Control method and device for self-cleaning of water tank

Abstract

The invention particularly provides a control method and device for self-cleaning of a water tank. The method comprises the steps of monitoring water quality data and cleaning data of each water tank in real time, selectively obtaining environment data of the water tanks according to the water quality data and the cleaning data of each water tank, and substituting the water quality data, the cleaning data and the environment data of the water tanks into a cleaning analysis and evaluation model when the environment data is obtained, obtaining a self-cleaning treatment scheme corresponding to the water tank, executing the self-cleaning treatment scheme on the water tank, obtaining cleaning water quality data of the water tank, and substituting the cleaning water quality data into the cleaning analysis and evaluation model again to obtain a self-cleaning evaluation result of the water tank. And feeding back the self-cleaning treatment scheme and the self-cleaning evaluation result to a user terminal corresponding to the water tank, and selectively cutting off water supply of the water tank based on the self-cleaning evaluation result of the water tank. And through real-time monitoring and timely self-cleaning treatment, water quality pollution is effectively prevented, and the safety of domestic water of a user is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of water tank self-cleaning control, and specifically provides a water tank self-cleaning control method and device. Background Art

[0002] The most common use of water tanks is as water storage containers for water supply in homes, businesses and industrial production. Water tanks are also widely used as water supply containers in the daily water supply of residents, and the water quality in the water tanks directly affects the health of residents' water use; however, the water tank cleaning technology in the prior art generally requires manual cleaning of the water tank, which prolongs the cleaning cycle of the water tank. It is very easy for the water tank to be contaminated and it takes a long time to clean the water tank, which poses a safety hazard to residents' water use.

[0003] Accordingly, the art needs a new control scheme for water tank self-cleaning to solve the above problems. Summary of the invention

[0004] In order to overcome the above-mentioned defects, the present invention is proposed to provide a control method and device for self-cleaning of water tanks to solve or at least partially solve the technical problem that the water tank cleaning technology in the prior art generally requires manual cleaning of the water tank, which prolongs the cleaning cycle of the water tank, and it is very easy for the water tank to be contaminated and it takes a long time to clean the water tank, which poses a safety hazard to residents' water use.

[0005] In a first aspect, the present invention provides a control method for self-cleaning of a water tank, the method being applied to a water tank self-cleaning control device, the device performing information exchange with different water tanks respectively, the method comprising the following steps: acquiring water quality data of each water tank and cleaning data corresponding to each water tank in real time, wherein the cleaning data comprises cleaning standard parameters and the latest historical cleaning information; selectively acquiring environmental data corresponding to each water tank based on the water quality data of each water tank and the cleaning data corresponding to each water tank, wherein the environmental data comprises current environmental data and historical environmental data corresponding to the water tank; if the environmental data corresponding to the water tank is acquired, the water quality data, cleaning data and environmental data corresponding to the water tank are substituted into a cleaning analysis and evaluation model, so that the spare water tank of the water tank is selectively updated according to the water quality data of the water tank. and obtain a self-cleaning treatment plan corresponding to the water tank according to the water quality data, cleaning data and environmental data of the water tank, wherein the self-cleaning treatment plan includes an estimated self-cleaning time, multiple self-cleaning execution operations and a cleaning treatment step corresponding to each self-cleaning execution operation; based on the self-cleaning treatment plan corresponding to the water tank, the self-cleaning treatment plan is executed on the water tank, and the cleaning water quality data of the water tank after self-cleaning is obtained; the cleaning water quality data of the water tank after self-cleaning is re-substituted into the cleaning analysis and evaluation model to obtain a self-cleaning evaluation result of the water tank, wherein the self-cleaning evaluation result includes a self-cleaning result and a self-cleaning evaluation score; the self-cleaning treatment plan and the self-cleaning evaluation result corresponding to the water tank are fed back to the user terminal corresponding to the water tank, and based on the self-cleaning evaluation result of the water tank, the water supply to the water tank is selectively cut off.

[0006] In a technical solution of the above-mentioned control method for water tank self-cleaning, the water quality data of the water tank includes data values ​​corresponding to multiple different data types, the cleaning standard parameters include standard parameter data ranges corresponding to multiple different data types, and the water quality data corresponds to the data type of the cleaning standard parameters one-to-one, and the selective acquisition of environmental data corresponding to each water tank based on the water quality data of each water tank and the cleaning data corresponding to each water tank includes: judging whether each water tank needs self-cleaning based on the water quality data of each water tank and the cleaning data corresponding to each water tank: if it is judged that the water tank needs self-cleaning, acquiring the environmental data corresponding to the water tank.

[0007] In a technical solution of the above-mentioned control method for water tank self-cleaning, the judgment of whether each water tank needs self-cleaning based on the water quality data of each water tank and the cleaning data corresponding to each water tank includes: if the data value of any data type of the water quality data of the water tank is not within the standard parameter data range of the data type in the cleaning standard parameter in the cleaning data corresponding to the water tank, it is judged that the water tank needs self-cleaning; or, based on the latest historical cleaning information in the cleaning data of the water tank, the uncleaned time of the water tank is determined; if the uncleaned time corresponding to the water tank exceeds a preset uncleaned time threshold corresponding to the water tank, it is judged that the water tank needs self-cleaning.

[0008] In a technical solution of the above-mentioned control method for water tank self-cleaning, the method further trains the cleaning analysis and evaluation model through the following steps: taking each water tank as a training sample, obtaining multiple groups of training sample sets corresponding to each training sample, wherein the training sample sets include water quality data and cleaning data corresponding to the training sample; obtaining water quality data of the spare water tank corresponding to each group of training sample sets; selectively updating the water in the spare water tank of the water tank based on the water quality data in each group of training sample sets and the water quality data of the spare water tank corresponding to each group of training sample sets; determining the self-cleaning estimated remaining time corresponding to each group of training sample sets based on each group of training sample sets and the environmental data corresponding to each group of training sample sets; generating multiple groups of self-cleaning sets corresponding to each group of training sample sets based on the self-cleaning estimated remaining time corresponding to each group of training sample sets, each group of training sample sets and the environmental data corresponding to each group of training sample sets The method comprises the steps of: selecting a self-cleaning combination parameter as the self-cleaning treatment scheme corresponding to the training sample set based on the multiple groups of self-cleaning combination parameters corresponding to the training sample set, so as to obtain the self-cleaning treatment scheme corresponding to each group of training sample sets; performing simulation based on the self-cleaning treatment scheme corresponding to each group of training sample sets, and obtaining simulation data of each group of training sample sets; determining the self-cleaning situation of the self-cleaning treatment scheme corresponding to each group of training sample sets based on the simulation data of each group of training sample sets and the cleaning standard parameters in the cleaning data in each group of training sample sets, wherein the self-cleaning situation includes the self-cleaning result and the self-cleaning evaluation score; and obtaining the training result of the cleaning analysis and evaluation model based on the self-cleaning situation corresponding to each group of training sample sets.

