Self-cleaning control method, controller and cleaning equipment

Abstract

The embodiment of the invention provides a self-cleaning control method, a controller and cleaning equipment. The method comprises the steps that a controller can input use information of cleaning equipment into a first model after obtaining the use information of the cleaning equipment, and the subsequent use probability of the cleaning equipment is obtained; the controller can also acquire scanning information of the suction ports and then input the scanning information into the second model to obtain stain information of each suction port. The controller may determine a self-cleaning mode based on the subsequent use probability. The controller can determine cleaning parameters based on the self-cleaning mode according to stain information of each suction port. The controller can complete the self-cleaning process according to the self-cleaning mode and the cleaning parameters. The method is used for achieving the effect of improving the self-cleaning efficiency and effect.

Description

Technical Field

[0001] The present application relates to the field of cleaning equipment, and in particular, to a self-cleaning control method, a controller, and a cleaning equipment. Background Art

[0002] After the cleaning equipment finishes cleaning the ground, or after the cleaning equipment finishes cleaning a partial area, it is usually necessary to perform self-cleaning on the cleaning equipment for subsequent use.

[0003] Currently, cleaning equipment usually has a fixed self-cleaning program. When the cleaning equipment starts the self-cleaning function, the cleaning equipment can call the self-cleaning program to perform self-cleaning on the cleaning equipment.

[0004] However, the current self-cleaning program has the problem of low cleaning efficiency. Summary of the Invention

[0005] Embodiments of the present application provide a self-cleaning control method, a controller, and a cleaning equipment, so as to achieve the effect of improving the self-cleaning efficiency of the cleaning equipment.

[0006] In a first aspect, an embodiment of the present application provides a self-cleaning control method, including:

[0007] The cleaning equipment includes a plurality of suction ports, including:

[0008] Obtaining usage information of the cleaning equipment, and inputting the usage information into a first model to obtain a subsequent usage probability; the first model is used to determine the subsequent usage probability of the cleaning equipment according to the usage information; the subsequent usage probability represents the probability that the user uses the cleaning equipment to continue cleaning after self-cleaning is completed;

[0009] Obtaining scanning information of the suction ports of the cleaning equipment, and inputting the scanning information into a second model to obtain stain information of each suction port; the second model is used to identify the stain information included in the scanning information of the suction ports;

[0010] Determining a self-cleaning mode of the cleaning equipment and cleaning parameters in the self-cleaning mode according to the subsequent usage probability and the stain information of each suction port; and controlling the cleaning equipment to perform self-cleaning according to the self-cleaning mode and the cleaning parameters.

[0011] In this embodiment, by comprehensively analyzing the usage information of the cleaning equipment and the stain information of the suction ports, the self-cleaning mode is intelligently determined and the cleaning parameters are optimized, so as to effectively control the cleaning equipment to perform efficient self-cleaning and improve the user experience.

[0012] Optionally, according to the subsequent usage probability and the stain information of each suction port, determine the self-cleaning mode of the cleaning device and the cleaning parameters in the self-cleaning mode, including:

[0013] Determine the self-cleaning mode of the cleaning device according to the subsequent usage probability and a preset first threshold; the self-cleaning mode includes reference parameters;

[0014] On the basis of the reference parameters of the self-cleaning mode, adjust according to the stain information to obtain the cleaning parameters.

[0015] In this embodiment, the self-cleaning mode of the cleaning device is intelligently determined based on the subsequent usage probability and the preset threshold, and the cleaning parameters are dynamically adjusted in combination with the stain information, so as to achieve precise and efficient control of the self-cleaning of the cleaning device.

[0016] Optionally, the cleaning parameters include the water supply amount of the suction port and the rotation speed of the roller brush; on the basis of the reference parameters of the self-cleaning mode, adjust according to the stain information to obtain the cleaning parameters, including:

[0017] Determine the cleaning parameters corresponding to each suction port according to the reference parameters and the stain information of each suction port;

[0018] Adjust the cleaning parameters of each suction port according to the positional relationship between the suction port and the roller brush of the cleaning device.

[0019] In this embodiment, by combining the reference parameters, the stain information of the suction port and the positional relationship between the suction port and the roller brush, the cleaning parameters of each suction port are dynamically adjusted, so as to achieve refined control of the self-cleaning of the cleaning device.

[0020] Optionally, the stain information includes at least one of stain area information, pollution degree information, and stain category information; determining the cleaning parameters corresponding to each suction port according to the reference parameters and the stain information of each suction port includes:

[0021] Determine the first adjustment coefficient of the pollution category according to the stain category information;

[0022] Determine the second adjustment coefficient according to the ratio of the pollution area indicated by the stain area information to the preset basic area;

[0023] Determine the third adjustment coefficient according to the pollution level indicated by the pollution degree information and the preset mapping table;

[0024] Determine the cleaning parameters of the suction port according to the reference parameters and the product of the first adjustment coefficient, the second adjustment coefficient, and the third adjustment coefficient.

[0025] In this embodiment, the stain area information, pollution degree information, and stain category information are obtained, and the benchmark parameters are precisely adjusted through a multi-level adjustment coefficient to achieve personalized customization and optimization of the cleaning parameters of the suction port.

[0026] Optionally, the cleaning parameters include the water supply amount of the suction port and the rotation speed of the roller brush; according to the positional relationship between the suction port and the roller brush of the cleaning device, adjusting the cleaning parameters of each suction port includes:

[0027] If there are two suction ports corresponding to the same position of a roller brush, then according to the average value of the water supply amounts of the two suction ports, determine the adjusted water supply amount of the two suction ports;

[0028] If there are multiple suction ports corresponding to a roller brush, then according to the average value of the rotation speeds corresponding to the multiple suction ports, determine the adjusted rotation speed of the roller brush.

