capacity performance data, it is judged whether the filter core meets the preset water purification performance abnormal condition; when it is judged that the filter core meets the water purification performance abnormal condition, the filtering application influence information of the filter core is determined, the filtering application influence information includes at least one of the sub-information of water use scene, equipment running condition, filter core filtering configuration and water quality; According to the filtering application influence information, the abnormal type causing the water purification performance abnormality of the filter core is determined, the abnormal type includes the first abnormal type of the filter core itself as an abnormal factor, or a non-first abnormal type; According to the filtering application influence information, the filter core is executed with the core replacement processing operation matched with the abnormal type, so that the new filter core after replacement does not meet the water purification performance abnormal condition.

[0008] As an optional implementation, in the first aspect of the present application, the determination of the purification capacity performance data corresponding to the filter core currently analyzed comprises: determining the first filter core parameter for the filter core currently analyzed, and collecting the first filter core data corresponding to the first filter core parameter; the first filter core parameter at least includes water inlet TDS parameter, water outlet TDS parameter, pure water TDS parameter and waste water TDS parameter; analyze the water inlet TDS data corresponding to the water inlet TDS parameter to obtain the water inlet TDS change curve for the water inlet TDS data, the water inlet TDS change curve includes at least one water inlet TDS change curve inflection point; determining the second filter core parameter for the filter core, the second filter core parameter at least includes the first ratio parameter and the second ratio parameter; the first ratio parameter is obtained by calculating the ratio of the water inlet TDS parameter and the water outlet TDS parameter; the second ratio parameter is obtained by calculating the ratio of the pure water TDS parameter and the waste water TDS parameter; According to the first filter core data, the second filter core data corresponding to the second filter core parameter is calculated; The first filter core parameter, the first filter core data, the second filter core parameter, the second filter core data and the water inlet change curve are determined as the purification capacity performance data corresponding to the filter core.

[0009] As an optional implementation, in the first aspect of the present application, the determination of the purification capacity performance data corresponding to the filter core currently analyzed comprises: determining a first reference value for the first filter parameter, a second reference value for the first filter parameter, and curve reference information for the water inlet TDS change curve; determining whether the first filter data is within a numerical range of the first reference value, to obtain a first determination result for the first filter data; when the first determination result indicates that the first filter data is not within the numerical range of the first reference value, determining the first determination result and the filter satisfying the preset water purification performance abnormal condition as a target determination result for the filter.

[0010] As an optional implementation, in the first aspect of the present application, the determining whether the filter satisfies the preset water purification performance abnormal condition according to the purification capability performance data further includes: when the first determination result indicates that the first filter data is within the numerical range of the first reference value, respectively determining whether the second filter data is within a numerical range of the second reference value, to obtain a second determination result for the second filter data, and determining whether the water inlet TDS change curve has abnormal curve information that does not conform to the curve reference information, to obtain a third determination result for the water inlet TDS change curve; when the second determination result indicates that the second filter data is not within the numerical range of the second reference value, adding the second determination result and the filter satisfying the preset water purification performance abnormal condition to the target determination result for the filter; when the third determination result indicates that the water inlet TDS change curve has abnormal curve information that does not conform to the curve reference information, adding the third determination result, the abnormal curve information, and the filter satisfying the preset water purification performance abnormal condition to the target determination result for the filter.

[0011] As an optional implementation, in the first aspect of the present application, the determining an abnormal type causing the filter to have a water purification performance abnormality according to the filter application influence information includes: when the filter application influence information includes the water use scene, performing a first abnormality analysis operation on a water use scene feature associated with the water use scene, to obtain a first abnormality analysis result for the water use scene feature; the water use scene feature includes a water use frequency for the filter and a cumulative water treatment amount; when the filter application influence information includes the equipment operation condition, performing a second abnormality analysis operation on an equipment operation condition feature associated with the equipment operation condition, to obtain a second abnormality analysis result for the equipment operation condition feature; the equipment operation condition feature includes water pressure data and outlet water temperature data using the filter. When the filter application influence information comprises the filter element filter configuration, a third abnormality analysis operation is performed on a filter element filter configuration feature associated with the filter element filter configuration to obtain a third abnormality analysis result for the filter element filter configuration feature; the filter element filter configuration feature comprises a filter element type of the filter element and a filter element cumulative use duration; When the filter application influence information comprises the inlet water quality, a fourth abnormality analysis operation is performed on an inlet water quality feature associated with the inlet water quality to obtain a fourth abnormality analysis result for the inlet water quality feature; the inlet water quality feature comprises an inlet water TDS value; A weighted summation operation is performed on a target abnormality analysis result, and a corresponding weighted summation result is numerically matched with a set abnormality classification benchmark to obtain a numerical matching result of the weighted summation result and the abnormality classification benchmark, the numerical matching result comprising an abnormality type causing the filter element to have abnormal water purification performance; the target abnormality analysis result comprises at least one of the first abnormality analysis result, the second abnormality analysis result, the third abnormality analysis result, and the fourth abnormality analysis result.

[0012] As an optional implementation, in the first aspect of the present application, the first abnormality analysis result is used to indicate whether the water use frequency is higher than a rated water filtering frequency of the filter element, and is also used to indicate whether the cumulative processed water volume is higher than a maximum processed water volume of the filter element; The second abnormality analysis result is used to indicate whether the water pressure data comprises high water pressure data and / or low water pressure data that do not conform to a rated water pressure, and is also used to indicate whether the outlet water temperature comprises high water temperature data and / or low water temperature data that do not conform to a rated temperature; The third abnormality analysis result is used to indicate whether the filter element type is suitable for processing an actual inlet water quality of the filter element, and is also used to indicate whether the filter element cumulative use duration is greater than a rated service life of the filter element; The fourth abnormality analysis result is used to indicate whether the inlet water TDS value is higher than an initial inlet water TDS value, the initial inlet water TDS value being a TDS value monitored for an inlet water source of the filter element when the filter element is initially installed, the initial inlet water TDS value being suitable for a rated water filtering capacity of the filter element.

[0013] As an optional implementation, in the first aspect of the present application, the performing, according to the filter application influence information, of the filter element replacement processing operation matching the abnormality type on the filter element comprises: According to the filter application influence information and the abnormality type, an abnormality detail for the filter element is determined, the abnormality detail being a first detail indicating that the filter element has a fault, or a second detail indicating that a filtering capacity of the filter element is lower than a water purification demand. when the abnormality details are the first details, performing a filter replacement operation on the filter to replace the filter with a new filter of the same filter model as the filter; when the abnormality details are the second details, performing a filter upgrade operation on the filter according to the water purification demand to replace the filter with a new filter adapted to the water purification demand; wherein the new filter adapted to the water purification demand corresponds to a filter performance higher than the filter performance of the filter.

[0014] The second aspect of the present application discloses an intelligent core replacement control device based on filter water purification capacity, which comprises: A first determination module is configured to determine the purification capacity performance data corresponding to the filter currently analyzed, which is obtained by analyzing the data corresponding to the TDS value of the filter; A judgment module is configured to determine whether the filter meets the preset water purification performance abnormality condition according to the purification capacity performance data; The first determination module is further configured to determine the filter application influence information of the filter when the judgment module determines that the filter meets the water purification performance abnormality condition, wherein the filter application influence information comprises at least one of the following sub-information: water use scenario, equipment operating condition, filter configuration, and water quality; A second determination module is configured to determine the abnormality type of the filter causing the water purification performance abnormality according to the filter application influence information, wherein the abnormality type comprises a first abnormality type of the filter itself as an abnormal factor, or a non-first abnormality type; A core replacement processing module is configured to perform a core replacement processing operation matched with the abnormality type on the filter according to the filter application influence information, so that the new filter after replacement does not meet the water purification performance abnormality condition.

