Washing machine control method, device, equipment, medium and product

Abstract

The embodiment of the invention provides a washing machine control method and device, equipment, a medium and a product. The method comprises the steps that initial attribute information of a target object in a washing machine is obtained; determining processing parameters for the target article according to the initial attribute information, and controlling the washing machine to process the target article according to the processing parameters; in the process of processing the target article, monitoring real-time data of the target article; according to the real-time data, dynamically adjusting processing parameters for the target object, and according to the dynamically adjusted processing parameters, controlling the washing machine to process the target object. According to the embodiment of the invention, the processing parameters for the target article are determined and dynamically adjusted according to the initial attribute information of the target article in the washing machine, different articles are adaptively processed, abrasion and deformation of the target article in the washing process are reduced, and the service life of the target article is prolonged.

Description

Technical Field

[0001] The present invention relates to the technical field of smart home appliances, and in particular to a method, device, equipment, medium and product for controlling a washing machine. Background Art

[0002] With the rapid progress and popularization of smart home appliance technology, washing machines, as essential household appliances, are experiencing an unprecedented improvement in their intelligence level.

[0003] In the prior art, generally, a user adds items such as clothes into the inner drum of a washing machine, sets and starts a washing program, and the washing machine operates automatically.

[0004] However, since different items have different requirements for washing, when this method is adopted, irreparable damage may be caused to the clothes during the operation of the washing machine, such as wear, pilling, and deformation, thereby reducing the service life of the clothes. Summary of the invention

[0005] In view of the above problems, a method, device, equipment, medium and product for controlling a washing machine are proposed to overcome the above problems or at least partially solve the above problems, including: A method for controlling a washing machine, the method comprising: Acquiring initial attribute information of a target item in the washing machine; Determining processing parameters for the target object according to the initial attribute information, and controlling the washing machine to process the target object according to the processing parameters; During the process of processing the target object, monitoring the real-time data of the target object; Dynamically adjusting processing parameters for the target object according to the real-time data, and controlling the washing machine to process the target object according to the dynamically adjusted processing parameters; Wherein, determining the processing parameters for the target object according to the initial attribute information includes: Establishing a fiber model for the target object according to the initial attribute information; the initial attribute information includes any one or more of the following: weaving method information, material information, thickness information; According to the fiber model, processing parameters for the target article are determined; the processing parameters include any one or more of the following: washing parameters, rinsing parameters, and drying parameters.

[0006] Optionally, before dynamically adjusting the processing parameters for the target object according to the real-time data, the method further includes: Determining whether the target object has a risk of damage based on the real-time data; When it is determined that the target object has a risk of damage, dynamically adjusting the processing parameters for the target object based on the real-time data is executed.

[0007] Optionally, the real-time data includes a real-time fiber state, and judging whether the target object has a risk of damage according to the real-time data includes: When it is detected that the real-time fiber status indicates that the target object has an abnormal fiber status, it is determined that the target object is at risk of damage; wherein the real-time fiber status is real-time attribute information of the fiber material in the target object, and the abnormal fiber status is a situation where the difference between the real-time attribute information and the initial attribute information exceeds a preset difference degree.

[0008] Optionally, the real-time data includes a real-time object temperature, and judging whether the target object has a risk of damage according to the real-time data includes: When it is detected that the real-time object temperature is greater than a temperature threshold corresponding to the target object, it is determined that the target object has a risk of damage.

[0009] Optionally, the real-time data includes real-time friction conditions, and judging whether the target object has a risk of damage according to the real-time data includes: When it is detected that the real-time friction condition indicates that the target object has excessive friction, it is determined that the target object has a risk of damage.

[0010] Optionally, the acquiring initial attribute information of the target item in the washing machine includes: Acquire image data collected by a camera for a target item in the washing machine; The knitting method information of the target object is determined according to the image data.

[0011] Optionally, the acquiring initial attribute information of the target item in the washing machine includes: Acquiring spectral data collected by a spectral sensor for a target item in the washing machine; The material information of the target object is determined according to the spectral data.

[0012] Optionally, the acquiring initial attribute information of the target item in the washing machine includes: Acquiring infrared data collected by an infrared sensor for a target item in the washing machine; The thickness information of the target object is determined according to the infrared data.

[0013] Optionally, the washing parameters include any one or more of the following: drum speed, water flow intensity, detergent concentration; the rinsing parameters include any one or more of the following: number of rinses, rinsing intensity; the drying parameters include any one or more of the following: drying temperature, drying time.

[0014] A device for controlling a washing machine, the device comprising: An initial attribute information acquisition module, used to acquire initial attribute information of a target item in the washing machine; A first processing module, configured to determine processing parameters for the target object according to the initial attribute information, and control the washing machine to process the target object according to the processing parameters; A real-time data monitoring module, used to monitor the real-time data of the target object during the processing of the target object; a second processing module, configured to dynamically adjust processing parameters for the target object according to the real-time data, and control the washing machine to process the target object according to the dynamically adjusted processing parameters; Wherein, the first processing module includes: A fiber model establishment submodule is used to establish a fiber model for the target object according to the initial attribute information; the initial attribute information includes any one or more of the following: weaving method information, material information, thickness information; The first processing parameter determination submodule is used to determine the processing parameters for the target article according to the fiber model; the processing parameters include any one or more of the following: washing parameters, rinsing parameters, and drying parameters.

[0015] An electronic device comprises a processor, a memory and a computer program stored in the memory and capable of running on the processor, wherein the computer program implements the method described above when executed by the processor.

[0016] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described above is implemented.

[0017] A computer program product comprises a computer program, wherein when the computer program is executed by a processor, the computer program implements the method as described above.

[0018] The embodiments of the present invention have the following advantages: In an embodiment of the present invention, initial attribute information of a target item in the washing machine is acquired; processing parameters for the target item are determined based on the initial attribute information, and the washing machine is controlled to process the target item according to the processing parameters; real-time data of the target item is monitored during processing of the target item; processing parameters for the target item are dynamically adjusted based on the real-time data, and the washing machine is controlled to process the target item according to the dynamically adjusted processing parameters. This achieves adaptive processing of different items by determining and dynamically adjusting processing parameters for the target item based on the initial attribute information of the target item in the washing machine, thereby reducing wear and deformation of the target item during the washing process and extending the service life of the target item. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solution of the present invention, the accompanying drawings required for use in the description of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0020] Figure 1 is a flowchart of steps of a method for controlling a washing machine provided by some embodiments of the present invention; Figure 2 is a flowchart of steps of another method for controlling a washing machine provided by some embodiments of the present invention; Figure 3 is a flowchart of steps of another method for controlling a washing machine provided by some embodiments of the present invention; Figure 4 It is a structural block diagram of a washing machine control device provided by some embodiments of the present invention. DETAILED DESCRIPTION

[0021] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] Reference Figure 1 , shows a flowchart of a method for controlling a washing machine provided by some embodiments of the present invention, which may specifically include the following steps: Step 101, obtaining initial attribute information of a target item in the washing machine.