[0009] In a technical solution of the above-mentioned control method for water tank self-cleaning, a preset water tank history database is stored in the cleaning analysis and evaluation model, and the preset water tank history database stores the numbers of each water tank, the historical cleaning standard parameters corresponding to each water tank, multiple groups of historical cleaning information and the cleaning time points corresponding to each group of historical cleaning information. The obtaining of multiple groups of training sample sets corresponding to each training sample includes: based on the preset water tank history database, randomly selecting multiple groups of historical cleaning standard parameters corresponding to each training sample and multiple groups of historical cleaning information corresponding to each group of historical cleaning standard parameters to obtain multiple groups of cleaning data corresponding to each training sample, wherein each group of cleaning The data includes a group of historical cleaning standard parameters corresponding to the training sample and a group of historical cleaning information corresponding to the historical cleaning standard parameters; based on the multiple groups of cleaning data corresponding to each training sample, each cleaning data is selectively marked; based on the multiple groups of cleaning data corresponding to each training sample and the marking of each cleaning data, water quality data corresponding to each group of cleaning data is randomly set; based on the multiple groups of cleaning data corresponding to each training sample and the water quality data corresponding to each group of cleaning data, multiple groups of training sample sets corresponding to each training sample are obtained; and based on the marking of the cleaning data in each group of training sample sets, each group of training sample sets is selectively marked.

[0010] In a technical solution of the above-mentioned control method for water tank self-cleaning, the method of determining the estimated remaining self-cleaning time corresponding to each group of training sample sets based on each group of training sample sets and the environmental data corresponding to each group of training sample sets includes: determining the estimated contamination scores of the training samples corresponding to each group of training sample sets at various time lengths based on each group of training sample sets and the environmental data corresponding to each group of training sample sets; determining the estimated remaining self-cleaning time corresponding to each group of training sample sets based on the estimated contamination scores of the training samples corresponding to each group of training sample sets at various time lengths.

[0011] In a technical solution of the above-mentioned control method for water tank self-cleaning, the historical cleaning information includes multiple self-cleaning processing solutions, and the generation of multiple groups of self-cleaning combination parameters corresponding to each training sample set based on the estimated remaining self-cleaning time corresponding to each training sample set, each training sample set and the environmental data corresponding to each training sample set includes: determining multiple executable self-cleaning execution operations corresponding to each training sample based on the historical cleaning information corresponding to each training sample in a preset water tank history database; determining the processing coefficient matched by each executable self-cleaning execution operation corresponding to each training sample based on the multiple executable self-cleaning execution operations corresponding to each training sample; generating multiple groups of self-cleaning combination parameters corresponding to each training sample set based on the processing coefficient matched by each executable self-cleaning execution operation corresponding to each training sample and the multiple groups of training sample sets corresponding to each training sample; screening the multiple groups of self-cleaning combination parameters corresponding to each training sample set based on the estimated remaining self-cleaning time corresponding to each training sample set and the environmental data corresponding to each training sample set to obtain the screened multiple groups of self-cleaning combination parameters corresponding to each training sample set.

[0012] In a technical solution of the above-mentioned control method for water tank self-cleaning, the selecting a group of self-cleaning combination parameters as the self-cleaning treatment scheme corresponding to the training sample set based on the multiple groups of self-cleaning combination parameters corresponding to the training sample set includes: obtaining the cleaning score corresponding to each group of self-cleaning combination parameters in the training sample set based on the screened multiple groups of self-cleaning combination parameters corresponding to the training sample set; and selecting a group of self-cleaning combination parameters with the highest cleaning score as the self-cleaning treatment scheme corresponding to the training sample set based on the cleaning score corresponding to each group of self-cleaning combination parameters in the training sample set.

[0013] In a technical solution of the above-mentioned control method for water tank self-cleaning, the self-cleaning condition of the self-cleaning treatment scheme corresponding to each group of training sample sets is determined based on the simulation data of each group of training sample sets and the cleaning standard parameters in the cleaning data in each group of training sample sets, including: determining the self-cleaning evaluation score of the self-cleaning treatment scheme corresponding to each group of training sample sets based on the simulation data and the cleaning standard parameters corresponding to each group of training sample sets; determining the self-cleaning result of the self-cleaning treatment scheme corresponding to each group of training sample sets based on the self-cleaning evaluation score of the self-cleaning treatment scheme corresponding to each group of training sample sets.

[0014] In a second aspect, the present invention provides a water tank self-cleaning control device, the water tank self-cleaning control device includes a cleaning analysis and evaluation model and a control device, the water tank self-cleaning control device also includes acquisition devices respectively installed in different water tanks and self-cleaning devices respectively connected to different water tanks, the cleaning analysis and evaluation model stores a preset water tank history database, the acquisition device is used to obtain water quality data of the water tank, and the self-cleaning device is used to perform water quality self-cleaning on the water tank according to the self-cleaning treatment scheme corresponding to the water tank; the control device includes a processor and a memory, the memory is suitable for storing multiple program codes, the program code is suitable for being loaded and run by the processor to execute the control method for self-cleaning of the water tank described in any one of the technical schemes of the above-mentioned control method for self-cleaning of the water tank; the control device also exchanges information with multiple user terminals and between different water tanks, and is used to feed back the self-cleaning treatment scheme and self-cleaning evaluation results of the water tank to the user terminal.

[0015] The above one or more technical solutions of the present invention have at least one or more of the following beneficial effects: by obtaining the water quality data and cleaning data of the water tank in real time, the environmental data of the water tank is selectively obtained, and when obtaining the environmental data, the water quality data, cleaning data and environmental data of the water tank are substituted into the cleaning analysis and evaluation model, so as to determine the optimal self-cleaning treatment scheme according to the water quality, cleaning and environmental data, and the self-cleaning treatment scheme includes an estimated time, an execution operation and an execution step, so as to realize online autonomous cleaning, greatly reducing the cost of manual intervention, and then by re-substituting the cleaning water quality data after self-cleaning into the cleaning analysis and evaluation model, the cleaning effect is evaluated, and the cleaning effect and the self-cleaning treatment scheme are fed back to the user terminal corresponding to the water tank, and the water supply of the water tank is selectively cut off, so as to realize the scheduling of automatic water supply according to the cleaning result, realize the cleaning control combining intelligence and humanization, avoid the technical problem that the water tank cleaning technology in the prior art generally needs manual cleaning of the water tank, prolongs the cleaning cycle of the water tank, and easily causes the water tank to be contaminated and it takes a long time to clean the water tank, which makes the water use of residents have safety hazards.

[0016] In the technical solution for implementing the present invention, whether self-cleaning is required is determined based on the water quality data and cleaning standards of the water tank, and for the water tank that needs self-cleaning, the environmental data corresponding to the water tank is obtained to facilitate determining the optimal cleaning time; and for the water tank that does not need self-cleaning, the water quality data is selectively fed back to the user based on the cleaning time in the cleaning data of the water tank, so that the user can timely understand the water quality status of the water tank they are using and avoid drinking contaminated water sources, which not only ensures the normal operation of the water tank, but also ensures the drinking water safety of the user.