[0015] As an optional implementation, in the second aspect of the present application, the first determination module determines the purification capacity performance data corresponding to the filter currently analyzed in the following manner: determining a first filter parameter for the filter currently analyzed, and collecting first filter data corresponding to the first filter parameter; the first filter parameter at least comprises an inlet water TDS parameter, an outlet water TDS parameter, a pure water TDS parameter, and a waste water TDS parameter; analyzing inlet water TDS data corresponding to the inlet water TDS parameter to obtain an inlet water TDS change curve for the inlet water TDS data, wherein the inlet water TDS change curve comprises at least one inlet water TDS change curve inflection point; determining a second filter parameter for the filter element, the second filter parameter comprising at least a first ratio parameter and a second ratio parameter, the first ratio parameter being obtained by calculating a ratio of the TDS parameter of the inlet water and the TDS parameter of the outlet water, and the second ratio parameter being obtained by calculating a ratio of the TDS parameter of the pure water and the TDS parameter of the waste water; calculating, according to the first filter element data, second filter element data corresponding to the second filter parameter; determining the first filter parameter, the first filter element data, the second filter parameter, the second filter element data and the TDS variation curve of the inlet water as the purification capability performance data corresponding to the filter element.

[0016] As an optional implementation, in the second aspect of the present application, the manner in which the judging module judges whether the filter element meets the preset water purification performance abnormal condition according to the purification capability performance data specifically comprises: determining a first reference value for the first filter parameter, a second reference value for the first filter parameter and curve reference information for the TDS variation curve of the inlet water; judging whether the first filter element data is within the numerical range of the first reference value to obtain a first judgment result for the first filter element data; when the first judgment result indicates that the first filter element data is not within the numerical range of the first reference value, determining the first judgment result and the filter element meeting the preset water purification performance abnormal condition as a target judgment result for the filter element.

[0017] As an optional implementation, in the second aspect of the present application, the manner in which the judging module judges whether the filter element meets the preset water purification performance abnormal condition according to the purification capability performance data specifically further comprises: when the first judgment result indicates that the first filter element data is within the numerical range of the first reference value, respectively judging whether the second filter element data is within the numerical range of the second reference value to obtain a second judgment result for the second filter element data, and judging whether the TDS variation curve of the inlet water has abnormal curve information that does not conform to the curve reference information to obtain a third judgment result for the TDS variation curve of the inlet water; when the second judgment result indicates that the second filter element data is not within the numerical range of the second reference value, adding the second judgment result and the filter element meeting the preset water purification performance abnormal condition to the target judgment result for the filter element; When the third determination result indicates that the water inlet TDS change curve has abnormal curve information that does not conform to the curve reference information, the third determination result, the abnormal curve information, and the filter element satisfying the preset water purification performance abnormality condition are added to the target determination result for the filter element.

[0018] As an optional implementation, in the second aspect of the present application, the second determination module determines the abnormal type causing the water purification performance abnormality of the filter element according to the filter application influence information, and the manner is specifically as follows: When the filter application influence information includes the water use scene, a first abnormality analysis operation is performed on a water use scene feature associated with the water use scene to obtain a first abnormality analysis result for the water use scene feature; the water use scene feature includes a water use frequency for the filter element and a cumulative water treatment amount; When the filter application influence information includes the equipment operation condition, a second abnormality analysis operation is performed on an equipment operation condition feature associated with the equipment operation condition to obtain a second abnormality analysis result for the equipment operation condition feature; the equipment operation condition feature includes water pressure data and outlet water temperature data of the filter element; When the filter application influence information includes the filter element filter configuration, a third abnormality analysis operation is performed on a filter element filter configuration feature associated with the filter element filter configuration to obtain a third abnormality analysis result for the filter element filter configuration feature; the filter element filter configuration feature includes a filter element type of the filter element and a cumulative use time length of the filter element; When the filter application influence information includes the water inlet quality, a fourth abnormality analysis operation is performed on a water inlet quality feature associated with the water inlet quality to obtain a fourth abnormality analysis result for the water inlet quality feature; the water inlet quality feature includes a water inlet TDS value; A weighted summation operation is performed on a target abnormality analysis result, and a corresponding weighted summation result is numerically matched with a set abnormality classification reference to obtain a numerical matching result of the weighted summation result and the abnormality classification reference, the numerical matching result including an abnormal type causing the water purification performance abnormality of the filter element; the target abnormality analysis result includes at least one of the first abnormality analysis result, the second abnormality analysis result, the third abnormality analysis result, and the fourth abnormality analysis result.

[0019] As an optional implementation, in the second aspect of the present application, the first abnormality analysis result is used to indicate whether the water use frequency is higher than a rated water filtering frequency of the filter element, and is also used to indicate whether the cumulative water treatment amount is higher than a maximum water treatment amount of the filter element. The second abnormality analysis result is used to indicate whether high water pressure data and / or low water pressure data that do not conform to the rated water pressure exist in the water pressure data, and is also used to indicate whether high water temperature data and / or low water temperature data that do not conform to the rated temperature exist in the outlet water temperature; The third abnormality analysis result is used to indicate whether the filter core type is adapted to process the actual inlet water quality of the filter core, and is also used to indicate whether the cumulative use duration of the filter core is greater than the rated use duration of the filter core. The fourth abnormality analysis result is used to indicate whether the inlet water TDS value is higher than an initial inlet water TDS value, the initial inlet water TDS value being a TDS value monitored for an inlet water source of the filter core when the filter core is initially installed, and the initial inlet water TDS value being adapted to the rated water filtering capacity of the filter core.

[0020] As an optional implementation, in the second aspect of the present application, the manner in which the filter core processing module performs the filter core replacement processing operation matching the abnormality type according to the filtering application influence information is specifically as follows: According to the filtering application influence information and the abnormality type, an abnormality detail for the filter core is determined, the abnormality detail being a first detail indicating that the filter core has a fault, or a second detail indicating that the filtering capacity of the filter core is lower than the water purification demand; When the abnormality detail is the first detail, a filter core replacement operation is performed on the filter core to replace the filter core with a new filter core of the same filter core model as the filter core. When the abnormality detail is the second detail, a filter core upgrade operation is performed on the filter core according to the water purification demand to replace the filter core with a new filter core adapted to the water purification demand, wherein the new filter core adapted to the water purification demand corresponds to a filter core performance higher than the filter core performance of the filter core.

[0021] The third aspect of the present application discloses another intelligent filter core replacement control device based on filter core water purification capacity, the device comprising: a memory storing executable program codes; a processor coupled with the memory; The processor invokes the executable program codes stored in the memory to execute part or all of the steps of the intelligent filter core replacement control method based on filter core water purification capacity according to any one of the first aspect of the present application.

[0022] The fourth aspect of the present application discloses a computer storage medium storing computer instructions, the computer instructions being invoked to execute part or all of the steps of the intelligent filter core replacement control method based on filter core water purification capacity according to any one of the first aspect of the present application.