[0023] The target item refers to the fabric to be washed in the washing machine, such as clothes, bed sheets, towels, etc. The initial attribute information may include weaving information, material information, and thickness information.

[0024] In practical applications, weave refers to how fabrics (clothing, sheets, towels, etc.) are interwoven with yarns or fibers. Weaves can generally include plain weave (such as cotton), twill weave (such as the fabric of some jeans), satin weave (such as silk), etc. Material refers to the main substance or component that makes up an item. In fabrics, common materials include cotton, linen, silk, wool, synthetic fibers (such as polyester, nylon), etc. Different materials have different requirements for washing conditions. For example, some materials need to be washed in cold water, while others require specific detergents or washing methods. Thickness refers to the thickness of the fabric. Determining the thickness of the fabric helps adjust parameters such as washing time, water temperature, and speed to ensure the washing effect and protect the fabric.

[0025] In actual applications, after placing the target object in the washing machine, the initial attribute information of the target object can be obtained through the built-in camera and sensors of the washing machine.

[0026] In some embodiments of the present invention, the initial attribute information includes weaving method information, and obtaining the initial attribute information of the target item in the washing machine includes: obtaining image data collected by a camera for the target item in the washing machine; and determining the weaving method information of the target item based on the image data.

[0027] The image data may include visual information such as the color, texture, and shape of the target object, which is the basis for subsequent identification of the weaving method.

[0028] In actual applications, after the user adds the target item to the washing machine and starts the washing program, the user can use the built-in camera of the washing machine to photograph the target item to collect image data of the target item, and analyze the image data to determine the preparation method of the target item.

[0029] In some examples, the camera can be used to extract the surface texture, fiber structure characteristics and weaving method of the target object. For example, the surface texture of cotton fabric is relatively uniform and smooth, while the surface texture of wool fabric is relatively rough with obvious fluff. Cotton fibers are usually short and curly, while polyester fibers are long and have a smooth and flexible structure. The camera can distinguish different fiber structures by analyzing the gloss, diameter, roughness and other characteristics of the fiber through image analysis.

[0030] Weaving method: For example, the surface of a plain weave is uniform and dense, while a twill weave has a certain angle of grain. The camera can identify the weaving method such as plain weave and twill according to the arrangement of the grain on the surface of the target object (such as vertical, oblique or staggered). For example, the weaving density and method, such as plain weave and twill, can be identified by the grain, density and weaving pattern on the surface of the target object.

[0031] In some embodiments of the present invention, the initial attribute information includes material information, and obtaining the initial attribute information of the target item in the washing machine includes: obtaining spectral data collected by a spectral sensor for the target item in the washing machine; and determining the material information of the target item based on the spectral data.

[0032] The spectral data includes the intensity information of the reflected or transmitted light of the target object at different wavelengths. Since different materials have different reflection, absorption and transmission characteristics of light, by analyzing the specific features in the spectral data (such as absorption peaks, reflectivity, etc.) and combining it with the spectral characteristic library of known materials, the material information of the target object can be inferred, such as cotton, polyester, silk, etc.

[0033] As some examples, the reflection and absorption characteristics of different fabrics to light of different wavelengths can be measured by a spectral sensor to identify the chemical composition of the fabrics and determine the material information corresponding to the fabrics, thereby building a spectral characteristic library.

[0034] In actual applications, after the user adds the target item to the washing machine and starts the washing program, the target item can be measured through the built-in spectral sensor of the washing machine to collect the spectral data of the target item, and the spectral data can be analyzed according to the spectral characteristic library to determine the material information of the target item.

[0035] In some embodiments of the present invention, the attribute information includes initial thickness information, and obtaining the initial attribute information of the target item in the washing machine includes: obtaining infrared data collected by an infrared sensor for the target item in the washing machine; and determining the thickness information of the target item based on the infrared data.

[0036] Among them, infrared data can include infrared radiation intensity, temperature distribution or reflection characteristics of the fabric surface. Different object thicknesses will affect the emission and reflection characteristics of their infrared radiation. For example, thicker objects may absorb more infrared radiation, while thinner objects may allow more infrared radiation to pass through. By analyzing specific features in infrared data (such as radiation intensity, temperature gradient, etc.) and combining the known relationship or model between infrared radiation and object thickness, the thickness of the target object can be inferred.

[0037] As some examples, fabrics of different thicknesses can be tested by infrared sensors to detect the thermal reflection characteristics of the fabrics and estimate the thickness of the fibers in combination with parameters such as thermal conductivity. For example, thicker fibers will have different thermal reflection curves, and the infrared sensor estimates the thickness of the fabric by analyzing these thermal reactions and building a known relationship between infrared data and thickness.

[0038] In actual applications, after the user adds the target item to the washing machine and starts the washing program, the target item can be detected through the built-in infrared sensor of the washing machine to collect infrared data of the target item, and the infrared data can be analyzed according to known relationships to determine the thickness information of the target item.

[0039] Step 102: determining processing parameters for the target object according to the initial attribute information, and controlling the washing machine to process the target object according to the processing parameters.

[0040] In some embodiments of the present invention, processing parameters refer to various parameters that can be adjusted and controlled by the washing machine during the washing, rinsing and drying processes, and the processing parameters include any one or more of the following: washing parameters, rinsing parameters, and drying parameters.

[0041] Among them, the washing parameters include any one or more of the following: drum speed, water flow intensity, detergent concentration; the rinsing parameters include any one or more of the following: number of rinses, rinsing intensity; the drying parameters include any one or more of the following: drying temperature, drying time.

[0042] Washing parameters refer to the parameters that can be adjusted during the washing stage. Drum speed: The rotation speed of the drum affects the degree of contact between the fabric and the detergent and water during washing, as well as the penetration and decontamination ability of the detergent. Water flow intensity: The water flow intensity determines the impact force and flow speed of the water during washing, affecting the distribution of the detergent and the decontamination effect. Detergent concentration: The concentration of the detergent directly affects its decontamination ability. Too high a concentration may result in detergent residue, while too low a concentration may not effectively remove stains.