[0029] In this embodiment, for the correspondence between multiple suction ports and the roller brush, the water supply amount and the rotation speed are coordinated by calculating the average value, realizing the dual optimization of the operation efficiency and cleaning effect of the cleaning device.

[0030] Optionally, inputting the scanning information into the second model to obtain the stain information of each suction port includes:

[0031] Input the scanning information into the detection unit of the second model to detect the stain area information;

[0032] Input the stain area information into the recognition unit of the second model to recognize the stain category information corresponding to the stain area;

[0033] Input the stain area information into the degree unit corresponding to the stain category information in the second model to judge and obtain the pollution degree information of the stain category corresponding to the stain area.

[0034] In this embodiment, through the detection, recognition, and degree judgment units of the second model, precise positioning, classification, and pollution degree evaluation of the stain area in the scanning information are realized, providing detailed cleaning guidance for the cleaning device.

[0035] Optionally, the obtaining step of the first model includes:

[0036] Record the usage information of the user before each self-cleaning execution and the result information of whether to continue using after the self-cleaning execution;

[0037] Train the first model according to the usage information and the result information to obtain the trained first model.

[0038] In this embodiment, by recording and analyzing the usage information and result feedback before and after self-cleaning of the user, the first model is continuously trained and optimized to improve the accuracy and intelligence level of the self-cleaning decision of the cleaning device.

[0039] Optionally, the method further includes:

[0040] Obtain the usage information of the user before each self-cleaning, the subsequent usage probability output by the first model, and the result information on whether the user continues to use;

[0041] If the subsequent usage probability does not match the result information, record the usage information and the result information; and periodically use the recorded usage information and result information to supplement the training of the first model to obtain the optimized first model.

[0042] In this embodiment, by real-time monitoring the behavior data of the user before and after self-cleaning, verifying and feeding back the prediction result of the first model, and periodically supplementing the training to continuously optimize the model, the accuracy and adaptability of the self-cleaning strategy of the cleaning device are improved.

[0043] In a second aspect, an embodiment of the present application provides a self-cleaning control device. The cleaning device includes a plurality of suction ports. The self-cleaning control device includes:

[0044] A first acquisition module, configured to acquire the usage information of the cleaning device and input the usage information into the first model to obtain a subsequent usage probability; the first model is used to determine the subsequent usage probability of the cleaning device according to the usage information; the subsequent usage probability represents the probability that the user uses the cleaning device to continue cleaning after completing self-cleaning;

[0045] A second acquisition module, configured to acquire the scanning information of the suction ports of the cleaning device and input the scanning information into the second model to obtain the stain information of each suction port; the second model is used to identify the stain information included in the scanning information of the suction port;

[0046] A control module, configured to determine the self-cleaning mode of the cleaning device and the cleaning parameters in the self-cleaning mode according to the subsequent usage probability and the stain information of each suction port; and control the cleaning device to perform self-cleaning according to the self-cleaning mode and the cleaning parameters.

[0047] Optionally, the control module is configured to:

[0048] Determine the self-cleaning mode of the cleaning device according to the subsequent usage probability and a preset first threshold; the self-cleaning mode includes reference parameters;

[0049] Based on the reference parameters in the self-cleaning mode, adjust according to the stain information to obtain the cleaning parameters.

[0050] Optionally, the cleaning parameters include the water supply volume of the suction port and the rotational speed of the roller brush; the control module is configured to:

[0051] Determine the cleaning parameters corresponding to each suction port according to the reference parameters and the stain information of each suction port;

[0052] Adjust the cleaning parameters of each suction port according to the positional relationship between the suction port and the roller brush of the cleaning device.

[0053] Optionally, the stain information includes at least one of stain area information, pollution degree information, and stain category information; the control module is configured to:

[0054] Determine the first adjustment coefficient of the pollution category according to the stain category information;

[0055] Determine the second adjustment coefficient according to the ratio of the pollution area indicated by the stain area information to the preset basic area;

[0056] Determine the third adjustment coefficient according to the pollution level indicated by the pollution degree information and the preset mapping table;

[0057] Determine the cleaning parameters of the suction port according to the reference parameters and the product of the first adjustment coefficient, the second adjustment coefficient, and the third adjustment coefficient.

[0058] Optionally, the cleaning parameters include the water supply volume of the suction port and the rotational speed of the roller brush; the control module is configured to:

[0059] If there are two suction ports corresponding to the same position of a roller brush, determine the adjusted water supply volume of the two suction ports according to the average value of the water supply volumes of the two suction ports;

[0060] If there are multiple suction ports corresponding to a roller brush, determine the adjusted rotational speed of the roller brush according to the average value of the rotational speeds corresponding to the multiple suction ports.

[0061] Optionally, the second acquisition module is configured to:

[0062] Input the scan information into the detection unit of the second model to detect and obtain the stain area information;

[0063] Input the stain area information into the recognition unit of the second model to recognize and obtain the stain category information corresponding to the stain area;

[0064] Input the stain area information into the degree unit corresponding to the stain category information in the second model, and judge to obtain the pollution degree information of the stain category corresponding to the stain area.

[0065] Optionally, the self-cleaning control device further includes:

[0066] A model module, configured to record the usage information of the user before each self-cleaning execution, and the result information of whether to continue using after the self-cleaning execution; train the first model according to the usage information and the result information to obtain the trained first model.