[0023] Compared with the prior art, the present application has the following beneficial effects: In the embodiment of the present application, an intelligent core replacement control method based on filter core water purification capacity is provided, which comprises: determining purification capacity performance data corresponding to the filter core being analyzed, the purification capacity performance data being obtained by analyzing data corresponding to the filter core and the TDS value; judging whether the filter core meets a preset water purification performance abnormal condition according to the purification capacity performance data; determining filter application influence information of the filter core when it is judged that the filter core meets the water purification performance abnormal condition, the filter application influence information comprising at least one of sub-information of a water use scenario, a device operating condition, a filter core filtering configuration, and an inlet water quality; determining an abnormal type causing the filter core to have the water purification performance abnormality according to the filter application influence information, the abnormal type comprising a first abnormal type of the filter core itself being an abnormal factor or a non-first abnormal type; and performing a core replacement processing operation matched with the abnormal type on the filter core according to the filter application influence information, so that the new filter core after replacement does not meet the water purification performance abnormal condition. It can be seen that, by analyzing the associated data of the filter core and the TDS value and dynamically evaluating the purification capacity performance, the accuracy of judging whether the filter core has the water purification performance abnormality can be improved according to the present application; after determining the abnormality, the abnormality is accurately distinguished from being caused by the aging of the filter core itself (the first abnormal type) or external factors (such as sudden change of water quality, device abnormality, etc.) by further combining multi-dimensional information such as the water use scenario, the device operating condition, the filter core configuration, and the inlet water quality, which is beneficial to improving the comprehensiveness and accuracy of the judgment of the water purification performance abnormality; further, the corresponding core replacement processing operation can be matched according to the abnormal type, and the execution pertinence of the core replacement processing operation is improved. BRIEF DESCRIPTION OF DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort.

[0025] Figure 1 is a structural schematic diagram of a water purification equipment disclosed by the embodiment of the present application; Figure 2 is a flow schematic diagram of an intelligent core replacement control method based on filter core water purification capacity disclosed by the embodiment of the present application; Figure 3 is a flow schematic diagram of another intelligent core replacement control method based on filter core water purification capacity disclosed by the embodiment of the present application; Figure 4 is a structural schematic diagram of an intelligent core replacement control device based on filter core water purification capacity disclosed by the embodiment of the present application; Figure 5is a structural schematic view of another intelligent core changing control device based on filter core water purification capacity disclosed by the embodiment of the present application. DETAILED DESCRIPTION

[0026] In order for those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0027] The terms "first", "second", and the like in the specification and claims of the present application and the above-mentioned drawings are used to distinguish different objects, not to describe a specific order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, device, product, or end including a series of steps or units is not limited to the listed steps or units, but can optionally include steps or units not listed, or can optionally include other steps or units inherent to the process, method, product, or end.

[0028] In this document, the reference to "embodiments" means that the specific features, structures, or characteristics described in connection with the embodiments can be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily mean the same embodiment is referred to, nor does it mean that the embodiments are mutually exclusive or alternative to each other. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with each other.

[0029] The present application discloses an intelligent core changing control method and device based on filter core water purification capacity. By analyzing the correlation data of the filter core and the TDS value, the purification capacity performance is dynamically evaluated, which can improve the accuracy of judging whether the filter core has abnormal water purification performance. After determining the abnormality, further combined with multi-dimensional information such as water use scene, equipment operating condition, filter core configuration and water quality, the abnormality is accurately distinguished whether it is caused by filter core aging (first abnormal type) or external factors (such as water quality mutation, equipment abnormality, etc.), which is beneficial to improve the comprehensiveness and accuracy of the judgment of water purification performance abnormality. Further, the corresponding core changing processing operation can be matched according to the abnormal type, which improves the execution pertinence of the core changing processing operation. The following will be described in detail.

[0030] In order to better understand the intelligent core changing control method and device based on filter core water purification capacity described in the present application, first, the device structure suitable for the intelligent core changing control method based on filter core water purification capacity is described. Specifically, the device structure can be as shown in Figure 1As shown in the accompanying drawings, Figure 1 is a structural schematic diagram of a water purification equipment disclosed by an embodiment of the present application. As shown in the accompanying drawings, Figure 1 the water purification equipment can include filter cartridges, wherein: The filter cartridges include three filter cartridges, i.e., a first filter cartridge, a second filter cartridge and a third filter cartridge, which are arranged longitudinally inside the water purification equipment. The first filter cartridge can be a PP cotton filter cartridge, which is used to achieve pre-filtering and coarsely filter silt, rust and the like. The second filter cartridge can be an activated carbon filter cartridge, which is used to adsorb residual chlorine and peculiar smell. The third filter cartridge can be an RO reverse osmosis membrane / ultrafiltration membrane filter cartridge, which is used as a core filter cartridge to remove bacteria, viruses, heavy metals and the like. In addition, each filter cartridge is connected through a transparent pipeline.

[0031] As shown in the accompanying drawings, Figure 1 the water purification equipment can further include a multi-stage sensing component, wherein: The multi-stage sensing component can be arranged at key nodes around and inside the water purification equipment, which is used to comprehensively monitor the working state and performance of the filter cartridges. The multi-stage sensing component can transmit data to the cloud / smart gateway through wireless signals.

[0032] Further, the multi-stage sensing component can include an inlet water TDS sensor, a flow sensor and a pressure sensor. The inlet water TDS sensor is used to monitor the total dissolved solids value of raw water (tap water). The flow sensor is used to monitor the raw water flow entering the equipment. The pressure sensor is used to monitor the inlet water pressure.

[0033] The multi-stage sensing component can further include a differential pressure sensor and a temperature sensor. The differential pressure sensor is used to be connected before and after each filter cartridge to monitor the pressure difference before and after water passes through the filter cartridge. An increase in the pressure difference is a key indicator that the filter cartridge is clogged and needs to be replaced. The temperature sensor is used to monitor the inlet water temperature (water temperature can affect the flux of the RO membrane).

[0034] The multi-stage sensing component can further include an outlet water TDS sensor and a flow sensor. The outlet water TDS sensor is used to monitor the TDS value of the purified water, which is the most direct basis for judging whether the performance of the RO membrane is attenuated. The flow sensor is used to monitor the pure water outlet flow to calculate the cumulative water production.

[0035] Optionally, the water purification equipment can further include a display component, which is used to display the equipment use state of the water purification equipment in real time, such as displaying the inlet water TDS value, the outlet water TDS value, the filter cartridge life and the like.

[0036] Optionally, the data collected by the multi-stage sensing component can be uploaded to the cloud platform or the user's mobile phone App through the built-in Internet of Things component of the water purification equipment, and big data analysis is performed, so as to realize accurate filter cartridge life prediction and abnormal alarm.

[0037] It should be noted that Figure 1 The water purification equipment shown is only to represent the equipment structure to which the intelligent core replacement control method based on the water purification capacity of the filter is applicable. The display components, first filter, second filter, third filter, multi-stage sensing components, etc. involved are only illustrative. The specific structure / size / shape / location / mounting method, etc. can be adaptively adjusted according to the actual scene. Figure 1 The water purification equipment shown is not limited in this regard.

[0038] The application scenarios to which the intelligent core replacement control method based on the water purification capacity of the filter is applicable are described above. The intelligent core replacement control method and device based on the water purification capacity of the filter are described in detail below.

[0039] Embodiment one Please refer to Figure 2 , Figure 2 is a flowchart of an intelligent core replacement control method based on the water purification capacity of the filter disclosed in an embodiment of the present application. Among them, Figure 2 The intelligent core replacement control method based on the water purification capacity of the filter described can be applied in an intelligent core replacement control device based on the water purification capacity of the filter. The present application embodiment is not limited. For example Figure 2 As shown, the intelligent core replacement control method based on the water purification capacity of the filter can include the following operations: 101, determine the purification capacity performance data corresponding to the filter core being analyzed, which is obtained by analyzing the data corresponding to the TDS value of the filter core.