[0043] Rinse parameters refer to the parameters that can be adjusted during the rinse phase. Rinse times: The number of rinses determines the extent to which the detergent is rinsed out. Multiple rinses ensure that the detergent is thoroughly rinsed out, but it also increases water consumption and washing time. Rinse intensity: Rinse intensity affects the impact force and flow speed of water during rinsing, thereby affecting the rinsing effect. Stronger rinse intensity can more effectively rinse out residual detergent, but it may also cause additional wear and tear on fabrics.

[0044] Drying parameters refer to the parameters that can be adjusted during the drying stage. Drying temperature: Drying temperature is a key factor affecting drying speed and fabric protection. Higher temperatures can speed up drying, but may also cause heat damage or shrinkage to the fabric. Drying time: Drying time determines how long the fabric stays in the dryer. Too long or too short a drying time may affect the drying effect and fabric quality.

[0045] After obtaining the initial attribute information of the target item in the washing machine, the washing parameters (drum revolutions) for the target item can be determined, such as determining the drum speed based on the material, thickness and weaving method. Thick cotton fabrics can be set to 800-1000RPM, while thin silk fabrics can be set to 200-400RPM.

[0046] After obtaining the initial attribute information of the target item in the washing machine, the washing parameters (water flow intensity) for the target item can be determined. The water flow intensity S=f(M, T), for example, the water flow intensity is determined according to the material and thickness. Among them, cotton fabrics can use medium to high intensity water flow, while thin fibers such as silk and wool use gentle water flow to reduce friction. The water flow intensity can be controlled by the variable frequency water pump in the washing machine to meet the needs of different fibers.

[0047] After obtaining the initial attribute information of the target item in the washing machine, the washing parameters (detergent concentration) for the target item can be determined. The detergent concentration C=f(M), such as adjusting the detergent concentration according to the material, where cotton fabrics can use regular concentrations, and for silk fabrics, the system will reduce the detergent concentration to avoid fiber damage caused by excessive chemical cleaning. For example, a regular concentration of about 10ml / kg is set for cotton fabrics, while fine fibers such as silk are reduced to 5ml / kg to reduce fiber damage caused by chemical effects. The washing machine can automatically dispense detergent of the corresponding concentration from the automatic detergent box according to the fabric material.

[0048] After obtaining the initial attribute information of the target item in the washing machine, the rinsing parameters (number of rinses) for the target item can be determined, such as setting the number of rinses according to the material and thickness; for example, for thick fabrics, the number of rinses can be increased to ensure that the detergent is completely removed; for thin fabrics, the number of rinses can be reduced to reduce the risk of damage.

[0049] After obtaining the initial attribute information of the target item in the washing machine, the rinsing parameters (rinsing intensity) for the target item can be determined, such as determining the rinsing intensity based on the material and thickness; among them, cotton fabrics can be rinsed with medium to high intensity water flow, while thin fibers such as silk and wool are rinsed with gentle water flow to reduce friction. The rinsing intensity can be controlled by the variable frequency water pump in the washing machine to adapt to the needs of different fibers.

[0050] After obtaining the initial attribute information of the target item in the washing machine, the drying parameters (drying temperature, drying time) for the target item can be determined, such as dynamically adjusting the drying temperature (D) and drying time (T_d) based on the multidimensional fiber model (M, T, W); wherein the drying temperature can be a temperature range, such as a high temperature range and a low temperature range. For example, for cotton fabrics, the drying temperature is in the range of 60°C-70°C, and the drying time is about 40 minutes; the low temperature range of silk fibers is below 40°C, and the drying time does not exceed 15 minutes.

[0051] In practical applications, after the processing parameters for the target items are determined, the washing machine can be controlled to process the target items, such as washing, rinsing, and drying.

[0052] As some examples, during the dehydration phase, the system can automatically adjust the dehydration speed (R) based on the material and thickness of the fibers to avoid excessive stretching or friction on delicate fibers. For example, silk fabrics use a lower dehydration speed, while cotton fabrics use a higher speed.

[0053] As some examples, if the user adds different types of target items, such as in the case of general household laundry, a lot of clothes will be washed at a time, and there are clothes of various thicknesses and materials, the material, thickness and other information of all fabrics can be collected according to the multiple cameras and sensors in the inner drum of the washing machine, as shown in Table 1, and the fabrics are grouped through the classification algorithm to set appropriate washing parameters. The system automatically detects the material (M), thickness (T), and weaving method (W) of each piece of fabric, and then sets the drum speed and water flow intensity based on the parameters of the most fragile fabric. If necessary, the washing machine can also prompt the user to wash in batches according to material and thickness to ensure that various types of fabrics are properly protected.

[0054]

[0055] Table 1 In some embodiments of the present invention, determining the processing parameters for the target object based on the initial attribute information includes: establishing a fiber model for the target object based on the initial attribute information; the initial attribute information includes any one or more of the following: weaving method information, material information, thickness information; determining the processing parameters for the target object based on the fiber model; the processing parameters include any one or more of the following: washing parameters, rinsing parameters, drying parameters.

[0056] As some examples, a fiber model for a target object can be established based on the initial attribute information. The fiber model construction formula is as follows:

[0057] in, It is a fiber model, which represents the comprehensive properties of material (M), thickness (T), and weaving method (W); It is the RGB image data of the camera, which is used to extract surface features such as weaving pattern (W); It is the spectral data of the spectral sensor, which represents the chemical composition of the material (M) information; The thermal reflectance data from the infrared sensor is used to estimate the fiber thickness (T). By integrating these data, a multi-dimensional fiber model is established to determine and dynamically adjust the processing parameters for the target item.

[0058] As some examples, the fiber model can be a neural network model.

[0059] In some examples, the material information (M), thickness information (T), weaving method information (W), etc. of the clothes in the washing machine can be collected through the RGB image data of the camera in the washing machine, the spectral data of the spectral sensor, and the thermal reflection data of the infrared sensor. Then, the collected material information (M), thickness information (T), weaving method information (W), etc. can be input into a preset neural network model to train the neural network model, and then the corresponding fiber model can be obtained.

[0060] After establishing a fiber model for a target object, the collected initial property information can be input into the fiber model, and after being processed by the fiber model, corresponding processing parameters can be output.

[0061] As shown in Table 1, the material information (M), thickness information (T), and weaving information (W) of the clothes in the washing machine are collected. Combined with the above formula, it can be seen that by inputting the material information (M), thickness information (T), and weaving information (W) into the fiber model, the drum speed (R), water flow intensity (S), detergent concentration (C), rinse times (N) and other processing parameters can be obtained.

[0062] As shown in Table 1, for the drum speed (R), the fiber model can be calculated by combining the material information (M), thickness information (T), and weaving information (W). For the water flow intensity (S), the fiber model can be calculated by combining the material information (M) and thickness information (T). For the detergent concentration (C), the fiber model can be calculated by combining the material information (M). For the number of rinses (N), the fiber model can be calculated by combining the material information (M) and thickness information (T).