[0067] Optionally, the model module is further configured to:

[0068] Obtain the usage information of the user before each self-cleaning execution, the subsequent usage probability output by the first model, and the result information of whether the user continues to use;

[0069] If the subsequent usage probability does not match the result information, record the usage information and the result information; and periodically use the recorded usage information and result information to supplement the training of the first model to obtain the optimized first model.

[0070] In a third aspect, an embodiment of the present application provides a controller, including: a memory, a processor;

[0071] The memory stores computer execution instructions;

[0072] The processor executes the computer execution instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementation manners of the first aspect.

[0073] In a fourth aspect, an embodiment of the present application provides a cleaning device, including: a plurality of suction ports, at least one roller brush, and the controller in the above third aspect and / or various possible controllers of the third aspect.

[0074] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer execution instructions are stored, and when the computer execution instructions are executed by a processor, they are used to implement the above first aspect and / or various possible implementation manners of the first aspect.

[0075] In a sixth aspect, an embodiment of the present application provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the above first aspect and / or various possible implementation manners of the first aspect.

[0076] The self-cleaning control method, controller, and cleaning device provided by the embodiments of the present application obtain the usage information of the cleaning device, input the usage information of the cleaning device into the first model to obtain the subsequent usage probability of the cleaning device; obtain the scanning information of the suction ports, input the scanning information into the second model to obtain the stain information of each suction port; determine the self-cleaning mode according to the subsequent usage probability; determine the cleaning parameters based on the self-cleaning mode according to the stain information of each suction port; and complete the self-cleaning process according to the self-cleaning mode and the cleaning parameters, thereby improving the self-cleaning efficiency and effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] The accompanying drawings herein are incorporated into and constitute a part of this specification, showing embodiments consistent with the present application and, together with the specification, are used to explain the principles of the present application.

[0078] Figure 1 It is a schematic structural diagram of the cleaning device provided by the present application;

[0079] Figure 2 It is a schematic flow chart of the self-cleaning control method provided by the present application Figure 1 ;

[0080] Figure 3 It is a schematic flow chart of the self-cleaning control method provided by the present application Figure 2 ;

[0081] Figure 4 It is an example diagram of the self-cleaning control method provided by the present application;

[0082] Figure 5 It is a schematic flow chart of the self-cleaning control method provided by the present application Figure 3 ;

[0083] Figure 6 It is a schematic structural diagram of the self-cleaning control device provided by the present application;

[0084] Figure 7 It is a schematic structural diagram of the controller provided by the present application.

[0085] Through the above accompanying drawings, specific embodiments of the present application have been shown, and there will be more detailed descriptions hereinafter. These drawings and textual descriptions are not intended to limit the scope of the concept of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0086] Exemplary embodiments will be described in detail herein, and examples thereof are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of apparatuses and methods consistent with some aspects of the present application as detailed in the appended claims.

[0087] After the cleaning device completes floor cleaning, or after the cleaning device completes cleaning of a partial area, it is usually necessary to perform self-cleaning on the cleaning device for subsequent use. Optionally, the cleaning device may be a vacuum cleaner, a floor washer, or the like. For a cleaning device with dual suction ports or multiple suction ports, during self-cleaning, it is usually necessary to supply water to each suction port to ensure complete self-cleaning. However, for different cleaning modes, in current cleaning devices, there is an inaccurate problem in controlling the water volume of the suction ports. This results in the inability to efficiently utilize the self-cleaning system, and it is easy to have situations of insufficient or excessive self-cleaning.

[0088] Based on the above situation, the present application proposes a self-cleaning control method. The self-cleaning control method can determine the cleaning mode and cleaning parameters according to information such as user habits and the degree of dirt on the suction ports, so as to adjust the efficiency and effect of self-cleaning. The present application can be implemented by Figure 1 the cleaning device shown. As Figure 1 shown, the cleaning device of the present application may include a user habit collector, a stain detection device, a memory, a controller, a water supply system, etc.

[0089] Among them, the user habit collector can statistically analyze the user's usage habits according to the user's multiple usage situations, and determine whether the user continues to use the floor washer after self-cleaning during a certain time period. The user's usage habits can be collected and updated periodically. The period can be one week, one month, etc. The user habit data can be stored in the memory. The stain detection device is located beside the suction port and can be used to detect the stain situation beside the corresponding suction port and feedback it to the controller. The water supply system includes components such as a water supply device, a water pump, and a solenoid valve. Among them, the solenoid valve is connected to different suction ports through different pipelines. For example, when there are suction port A and suction port B, the solenoid valve can be connected to the two suction ports through different pipelines. The water supply system, together with the base station drying system, the roller brush, the suction fan, etc., constitutes the execution of the entire self-cleaning process.

[0090] Under the control of the controller, the water supply system can adjust parameters such as the water supply volume to the suction port and the rotation speed of the roller brush according to the amount of stains at the suction port. At the same time, the entire cleaning device can select a fast mode or a silent mode according to the user's usage habits. Through this control logic, the cleaning device can achieve efficient self-cleaning. When the user needs to continue using the floor washer, the fast mode can be used for rapid self-cleaning; when the user does not need to continue using it, or during non-normal time periods, the silent mode with less interference to the user can be selected to improve the user experience.