[0040] 102, according to the purification capacity performance data, judge whether the filter core meets the preset water purification performance abnormal condition.

[0041] 103, when it is judged that the filter core meets the water purification performance abnormal condition, determine the filter application influence information of the filter core.

[0042] In the present application embodiment, the filter application influence information includes at least one of the following sub-information: water use scene, equipment operating condition, filter core filtering configuration, and water inlet quality.

[0043] 104, according to the filter application influence information, determine the abnormal type causing the water purification performance abnormality of the filter core. The abnormal type includes a first abnormal type in which the filter core itself is an abnormal factor, or a non-first abnormal type.

[0044] 105, according to the filter application influence information, perform a core replacement processing operation matched with the abnormal type on the filter core, so that the new filter core after replacement does not meet the water purification performance abnormal condition.

[0045] In the embodiment of the present application, the first abnormal type is used to indicate that the abnormality is a problem of the filter element itself, such as aging or damage; and the non-first abnormal type is an external factor, such as sudden change of water quality or equipment abnormality. On this basis, the filter replacement processing operation matched with the abnormal type is performed, and for the abnormality of the filter element itself, the filter element is replaced in time, and for the non-filter element problem, the device operating parameter is adjusted or the user is prompted to check the water quality, thereby avoiding unnecessary filter replacement and reducing the use cost.

[0046] It can be seen that the implementation Figure 2 The intelligent filter replacement control method based on the water purification capacity of the filter element described above can improve the accuracy of judging whether the filter element has abnormal water purification performance by analyzing the correlation data of the filter element and the TDS value and dynamically evaluating the purification capacity performance. After determining the abnormality, the multi-dimensional information such as the water use scene, the device operating condition, the filter element configuration and the water quality is further combined to accurately distinguish whether the abnormality is caused by the aging of the filter element (the first abnormal type) or the external factor (such as sudden change of water quality or equipment abnormality), which is beneficial to improve the comprehensiveness and accuracy of the judgment of the abnormal water purification performance. Further, the corresponding filter replacement processing operation can be matched according to the abnormal type, thereby improving the execution pertinence of the filter replacement processing operation.

[0047] In an optional embodiment, the manner of determining the purification capacity performance data corresponding to the filter element currently analyzed in the step 101 specifically includes: determining a first filter element parameter for the filter element currently analyzed, and collecting first filter element data corresponding to the first filter element parameter; the first filter element parameter at least includes an inlet water TDS parameter, an outlet water TDS parameter, a pure water TDS parameter and a waste water TDS parameter; analyzing inlet water TDS data corresponding to the inlet water TDS parameter to obtain an inlet water TDS change curve for the inlet water TDS data, and the inlet water TDS change curve includes at least one inlet water TDS change curve inflection point; determining a second filter element parameter for the filter element, and the second filter element parameter at least includes a first ratio parameter and a second ratio parameter; the first ratio parameter is obtained by calculating the ratio of the inlet water TDS parameter and the outlet water TDS parameter; and the second ratio parameter is obtained by calculating the ratio of the pure water TDS parameter and the waste water TDS parameter; calculating second filter element data corresponding to the second filter element parameter according to the first filter element data; determining the first filter element parameter, the first filter element data, the second filter element parameter, the second filter element data and the inlet water change curve as the purification capacity performance data corresponding to the filter element.

[0048] In the optional embodiment, by comprehensively collecting four types of core TDS parameters of influent water, effluent water, pure water and waste water, and further calculating two key ratio parameters (desalination rate related parameters and system recovery rate / concentration related parameters), a multi-dimensional filter performance evaluation data pool is constructed. The rich data quantity overcomes the limitation of relying on single influent and effluent water TDS to calculate desalination rate, making the determination of filter water purification capacity more comprehensive and accurate.

[0049] In the optional embodiment, on the basis of collecting the first filter data, curve analysis can also be performed on the influent water TDS data to identify the change inflection point. Based on the TDS change curve, the dynamic fluctuation of water source water quality (such as seasonal change, pipeline pollution, etc.) can be effectively captured, so as to distinguish the change of filter performance from the mutation of influent water condition, and avoid misjudgment of filter failure due to sudden deterioration of influent water quality. By using the TDS change curve, the diagnostic accuracy of subsequent filter water purification performance is significantly improved.

[0050] It can be seen that in the optional embodiment, by collecting and fusing multi-source TDS data, calculating key ratios and performing accurate analysis of influent water quality trend, reliable data support is provided for subsequent accurate identification of filter performance abnormalities and correct attribution, that is, the determination of comprehensive and accurate purification capacity performance data is improved.

[0051] In another optional embodiment, the manner of determining whether the filter satisfies the preset water purification performance abnormal condition according to the purification capacity performance data in the above step 102 specifically comprises: determining a first reference value for the first filter parameter, a second reference value for the first filter parameter, and curve reference information for the influent water TDS change curve; determining whether the first filter data is within the numerical range of the first reference value to obtain a first determination result for the first filter data; when the first determination result indicates that the first filter data is not within the numerical range of the first reference value, determining the first determination result and the filter satisfying the preset water purification performance abnormal condition as the target determination result for the filter.

[0052] It can be seen that in the optional embodiment, multi-dimensional reference is set to achieve fine monitoring of filter purification capacity; by judging whether the first filter data deviates from the numerical range of the first reference value, the filter performance abnormality can be quickly identified, and the water purification performance abnormal condition determination is triggered immediately when the data is abnormal, improving the accuracy and real-time performance of filter state detection, and avoiding the limitation of traditional single threshold judgment.

[0053] In yet another optional embodiment, the manner of determining whether the filter satisfies the preset water purification performance abnormal condition according to the purification capacity performance data in the above step 102 specifically further comprises: When the first judgment result indicates that the first filter element data is within the numerical range of the first reference value, it is determined whether the second filter element data is within the numerical range of the second reference value, respectively, to obtain a second judgment result for the second filter element data, and whether the water inlet TDS change curve exists abnormal curve information that does not conform to the curve reference information, to obtain a third judgment result for the water inlet TDS change curve; When the second judgment result indicates that the second filter element data is outside the numerical range of the second reference value, the second judgment result and the filter element satisfying the preset water purification performance abnormal condition are added to the target judgment result for the filter element; When the third judgment result indicates that the water inlet TDS change curve exists abnormal curve information that does not conform to the curve reference information, the third judgment result, the abnormal curve information, and the filter element satisfying the preset water purification performance abnormal condition are added to the target judgment result for the filter element.

[0054] It can be seen that in the optional embodiment, on the basis that no abnormality is found in the preliminary judgment (first filter element parameter), a deeper level of cooperative diagnosis mechanism is introduced. By detecting whether the second filter element parameter is outside the reference range and whether the water inlet TDS change curve appears abnormal morphology in parallel, multi-dimensional and cross-verification diagnosis of the filter element performance is realized. Through the progressive judgment logic, the possibility of false alarm of a single parameter is greatly reduced, and the comprehensiveness and accuracy of the determination of the filter element performance are ensured. By introducing intelligent recognition and comparison of the water inlet water quality dynamic change curve, the outflow abnormality caused by the performance degradation of the filter element itself and the temporary change caused by the sharp fluctuation of the water inlet water quality can be effectively distinguished, so that the fault root cause is accurately located, and the misjudgment of the filter element health state caused by the water inlet interference is avoided.