[0063] Step 103: During the process of processing the target object, monitor the real-time data of the target object.

[0064] Among them, the real-time data of the target object refers to the data information on the target object collected by the camera and sensors (spectral sensor, infrared sensor) during the processing (washing, rinsing, drying) of the washing machine, such as the real-time fiber status (M, T, W), real-time temperature, and real-time friction conditions of the target object.

[0065] Step 104: dynamically adjust the processing parameters for the target object according to the real-time data, and control the washing machine to process the target object according to the dynamically adjusted processing parameters.

[0066] In actual applications, the processing parameters for the target items can be dynamically adjusted according to real-time data, such as adjusting the drum speed, water flow intensity, detergent concentration, number of rinses, rinse intensity, drying temperature, and drying time. The target items can be washed, rinsed, and dried according to the adjusted processing parameters.

[0067] For example, during the rinsing process, the system can dynamically adjust the number of rinses (N) based on the real-time monitored fiber status (M, T, W). The rinsing intensity and number are adjusted according to the fiber model to ensure that the detergent is thoroughly rinsed and avoid secondary damage to the fiber.

[0068] In some embodiments of the present invention, before dynamically adjusting the processing parameters for the target item based on the real-time data, it also includes: judging whether the target item has a risk of damage based on the real-time data; when it is judged that the target item has a risk of damage, dynamically adjusting the processing parameters for the target item based on the real-time data.

[0069] As some examples, algorithms or empirical models can be used to assess whether a target item is likely to be damaged during processing based on real-time data. For example, if real-time data shows that fabrics are subjected to excessive mechanical forces during washing, or that certain delicate fabrics are treated at high temperatures for too long, then it is determined that these items may be at risk of damage.

[0070] In actual applications, when it is determined that the target item is at risk of damage, the processing parameters for the target item can be dynamically adjusted according to real-time data. For example, if the drum speed in the processing parameters for the target item is 800-1000RPM, when it is determined that the target item is at risk of damage, the drum speed can be dynamically adjusted to 600-800RPM.

[0071] In some embodiments of the present invention, the real-time data includes real-time fiber status, and whether the target item is at risk of damage is determined based on the real-time data, including: when it is detected that the real-time fiber status indicates that the target item has an abnormal fiber status, determining that the target item is at risk of damage; wherein the real-time fiber status is real-time attribute information of the fiber material in the target item, and the abnormal fiber status is a situation where the difference between the real-time attribute information and the initial attribute information exceeds a preset difference degree.

[0072] As some examples, real-time attribute information refers to current or immediate attribute information for a target item; a preset degree of difference may be a threshold or standard for determining when a change in fiber state is considered abnormal or normal.

[0073] In some examples, a camera inside a washing machine can periodically obtain real-time attribute information of the fiber material in a target item, and through image processing technology, compare the real-time attribute information with the initial attribute information of the target item to determine whether the difference between the real-time attribute information and the initial attribute information exceeds a preset difference degree; if it exceeds the preset difference degree, it indicates that the fiber state of the target item is abnormal, and it is determined that the target item is at risk of damage; if it does not exceed the preset difference degree, it indicates that the fiber state of the target item is not abnormal, and it is determined that the target item is not at risk of damage.

[0074] For example, the preset threshold of the degree of difference may be 20%. Through image processing technology, the image data in the initial attribute information and the real-time attribute information are analyzed, the pixel values ​​of the two images are compared, and the degree of difference is calculated. If the degree of difference is greater than the preset degree of difference, it indicates that the fiber state of the target object is abnormal; if the degree of difference is less than or equal to the preset degree of difference, it indicates that the fiber state of the target object is not abnormal.

[0075] During the washing process, the system continuously monitors the fiber status (M, T, W) of the fabric. If it detects that the fiber is at risk of damage, it can reduce the drum speed (R) of the washing machine or reduce the water flow intensity (S) to protect the fabric.

[0076] In some embodiments of the present invention, the real-time data includes real-time object temperature, and judging whether the target object is at risk of damage is performed based on the real-time data, including: when it is detected that the real-time object temperature is greater than a temperature threshold corresponding to the target object, judging that the target object is at risk of damage.

[0077] The real-time object temperature is the surface temperature of the object, such as the object surface temperature can be detected in real time by an infrared sensor. The temperature threshold corresponding to the target object is determined according to the material corresponding to the target object, and the temperature threshold of each type of object is set according to the heat resistance of the material. For example, the safe temperature range of cotton fabric is below 60°C. When the temperature exceeds this value, the system will lower the water temperature to prevent fiber shrinkage or deformation caused by high temperature. Relatively speaking, the temperature threshold of silk is lower than 30°C.

[0078] In actual applications, when it is detected that the real-time object temperature is greater than the temperature threshold corresponding to the target object, it is determined that the target object is at risk of damage. The washing machine can automatically lower the water temperature or pause washing to prevent damage to the object.

[0079] In some embodiments of the present invention, the real-time data includes real-time friction conditions, and whether the target object is at risk of damage is determined based on the real-time data, including: when it is detected that the real-time friction conditions indicate that the target object is at risk of damage, determining that the target object is at risk of damage.

[0080] As some examples, friction conditions refer to the friction conditions between target objects, since friction between fabrics is mainly caused by the fabrics contacting each other during the beating process, resulting in relative sliding and pulling, which leads to surface fuzzing, fiber stretching or local wear. The camera can be used to detect whether there is abnormal stretching or fuzzing of the fabric during rotation through image comparison and analysis. For example, the camera will compare the texture difference of the fiber surface at the beginning and during washing. If blurred texture or hair balls appear on the fiber surface, there is excessive friction, and it is determined that the target object is at risk of damage, and the drum speed or water flow intensity of the washing machine can be reduced.

[0081] In an embodiment of the present invention, initial attribute information of a target item in the washing machine is acquired; processing parameters for the target item are determined based on the initial attribute information, and the washing machine is controlled to process the target item according to the processing parameters; real-time data of the target item is monitored during processing of the target item; processing parameters for the target item are dynamically adjusted based on the real-time data, and the washing machine is controlled to process the target item according to the dynamically adjusted processing parameters. This achieves adaptive processing of different items by determining and dynamically adjusting processing parameters for the target item based on the initial attribute information of the target item in the washing machine, thereby reducing wear and deformation of the target item during the washing process and extending the service life of the target item.

[0082] The following combination Figure 2 The present invention is exemplified as follows: [1] Washing starts.

[0083] [2] Scan and analyze the fabric and establish a fiber model.