[0017] In the technical solution for implementing the present invention, in model training, by obtaining multiple groups of training sample sets for each training sample and obtaining the water quality data of the standby water tank corresponding to each training sample set, the water in the standby water tank of the water tank is selectively updated, so as to ensure that the water in the standby water tank meets the user's water use standards, thereby ensuring the user's water demand during the self-cleaning process, and determining the corresponding self-cleaning estimated remaining time based on the training sample set and its corresponding environmental data, and then generating multiple groups of self-cleaning combination parameters based on the self-cleaning estimated remaining time, the training sample set and its environmental data, and screening them to select a group of self-cleaning combination parameters as the self-cleaning treatment scheme of the training sample set, thereby ensuring the matching degree between the self-cleaning treatment scheme and the training sample set, and then simulating each group of self-cleaning treatment schemes to obtain corresponding simulation data, and determining the self-cleaning situation of each self-cleaning treatment scheme based on the simulation data, thereby obtaining the training result of this cleaning analysis and evaluation model, realizing automatic verification of the training of the cleaning analysis and evaluation model, and thereby improving the intelligence of the cleaning analysis and evaluation model.

[0018] In the technical solution of the present invention, a plurality of groups of historical cleaning standard parameters and their corresponding historical cleaning information are randomly selected through a preset water tank history database to obtain a plurality of groups of cleaning data for each training sample, and each cleaning data is selectively marked, thereby realizing training for water tanks whose water quality meets the requirements but has reached the cleaning time. According to the marking situation, the water quality data corresponding to each group of cleaning data is randomly set to obtain a plurality of training sample sets corresponding to each training sample, and according to the marking situation of the cleaning data in the training sample set, the training sample set is selectively marked to facilitate the training of water quality data and cleaning data of water tanks in different situations, thereby improving the training accuracy of the cleaning analysis and evaluation model. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The disclosure of the present invention will become more easily understood with reference to the accompanying drawings. It is easy for those skilled in the art to understand that these drawings are only for illustrative purposes and are not intended to limit the scope of protection of the present invention. In addition, similar numbers in the figures are used to represent similar components, among which: Figure 1 is a flow chart of main steps of a control method for water tank self-cleaning according to an embodiment of the present invention; Figure 2 is a flowchart of the main steps of training a cleaning analysis and evaluation model according to an embodiment of the present invention; Figure 3 It is a schematic diagram of the main structure block diagram of a water tank self-cleaning control device according to an embodiment of the present invention.

[0020] List of reference numerals: 300: water tank self-cleaning control device; 301: control device; 3011: processor; 3012: memory; 3013: program code; 302: cleaning analysis and evaluation model; 3021: water tank history database; 303: acquisition device; 304: self-cleaning device. DETAILED DESCRIPTION

[0021] Some embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0022] In the description of the present invention, "module" and "processor" may include hardware, software or a combination of the two. A module may include hardware circuits, various suitable sensors, communication ports, and memories, and may also include software parts, such as program codes, or a combination of software and hardware. The processor may be a central processing unit, a microprocessor, an image processor, a digital signal processor, or any other suitable processor. The processor has data and / or signal processing functions. The processor may be implemented in software, hardware, or a combination of the two. Non-temporary computer-readable storage media include any suitable medium that can store program codes, such as a magnetic disk, a hard disk, an optical disk, a flash memory, a read-only memory, a random access memory, and the like. The term "A and / or B" means all possible combinations of A and B, such as only A, only B, or A and B. The term "at least one A or B" or "at least one of A and B" has a similar meaning to "A and / or B", and may include only A, only B, or A and B. The singular terms "one" and "the" may also include plural forms.

[0023] See attached Figure 1 , Figure 1 FIG. 1 is a flow chart showing the main steps of a control method for water tank self-cleaning according to an embodiment of the present invention. Figure 1 As shown, the control method for water tank self-cleaning in an embodiment of the present invention is applied to a water tank self-cleaning control device, and the device exchanges information with different water tanks respectively. The method mainly includes the following steps S101 to S106.

[0024] Step S101: Acquire water quality data of each water tank and cleaning data corresponding to each water tank in real time, wherein the cleaning data includes cleaning standard parameters and the latest historical cleaning information; Step S102: Based on the water quality data of each water tank and the cleaning data corresponding to each water tank, selectively acquire environmental data corresponding to each water tank, wherein the environmental data includes current environmental data and historical environmental data corresponding to the water tank; specifically, in some embodiments, the water quality data of the water tank includes data values ​​corresponding to a plurality of different data types, the cleaning standard parameters include standard parameter data ranges corresponding to a plurality of different data types, and, The water quality data corresponds to the data type of the cleaning standard parameter one by one. The selective acquisition of the environmental data corresponding to each water tank based on the water quality data of each water tank and the cleaning data corresponding to each water tank includes: judging whether each water tank needs self-cleaning based on the water quality data of each water tank and the cleaning data corresponding to each water tank: if it is judged that the water tank needs self-cleaning, obtaining the environmental data corresponding to the water tank; otherwise, not obtaining the environmental data corresponding to the water tank, and based on the uncleaned time in the cleaning data corresponding to the water tank, feeding back the water quality data of the water tank to the user terminal, so that water users can promptly know the water quality of the water tank they use.

[0025] In the above embodiment, whether self-cleaning is required is determined based on the water quality data and cleaning standards of the water tank, and for the water tank that needs self-cleaning, the corresponding environmental data of the water tank is obtained to facilitate determining the optimal cleaning time; and for the water tank that does not need self-cleaning, the water quality data is fed back to the user based on the cleaning time in the cleaning data of the water tank, so that the user can timely understand the water quality status of the water tank they are using and avoid drinking contaminated water sources, which not only ensures the normal operation of the water tank, but also ensures the drinking water safety of the user.

[0026] Specifically, in some embodiments, judging whether each water tank needs self-cleaning based on the water quality data of each water tank and the cleaning data corresponding to each water tank includes: if the data value of any data type of the water quality data of the water tank is not within the standard parameter data range of the data type in the cleaning standard parameter in the cleaning data corresponding to the water tank, then judging that the water tank needs self-cleaning; or, determining the cleaning time of the water tank based on the latest historical cleaning information in the cleaning data of the water tank; if the cleaning time corresponding to the water tank exceeds a preset cleaning time threshold corresponding to the water tank, then judging that the water tank needs self-cleaning.

[0027] Specifically, in some embodiments, when the judgment result of whether the water tank is cleaned based on the water quality data of the water tank is inconsistent with the judgment result of whether the water tank is cleaned based on the cleaning data of the water tank, it is determined that the water tank needs self-cleaning.