[0055] Embodiment two Please refer to Figure 3 , Figure 3 is a flowchart of another intelligent filter replacement control method based on filter water purification capacity disclosed in the embodiment of the application. Among them, Figure 3 The intelligent filter replacement control method based on filter water purification capacity described can be applied to an intelligent filter replacement control device based on filter water purification capacity, and the embodiment of the application is not limited. As Figure 3 shown, the intelligent filter replacement control method based on filter water purification capacity can include the following operations: 201, determine the purification capacity performance data corresponding to the filter element currently analyzed, which is obtained by analyzing the data corresponding to the filter element and the TDS value.

[0056] 202, according to the purification capacity performance data, determine whether the filter element satisfies the preset water purification performance abnormal condition.

[0057] 203. When it is determined that the filter element meets the abnormal conditions for water purification performance, determine the filter element's filtration application impact information.

[0058] 204. Based on the information on the impact of filtration applications, determine the type of abnormality that causes the filter element to have abnormal water purification performance. The abnormality type includes the first type of abnormality, where the filter element itself is the abnormal factor, or a non-first type of abnormality.

[0059] 205. Based on the information on the impact of the filtration application and the type of anomaly, determine the details of the anomalies for the filter element.

[0060] In this embodiment of the invention, the abnormal details are either a first detail indicating that the filter element is faulty, or a second detail indicating that the filter element's filtration capacity is lower than the water purification requirements.

[0061] 206. When the abnormality is the first abnormality, perform a filter replacement operation to replace the filter with a new filter of the same model.

[0062] 207. When the abnormality is the second abnormality, perform a filter upgrade operation according to the water purification requirements to replace the filter with a new filter that is suitable for the water purification requirements.

[0063] In this embodiment of the invention, the performance of the new filter element adapted to the water purification requirements is higher than that of the original filter element.

[0064] For further descriptions of steps 201-204 in this embodiment of the invention, please refer to the other specific descriptions of steps 101-104 in Embodiment 1. These descriptions will not be repeated in this embodiment of the invention.

[0065] It is evident that implementation Figure 3 The described intelligent filter replacement control method based on filter purification capabilities sets up replacement procedures for different anomalies. For the first anomaly, a standard filter replacement operation is performed; for the second anomaly, a matching filter upgrade operation is performed, allowing the selection of a new filter with higher performance and better suited to the current water usage scenario. In other words, by differentiating between "fault replacement" and "capability upgrade"—two refined processing modes—an intelligent and differentiated filter maintenance strategy is achieved. This improves the targetedness and accuracy of filter replacement while ensuring reliable filter use and proactively optimizing its purification capabilities and output water quality, ultimately enhancing the user experience.

[0066] In an optional embodiment, step 204 above, which determines the type of abnormality causing the filter cartridge to exhibit abnormal water purification performance based on the filtration application impact information, specifically includes the following methods: When the filtering application influence information comprises the water use scenario, a first abnormality analysis operation is performed on water use scenario features associated with the water use scenario to obtain a first abnormality analysis result for the water use scenario features; the water use scenario features comprise a water use frequency for the filter element and a cumulative water treatment volume; When the filtering application influence information comprises the device operating condition, a second abnormality analysis operation is performed on device operating condition features associated with the device operating condition to obtain a second abnormality analysis result for the device operating condition features; the device operating condition features comprise water pressure data and outlet water temperature data for the filter element; When the filtering application influence information comprises the filter element filtering configuration, a third abnormality analysis operation is performed on filter element filtering configuration features associated with the filter element filtering configuration to obtain a third abnormality analysis result for the filter element filtering configuration features; the filter element filtering configuration features comprise a filter element type of the filter element and a cumulative use duration of the filter element; When the filtering application influence information comprises the incoming water quality, a fourth abnormality analysis operation is performed on incoming water quality features associated with the incoming water quality to obtain a fourth abnormality analysis result for the incoming water quality features; the incoming water quality features comprise an incoming water TDS value; A weighted summation operation is performed on the target abnormality analysis result, and a corresponding weighted summation result is numerically matched with a set abnormality classification benchmark to obtain a numerical matching result of the weighted summation result and the abnormality classification benchmark, the numerical matching result comprising an abnormality type causing the filter element to have abnormal water purification performance; the target abnormality analysis result comprises at least one of the first abnormality analysis result, the second abnormality analysis result, the third abnormality analysis result, and the fourth abnormality analysis result.

[0067] In this optional embodiment, the first abnormality analysis result is used to indicate whether the water use frequency is higher than a rated water purification frequency of the filter element, and is also used to indicate whether the cumulative water treatment volume is higher than a maximum water treatment volume of the filter element.

[0068] In this optional embodiment, the second abnormality analysis result is used to indicate whether the water pressure data includes high water pressure data and / or low water pressure data that do not conform to a rated water pressure, and is also used to indicate whether the outlet water temperature includes high water temperature data and / or low water temperature data that do not conform to a rated temperature.

[0069] In this optional embodiment, the third abnormality analysis result is used to indicate whether the filter element type is adapted to the actual incoming water quality of the filter element, and is also used to indicate whether the cumulative use duration of the filter element is greater than a rated service life of the filter element.

[0070] In this optional embodiment, the fourth abnormality analysis result is used to indicate whether the incoming water TDS value is higher than an initial incoming water TDS value, the initial incoming water TDS value being a TDS value monitored for an incoming water source of the filter element when the filter element is initially installed, the initial incoming water TDS value being adapted to a rated water purification capacity of the filter element.

[0071] It can be seen that in this optional embodiment, by classifying the factors that may cause the anomaly into four categories of key influence information (water use scenario, equipment operating condition, filter element filtering configuration, and influent water quality), and performing directional analysis on the specific characteristics under each category of information, the one-sidedness of single factor diagnosis is avoided, and the pertinence and refinement of anomaly diagnosis are improved. Further, by weighting and summing the discrete analysis results of each feature (the first to fourth anomaly analysis results), and finally matching with the preset anomaly classification benchmark, the contribution of different influencing factors to the anomaly result can be quantified, so as to accurately lock the main anomaly type, and further improve the accuracy of determining the anomaly type.

[0072] In another optional embodiment, the manner in which the step 207 performs the filter element upgrade operation on the filter element according to the water purification demand specifically includes: analyzing the water purification demand to obtain an analysis result for the water purification demand, the analysis result including at least a purified water quantity and a water quality standard, and further including a performance index for the filter element, the performance index including a filtering precision and a filtering material; determining a plurality of to-be-screened filter elements matching the analysis result from a database; obtaining installation information corresponding to the filter element, the installation information including an installation manner and an interface specification; performing information matching on all the to-be-screened filter elements according to the installation information to obtain at least one target filter element adapted to the installation information; generating upgrade information for the filter element according to the target filter element and filter element configuration information recorded in the database for the target filter element, the filter element configuration information including at least the installation information corresponding to the target filter element; sending the upgrade information to a user to prompt the user to select the target filter element and perform an upgrade replacement on the filter element.

[0073] It can be seen that in this optional embodiment, an intelligent analysis mechanism for upgrading the filter element is provided, and in the case where the currently used filter element cannot meet the water purification demand, the water purification demand can be intelligently analyzed to preliminarily screen a plurality of to-be-screened filter elements from the database according to the corresponding analysis result, and then a target filter element that can replace the currently used filter element is determined from all the to-be-screened filter elements by taking the installation information as a second-level screening condition, so that the finally screened target filter element not only meets the use demand in terms of water purification performance, but also accurately adapts to the installation specification, greatly improving the selection accuracy and convenience of the target filter element.