[0084] [3] Set washing parameters according to the fiber model.

[0085] [4] During the washing process, the fiber status of clothing is monitored in real time.

[0086] [5] Determine whether there is a risk of fiber damage. If so, adjust the washing parameters and proceed to [4]. If not, directly proceed to [4] until the washing process is completed.

[0087] [6] During the rinsing and dehydration phases, the fiber status of clothing is monitored in real time.

[0088] [7] Determine whether there is a risk of fiber damage. If so, reduce the rinsing intensity and dehydration speed and proceed to [6]. Otherwise, proceed directly to [6] until the rinsing and dehydration process is completed.

[0089] [8] Drying (if it is a washer-dryer).

[0090] Reference Figure 3 , shows a flowchart of another method for controlling a washing machine provided by some embodiments of the present invention, which may specifically include the following steps: Step 301, obtaining initial attribute information of the target item in the washing machine.

[0091] The target item refers to the fabric to be washed in the washing machine, such as clothes, bed sheets, towels, etc. The initial attribute information may include weaving information, material information, and thickness information.

[0092] In practical applications, weave refers to how fabrics (clothing, sheets, towels, etc.) are interwoven with yarns or fibers. Weaves can generally include plain weave (such as cotton), twill weave (such as the fabric of some jeans), satin weave (such as silk), etc. Material refers to the main substance or component that makes up an item. In fabrics, common materials include cotton, linen, silk, wool, synthetic fibers (such as polyester, nylon), etc. Different materials have different requirements for washing conditions. For example, some materials need to be washed in cold water, while others require specific detergents or washing methods. Thickness refers to the thickness of the fabric. Determining the thickness of the fabric helps adjust parameters such as washing time, water temperature, and speed to ensure the washing effect and protect the fabric.

[0093] In actual applications, after placing the target object in the washing machine, the initial attribute information of the target object can be obtained through the built-in camera and sensors of the washing machine.

[0094] In some embodiments of the present invention, the initial attribute information includes weaving method information, and obtaining the initial attribute information of the target item in the washing machine includes: obtaining image data collected by a camera for the target item in the washing machine; and determining the weaving method information of the target item based on the image data.

[0095] The image data may include visual information such as the color, texture, and shape of the target object, which is the basis for subsequent identification of the weaving method.

[0096] In actual applications, after the user adds the target item to the washing machine and starts the washing program, the user can use the built-in camera of the washing machine to photograph the target item to collect image data of the target item, and analyze the image data to determine the preparation method of the target item.

[0097] In some examples, the camera can be used to extract the surface texture, fiber structure characteristics and weaving method of the target object. For example, the surface texture of cotton fabric is relatively uniform and smooth, while the surface texture of wool fabric is relatively rough with obvious fluff. Cotton fibers are usually short and curly, while polyester fibers are long and have a smooth and flexible structure. The camera can distinguish different fiber structures by analyzing the gloss, diameter, roughness and other characteristics of the fiber through image analysis.

[0098] Weaving method: For example, the surface of a plain weave is uniform and dense, while a twill weave has a certain angle of grain. The camera can identify the weaving method such as plain weave and twill according to the arrangement of the grain on the surface of the target object (such as vertical, oblique or staggered). For example, the weaving density and method, such as plain weave and twill, can be identified by the grain, density and weaving pattern on the surface of the target object.

[0099] In some embodiments of the present invention, the initial attribute information includes material information, and obtaining the initial attribute information of the target item in the washing machine includes: obtaining spectral data collected by a spectral sensor for the target item in the washing machine; and determining the material information of the target item based on the spectral data.

[0100] The spectral data includes the intensity information of the reflected or transmitted light of the target object at different wavelengths. Since different materials have different reflection, absorption and transmission characteristics of light, by analyzing the specific features in the spectral data (such as absorption peaks, reflectivity, etc.) and combining it with the spectral characteristic library of known materials, the material information of the target object can be inferred, such as cotton, polyester, silk, etc.

[0101] As some examples, the reflection and absorption characteristics of different fabrics to light of different wavelengths can be measured by a spectral sensor to identify the chemical composition of the fabrics and determine the material information corresponding to the fabrics, thereby building a spectral characteristic library.

[0102] In actual applications, after the user adds the target item to the washing machine and starts the washing program, the target item can be measured through the built-in spectral sensor of the washing machine to collect the spectral data of the target item, and the spectral data can be analyzed according to the spectral characteristic library to determine the material information of the target item.

[0103] In some embodiments of the present invention, the initial attribute information includes thickness information, and obtaining the initial attribute information of the target item in the washing machine includes: obtaining infrared data collected by an infrared sensor for the target item in the washing machine; and determining the thickness information of the target item based on the infrared data.

[0104] Among them, infrared data can include infrared radiation intensity, temperature distribution or reflection characteristics of the fabric surface. Different object thicknesses will affect the emission and reflection characteristics of their infrared radiation. For example, thicker objects may absorb more infrared radiation, while thinner objects may allow more infrared radiation to pass through. By analyzing specific features in infrared data (such as radiation intensity, temperature gradient, etc.) and combining the known relationship or model between infrared radiation and object thickness, the thickness of the target object can be inferred.

[0105] As some examples, fabrics of different thicknesses can be tested by infrared sensors to detect the thermal reflection characteristics of the fabrics and estimate the thickness of the fibers in combination with parameters such as thermal conductivity. For example, thicker fibers will have different thermal reflection curves, and the infrared sensor estimates the thickness of the fabric by analyzing these thermal reactions and building a known relationship between infrared data and thickness.

[0106] In actual applications, after the user adds the target item to the washing machine and starts the washing program, the target item can be detected through the built-in infrared sensor of the washing machine to collect infrared data of the target item, and the infrared data can be analyzed according to known relationships to determine the thickness information of the target item.

[0107] Step 302: determining processing parameters for the target object according to the initial attribute information, and controlling the washing machine to process the target object according to the processing parameters.

[0108] In some embodiments of the present invention, the processing parameters include any one or more of the following: washing parameters, rinsing parameters, and drying parameters; wherein the washing parameters include any one or more of the following: drum speed, water flow intensity, and detergent concentration; the rinsing parameters include any one or more of the following: number of rinses and rinsing intensity; the drying parameters include any one or more of the following: drying temperature and drying time.

[0109] Among them, the washing parameters include any one or more of the following: drum speed, water flow intensity, detergent concentration; the rinsing parameters include any one or more of the following: number of rinses, rinsing intensity; the drying parameters include any one or more of the following: drying temperature, drying time.