[0028] Step S103: If the environmental data corresponding to the water tank is obtained, the water quality data, cleaning data and environmental data corresponding to the water tank are substituted into the cleaning analysis and evaluation model, so that the water in the standby water tank of the water tank is selectively updated according to the water quality data of the water tank, and the self-cleaning treatment plan corresponding to the water tank is obtained according to the water quality data, cleaning data and environmental data of the water tank, wherein the self-cleaning treatment plan includes a self-cleaning estimated time, a plurality of self-cleaning execution operations and a cleaning treatment step corresponding to each self-cleaning execution operation; Figure 2 As shown, further, in some embodiments, the method also trains the cleaning analysis and evaluation model through the following steps: taking each water tank as a training sample, obtaining multiple groups of training sample sets corresponding to each training sample, wherein the training sample sets include water quality data and cleaning data corresponding to the training sample; obtaining water quality data of the spare water tank corresponding to each group of training sample sets; selectively updating the water in the spare water tank of the water tank based on the water quality data in each group of training sample sets and the water quality data of the spare water tank corresponding to each group of training sample sets; determining the self-cleaning estimated remaining time corresponding to each group of training sample sets based on each group of training sample sets and the environmental data corresponding to each group of training sample sets; generating multiple groups of self-cleaning combination parameters corresponding to each group of training sample sets based on the self-cleaning estimated remaining time corresponding to each group of training sample sets, each group of training sample sets and the environmental data corresponding to each group of training sample sets, The self-cleaning combination parameters include an estimated self-cleaning time point, an estimated self-cleaning time, multiple self-cleaning execution operations, and a cleaning processing step corresponding to each self-cleaning execution operation; based on multiple groups of self-cleaning combination parameters corresponding to the training sample set, a group of self-cleaning combination parameters is selected as the self-cleaning processing scheme corresponding to the training sample set to obtain the self-cleaning processing scheme corresponding to each group of training sample sets; based on the self-cleaning processing scheme corresponding to each group of training sample sets, simulation is performed to obtain simulation data for each group of training sample sets; based on the simulation data of each group of training sample sets and the cleaning standard parameters in the cleaning data in each group of training sample sets, the self-cleaning situation of the self-cleaning processing scheme corresponding to each group of training sample sets is determined, wherein the self-cleaning situation includes a self-cleaning result and a self-cleaning evaluation score; based on the self-cleaning situation corresponding to each group of training sample sets, the training result of the cleaning analysis and evaluation model is obtained.

[0029] Specifically, in some embodiments, the cleaning analysis and evaluation model stores a preset water tank history database, the preset water tank history database stores the serial number of each water tank, the historical cleaning standard parameters corresponding to each water tank, multiple groups of historical cleaning information and the cleaning time points corresponding to each group of historical cleaning information, and the obtaining of multiple groups of training sample sets corresponding to each training sample includes: based on the preset water tank history database, randomly selecting multiple groups of historical cleaning standard parameters corresponding to each training sample and multiple groups of historical cleaning information corresponding to each group of historical cleaning standard parameters to obtain multiple groups of cleaning data corresponding to each training sample, wherein each group of cleaning data includes the A set of historical cleaning standard parameters corresponding to the training sample and a set of historical cleaning information corresponding to the historical cleaning standard parameters; based on the multiple sets of cleaning data corresponding to each training sample, selectively marking each cleaning data; based on the multiple sets of cleaning data corresponding to each training sample and the marking of each cleaning data, randomly setting the water quality data corresponding to each set of cleaning data; based on the multiple sets of cleaning data corresponding to each training sample and the water quality data corresponding to each set of cleaning data, to obtain multiple sets of training sample sets corresponding to each training sample; and based on the marking of the cleaning data in each set of training sample sets, selectively marking each set of training sample sets.

[0030] Specifically, in some embodiments, obtaining the water quality data of the standby water tank corresponding to each group of training sample sets includes: based on the marking status of each group of training sample sets and the water quality data of each group of training sample sets, setting the water quality data of the standby water tank corresponding to each group of training sample sets to obtain the water quality data of the standby water tank corresponding to each group of training sample sets.

[0031] Specifically, in some embodiments, the selectively marking each cleaning data based on the multiple groups of cleaning data corresponding to each training sample includes: if the data value of any data type of the water quality data corresponding to the cleaning data is within the standard parameter data range of the data type in the historical cleaning standard parameters in the cleaning data, the cleaning data is marked; otherwise, the cleaning data is not marked.

[0032] In the above embodiment, through a preset water tank history database, multiple groups of historical cleaning standard parameters and their corresponding historical cleaning information are randomly selected to obtain multiple groups of cleaning data for each training sample, and each cleaning data is selectively marked to achieve training for water tanks where the water quality meets the requirements but has reached the cleaning time. According to the marking situation, the water quality data corresponding to each group of cleaning data is randomly set to obtain multiple groups of training sample sets corresponding to each training sample, and according to the marking situation of the cleaning data in the training sample set, the training sample set is selectively marked to facilitate the training of water quality data and cleaning data of water tanks in different situations, thereby improving the training accuracy of the cleaning analysis and evaluation model.

[0033] Specifically, in some embodiments, the selectively updating the water in the spare water tank of the water tank based on the water quality data in each group of training sample sets and the water quality data of the spare water tank corresponding to each group of training sample sets includes: determining the water quality assessment score corresponding to each group of training sample sets and the water quality assessment score of each spare water tank based on the water quality data in each group of training sample sets and the water quality assessment score of each spare water tank; if the water quality assessment score corresponding to the training sample set exceeds the water quality assessment score of the spare water tank corresponding to the training sample set, updating the water in the spare water tank of the water tank; otherwise, maintaining the water in the spare water tank of the water tank unchanged.

[0034] Specifically, in some embodiments, the water quality evaluation score corresponding to each training sample set and the water quality evaluation score of each backup water tank are determined based on the water quality data in each training sample set and the water quality data of the backup water tank corresponding to each training sample set, including: if the data value of any data type of the water quality data in the training sample set is better than the data value of the data type of the water quality data of the backup water tank corresponding to the training sample set, the score of the data type of the backup water tank is recorded as "1", and the score of the data type of the training sample set is recorded as "0"; if the data value of any data type of the water quality data of the backup water tank corresponding to the training sample set is better than the data value of the data type of the water quality data in the training sample set, the score of the data type of the backup water tank is recorded as "0", and the score of the data type of the training sample set is recorded as "1"; specifically, the water quality evaluation score is obtained by the following formula: water quality evaluation score = score of each data type * sum of weight coefficients corresponding to the data type.

[0035] Specifically, in some embodiments, determining the estimated remaining self-cleaning time corresponding to each group of training sample sets based on each group of training sample sets and the environmental data corresponding to each group of training sample sets includes: determining the estimated contamination scores of the training samples corresponding to each group of training sample sets at various time lengths based on each group of training sample sets and the environmental data corresponding to each group of training sample sets; determining the estimated remaining self-cleaning time corresponding to each group of training sample sets based on the estimated contamination scores of the training samples corresponding to each group of training sample sets at various time lengths.

[0036] Specifically, in some embodiments, the time interval between two adjacent time periods of each time period can be 10 minutes or 15 minutes. The setting of the time interval here is only an exemplary description. In actual testing, those skilled in the art can set it according to actual needs, which will not be repeated here.