[0074] Embodiment Three Please refer to Figure 4 , Figure 4is a structural schematic view of an intelligent filter replacement control device based on filter water purification capacity disclosed by the embodiment of the present application. The intelligent filter replacement control device based on filter water purification capacity can be an intelligent filter replacement control terminal, device, system or server based on filter water purification capacity. The server can be a local server, a remote server or a cloud server (also known as a cloud server). When the server is a non-cloud server, the non-cloud server can be connected to the cloud server for communication. The embodiment of the present application does not make any limitation. As shown in Figure 4 The intelligent filter replacement control device based on filter water purification capacity can include a first determination module 301, a judgment module 302, a second determination module 303 and a filter replacement processing module 304, wherein: The first determination module 301 is configured to determine the purification capacity performance data corresponding to the filter analyzed at present. The purification capacity performance data is obtained by analyzing the data corresponding to the filter and the TDS value.

[0075] The judgment module 302 is configured to determine whether the filter meets the preset water purification performance abnormal condition according to the purification capacity performance data.

[0076] The first determination module 301 is further configured to determine the filter application influence information of the filter when the judgment module 302 determines that the filter meets the water purification performance abnormal condition. The filter application influence information includes at least one sub-information in the water use scene, the equipment operation condition, the filter configuration and the water quality.

[0077] The second determination module 303 is configured to determine the abnormal type causing the water purification performance abnormality of the filter according to the filter application influence information. The abnormal type includes a first abnormal type of the filter itself as an abnormal factor or a non-first abnormal type.

[0078] The filter replacement processing module 304 is configured to perform the filter replacement processing operation matched with the abnormal type on the filter according to the filter application influence information, so that the new filter after replacement does not meet the water purification performance abnormal condition.

[0079] It can be seen that the embodiment of the present application implements Figure 4 The intelligent filter replacement control device based on filter water purification capacity described above can dynamically evaluate the purification capacity performance by analyzing the associated data of the filter and the TDS value, which can improve the accuracy of determining whether the filter appears the water purification performance abnormality. After determining the abnormality, the multi-dimensional information such as the water use scene, the equipment operation condition, the filter configuration and the water quality is further combined to accurately distinguish whether the abnormality is caused by the aging of the filter itself (the first abnormal type) or the external factors (such as water quality mutation, equipment abnormality, etc.), which is beneficial to improve the comprehensiveness and accuracy of the judgment of the water purification performance abnormality. Furthermore, the corresponding filter replacement processing operation can be matched according to the abnormal type, which improves the execution pertinence of the filter replacement processing operation.

[0080] In an optional embodiment, the first determining module 301 determines the current analysis of the filter corresponding to the purification ability performance data in the following manner: determining a first filter parameter for the filter currently analyzed, and collecting first filter data corresponding to the first filter parameter; the first filter parameter at least includes an inlet water TDS parameter, an outlet water TDS parameter, a pure water TDS parameter, and a waste water TDS parameter; analyzing inlet water TDS data corresponding to the inlet water TDS parameter to obtain an inlet water TDS change curve for the inlet water TDS data, the inlet water TDS change curve including at least one inlet water TDS change curve inflection point; determining a second filter parameter for the filter, the second filter parameter at least including a first ratio parameter and a second ratio parameter; the first ratio parameter is obtained by calculating the ratio of the inlet water TDS parameter and the outlet water TDS parameter; the second ratio parameter is obtained by calculating the ratio of the pure water TDS parameter and the waste water TDS parameter; According to the first filter data, calculating second filter data corresponding to the second filter parameter; determining the first filter parameter, the first filter data, the second filter parameter, the second filter data, and the inlet water change curve as the purification ability performance data corresponding to the filter.

[0081] As can be seen, in this optional embodiment, by collecting and fusing multi-source TDS data, calculating key ratios, and performing accurate analysis of inlet water quality trends, reliable data support is provided for subsequent accurate identification of filter performance abnormalities and correct attribution, that is, the determination of the purification ability performance data is improved in comprehensiveness and accuracy.

[0082] In another optional embodiment, the judging module 302 judges whether the filter meets the preset water purification performance abnormality condition according to the purification ability performance data in the following manner: determining a first reference value for the first filter parameter, a second reference value for the first filter parameter, and curve reference information for the inlet water TDS change curve; judging whether the first filter data is within the numerical range of the first reference value to obtain a first judgment result for the first filter data; When the first judgment result indicates that the first filter data is not within the numerical range of the first reference value, the first judgment result and the filter meeting the preset water purification performance abnormality condition are determined as the target judgment result for the filter.

[0083] It can be seen that in the optional embodiment, a multi-dimensional reference is set, and fine monitoring of the purification capacity of the filter element can be realized; by judging whether the first filter element data deviates from the numerical range of the first reference value, the performance abnormality of the filter element can be quickly identified, and the water purification performance abnormality condition judgment is triggered immediately when the data is abnormal, which improves the accuracy and real-time performance of the filter element state detection, and avoids the limitations of traditional single threshold judgment.

[0084] In yet another optional embodiment, the manner in which the judgment module 302 judges whether the filter element meets the preset water purification performance abnormality condition according to the purification capacity performance data specifically includes: When the first judgment result indicates that the first filter element data is within the numerical range of the first reference value, it is respectively judged whether the second filter element data is within the numerical range of the second reference value to obtain a second judgment result for the second filter element data, and it is judged whether the water inlet TDS change curve has abnormal curve information that does not conform to the curve reference information to obtain a third judgment result for the water inlet TDS change curve; When the second judgment result indicates that the second filter element data is outside the numerical range of the second reference value, the second judgment result and the filter element meeting the preset water purification performance abnormality condition are added to the target judgment result for the filter element; When the third judgment result indicates that the water inlet TDS change curve has abnormal curve information that does not conform to the curve reference information, the third judgment result, the abnormal curve information, and the filter element meeting the preset water purification performance abnormality condition are added to the target judgment result for the filter element.

[0085] It can be seen that in this optional embodiment, on the basis of no abnormality being found in the preliminary judgment (first filter element parameter), a deeper level of cooperative diagnosis mechanism is introduced. By detecting whether the second filter element parameter exceeds its reference range and whether the water inlet TDS change curve has an abnormal shape in parallel, multi-dimensional and cross-verification diagnosis of the filter element performance is realized. Through this progressive judgment logic, the possibility of false positives of a single parameter is greatly reduced, ensuring the comprehensiveness and accuracy of the judgment of the filter element performance. By introducing intelligent recognition and comparison of the dynamic change curve of the water inlet quality, the outflow abnormality caused by the performance degradation of the filter element itself and the temporary change caused by the sharp fluctuation of the water inlet quality can be effectively distinguished, so as to accurately locate the fault source and avoid the misjudgment of the health state of the filter element caused by the water inlet interference.