[0091] The technical solution of the present application and how the technical solution of the present application solves the above technical problems will be described in detail below with specific embodiments. These several specific embodiments below can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0092] Figure 2 Flow schematic of the self-cleaning control method provided by the present application Figure 1 , such as Figure 2 shown, the method includes:

[0093] S201. Obtain the usage information of the cleaning device, and input the usage information into the first model to obtain the subsequent usage probability. The first model is used to determine the subsequent usage probability of the cleaning device according to the usage information. The subsequent usage probability represents the probability that the user will use the cleaning device to continue cleaning after self-cleaning is completed.

[0094] In this embodiment, after obtaining the usage information of the cleaning device, the controller can input the usage information of the cleaning device into the first model. The first model can output the subsequent usage probability of the cleaning device according to the usage information. The subsequent usage probability is the probability that the user will continue to use the cleaning device to clean after this self-cleaning.

[0095] Optionally, the usage information of the cleaning device can be the information generated after the cleaning device is started this time. Optionally, the usage information may include information such as the start time, usage duration, usage mode, etc. Optionally, the usage information may further include information such as the cleaning area. Optionally, the usage information may further include information such as the quantity and type of pollutants.

[0096] Optionally, the first model can be a deep learning model. Optionally, the subsequent usage probability output by the first model can be a probability value. Optionally, the value of the probability value can be between 0 and 1.

[0097] S202. Obtain the scanning information of the suction port of the cleaning device, and input the scanning information into the second model to obtain the stain information of each suction port. The second model is used to identify the stain information contained in the scanning information of the suction port.

[0098] In this embodiment, the controller can also obtain the scanning information of the suction port. Optionally, the scanning information can be implemented by a stain detection component disposed on the suction port. Optionally, a stain detection component can be correspondingly provided for each suction port. Alternatively, a stain cleaning component of the cleaning device can complete the acquisition of the scanning information of multiple suction ports. Optionally, the stain detection component can be a sensor such as a camera that can collect visual information. Optionally, the scanning information can be visual information such as an image. For example, when the camera captures a picture of the cleaning device, pictures of each suction port can be cropped from the picture according to the preset positions of the suction ports. The picture of each suction port is the scanning information of the suction port.

[0099] The controller can input the scanning information into a second model. The second model can be a deep learning model. The second model can output the stain information of each suction port. Optionally, the stain information can include multiple sub-items such as stain area information, stain category information, and pollution degree information.

[0100] In one example, the second model can include multiple detection units. After the controller inputs the scanning information into the second model, the multiple detection units are sequentially used for detection to obtain the stain information. The specific process can include:

[0101] Step 1: Input the scanning information into the detection unit of the second model to detect and obtain the stain area information.

[0102] In this step, the controller can first input the scanning information into the detection unit of the second model. The detection unit can detect the stain area in the scanning information to obtain the stain area information.

[0103] Step 2: Input the stain area information into the recognition unit of the second model to recognize and obtain the stain category information corresponding to the stain area.

[0104] In this step, the controller can crop the scanning information according to the stain area information to obtain the stain area. Furthermore, the controller can input the cropped stain area into the recognition unit of the second model. The recognition unit can recognize the stain area to determine the stain category corresponding to each stain area. The controller can summarize to obtain the stain category information of the suction port.

[0105] Step 3: Input the stain area information into the degree unit corresponding to the stain category information in the second model to judge and obtain the pollution degree information of the stain category corresponding to the stain area.

[0106] In this step, the controller can determine the degree unit in the second model that needs to be used according to the stain category information corresponding to each stain area. After the stain area is input into the degree unit corresponding to the stain category, the pollution degree of the stain area can be output. The controller can summarize the pollution degree information of the suction port. Optionally, the controller can also calculate the pollution degree included in the scan information according to the average value of the pollution degrees of each stain area.

[0107] S203. Determine the self-cleaning mode of the cleaning device and the cleaning parameters in the self-cleaning mode according to the subsequent usage probability and the stain information of each suction port; and control the cleaning device to perform self-cleaning according to the self-cleaning mode and the cleaning parameters.

[0108] In this embodiment, the controller can map the subsequent usage probability to obtain the self-cleaning mode of the cleaning device. Furthermore, based on the self-cleaning mode, the controller can adjust the cleaning parameters of the self-cleaning mode according to the stain information of each suction port, so as to determine the cleaning parameters for this self-cleaning. The controller can start self-cleaning according to the self-cleaning mode and complete the control of the self-cleaning process according to the cleaning parameters, so as to realize the self-cleaning of the cleaning device.

[0109] In one example, the specific process for the controller to determine the self-cleaning mode and the cleaning parameters may include the following steps:

[0110] Step 1. Determine the self-cleaning mode of the cleaning device according to the subsequent usage probability and a preset first threshold. The self-cleaning mode includes reference parameters.

[0111] In this step, a first threshold may be preset in the controller. When the subsequent usage probability is less than the first threshold, it can be considered that the user will not use it subsequently. When the subsequent usage probability is greater than or equal to the probability threshold, it can be considered that the user will continue to use it subsequently. The controller can compare the subsequent usage probability with the probability threshold and determine the self-cleaning mode of the cleaning device according to the judgment result. According to the self-cleaning mode.

[0112] Step 2. On the basis of the reference parameters of the self-cleaning mode, adjust according to the stain information to obtain the cleaning parameters.

[0113] In this step, after obtaining the reference parameters of the self-cleaning mode, the controller can adjust the reference parameters based on the stain information to obtain the cleaning parameters. The specific adjustment process may be as Figure 3 shown in the embodiments shown.