[0037] Specifically, in some embodiments, the current environmental data and the historical environmental data both include data values ​​of different environmental types, and the cleaning analysis and evaluation model also stores a preset pollution parameter reference library. The method of determining the estimated contamination scores of the training samples corresponding to each training sample set at each time period based on each group of training sample sets and the environmental data corresponding to each training sample set includes: determining the current contamination scores of the training samples corresponding to each training sample set based on the current environmental data in each training sample set and the environmental data corresponding to each training sample set; determining the estimated contamination scores of the training samples corresponding to each training sample set at each time period based on the current contamination scores of the training samples corresponding to each training sample set and the historical environmental data in the environmental data corresponding to each training sample set.

[0038] Specifically, the preset pollution parameter reference library includes different pollution types, pollution levels corresponding to each pollution type, weight values ​​corresponding to each pollution level, environment types corresponding to each pollution type, and data ranges corresponding to each pollution level of each pollution type.

[0039] Specifically, in some embodiments, each of the environment types corresponds one-to-one to the data type of each water quality data, and the current pollution score of the training samples corresponding to each group of training sample sets is obtained by the following formula: the current pollution score of the training samples corresponding to the training sample set = the sum of [(data value of any data type of the water quality data + data value of the environment type corresponding to the data type in the current environment data) * weight value of the pollution level corresponding to the data value of the environment type].

[0040] Specifically, the method of determining the estimated pollution scores of the training samples corresponding to each group of training sample sets at each time period based on the current pollution scores of the training samples corresponding to each group of training sample sets and the historical environmental data in the environmental data corresponding to each group of training sample sets includes: estimating the historical environmental data and the current environmental data in the environmental data corresponding to each group of training sample sets to obtain the estimated environmental data of each group of training sample sets at each time period; determining the estimated pollution scores of each group of training sample sets at each time period based on the estimated environmental data of each group of training sample sets at each time period and each group of training sample sets.

[0041] Specifically, the method for obtaining the estimated contamination score of each training sample set at each time length is the same as the method for obtaining the current contamination score of the training samples corresponding to each training sample set, which will not be repeated here.

[0042] Specifically, in some embodiments, the determining of the self-cleaning estimated remaining time corresponding to each group of training sample sets based on the estimated contamination scores of the training samples corresponding to each group of training sample sets at various time lengths includes: comparing the estimated contamination scores of the training samples corresponding to each group of training sample sets at various time lengths with a preset estimated contamination score threshold: if the estimated contamination scores of the training samples corresponding to the training sample set at any time length exceed the preset estimated contamination score threshold, then the time length is used as the self-cleaning estimated remaining time corresponding to the training sample set; if the estimated contamination scores of the training samples corresponding to the training sample set at multiple time lengths exceed the preset estimated contamination score threshold, then the shortest time length is taken as the self-cleaning estimated remaining time corresponding to the training sample set.

[0043] Specifically, in some embodiments, the historical cleaning information includes multiple self-cleaning processing schemes, and the generating of multiple sets of self-cleaning combination parameters corresponding to each training sample set based on the self-cleaning estimated remaining time corresponding to each training sample set, each training sample set, and the environmental data corresponding to each training sample set includes: determining multiple executable self-cleaning execution operations corresponding to each training sample based on the historical cleaning information corresponding to each training sample in a preset water tank history database; determining the processing coefficient matched by each executable self-cleaning execution operation corresponding to each training sample based on the multiple executable self-cleaning execution operations corresponding to each training sample; generating multiple sets of self-cleaning combination parameters corresponding to each training sample set based on the processing coefficient matched by each executable self-cleaning execution operation corresponding to each training sample and the multiple sets of training sample sets corresponding to each training sample; screening the multiple sets of self-cleaning combination parameters corresponding to each training sample set based on the self-cleaning estimated remaining time corresponding to each training sample set and the environmental data corresponding to each training sample set to obtain the screened multiple sets of self-cleaning combination parameters corresponding to each training sample set.

[0044] Specifically, in some embodiments, the selecting a group of self-cleaning combination parameters as the self-cleaning treatment scheme corresponding to the training sample set based on the multiple groups of self-cleaning combination parameters corresponding to the training sample set includes: obtaining the cleaning score corresponding to each group of self-cleaning combination parameters in the training sample set based on the multiple groups of self-cleaning combination parameters screened corresponding to the training sample set; and selecting a group of self-cleaning combination parameters with the highest cleaning score as the self-cleaning treatment scheme corresponding to the training sample set based on the cleaning score corresponding to each group of self-cleaning combination parameters in the training sample set.

[0045] Specifically, in some embodiments, obtaining the cleaning score corresponding to each group of self-cleaning combination parameters in the training sample set based on the screened multiple groups of self-cleaning combination parameters corresponding to the training sample set includes: performing simulation based on the screened multiple groups of self-cleaning combination parameters corresponding to the training sample set to obtain simulation data corresponding to each group of self-cleaning combination parameters, wherein the simulation data includes simulation numerical values ​​of different data types; obtaining the cleaning score corresponding to each screened group of self-cleaning combination parameters corresponding to the training sample set based on the simulation data corresponding to each group of self-cleaning combination parameters.

[0046] Specifically, the cleaning score corresponding to each set of self-cleaning combination parameters after screening corresponding to the training sample set is obtained by the following formula: the cleaning score corresponding to the self-cleaning combination parameter = the sum of [(the data value of the data type of the water quality data corresponding to the training sample set - the simulated numerical value of each data type in the simulated data corresponding to the self-cleaning combination parameter) * the treatment coefficient value corresponding to the data type * the weight corresponding to the data type].

[0047] In the above embodiment, the multiple executable self-cleaning execution operations corresponding to the training samples are determined through the historical cleaning information corresponding to the training samples to ensure that the training samples can execute the corresponding self-cleaning combination parameters, and then the processing coefficient of each self-cleaning execution operation corresponding to each training sample is determined, and then the training sample set is combined to generate multiple groups of self-cleaning combination parameters corresponding to each group of training sample sets, and then the multiple groups of self-cleaning combination parameters are screened according to the estimated remaining time of self-cleaning of the training sample set and its environmental data, and then the cleaning scores corresponding to the screened multiple groups of self-cleaning combination parameters are determined, and a group of self-cleaning combination parameters with the highest cleaning score is selected as the self-cleaning processing scheme for the training sample set, thereby realizing the automatic generation and screening of multiple groups of self-cleaning combination parameters to obtain the self-cleaning processing scheme with the highest matching degree with the training sample set.

[0048] Specifically, in some embodiments, the simulation technology used to simulate the self-cleaning processing scheme corresponding to the training sample set can be a trained network model in the prior art, or it can be a simulation technology in the prior art. The choice of simulation technology here is only an exemplary explanation. In actual testing, technical personnel in this field can make a choice according to actual needs, which will not be repeated here.

[0049] Specifically, in some embodiments, the self-cleaning condition of the self-cleaning treatment scheme corresponding to each group of training sample sets based on the simulation data of each group of training sample sets and the cleaning standard parameters in the cleaning data in each group of training sample sets includes: determining the self-cleaning evaluation score of the self-cleaning treatment scheme corresponding to each group of training sample sets based on the simulation data and the cleaning standard parameters corresponding to each group of training sample sets; determining the self-cleaning result of the self-cleaning treatment scheme corresponding to each group of training sample sets based on the self-cleaning evaluation score of the self-cleaning treatment scheme corresponding to each group of training sample sets.