[0086] In another optional embodiment, the manner in which the second determination module 303 determines the abnormal type causing the water purification performance abnormality of the filter element according to the filtration application influence information is specifically: When the filtering application influence information comprises the water use scenario, a first abnormality analysis operation is performed on water use scenario features associated with the water use scenario to obtain a first abnormality analysis result for the water use scenario features; the water use scenario features comprise a water use frequency for the filter element and a cumulative water treatment volume; When the filtering application influence information comprises the device operating condition, a second abnormality analysis operation is performed on device operating condition features associated with the device operating condition to obtain a second abnormality analysis result for the device operating condition features; the device operating condition features comprise water pressure data and outlet water temperature data for the filter element; When the filtering application influence information comprises the filter element filtering configuration, a third abnormality analysis operation is performed on filter element filtering configuration features associated with the filter element filtering configuration to obtain a third abnormality analysis result for the filter element filtering configuration features; the filter element filtering configuration features comprise a filter element type of the filter element and a cumulative use duration of the filter element; When the filtering application influence information comprises the incoming water quality, a fourth abnormality analysis operation is performed on incoming water quality features associated with the incoming water quality to obtain a fourth abnormality analysis result for the incoming water quality features; the incoming water quality features comprise an incoming water TDS value; A weighted summation operation is performed on the target abnormality analysis result, and a corresponding weighted summation result is numerically matched with a set abnormality classification benchmark to obtain a numerical matching result of the weighted summation result and the abnormality classification benchmark, the numerical matching result comprising an abnormality type causing the filter element to have abnormal water purification performance; the target abnormality analysis result comprises at least one of the first abnormality analysis result, the second abnormality analysis result, the third abnormality analysis result, and the fourth abnormality analysis result.

[0087] In this optional embodiment, the first abnormality analysis result is used to indicate whether the water use frequency is higher than a rated water purification frequency of the filter element, and is also used to indicate whether the cumulative water treatment volume is higher than a maximum water treatment volume of the filter element.

[0088] In this optional embodiment, the second abnormality analysis result is used to indicate whether the water pressure data comprises high water pressure data and / or low water pressure data that do not conform to a rated water pressure, and is also used to indicate whether the outlet water temperature comprises high water temperature data and / or low water temperature data that do not conform to a rated temperature.

[0089] In this optional embodiment, the third abnormality analysis result is used to indicate whether the filter element type is adapted to the actual incoming water quality of the filter element, and is also used to indicate whether the cumulative use duration of the filter element is greater than a rated service life of the filter element.

[0090] In this optional embodiment, the fourth abnormality analysis result is used to indicate whether the incoming water TDS value is higher than an initial incoming water TDS value, the initial incoming water TDS value being a TDS value monitored for an incoming water source of the filter element when the filter element is initially installed, the initial incoming water TDS value being adapted to a rated water purification capacity of the filter element.

[0091] It can be seen that in this optional embodiment, by classifying the factors that may cause the anomaly into four categories of key influence information (water use scenario, equipment operating condition, filter element filtering configuration, and influent water quality), and performing directional analysis on the specific characteristics under each category of information, the one-sidedness of single-factor diagnosis is avoided, and the pertinence and refinement of anomaly diagnosis are improved. Further, by weighting and summing the discrete analysis results of each feature (the first to fourth anomaly analysis results), and finally matching with the preset anomaly classification benchmark, the contribution of different influencing factors to the anomaly result can be quantified, so that the main anomaly type is accurately locked, and the determination accuracy of the anomaly type is further improved.

[0092] In yet another optional embodiment, the filter element replacement processing module 304 performs a filter element replacement processing operation matching the anomaly type on the filter element according to the filtering application influence information in the following manner: According to the filtering application influence information and the anomaly type, an anomaly detail for the filter element is determined, the anomaly detail being a first detail indicating that the filter element has a fault, or a second detail indicating that the filtering capacity of the filter element is lower than the water purification demand; When the anomaly detail is the first detail, a filter element replacement operation is performed on the filter element to replace the filter element with a new filter element of the same filter element model as the filter element; When the anomaly detail is the second detail, a filter element upgrade operation is performed on the filter element according to the water purification demand to replace the filter element with a new filter element that adapts to the water purification demand; wherein the new filter element that adapts to the water purification demand has a filter element performance higher than the filter element performance of the filter element.

[0093] It can be seen that in this optional embodiment, the filter element replacement processing procedures for different anomaly details are set, for the first detail, a standard filter element replacement operation is performed; for the second detail, a matching filter element upgrade operation is performed, which can select a new filter element with higher performance and more suitable for the current water use scenario. That is, by distinguishing between the two refined processing modes of "fault replacement" and "capacity upgrade", an intelligent and differentiated filter element maintenance strategy is realized, which improves the processing pertinence and accuracy of the filter element replacement, ensures the reliable use of the filter element, and actively optimizes the water purification capacity and output water quality of the filter element, which is beneficial to improving the user's experience of using the filter element.

[0094] Embodiment Four Please refer to Figure 5 , Figure 5 is another structure diagram of an intelligent filter element replacement control device based on filter element water purification capacity disclosed by the embodiments of the present application. As Figure 5 shown, the intelligent filter element replacement control device based on filter element water purification capacity can include: a memory 401 storing executable program codes; a processor 402 coupled with the memory 401; The processor 402 invokes the executable program code stored in the memory 401 to execute part or all of the steps in the intelligent filter core replacement control based on the water purification capacity of the filter core according to the first embodiment or the second embodiment of the present application.

[0095] Embodiment five The computer storage medium according to the embodiments of the present application stores computer instructions, which, when invoked, are used to execute part or all of the steps in the intelligent filter core replacement control based on the water purification capacity of the filter core according to the first embodiment or the second embodiment of the present application.

[0096] The above-described device embodiments are only illustrative, wherein the modules described as separate components can or can not be physically separated, and the components shown as modules can or can not be physical modules, i.e., can be located in one place or distributed on multiple network modules. Part or all of the modules can be selected to achieve the purposes of the embodiments according to actual needs. Those skilled in the art can understand and implement without creative labor.

[0097] From the above detailed description of the embodiments, those skilled in the art can clearly understand that the embodiments can be realized by means of software and necessary universal hardware platforms, and of course can also be realized by hardware. Based on such understanding, the above technical solutions, essentially or in terms of contribution to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a computer readable storage medium, which includes a Read-Only Memory (ROM), a Random Access Memory (RAM), a Programmable Read-only Memory (PROM), an Erasable Programmable Read Only Memory (EPROM), a One-time Programmable Read-Only Memory (OTPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a Compact Disc Read-Only Memory (CD-ROM) or other optical disk storage, a magnetic disk storage, a magnetic tape storage, or any other medium that can be used to carry or store data.

[0098] It should be pointed out finally that the above-described embodiments only disclose the preferred embodiments of the present application and are only used for illustrating the technical solutions of the present application but not for limiting the same. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can be modified or some technical features thereof can be replaced equivalently, and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. An intelligent filter replacement control method based on filter water purification capacity, characterized in that, The method comprises: determining the purification performance data corresponding to the filter core currently analyzed, the purification performance data being obtained by analyzing the data corresponding to the TDS value of the filter core; judging whether the filter core meets the preset water purification performance abnormal condition according to the purification performance data; when it is judged that the filter core meets the water purification performance abnormal condition, determining the filter application influence information of the filter core, the filter application influence information comprising at least one of the sub-information of the water use scene, the equipment operation condition, the filter core filtering configuration and the water inlet quality; determining the abnormal type causing the water purification performance abnormality of the filter core according to the filter application influence information, the abnormal type comprising a first abnormal type that the filter core itself is an abnormal factor or a non-first abnormal type; performing the filter core replacement processing operation matched with the abnormal type on the filter core according to the filter application influence information, so that the new filter core after replacement does not meet the water purification performance abnormal condition.