[0114] In the self-cleaning control method provided by the embodiments of the present application, after obtaining the usage information of the cleaning device, the controller can input the usage information of the cleaning device into the first model to obtain the subsequent usage probability of the cleaning device. After obtaining the scanning information of the suction nozzle, the controller can also input the scanning information into the second model to obtain the stain information of each suction nozzle. The controller can determine the self-cleaning mode according to the subsequent usage probability. Based on the self-cleaning mode, the controller can determine the cleaning parameters according to the stain information of each suction nozzle. The controller can complete the self-cleaning process according to the self-cleaning mode and the cleaning parameters. In the present application, by obtaining the usage information of the cleaning device and the suction nozzle scanning information, and respectively inputting them into the first model and the second deep learning model to predict the subsequent usage probability and stain information, the optimization of the self-cleaning process of the cleaning device is realized, and the self-cleaning efficiency and effect are improved.

[0115] Figure 3 is a flowchart of the self-cleaning control method provided by the present application Figure 2 , such as Figure 3 shown, on the basis of the Figure 2 embodiment, the specific process of adjusting the benchmark parameters of the self-cleaning mode according to the stain information to obtain the cleaning parameters may include:

[0116] S301. Determine the cleaning parameter corresponding to each suction nozzle according to the benchmark parameter and the stain information of each suction nozzle.

[0117] In this embodiment, the controller can adjust the benchmark parameter according to the stain information of each suction nozzle to obtain the cleaning parameter corresponding to each suction nozzle.

[0118] Stain area information, stain category information, pollution degree information

[0119] Optionally, when the stain information includes stain area information, pollution degree information, and stain category information, the adjustment process of the cleaning parameter corresponding to each suction nozzle may include:

[0120] Step 1. Determine the first adjustment coefficient of the pollution category according to the stain category information.

[0121] In this step, a mapping table may be preset in the controller. Based on the mapping table, the controller can look up the table to determine the first adjustment coefficient corresponding to the stain category indicated by the stain category information. Among them, different stains may correspond to different adjustment coefficients. For example, for some stains that are not easy to clean, an adjustment coefficient greater than 1 may be set to increase the cleaning parameter. For some stains that are easy to clean, an adjustment coefficient less than 1 may be set to reduce the cleaning parameter.

[0122] Step 2: Determine a second adjustment coefficient according to the ratio of the pollution area indicated by the stain area information to the preset basic area.

[0123] In this step, the controller can determine the pollution area according to the stain area information. A basic area can also be set in the controller. Based on the ratio of the pollution area to the basic area, the controller can determine the second adjustment coefficient. When the ratio is greater than 1, it indicates that the pollution area is large, and correspondingly larger cleaning parameters are required. When the ratio is less than 1, it indicates that the pollution area is small, and the cleaning parameters can be correspondingly lowered.

[0124] Step 3: Determine a third adjustment coefficient according to the pollution level indicated by the pollution degree information and the preset mapping table.

[0125] In this step, the controller can determine the pollution level according to the pollution degree information. A mapping table can also be preset in the controller. This mapping table is different from the mapping table in Step 1. Based on this mapping table, the controller can determine the third adjustment coefficient corresponding to the pollution level. When the pollution level is high, it indicates that larger cleaning parameters are required. When the pollution level is low, the cleaning parameters can be lowered.

[0126] Step 4: Determine the cleaning parameters of the suction nozzle according to the reference parameter and the product of the first adjustment coefficient, the second adjustment coefficient, and the third adjustment coefficient.

[0127] In this step, after calculating the first adjustment coefficient, the second adjustment coefficient, and the third adjustment coefficient, the product of the reference parameter and the first adjustment coefficient, the second adjustment coefficient, and the third adjustment coefficient can be calculated to obtain the final cleaning parameters. Optionally, each suction nozzle corresponds to a cleaning parameter. Optionally, the cleaning parameters can specifically include the water supply amount of the suction nozzle and the rotation speed of the roller brush. At this time, each suction nozzle can correspond to a water supply amount of the suction nozzle and a rotation speed of the roller brush.

[0128] S302: Adjust the cleaning parameters of each suction nozzle according to the positional relationship between the suction nozzle and the roller brush of the cleaning device.

[0129] In this embodiment, the controller can obtain the positional relationship between the suction nozzle and the roller brush on the cleaning device. The controller can adjust the cleaning parameters according to the positional relationship between the suction nozzle and the roller brush to obtain the final cleaning parameters.

[0130] In one example, the adjustment process of the cleaning parameter pair can include:

[0131] Step 1: If there are two suction nozzles corresponding to the same position of a roller brush, determine the adjusted water supply amounts of the two suction nozzles according to the average value of the water supply amounts of the two suction nozzles.

[0132] In this step, the controller can determine whether there are multiple suction nozzles corresponding to the same position of a roller brush. If multiple suction nozzles correspond to the same position of a roller brush, the water output by these multiple suction nozzles will all act on this position of the roller brush. Moreover, the suction nozzle will be self-cleaned by the rotation of the roller brush. At this time, if the water supply amounts of the multiple suction nozzles corresponding to the same position are different, it may instead cause uneven wetting of this position of the roller brush, thereby affecting the effect of the roller brush during self-cleaning. Therefore, the average value of the water supply amounts of these multiple suction nozzles can be calculated to obtain the adjusted water supply amount. Optionally, the specific number of the multiple suction nozzles can be 2. The positional relationship between the suction nozzle and the roller brush can be that one suction nozzle is provided in front of and behind the roller brush respectively.

[0133] Step 2: If there are multiple suction nozzles corresponding to a roller brush, determine the adjusted rotation speed of the roller brush according to the average value of the rotation speeds corresponding to the multiple suction nozzles.