[0110] Washing parameters refer to the parameters that can be adjusted during the washing stage. Drum speed: The rotation speed of the drum affects the degree of contact between the fabric and the detergent and water during washing, as well as the penetration and decontamination ability of the detergent. Water flow intensity: The water flow intensity determines the impact force and flow speed of the water during washing, affecting the distribution of the detergent and the decontamination effect. Detergent concentration: The concentration of the detergent directly affects its decontamination ability. Too high a concentration may result in detergent residue, while too low a concentration may not effectively remove stains.

[0111] Rinse parameters refer to the parameters that can be adjusted during the rinse phase. Rinse times: The number of rinses determines the extent to which the detergent is rinsed out. Multiple rinses ensure that the detergent is thoroughly rinsed out, but it also increases water consumption and washing time. Rinse intensity: Rinse intensity affects the impact force and flow speed of water during rinsing, thereby affecting the rinsing effect. Stronger rinse intensity can more effectively rinse out residual detergent, but it may also cause additional wear and tear on fabrics.

[0112] Drying parameters refer to the parameters that can be adjusted during the drying stage. Drying temperature: Drying temperature is a key factor affecting drying speed and fabric protection. Higher temperatures can speed up drying, but may also cause heat damage or shrinkage to the fabric. Drying time: Drying time determines how long the fabric stays in the dryer. Too long or too short a drying time may affect the drying effect and fabric quality.

[0113] After obtaining the initial attribute information of the target item in the washing machine, the washing parameters (drum revolutions) for the target item can be determined, such as determining the drum speed based on the material, thickness and weaving method. Thick cotton fabrics can be set to 800-1000RPM, while thin silk fabrics can be set to 200-400RPM.

[0114] After obtaining the initial attribute information of the target item in the washing machine, the washing parameters (water flow intensity) for the target item can be determined. The water flow intensity S=f(M, T), for example, the water flow intensity is determined according to the material and thickness. Among them, cotton fabrics can use medium to high intensity water flow, while thin fibers such as silk and wool use gentle water flow to reduce friction. The water flow intensity can be controlled by the variable frequency water pump in the washing machine to meet the needs of different fibers.

[0115] After obtaining the initial attribute information of the target item in the washing machine, the washing parameters (detergent concentration) for the target item can be determined. The detergent concentration C=f(M), such as adjusting the detergent concentration according to the material, where cotton fabrics can use regular concentrations, and for silk fabrics, the system will reduce the detergent concentration to avoid fiber damage caused by excessive chemical cleaning. For example, a regular concentration of about 10ml / kg is set for cotton fabrics, while fine fibers such as silk are reduced to 5ml / kg to reduce fiber damage caused by chemical effects. The washing machine can automatically dispense detergent of the corresponding concentration from the automatic detergent box according to the fabric material.

[0116] After obtaining the initial attribute information of the target item in the washing machine, the rinsing parameters (number of rinses) for the target item can be determined, such as setting the number of rinses according to the material and thickness; for example, for thick fabrics, the number of rinses can be increased to ensure that the detergent is completely removed; for thin fabrics, the number of rinses can be reduced to reduce the risk of damage.

[0117] After obtaining the initial attribute information of the target item in the washing machine, the rinsing parameters (rinsing intensity) for the target item can be determined, such as determining the rinsing intensity based on the material and thickness; among them, cotton fabrics can be rinsed with medium to high intensity water flow, while thin fibers such as silk and wool are rinsed with gentle water flow to reduce friction. The rinsing intensity can be controlled by the variable frequency water pump in the washing machine to adapt to the needs of different fibers.

[0118] After obtaining the initial attribute information of the target item in the washing machine, the drying parameters (drying temperature, drying time) for the target item can be determined, such as dynamically adjusting the drying temperature (D) and drying time (T_d) based on the multidimensional fiber model (M, T, W); wherein the drying temperature can be a temperature range, such as a high temperature range and a low temperature range. For example, for cotton fabrics, the drying temperature is in the range of 60°C-70°C, and the drying time is about 40 minutes; the low temperature range of silk fibers is below 40°C, and the drying time does not exceed 15 minutes.

[0119] In practical applications, after the processing parameters for the target items are determined, the washing machine can be controlled to process the target items, such as washing, rinsing, and drying.

[0120] As some examples, during the dehydration phase, the system can automatically adjust the dehydration speed (R) based on the material and thickness of the fibers to avoid excessive stretching or friction on delicate fibers. For example, silk fabrics use a lower dehydration speed, while cotton fabrics use a higher speed.

[0121] As some examples, if the user adds different types of target items, such as in the case of general household laundry, a lot of clothes will be washed at a time, and there are clothes of various thicknesses and materials, the material, thickness and other information of all fabrics can be collected according to the multiple cameras and sensors in the inner drum of the washing machine, as shown in Table 1, and the fabrics are grouped through the classification algorithm to set appropriate washing parameters. The system automatically detects the material (M), thickness (T), and weaving method (W) of each piece of fabric, and then sets the drum speed and water flow intensity based on the parameters of the most fragile fabric. If necessary, the washing machine can also prompt the user to wash in batches according to material and thickness to ensure that various types of fabrics are properly protected.

[0122]

[0123] Table 1 In some embodiments of the present invention, determining the processing parameters for the target object based on the initial attribute information includes: establishing a fiber model for the target object based on the initial attribute information; the initial attribute information includes any one or more of the following: weaving method information, material information, thickness information; determining the processing parameters for the target object based on the fiber model; the processing parameters include any one or more of the following: washing parameters, rinsing parameters, drying parameters.

[0124] As some examples, a fiber model for a target object can be established based on the initial attribute information. The fiber model construction formula is as follows:

[0125] in, It is a fiber model, which represents the comprehensive properties of material (M), thickness (T), and weaving method (W); It is the RGB image data of the camera, which is used to extract surface features such as weaving pattern (W); It is the spectral data of the spectral sensor, which represents the chemical composition of the material (M) information; The thermal reflectance data from the infrared sensor is used to estimate the fiber thickness (T). By integrating these data, a multi-dimensional fiber model is established to determine and dynamically adjust the processing parameters for the target item.

[0126] Step 303: During the process of processing the target object, monitor the real-time data of the target object.

[0127] Among them, the real-time data of the target object refers to the data information on the target object collected by the camera and sensors (spectral sensor, infrared sensor) during the processing (washing, rinsing, drying) of the washing machine, such as the real-time fiber status (M, T, W), real-time temperature, and real-time friction conditions of the target object.

[0128] Step 304: Determine whether the target object has a risk of damage based on the real-time data.

[0129] As some examples, algorithms or empirical models can be used to assess whether a target item is likely to be damaged during processing based on real-time data. For example, if real-time data shows that fabrics are subjected to excessive mechanical forces during washing, or that certain delicate fabrics are treated at high temperatures for too long, then it is determined that these items may be at risk of damage.