[0050] Specifically, the simulation data includes simulation values ​​of different data types. If the simulation value corresponding to the data type in the simulation data corresponding to the training sample set is within the standard parameter data range corresponding to the data type in the cleaning standard parameter in the cleaning data in the training sample set, the self-cleaning evaluation score corresponding to the data type in the self-cleaning evaluation score corresponding to the training sample set is recorded as "1"; otherwise, the self-cleaning evaluation score corresponding to the data type in the self-cleaning evaluation score corresponding to the training sample set is recorded as "0"; based on the self-cleaning evaluation scores of all data types in the self-cleaning evaluation score corresponding to the training sample set, the self-cleaning evaluation score of the self-cleaning processing scheme corresponding to the training sample set is obtained.

[0051] Specifically, the self-cleaning evaluation score of the self-cleaning processing scheme corresponding to each group of training sample sets is obtained by the following formula: the self-cleaning evaluation score of the self-cleaning processing scheme corresponding to the training sample set = the sum of (the processing evaluation score of each data type in the self-cleaning evaluation score corresponding to the training sample set * the weight corresponding to the data type), wherein the sum of the weights corresponding to all data types is 1.

[0052] Specifically, in some embodiments, the self-cleaning result of the self-cleaning treatment scheme corresponding to each group of training sample sets is determined based on the self-cleaning evaluation score of the self-cleaning treatment scheme corresponding to each group of training sample sets, including: if the self-cleaning evaluation score of the self-cleaning treatment scheme corresponding to the training sample set exceeds a preset self-cleaning treatment threshold, then the self-cleaning result of the self-cleaning treatment scheme corresponding to the training sample set is judged to be a successful processing; otherwise, then the self-cleaning result of the self-cleaning treatment scheme corresponding to the training sample set is judged to be a failed processing.

[0053] Specifically, the preset self-cleaning processing threshold may be 0.95 or 0.9. The setting of the preset self-cleaning processing threshold here is only an exemplary description. In actual testing, those skilled in the art may set it according to actual needs, which will not be elaborated here.

[0054] Specifically, in some embodiments, based on the self-cleaning situation corresponding to each group of training sample sets, obtaining the training result of the cleaning analysis and evaluation model includes: determining the training success rate of all training sample sets based on the self-cleaning result in the self-cleaning situation corresponding to each group of training sample sets; if the training success rate of all training sample sets is higher than a preset training success rate threshold, then determining that the training result of the cleaning analysis and evaluation model is a training success; otherwise, determining that the training result of the cleaning analysis and evaluation model is a training failure, then re-executing the training of the cleaning analysis and evaluation model.

[0055] Specifically, the preset training success rate threshold may be 95% or 98%. The setting of the preset training success rate threshold here is only an exemplary description. In actual testing, those skilled in the art may set it according to actual needs, which will not be elaborated here.

[0056] Step S104: Based on the self-cleaning treatment scheme corresponding to the water tank, execute the self-cleaning treatment scheme on the water tank, and obtain the cleaning water quality data of the water tank after self-cleaning; Step S105: Re-substitute the cleaning water quality data of the water tank after self-cleaning into the cleaning analysis and evaluation model to obtain the self-cleaning evaluation result of the water tank, wherein the self-cleaning evaluation result includes the self-cleaning result and the self-cleaning evaluation score; Step S106: Feedback the self-cleaning treatment scheme and the self-cleaning evaluation result corresponding to the water tank to the user terminal corresponding to the water tank, and based on the self-cleaning evaluation result of the water tank, selectively cut off the water supply to the water tank.

[0057] Specifically, in some embodiments, selectively cutting off the water supply to the water tank based on the self-cleaning evaluation result of the water tank includes: if the self-cleaning result in the self-cleaning evaluation result of the water tank is a processing failure, then immediately cutting off the water supply to the water tank; otherwise, maintaining the current water supply status of the water tank, and selectively cutting off the water supply to the water tank based on the feedback result of the user corresponding to the water tank.

[0058] Specifically, the selective execution of cutting off the water supply to the water tank based on the feedback results of the users corresponding to the water tank includes: obtaining the feedback results of all users corresponding to the water tank, and determining the decision result of whether the water supply corresponding to the water tank is cut off based on cluster analysis; if the decision result of whether the water supply corresponding to the water tank is cut off is to cut off the water supply, cutting off the water supply to the water tank; otherwise, maintaining the current water supply status of the water tank.

[0059] Specifically, in some embodiments, while the water supply of the water tank is cut off, the water supply switch of the standby water tank corresponding to the water tank is turned on to ensure the user's water demand and improve the user's usage experience.

[0060] Based on the above steps S101 to S106, the environmental data of the water tank is selectively obtained by implementing the acquired water quality data and cleaning data of the water tank, and when obtaining the environmental data, the water quality data, cleaning data and environmental data of the water tank are substituted into the cleaning analysis and evaluation model to determine the optimal self-cleaning treatment plan based on the water quality, cleaning and environmental data. In addition, the self-cleaning treatment plan includes an estimated time, an execution operation and an execution step, so as to realize online autonomous cleaning, which greatly reduces the cost of manual intervention. Then, by re-substituting the cleaning water quality data after self-cleaning into the cleaning analysis and evaluation model, the cleaning effect is evaluated, and the cleaning effect and the self-cleaning treatment plan are fed back to the user terminal corresponding to the water tank, and the water supply of the water tank is selectively cut off, so as to realize automatic water supply scheduling according to the cleaning results, and realize cleaning control combining intelligence and humanity, so as to avoid the technical problem that the water tank cleaning technology in the prior art generally requires manual cleaning of the water tank, which prolongs the cleaning cycle of the water tank, and it is very easy for the water tank to be contaminated and it takes a long time to clean the water tank, which makes the water use of residents have safety hazards.

[0061] It should be pointed out that although the various steps in the above embodiments are described in a specific order, those skilled in the art can understand that in order to achieve the effects of the present invention, different steps do not have to be performed in such an order. They can be performed simultaneously (in parallel) or in other orders. These changes are within the scope of protection of the present invention.

[0062] Furthermore, the present invention also provides a water tank self-cleaning control device.

[0063] See attached Figure 3 , Figure 3 FIG. 1 is a main structural block diagram of a water tank self-cleaning control device according to an embodiment of the present invention. Figure 3As shown, the water tank self-cleaning control device 300 in the embodiment of the present invention mainly includes a cleaning analysis and evaluation model 302 and a control device 301, the water tank self-cleaning control device also includes a collection device 303 respectively installed in different water tanks and a self-cleaning device 304 respectively connected to different water tanks, the cleaning analysis and evaluation model 302 stores a preset water tank history database 3021, the collection device 303 is used to obtain water quality data of the water tank, and the self-cleaning device 304 is used to perform water quality self-cleaning on the water tank according to the self-cleaning treatment scheme corresponding to the water tank; the control device 301 includes a processor 3011 and a memory 3012, the memory 3012 can be configured to store a program code 3013 for executing the control method for water tank self-cleaning of the above method embodiment, the processor 3011 can be configured to execute the program code 3013 in the memory 3012, the program code 3013 includes but is not limited to the program code 3013 for executing the control method for water tank self-cleaning of the above method embodiment. For ease of explanation, only the parts related to the embodiment of the present invention are shown. For specific technical details not disclosed, please refer to the method part of the embodiment of the present invention. The control device 301 can be a control device 301 device formed by various electronic devices; the control device 301 also interacts with multiple user terminals and different water tanks to feedback the self-cleaning treatment plan and self-cleaning evaluation results of the water tank to the user terminal.