2. The method according to claim 1, wherein, The determination of the purification performance data corresponding to the filter core currently analyzed comprises: determining the first filter core parameter for the filter core currently analyzed and collecting the first filter core data corresponding to the first filter core parameter; the first filter core parameter at least comprises the water inlet TDS parameter, the water outlet TDS parameter, the pure water TDS parameter and the waste water TDS parameter; analyzing the water inlet TDS data corresponding to the water inlet TDS parameter to obtain the water inlet TDS change curve for the water inlet TDS data, the water inlet TDS change curve comprising at least one water inlet TDS change curve inflection point; determining the second filter core parameter for the filter core, the second filter core parameter at least comprising the first ratio parameter and the second ratio parameter; the first ratio parameter is obtained by calculating the ratio of the water inlet TDS parameter and the water outlet TDS parameter; the second ratio parameter is obtained by calculating the ratio of the pure water TDS parameter and the waste water TDS parameter; calculating the second filter core data corresponding to the second filter core parameter according to the first filter core data; determining the first filter core parameter, the first filter core data, the second filter core parameter, the second filter core data and the water inlet change curve as the purification performance data corresponding to the filter core.

3. The method according to claim 2, wherein, The judgment of whether the filter core meets the preset water purification performance abnormal condition according to the purification performance data comprises: determining the first reference value for the first filter core parameter, the second reference value for the first filter core parameter and the curve reference information for the water inlet TDS change curve; judging whether the first filter core data is within the numerical range of the first reference value to obtain the first judgment result for the first filter core data; when the first judgment result indicates that the first filter core data is not within the numerical range of the first reference value, determining the first judgment result and the fact that the filter core meets the preset water purification performance abnormal condition as the target judgment result for the filter core.

4. The method according to claim 3, wherein, The judgment of whether the filter core meets the preset water purification performance abnormal condition according to the purification performance data further comprises: When the first judgment result indicates that the first filter element data is within the numerical range of the first reference value, it is determined whether the second filter element data is within the numerical range of the second reference value to obtain a second judgment result for the second filter element data, and it is determined whether the water inlet TDS change curve has abnormal curve information that does not conform to the curve reference information to obtain a third judgment result for the water inlet TDS change curve; When the second judgment result indicates that the second filter element data is outside the numerical range of the second reference value, the second judgment result and the filter element satisfying the preset water purification performance abnormal condition are added to the target judgment result for the filter element; When the third judgment result indicates that the water inlet TDS change curve has abnormal curve information that does not conform to the curve reference information, the third judgment result, the abnormal curve information, and the filter element satisfying the preset water purification performance abnormal condition are added to the target judgment result for the filter element.

5. The intelligent filter cartridge replacement control method based on the water purification capacity of the filter cartridge according to any one of claims 1-4, characterized in that, The abnormal type causing the filter element to have the water purification performance abnormality is determined according to the filtering application influence information, including: When the filtering application influence information includes the water use scene, a first abnormality analysis operation is performed on a water use scene feature associated with the water use scene to obtain a first abnormality analysis result for the water use scene feature; the water use scene feature includes a water use frequency for the filter element and a cumulative water treatment amount; When the filtering application influence information includes the equipment operation condition, a second abnormality analysis operation is performed on an equipment operation condition feature associated with the equipment operation condition to obtain a second abnormality analysis result for the equipment operation condition feature; the equipment operation condition feature includes water pressure data and outlet water temperature data using the filter element; When the filtering application influence information includes the filter element filtering configuration, a third abnormality analysis operation is performed on a filter element filtering configuration feature associated with the filter element filtering configuration to obtain a third abnormality analysis result for the filter element filtering configuration feature; the filter element filtering configuration feature includes a filter element type of the filter element and a filter element cumulative use time length; When the filtering application influence information includes the water inlet quality, a fourth abnormality analysis operation is performed on a water inlet quality feature associated with the water inlet quality to obtain a fourth abnormality analysis result for the water inlet quality feature; the water inlet quality feature includes a water inlet TDS value; A weighted summation operation is performed on a target abnormality analysis result, and a corresponding weighted summation result is numerically matched with a set abnormality classification reference to obtain a numerical matching result of the weighted summation result and the abnormality classification reference, the numerical matching result including an abnormal type causing the filter element to have the water purification performance abnormality; the target abnormality analysis result includes at least one of the first abnormality analysis result, the second abnormality analysis result, the third abnormality analysis result, and the fourth abnormality analysis result.

6. The intelligent core changing control method based on the core water purification capacity according to claim 5, characterized in that, The first abnormality analysis result is used to indicate whether the water use frequency is higher than a rated water filtering frequency of the filter element, and is also used to indicate whether the cumulative water treatment amount is higher than a maximum water treatment amount of the filter element; The second abnormality analysis result is used to indicate whether high water pressure data and / or low water pressure data that do not conform to the rated water pressure exist in the water pressure data, and is also used to indicate whether high water temperature data and / or low water temperature data that do not conform to the rated temperature exist in the outlet water temperature; The third abnormality analysis result is used to indicate whether the filter type is adapted to process the actual inlet water quality of the filter, and is also used to indicate whether the cumulative use time length of the filter is greater than the rated use life of the filter; The fourth abnormality analysis result is used to indicate whether the inlet water TDS value is higher than an initial inlet water TDS value, the initial inlet water TDS value being a TDS value monitored for an inlet water source of the filter during initial installation of the filter, the initial inlet water TDS value being adapted to the rated water filtering capacity of the filter.

7. The intelligent filter cartridge replacement control method based on the water purification capacity of a filter cartridge according to claim 1 or 2 or 3 or 4 or 6, characterized in that, The filter replacement processing operation matched with the abnormality type is performed on the filter according to the filter application influence information, including: According to the filter application influence information and the abnormality type, an abnormality detail for the filter is determined, the abnormality detail being a first detail indicating that the filter has a fault, or a second detail indicating that the filtering capacity of the filter is lower than the water purification demand; When the abnormality detail is the first detail, a filter replacement operation is performed on the filter to replace the filter with a new filter of the same filter type as the filter; When the abnormality detail is the second detail, a filter upgrade operation is performed on the filter according to the water purification demand to replace the filter with a new filter adapted to the water purification demand, wherein the new filter adapted to the water purification demand corresponds to a filter performance higher than a filter performance of the filter.

8. An intelligent filter replacement control device based on the water purification capacity of a filter cartridge, characterized in that, The device comprises: A first determination module is configured to determine purification capacity performance data corresponding to a currently analyzed filter, the purification capacity performance data being obtained by analyzing data corresponding to a TDS value of the filter; A judgment module is configured to determine whether the filter meets a preset water purification performance abnormality condition according to the purification capacity performance data; The first determination module is further configured to determine filter application influence information of the filter when the judgment module determines that the filter meets the water purification performance abnormality condition, the filter application influence information including at least one of use water scene, equipment operation condition, filter filtering configuration, and inlet water quality; A second determination module is configured to determine an abnormality type causing the water purification performance abnormality of the filter according to the filter application influence information, the abnormality type including a first abnormality type in which the filter itself is an abnormal factor, or a non-first abnormality type; A filter replacement processing module is configured to perform a filter replacement processing operation matched with the abnormality type on the filter according to the filter application influence information, so that a new filter after replacement does not meet the water purification performance abnormality condition.

9. An intelligent filter replacement control device based on the water purification capacity of a filter cartridge, characterized in that, The device comprises: A memory storing executable program codes; A processor coupled with the memory; The processor invokes the executable program codes stored in the memory to execute the intelligent filter replacement control method based on a filter water purification capacity according to any one of claims 1-7.

10. A computer storage medium, characterized in that, The computer storage medium stores computer instructions, which are called to execute the intelligent filter core changing control method based on the filter core water purification capacity according to any one of claims 1-7.

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