[0130] In actual applications, when it is determined that the target item is at risk of damage, the processing parameters for the target item can be dynamically adjusted according to real-time data. For example, if the drum speed in the processing parameters for the target item is 800-1000RPM, when it is determined that the target item is at risk of damage, the drum speed can be dynamically adjusted to 600-800RPM.

[0131] In some embodiments of the present invention, the real-time data includes real-time fiber status, and whether the target item is at risk of damage is determined based on the real-time data, including: when it is detected that the real-time fiber status indicates that the target item has an abnormal fiber status, determining that the target item is at risk of damage; wherein the real-time fiber status is real-time attribute information of the fiber material in the target item, and the abnormal fiber status is a situation where the difference between the real-time attribute information and the initial attribute information exceeds a preset difference degree.

[0132] During the washing process, the system continuously monitors the fiber status (M, T, W) of the fabric. If it detects that the fiber is at risk of damage, it can reduce the drum speed (R) of the washing machine or reduce the water flow intensity (S) to protect the fabric.

[0133] In some embodiments of the present invention, the real-time data includes real-time object temperature, and judging whether the target object is at risk of damage is performed based on the real-time data, including: when it is detected that the real-time object temperature is greater than a temperature threshold corresponding to the target object, judging that the target object is at risk of damage.

[0134] The real-time object temperature is the surface temperature of the object, such as the object surface temperature can be detected in real time by an infrared sensor. The temperature threshold corresponding to the target object is determined according to the material corresponding to the target object, and the temperature threshold of each type of object is set according to the heat resistance of the material. For example, the safe temperature range of cotton fabric is below 60°C. When the temperature exceeds this value, the system will lower the water temperature to prevent fiber shrinkage or deformation caused by high temperature. Relatively speaking, the temperature threshold of silk is lower than 30°C.

[0135] In actual applications, when it is detected that the real-time object temperature is greater than the temperature threshold corresponding to the target object, it is determined that the target object is at risk of damage. The washing machine can automatically lower the water temperature or pause washing to prevent damage to the object.

[0136] In some embodiments of the present invention, the real-time data includes real-time friction conditions, and whether the target object is at risk of damage is determined based on the real-time data, including: when it is detected that the real-time friction conditions indicate that the target object is at risk of damage, determining that the target object is at risk of damage.

[0137] As some examples, friction conditions refer to the friction conditions between target objects, since friction between fabrics is mainly caused by the fabrics contacting each other during the beating process, resulting in relative sliding and pulling, which leads to surface fuzzing, fiber stretching or local wear. The camera can be used to detect whether there is abnormal stretching or fuzzing of the fabric during rotation through image comparison and analysis. For example, the camera will compare the texture difference of the fiber surface at the beginning and during washing. If blurred texture or hair balls appear on the fiber surface, there is excessive friction, and it is determined that the target object is at risk of damage, and the drum speed or water flow intensity of the washing machine can be reduced.

[0138] Step 305, when it is determined that the target object has a risk of damage, dynamically adjust the processing parameters for the target object according to the real-time data, and control the washing machine to process the target object according to the dynamically adjusted processing parameters.

[0139] In actual applications, the processing parameters for the target items can be dynamically adjusted according to real-time data, such as adjusting the drum speed, water flow intensity, detergent concentration, number of rinses, rinse intensity, drying temperature, and drying time. The target items can be washed, rinsed, and dried according to the adjusted processing parameters.

[0140] For example, during the rinsing process, the system can dynamically adjust the number of rinses (N) based on the real-time monitored fiber status (M, T, W). The rinsing intensity and number are adjusted according to the fiber model to ensure that the detergent is thoroughly rinsed and avoid secondary damage to the fiber.

[0141] In an embodiment of the present invention, initial attribute information of a target item in the washing machine is acquired; processing parameters for the target item are determined based on the initial attribute information, and the washing machine is controlled to process the target item according to the processing parameters; real-time data of the target item is monitored during processing of the target item; processing parameters for the target item are dynamically adjusted based on the real-time data, and the washing machine is controlled to process the target item according to the dynamically adjusted processing parameters. This achieves adaptive processing of different items by determining and dynamically adjusting processing parameters for the target item based on the initial attribute information of the target item in the washing machine, thereby reducing wear and deformation of the target item during the washing process and extending the service life of the target item.

[0142] It should be noted that, for the sake of simplicity, the method embodiments are described as a series of action combinations, but those skilled in the art should be aware that the embodiments of the present invention are not limited by the order of the actions described, because according to the embodiments of the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present invention.

[0143] Reference Figure 4 , shows a schematic diagram of the structure of a washing machine control device provided by some embodiments of the present invention, which may specifically include the following modules: An initial attribute information acquisition module 401 is used to acquire initial attribute information of a target item in the washing machine; A first processing module 402, configured to determine processing parameters for the target object according to the initial attribute information, and control the washing machine to process the target object according to the processing parameters; A real-time data monitoring module 403 is used to monitor the real-time data of the target object during the process of processing the target object; The second processing module 404 is used to dynamically adjust the processing parameters for the target object according to the real-time data, and control the washing machine to process the target object according to the dynamically adjusted processing parameters.

[0144] In some embodiments of the present invention, the first processing module 402 includes: A fiber model establishment submodule is used to establish a fiber model for the target object according to the initial attribute information; the initial attribute information includes any one or more of the following: weaving method information, material information, thickness information; The first processing parameter determination submodule is used to determine the processing parameters for the target article according to the fiber model; the processing parameters include any one or more of the following: washing parameters, rinsing parameters, and drying parameters.

[0145] In some embodiments of the present invention, the device further comprises: A target object determination module, used to determine whether the target object has a risk of damage according to the real-time data; The first execution module is used to dynamically adjust the processing parameters for the target object according to the real-time data when it is determined that the target object has a damage risk.

[0146] In some embodiments of the present invention, the real-time data includes real-time fiber status, and the target object determination module is used to: When it is detected that the real-time fiber status indicates that the target object has an abnormal fiber status, it is determined that the target object is at risk of damage; wherein the real-time fiber status is real-time attribute information of the fiber material in the target object, and the abnormal fiber status is a situation where the difference between the real-time attribute information and the initial attribute information exceeds a preset difference degree.

[0147] In some embodiments of the present invention, the real-time data includes real-time object temperature, and the target object determination module is used to: When it is detected that the real-time object temperature is greater than a temperature threshold corresponding to the target object, it is determined that the target object has a risk of damage.