[0064] Specifically, in some embodiments, the preset water tank history database 3021 stores the serial number of each water tank, the historical cleaning standard parameters corresponding to each water tank, multiple groups of historical cleaning information and the cleaning time point corresponding to each group of historical cleaning information.

[0065] Specifically, in some embodiments, the user terminal may be a mobile phone, a tablet computer, or a notebook, a desktop computer, etc. This is not restrictive, and the technicians may set it according to actual usage requirements.

[0066] Specifically, in some embodiments, the control device 301 also exchanges information with multiple user terminals to feed back the self-cleaning treatment plan and self-cleaning evaluation results of the water tank to the user terminals. The specific communication connection method for the information exchange between the user terminal and the control device 301 is not restrictive, and the technician can set it by himself according to the actual use requirements, as long as the communication connection can be achieved, for example, it can be connected through wifi or Bluetooth, etc. In addition, as a preferred setting method, when the user terminal is a mobile phone or a tablet computer, the technician can set the app to facilitate user operation. Of course, it can also be operated directly through the web page. This is not restrictive, and the technician can set it by himself according to the actual use requirements.

[0067] In one implementation, the description of the specific implementation functions may refer to steps S101 to S106.

[0068] The water tank self-cleaning control device 300 is used to execute Figure 1 The control method embodiment for water tank self-cleaning shown in the figure has similar technical principles, technical problems solved and technical effects produced. Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working process and related instructions of the water tank self-cleaning control device 300 can refer to the contents described in the control method embodiment for water tank self-cleaning, and will not be repeated here.

[0069] It is understood by those skilled in the art that the present invention implements all or part of the processes in the method of the above embodiment, and can also be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable storage medium may include: any entity or device, medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory, random access memory, electric carrier signal, telecommunication signal and software distribution medium that can carry the computer program code. It should be noted that the content contained in the computer-readable storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable storage media do not include electric carrier signals and telecommunication signals.

[0070] Furthermore, the present invention also provides a computer-readable storage medium. In a computer-readable storage medium embodiment according to the present invention, the computer-readable storage medium can be configured to store a program code 3013 for executing the control method for self-cleaning of a water tank in the above method embodiment, and the program code 3013 can be loaded and run by the processor 3011 to implement the above control method for self-cleaning of a water tank. For ease of explanation, only the parts related to the embodiment of the present invention are shown. For specific technical details not disclosed, please refer to the method part of the embodiment of the present invention. The computer-readable storage medium can be a memory 3012 device formed by various electronic devices. Optionally, the computer-readable storage medium in the embodiment of the present invention is a non-temporary computer-readable storage medium.

[0071] Further, it should be understood that since the setting of each module is only for illustrating the functional units of the device of the present invention, the physical devices corresponding to these modules may be the processor 3011 itself, or a part of the software, a part of the hardware, or a part of the combination of software and hardware in the processor 3011. Therefore, the number of each module in the figure is only schematic.

[0072] Those skilled in the art will appreciate that the modules in the device can be adaptively split or merged. Such splitting or merging of specific modules will not cause the technical solution to deviate from the principle of the present invention, and therefore, the technical solutions after splitting or merging will fall within the protection scope of the present invention.

[0073] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. A control method for water tank self-cleaning, characterized in that: The method is applied to a water tank self-cleaning control device, and the device exchanges information with different water tanks respectively. The method includes the following steps: acquiring water quality data of each water tank and cleaning data corresponding to each water tank in real time, wherein the cleaning data includes cleaning standard parameters and the latest historical cleaning information; selectively acquiring environmental data corresponding to each water tank based on the water quality data of each water tank and cleaning data corresponding to each water tank, wherein the environmental data includes current environmental data and historical environmental data corresponding to the water tank; if the environmental data corresponding to the water tank is acquired, the water quality data, cleaning data and environmental data corresponding to the water tank are substituted into a cleaning analysis and evaluation model, so that the water in the standby water tank of the water tank is selectively updated according to the water quality data of the water tank, and the water in the standby water tank of the water tank is updated according to the water quality data of the water tank. The method comprises the following steps: obtaining a self-cleaning treatment scheme corresponding to the water tank according to the self-cleaning treatment scheme corresponding to the water tank, wherein the self-cleaning treatment scheme includes an estimated self-cleaning time, multiple self-cleaning execution operations and a cleaning treatment step corresponding to each self-cleaning execution operation; executing the self-cleaning treatment scheme on the water tank based on the self-cleaning treatment scheme corresponding to the water tank, and obtaining the cleaning water quality data of the water tank after self-cleaning; re-substituting the cleaning water quality data of the water tank after self-cleaning into the cleaning analysis and evaluation model to obtain a self-cleaning evaluation result of the water tank, wherein the self-cleaning evaluation result includes a self-cleaning result and a self-cleaning evaluation score; feeding back the self-cleaning treatment scheme and the self-cleaning evaluation result corresponding to the water tank to the user terminal corresponding to the water tank, and selectively cutting off the water supply to the water tank based on the self-cleaning evaluation result of the water tank.

2. The control method for water tank self-cleaning according to claim 1, characterized in that: The water quality data of the water tank includes data values ​​corresponding to multiple different data types, the cleaning standard parameters include standard parameter data ranges corresponding to multiple different data types, and the water quality data corresponds to the data type of the cleaning standard parameters one-to-one. The selective acquisition of environmental data corresponding to each water tank based on the water quality data of each water tank and the cleaning data corresponding to each water tank includes: judging whether each water tank needs self-cleaning based on the water quality data of each water tank and the cleaning data corresponding to each water tank: if it is judged that the water tank needs self-cleaning, acquiring the environmental data corresponding to the water tank.

3. The control method for water tank self-cleaning according to claim 2, characterized in that: The method of judging whether each water tank needs self-cleaning based on the water quality data of each water tank and the cleaning data corresponding to each water tank includes: if the data value of any data type of the water quality data of the water tank is not within the standard parameter data range of the data type in the cleaning standard parameter in the cleaning data corresponding to the water tank, then judging that the water tank needs self-cleaning; or, determining the cleaning time of the water tank based on the latest historical cleaning information in the cleaning data of the water tank; if the cleaning time corresponding to the water tank exceeds a preset cleaning time threshold corresponding to the water tank, then judging that the water tank needs self-cleaning.