[0134] In this step, if there are multiple suction nozzles corresponding to a roller brush, the roller brush can actually achieve self-cleaning of these multiple suction nozzles after rotation. Therefore, the average value can be determined according to the rotation speeds corresponding to these multiple suction nozzles, and then the adjusted rotation speed of the roller brush can be determined according to this average value. Optionally, the adjusted rotation speed of the roller brush can also be determined according to values such as the median value or the maximum value of the rotation speeds corresponding to these multiple suction nozzles.

[0135] In the self-cleaning control method provided by the embodiment of the present application, the controller can adjust the reference parameter according to the stain information of each suction nozzle to obtain the cleaning parameter corresponding to each suction nozzle. The controller can obtain the positional relationship between the suction nozzle and the roller brush on the cleaning device. The controller can adjust the cleaning parameter according to the positional relationship between the suction nozzle and the roller brush to obtain the final cleaning parameter. In this application, by adjusting the reference parameter according to the suction nozzle stain information and further optimizing the cleaning parameter in combination with the positional relationship between the suction nozzle and the roller brush, precise control of the cleaning parameters of the cleaning device is achieved, and the self-cleaning efficiency and effect are further improved.

[0136] Based on the above embodiments, as Figure 4 shown, during the actual use process of the user, the use process of the cleaning device can include the following steps:

[0137] After the cleaning device is started, the user can use the cleaning device to start cleaning. After a single cleaning is completed, the controller in the cleaning device can remind the user to perform self-cleaning. The controller in the cleaning device can determine whether the user places the cleaning device on the base. If the placement is not completed, the controller in the cleaning device can remind the user to place it on the base. After the cleaning device is placed on the base, the controller in the cleaning device can obtain the user's habits and complete the scanning of the suction port and surrounding stains. The controller in the cleaning device can determine the difference between the stains on the front suction port and the rear suction port. Based on this difference, the controller can complete the setting of the proportion of the water output of the front and rear suction ports. The controller in the cleaning device can determine whether the user continues to use the floor washer. If the user does not use the floor washer, the self-cleaning can be completed in the silent mode. If it is determined that the user needs to continue using the floor washer, the cleaning device continues to determine whether the cleaning device is used during abnormal periods. If so, the silent mode is started to complete the self-cleaning. Otherwise, the self-cleaning can be completed in the fast mode. Among them, the fast mode can perform high-power self-cleaning with fast self-cleaning efficiency but relatively high noise. The silent mode is low-power self-cleaning with low self-cleaning efficiency but low noise. Based on the cleaning mode selected by the cleaning device, the cleaning device can complete the self-cleaning.

[0138] Figure 5 Flow schematic of the self-cleaning control method provided by this application Figure 3 , such as Figure 4 shown, in this embodiment, on the basis of the embodiment shown in Figures 2 to 4 , the acquisition step of the first model, the method includes:

[0139] S501. Record the usage information of the user before each self-cleaning execution, and the result information of whether to continue using after the self-cleaning execution.

[0140] In this embodiment, the controller can record the usage information of the user before each self-cleaning execution. The controller can also record the result information of whether the user continues to use the cleaning device for cleaning after the self-cleaning is completed. This result information is the label of this usage information.

[0141] S502. Train the first model according to the usage information and the result information to obtain the trained first model.

[0142] In this embodiment, the controller uses the usage information as the input data and the result information as the label to train the first model. The first model can be a deep learning model. The controller can obtain the finally trained first model. The trained first model can be arranged on the controller to realize the calculation of the subsequent usage probability in subsequent use.

[0143] S503. Obtain the usage information of the user before each self - cleaning execution, the subsequent usage probability output by the first model, and the result information on whether the user continues to use.

[0144] In this embodiment, the controller can continue to record the usage information of the user before each self - cleaning execution during the actual usage process. The controller can also obtain the subsequent usage probability output by the first model. The controller can determine a judgment result according to the subsequent usage probability and the first threshold. The judgment result is used to indicate that the user continues to use the cleaning device, or the user does not continue to use the cleaning device. The controller can also record the actual usage result information of the user after this self - cleaning after the self - cleaning is completed. The result information is use or not use.

[0145] S504. If the subsequent usage probability does not match the result information, record the usage information and the result information; and periodically use the recorded usage information and result information to supplement the training of the first model to obtain an optimized first model.

[0146] In this embodiment, the controller can compare the result information with the judgment result. If the judgment result and the result information are consistent, it means that the first model predicts correctly. If the judgment result and the result information are inconsistent, it means that the first model predicts incorrectly. The controller can record the usage information and result information for which the first model predicts incorrectly, and periodically optimize and train the first model according to the recorded information to improve the matching degree of the first model with the user's usage habits.

[0147] For the self - cleaning control method provided in the embodiments of the present application, the controller can record the usage information of the user before each self - cleaning execution, and the result information on whether to continue using the cleaning device for cleaning after the self - cleaning is completed. The controller uses the usage information and the result information to train with the first model to obtain a trained first model. The controller can continue to record the usage information of the user before each self - cleaning execution, the judgment result of the first model, and the user result information during the actual usage process. If the judgment result and the result information are inconsistent, the controller can record the usage information and the result information, and periodically optimize and train the first model. In the present application, by recording the usage information of the user and the result information after self - cleaning, the training and optimization of the first model are completed to improve the matching degree of the first model with the user's usage habits and improve the judgment accuracy of the first model.