[0148] In some embodiments of the present invention, the real-time data includes real-time friction conditions, and the target object determination module is used to: When it is detected that the real-time friction condition indicates that the target object has excessive friction, it is determined that the target object has a risk of damage.

[0149] In some embodiments of the present invention, the attribute information acquisition module 401 includes: An image data acquisition submodule, used to acquire image data collected by a camera for a target item in the washing machine; The knitting method information determination submodule is used to determine the knitting method information of the target object according to the image data.

[0150] In some embodiments of the present invention, the attribute information acquisition module 401 includes: A spectral data acquisition submodule, used to acquire spectral data collected by a spectral sensor for a target item in the washing machine; The material information determination submodule is used to determine the material information of the target object according to the spectral data.

[0151] In some embodiments of the present invention, the attribute information acquisition module 401 includes: An infrared data acquisition submodule, used to acquire infrared data collected by an infrared sensor for a target item in the washing machine; The thickness information determination submodule is used to determine the thickness information of the target object according to the infrared data.

[0152] In some embodiments of the present invention, the processing parameters include any one or more of the following: washing parameters, rinsing parameters, and drying parameters; Among them, the washing parameters include any one or more of the following: drum speed, water flow intensity, detergent concentration; the rinsing parameters include any one or more of the following: number of rinses, rinsing intensity; the drying parameters include any one or more of the following: drying temperature, drying time.

[0153] In an embodiment of the present invention, by acquiring the attribute information of the target item in the washing machine; determining the processing parameters for the target item according to the attribute information, and controlling the washing machine to process the target item according to the processing parameters; monitoring the real-time data of the target item during the processing of the target item; dynamically adjusting the processing parameters for the target item according to the real-time data, and controlling the washing machine to process the target item according to the dynamically adjusted processing parameters, it is achieved that by determining and dynamically adjusting the processing parameters for the target item according to the attribute information of the target item in the washing machine, adaptive processing of different items is performed, the wear and deformation of the target item during the washing process is reduced, and the service life of the target item is extended.

[0154] Some embodiments of the present invention further provide an electronic device, comprising a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the above method is implemented when the computer program is executed by the processor.

[0155] Some embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored, and the computer program implements the above method when executed by a processor.

[0156] Some embodiments of the present invention further provide a computer program product, including a computer program, which implements the above method when executed by a processor.

[0157] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0158] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0159] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0160] Those skilled in the art will appreciate that the embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the embodiments of the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0161] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0162] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0163] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0164] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0165] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the above elements.

[0166] The above is a detailed introduction to the provided method, device, equipment, medium and product for controlling a washing machine. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for a person skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for controlling a washing machine, characterized in that: The method comprises: Acquiring initial attribute information of a target item in the washing machine; Determining processing parameters for the target object according to the initial attribute information, and controlling the washing machine to process the target object according to the processing parameters; During the process of processing the target object, monitoring the real-time data of the target object; Dynamically adjusting processing parameters for the target object according to the real-time data, and controlling the washing machine to process the target object according to the dynamically adjusted processing parameters; Wherein, determining the processing parameters for the target object according to the initial attribute information includes: Establishing a fiber model for the target object according to the initial attribute information; the initial attribute information includes any one or more of the following: weaving method information, material information, thickness information; According to the fiber model, processing parameters for the target article are determined; the processing parameters include any one or more of the following: washing parameters, rinsing parameters, and drying parameters.

2. The method according to claim 1, characterized in that Before dynamically adjusting the processing parameters for the target object according to the real-time data, the method further includes: Determining whether the target object has a risk of damage based on the real-time data; When it is determined that the target object has a risk of damage, dynamically adjusting the processing parameters for the target object based on the real-time data is executed.

3. The method according to claim 2, characterized in that The real-time data includes a real-time fiber state, and judging whether the target object has a risk of damage according to the real-time data includes: When it is detected that the real-time fiber status indicates that the target object has an abnormal fiber status, it is determined that the target object is at risk of damage; wherein the real-time fiber status is real-time attribute information of the fiber material in the target object, and the abnormal fiber status is a situation where the difference between the real-time attribute information and the initial attribute information exceeds a preset difference degree.

4. The method according to claim 2, characterized in that: The real-time data includes the real-time object temperature, and judging whether the target object has a risk of damage according to the real-time data includes: When it is detected that the real-time object temperature is greater than a temperature threshold corresponding to the target object, it is determined that the target object has a risk of damage.

5. The method according to claim 2, characterized in that: The real-time data includes real-time friction conditions, and judging whether the target object has a risk of damage based on the real-time data includes: When it is detected that the real-time friction condition indicates that the target object has excessive friction, it is determined that the target object has a risk of damage.

6. The method according to any one of claims 1 to 5, characterized in that: The obtaining of initial attribute information of the target item in the washing machine includes: Acquire image data collected by a camera for a target item in the washing machine; The knitting method information of the target object is determined according to the image data.

7. The method according to any one of claims 1 to 5, characterized in that: The obtaining of initial attribute information of the target item in the washing machine includes: Acquiring spectral data collected by a spectral sensor for a target item in the washing machine; The material information of the target object is determined according to the spectral data.

8. The method according to any one of claims 1 to 5, characterized in that: The obtaining of initial attribute information of the target item in the washing machine includes: Acquiring infrared data collected by an infrared sensor for a target item in the washing machine; The thickness information of the target object is determined according to the infrared data.

9. The method according to claim 1, characterized in that: The washing parameters include any one or more of the following: drum speed, water flow intensity, detergent concentration; the rinsing parameters include any one or more of the following: number of rinses, rinsing intensity; the drying parameters include any one or more of the following: drying temperature, drying time.

10. A washing machine control device, characterized in that: The device comprises: An initial attribute information acquisition module, used to acquire initial attribute information of a target item in the washing machine; A first processing module, configured to determine processing parameters for the target object according to the initial attribute information, and control the washing machine to process the target object according to the processing parameters; A real-time data monitoring module, used to monitor the real-time data of the target object during the processing of the target object; a second processing module, configured to dynamically adjust processing parameters for the target object according to the real-time data, and control the washing machine to process the target object according to the dynamically adjusted processing parameters; Wherein, the first processing module includes: A fiber model establishment submodule is used to establish a fiber model for the target object according to the initial attribute information; the initial attribute information includes any one or more of the following: weaving method information, material information, thickness information; The first processing parameter determination submodule is used to determine the processing parameters for the target article according to the fiber model; the processing parameters include any one or more of the following: washing parameters, rinsing parameters, and drying parameters.

11. An electronic device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program implements the method according to any one of claims 1 to 9 when executed by the processor.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 9 is implemented.

13. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 9.

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