4. The control method for water tank self-cleaning according to claim 3, characterized in that: The method also trains the cleaning analysis and evaluation model through the following steps: using each water tank as a training sample, obtaining multiple groups of training sample sets corresponding to each training sample, wherein the training sample sets include water quality data and cleaning data corresponding to the training sample; obtaining water quality data of the spare water tank corresponding to each group of training sample sets; selectively updating the water in the spare water tank of the water tank based on the water quality data in each group of training sample sets and the water quality data of the spare water tank corresponding to each group of training sample sets; determining the self-cleaning estimated remaining time corresponding to each group of training sample sets based on each group of training sample sets and the environmental data corresponding to each group of training sample sets; generating multiple groups of self-cleaning combination parameters corresponding to each group of training sample sets based on the self-cleaning estimated remaining time corresponding to each group of training sample sets, each group of training sample sets and the environmental data corresponding to each group of training sample sets, wherein the self-cleaning The combined parameters include an estimated self-cleaning time point, an estimated self-cleaning time, multiple self-cleaning execution operations, and a cleaning processing step corresponding to each self-cleaning execution operation; based on multiple groups of self-cleaning combined parameters corresponding to the training sample set, a group of self-cleaning combined parameters is selected as the self-cleaning processing scheme corresponding to the training sample set to obtain the self-cleaning processing scheme corresponding to each group of training sample sets; based on the self-cleaning processing scheme corresponding to each group of training sample sets, simulation is performed to obtain simulation data for each group of training sample sets; based on the simulation data of each group of training sample sets and the cleaning standard parameters in the cleaning data in each group of training sample sets, the self-cleaning situation of the self-cleaning processing scheme corresponding to each group of training sample sets is determined, wherein the self-cleaning situation includes a self-cleaning result and a self-cleaning evaluation score; based on the self-cleaning situation corresponding to each group of training sample sets, the training result of the cleaning analysis and evaluation model is obtained.

5. The control method for water tank self-cleaning according to claim 4, characterized in that: The cleaning analysis and evaluation model stores a preset water tank history database, which stores the numbers of each water tank, the historical cleaning standard parameters corresponding to each water tank, multiple groups of historical cleaning information, and the cleaning time points corresponding to each group of historical cleaning information. The step of obtaining multiple groups of training sample sets corresponding to each training sample includes: based on the preset water tank history database, randomly selecting multiple groups of historical cleaning standard parameters corresponding to each training sample and multiple groups of historical cleaning information corresponding to each group of historical cleaning standard parameters to obtain multiple groups of cleaning data corresponding to each training sample, wherein each group of cleaning data includes the cleaning time points corresponding to the training sample. A set of historical cleaning standard parameters corresponding to the historical cleaning standard parameters and a set of historical cleaning information corresponding to the historical cleaning standard parameters; based on the multiple sets of cleaning data corresponding to each training sample, each cleaning data is selectively marked; based on the multiple sets of cleaning data corresponding to each training sample and the marking of each cleaning data, water quality data corresponding to each set of cleaning data is randomly set; based on the multiple sets of cleaning data corresponding to each training sample and the water quality data corresponding to each set of cleaning data, multiple sets of training sample sets corresponding to each training sample are obtained; and based on the marking of the cleaning data in each set of training sample sets, each set of training sample sets is selectively marked.

6. The control method for water tank self-cleaning according to claim 5, characterized in that: The method of determining the estimated remaining self-cleaning time corresponding to each group of training sample sets based on each group of training sample sets and the environmental data corresponding to each group of training sample sets includes: determining the estimated contamination scores of the training samples corresponding to each group of training sample sets at various time lengths based on the estimated contamination scores of the training samples corresponding to each group of training sample sets at various time lengths; determining the estimated remaining self-cleaning time corresponding to each group of training sample sets based on the estimated contamination scores of the training samples corresponding to each group of training sample sets at various time lengths.

7. The control method for water tank self-cleaning according to claim 6, characterized in that: The historical cleaning information includes multiple self-cleaning processing schemes, and the generation of multiple groups of self-cleaning combination parameters corresponding to each group of training sample sets based on the self-cleaning estimated remaining time corresponding to each group of training sample sets, each group of training sample sets, and the environmental data corresponding to each group of training sample sets includes: determining multiple executable self-cleaning execution operations corresponding to each training sample based on the historical cleaning information corresponding to each training sample in a preset water tank history database; determining the processing coefficient matched by each executable self-cleaning execution operation corresponding to each training sample based on the multiple executable self-cleaning execution operations corresponding to each training sample; generating multiple groups of self-cleaning combination parameters corresponding to each group of training sample sets based on the processing coefficient matched by each executable self-cleaning execution operation corresponding to each training sample and the multiple groups of training sample sets corresponding to each training sample; based on the self-cleaning estimated remaining time corresponding to each group of training sample sets and the environmental data corresponding to each group of training sample sets, screening the multiple groups of self-cleaning combination parameters corresponding to each group of training sample sets to obtain the screened multiple groups of self-cleaning combination parameters corresponding to each group of training sample sets.

8. The control method for water tank self-cleaning according to claim 7, characterized in that: The method of selecting a group of self-cleaning combination parameters as the self-cleaning treatment plan corresponding to the training sample set based on the multiple groups of self-cleaning combination parameters corresponding to the training sample set includes: obtaining the cleaning score corresponding to each group of self-cleaning combination parameters in the training sample set based on the multiple groups of self-cleaning combination parameters screened corresponding to the training sample set; and selecting a group of self-cleaning combination parameters with the highest cleaning score as the self-cleaning treatment plan corresponding to the training sample set based on the cleaning score corresponding to each group of self-cleaning combination parameters in the training sample set.

9. The control method for water tank self-cleaning according to claim 8, characterized in that: The method of determining the self-cleaning condition of the self-cleaning treatment scheme corresponding to each group of training sample sets based on the simulation data of each group of training sample sets and the cleaning standard parameters in the cleaning data in each group of training sample sets includes: determining the self-cleaning evaluation score of the self-cleaning treatment scheme corresponding to each group of training sample sets based on the simulation data and the cleaning standard parameters corresponding to each group of training sample sets; and determining the self-cleaning result of the self-cleaning treatment scheme corresponding to each group of training sample sets based on the self-cleaning evaluation score of the self-cleaning treatment scheme corresponding to each group of training sample sets.

10. A water tank self-cleaning control device, characterized in that: The water tank self-cleaning control device includes a cleaning analysis and evaluation model and a control device, the water tank self-cleaning control device also includes acquisition devices respectively installed in different water tanks and self-cleaning devices respectively connected to different water tanks, the cleaning analysis and evaluation model stores a preset water tank history database, the acquisition device is used to obtain water quality data of the water tank, and the self-cleaning device is used to perform water quality self-cleaning on the water tank according to the self-cleaning treatment scheme corresponding to the water tank; the control device includes a processor and a memory, the memory is suitable for storing multiple program codes, the program code is suitable for being loaded and run by the processor to execute the control method for water tank self-cleaning described in any one of claims 1 to 9; the control device also exchanges information with multiple user terminals and different water tanks, and is used to feed back the self-cleaning treatment scheme and self-cleaning evaluation results of the water tank to the user terminal.

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