[0148] Figure 6 The following is a schematic structural diagram of the self - cleaning control device provided by the present application, as Figure 6 shown. The self - cleaning control device 600 provided in this embodiment includes:

[0149] The first acquisition module 601 is configured to acquire the usage information of the cleaning device, input the usage information into the first model, and obtain the subsequent usage probability; the first model is used to determine the subsequent usage probability of the cleaning device according to the usage information; the subsequent usage probability represents the probability that the user uses the cleaning device to continue cleaning after self-cleaning is completed.

[0150] The second acquisition module 602 is configured to acquire the scanning information of the suction ports of the cleaning device, input the scanning information into the second model, and obtain the stain information of each suction port; the second model is used to identify the stain information included in the scanning information of the suction ports.

[0151] The control module 603 is configured to determine the self-cleaning mode of the cleaning device and the cleaning parameters in the self-cleaning mode according to the subsequent usage probability and the stain information of each suction port; and control the cleaning device to perform self-cleaning according to the self-cleaning mode and the cleaning parameters.

[0152] Optionally, the control module 603 is configured to:

[0153] Determine the self-cleaning mode of the cleaning device according to the subsequent usage probability and a preset first threshold; the self-cleaning mode includes reference parameters;

[0154] On the basis of the reference parameters of the self-cleaning mode, adjust according to the stain information to obtain the cleaning parameters.

[0155] Optionally, the cleaning parameters include the water supply amount of the suction port and the rotation speed of the roller brush; the control module 603 is configured to:

[0156] Determine the cleaning parameters corresponding to each suction port according to the reference parameters and the stain information of each suction port;

[0157] Adjust the cleaning parameters of each suction port according to the positional relationship between the suction port and the roller brush of the cleaning device.

[0158] Optionally, the stain information includes at least one of stain area information, pollution degree information, and stain category information; the control module 603 is configured to:

[0159] Determine the first adjustment coefficient of the pollution category according to the stain category information;

[0160] Determine the second adjustment coefficient according to the ratio of the pollution area indicated by the stain area information to the preset basic area;

[0161] Determine the third adjustment coefficient according to the pollution level indicated by the pollution degree information and the preset mapping table;

[0162] Determine the cleaning parameters of the suction port according to the reference parameters and the product of the first adjustment coefficient, the second adjustment coefficient, and the third adjustment coefficient.

[0163] Optionally, the cleaning parameters include the water supply amount of the suction nozzle and the rotation speed of the roller brush; the control module 603 is configured to:

[0164] If there are two suction nozzles corresponding to the same position of a roller brush, determine the adjusted water supply amounts of the two suction nozzles according to the average value of the water supply amounts of the two suction nozzles;

[0165] If there are multiple suction nozzles corresponding to a roller brush, determine the adjusted rotation speed of the roller brush according to the average value of the rotation speeds corresponding to the multiple suction nozzles.

[0166] Optionally, the second acquisition module 602 is configured to:

[0167] Input the scan information into the detection unit of the second model to detect the stain area information;

[0168] Input the stain area information into the recognition unit of the second model to recognize the stain category information corresponding to the stain area;

[0169] Input the stain area information into the degree unit corresponding to the stain category information in the second model to judge the pollution degree information of the stain category corresponding to the stain area.

[0170] Optionally, the self-cleaning control device further includes:

[0171] The model module is configured to record the usage information of the user before each self-cleaning execution and the result information of whether to continue using after the self-cleaning execution; train the first model according to the usage information and the result information to obtain a trained first model.

[0172] Optionally, the model module is further configured to:

[0173] Obtain the usage information of the user before each self-cleaning execution, the subsequent usage probability output by the first model, and the result information of whether the user continues to use;

[0174] If the subsequent usage probability does not match the result information, record the usage information and the result information; and periodically use the recorded usage information and the result information to supplement the training of the first model to obtain an optimized first model.

[0175] The self-cleaning control device provided in this embodiment can execute the method provided in the above method embodiment, and its implementation principle and technical effects are similar, which will not be elaborated here in this embodiment.

[0176] Figure 7 It is a schematic structural diagram of the controller provided in this application. As Figure 7As shown, the controller 700 provided in this embodiment includes: at least one processor 701 and a memory 702. Optionally, the device 70 further includes a communication component 703. Among them, the processor 701, the memory 702, and the communication component 703 are connected through a bus.

[0177] In a specific implementation process, at least one processor 701 executes the computer-executable instructions stored in the memory 702, so that at least one processor 701 executes the above-mentioned method.

[0178] For the specific implementation process of the processor 701, reference may be made to the above method embodiment. The implementation principle and technical effects are similar, and will not be elaborated here in this embodiment.

[0179] In the above embodiment, it should be understood that the processor may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in combination with the invention can be directly implemented by the execution of the hardware processor, or can be implemented by the combination of hardware and software modules in the processor.

[0180] The memory may include a high-speed random access memory (RAM), and may also include a non-volatile memory (NVM), such as at least one disk memory.

[0181] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of this application is not limited to only one bus or one type of bus.

[0182] This application also provides a computer program product, including a computer program, which implements the above-mentioned method when executed by a processor.

[0183] The present application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above method.

[0184] The above-readable storage medium may be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, a magnetic disk, or an optical disk. The readable storage medium may be any available medium accessible by a general-purpose or special-purpose computer.

[0185] An exemplary readable storage medium is coupled to the processor so that the processor can read information from and write information to the readable storage medium. Of course, the readable storage medium may also be a component of the processor. The processor and the readable storage medium may be located in an application specific integrated circuit (ASIC). Of course, the processor and the readable storage medium may also exist as discrete components in a device.

[0186] The division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other may be through some interfaces, and the indirect couplings or communication connections of devices or units may be in electrical, mechanical, or other forms.

[0187] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0188] In addition, in each embodiment of the present invention, the functional units may be integrated in a processing unit, or each unit may exist physically alone, or two or more units may be integrated in one unit.

[0189] If a function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes: USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs and other various media that can store program codes.

[0190] Those of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When this program is executed, it executes the steps including the above method embodiments; and the aforementioned storage medium includes: ROM, RAM, magnetic disks, or optical discs and other various media that can store program codes.

[0191] Finally, it should be noted that: After considering the specification and practicing the invention disclosed herein, those skilled in the art will readily think of other implementation manners of the present invention. The present invention is intended to cover any variations, uses, or adaptations of the present invention, which follow the general principles of the present invention and include the common general knowledge or conventional technical means in the technical field not disclosed in the present invention. It is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present invention is only limited by the appended claims.

Claims

1. A self-cleaning control method, characterized in that Applied to a cleaning device, the cleaning device includes a plurality of suction ports, including: Obtain the usage information of the cleaning device, input the usage information into a first model to obtain a subsequent usage probability; the first model is used to determine the subsequent usage probability of the cleaning device according to the usage information; the subsequent usage probability represents the probability that the user uses the cleaning device to continue cleaning after self-cleaning; Obtain the scanning information of the suction ports of the cleaning device, input the scanning information into a second model to obtain the stain information of each suction port; the second model is used to identify the stain information contained in the scanning information of the suction port; Determine the self-cleaning mode of the cleaning device and the cleaning parameters in the self-cleaning mode according to the subsequent usage probability and the stain information of each suction port; and control the cleaning device to perform self-cleaning according to the self-cleaning mode and the cleaning parameters.

2. The method according to claim 1, wherein Determine the self-cleaning mode of the cleaning device and the cleaning parameters in the self-cleaning mode according to the subsequent usage probability and the stain information of each suction port, including: Determine the self-cleaning mode of the cleaning device according to the subsequent usage probability and a preset first threshold; the self-cleaning mode includes reference parameters; On the basis of the reference parameters of the self-cleaning mode, adjust according to the stain information to obtain the cleaning parameters.

3. The method according to claim 2, characterized in that, The cleaning parameters include the water supply volume of the suction port and the rotation speed of the roller brush; on the basis of the reference parameters of the self-cleaning mode, adjust according to the stain information to obtain the cleaning parameters, including: Determine the cleaning parameters corresponding to each suction port according to the reference parameters and the stain information of each suction port; Adjust the cleaning parameters of each suction port according to the positional relationship between the suction port and the roller brush of the cleaning device.

4. The method according to claim 3, characterized in that, The stain information includes at least one of stain area information, pollution degree information, and stain category information; determining the cleaning parameters corresponding to each suction port according to the reference parameters and the stain information of each suction port includes: Determine the first adjustment coefficient of the pollution category according to the stain category information; Determine the second adjustment coefficient according to the ratio of the pollution area indicated by the stain area information to the preset basic area; Determine the third adjustment coefficient according to the pollution level indicated by the pollution degree information and a preset mapping table; Determine the cleaning parameters of the suction port according to the reference parameters and the product of the first adjustment coefficient, the second adjustment coefficient, and the third adjustment coefficient.

5. The method according to claim 3, wherein The cleaning parameters include the water supply volume of the suction port and the rotation speed of the roller brush; Adjust the cleaning parameters of each suction port according to the positional relationship between the suction port and the roller brush of the cleaning device, including: If there are two suction ports corresponding to the same position of a roller brush, determine the adjusted water supply volume of the two suction ports according to the average value of the water supply volumes of the two suction ports; If there are multiple suction ports corresponding to a roller brush, determine the adjusted rotation speed of the roller brush according to the average value of the rotation speeds corresponding to the multiple suction ports.

6. The method according to claim 1, characterized in that, Input the scanning information into the second model to obtain the stain information of each suction port, including: Input the scanning information into the detection unit of the second model to detect the stain area information; Input the stain area information into the recognition unit of the second model to recognize the stain category information corresponding to the stain area; Input the stain area information into the degree unit corresponding to the stain category information in the second model to determine the pollution degree information of the stain category corresponding to the stain area.

7. The method according to any one of claims 1-6, characterized in that, The obtaining steps of the first model include: Record the usage information of the user before each self-cleaning execution, and the result information of whether to continue using after the self-cleaning execution; Train the first model according to the usage information and the result information to obtain the trained first model.

8. The method according to claim 7, wherein The method further includes: Obtain the usage information of the user before each self-cleaning execution, the subsequent usage probability output by the first model, and the result information of whether the user continues to use; If the subsequent usage probability does not match the result information, record the usage information and the result information; and periodically use the recorded usage information and result information to supplement the training of the first model to obtain the optimized first model.

9. A controller, characterized in that, Including: A memory and a processor; The memory stores computer execution instructions; The processor executes the computer execution instructions stored in the memory, so that the processor executes the method according to any one of claims 1-8.

10. A cleaning device, characterized in that, Including: Multiple suction ports, at least one roller brush, and a controller as shown in claim 9.

11. A computer-readable storage medium, characterized in that, Computer execution instructions are stored in the computer-readable storage medium, and when the computer execution instructions are executed by a processor, they are used to implement the method according to any one of claims 1-8.

12. A computer program product, characterized in that, Including a computer program, which when executed by a processor implements the method according to any one of claims 1-8.

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