Washing control method and device for dynamically adjusting water flow, medium and washing machine

Abstract

The invention provides a washing control method and device for dynamically adjusting water flow, a medium and a washing machine, and the method comprises the steps: obtaining image data and ultrasonic monitoring data of clothes in a roller of the washing machine, and carrying out the modeling of the clothes according to the image data and the ultrasonic monitoring data, and obtaining clothes distribution data; uniformly dividing the internal space of the roller to obtain a plurality of cells, and determining the proportion of the space not occupied by the clothes in each cell according to the clothes distribution data to obtain a plurality of void ratios; drawing a void ratio heat map according to the plurality of void ratios, and querying the first mapping relation according to the void ratio heat map to obtain a plurality of target control parameters; and controlling the corresponding nozzles to spray according to the target control parameters. The method solves the problem that in the prior art, dynamic adjustment of a nozzle is lacked in the washing process, and consequently clothes are damaged.

Description

Technical Field

[0001] The present invention relates to the technical field of washing machine control, and in particular to a washing control method and device for dynamically adjusting water flow, a computer-readable storage medium, and a washing machine. Background Art

[0002] The water flow control of traditional washing machines is mostly based on fixed programs, which is difficult to adapt to different clothing conditions and can easily lead to insufficient washing or fiber damage.

[0003] In order to address the above shortcomings, the prior art proposes to estimate the real-time water flow intensity based on the vibration data of the washing machine outer drum, and compare the real-time value with the preset value to adjust the water flow intensity to an appropriate range, thereby taking into account the effects of both cleaning and clothing protection.

[0004] However, the above improvements still have certain limitations. Due to the randomness of the stacking state of clothes inside the drum, the washing and water flushing strength are affected. The existing technology has not made improvements to the above shortcomings, and there is still a risk of damaging clothes. Summary of the Invention

[0005] The main purpose of this application is to provide a washing control method, device, computer-readable storage medium and washing machine with dynamic water flow regulation, so as to at least solve the problem in the prior art of lack of dynamic adjustment of the nozzle during the washing process, resulting in damage to clothes.

[0006] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a washing control method with dynamic water flow regulation is provided, including: obtaining image data and ultrasonic monitoring data of clothes in the washing machine drum, modeling the clothes according to the image data and ultrasonic monitoring data, and obtaining clothes distribution data; evenly dividing the internal space of the drum to obtain multiple cells, determining the proportion of space not occupied by clothes in each cell according to the clothes distribution data, and obtaining multiple void ratios; drawing a void ratio heat map according to the multiple void ratios, and querying a first mapping relationship according to the void ratio heat map to obtain multiple target control parameters, the first mapping relationship being a mapping relationship between the void ratio distribution heat map and the control parameters corresponding to each nozzle inside the drum, the control parameters including nozzle angle, nozzle flow and total output flow rate; controlling the corresponding nozzle to spray according to each target control parameter.

[0007] Optionally, a first mapping relationship is queried according to the void ratio heat map to obtain multiple target control parameters, including: querying a second mapping relationship according to the void ratio heat map to obtain multiple target washing parameters, the second mapping relationship is a mapping relationship between the void ratio heat map and the corresponding washing environment parameter with the highest score, the score is determined based on the stain residue and fiber damage degree of the clothes, the washing environment parameters include water flow rate, water flow scouring intensity and water flow coverage, and there is a one-to-one correspondence between the target washing parameters and the cells; querying a third mapping relationship according to each target washing parameter to obtain the corresponding target control parameter, the third mapping relationship is a mapping relationship between the washing environment parameter and the control parameter.

[0008] Optionally, before querying the second mapping relationship according to the void ratio heat map and obtaining multiple target washing parameters, the method also includes: a simulation step, taking any preset clothing distribution data as the boundary condition, the nozzle angle, the nozzle flow rate and the total output flow rate as input variables, adjusting the input variables, and performing simulation under each input variable to obtain multiple simulated washing conditions; a first determination step, determining the water flow rate, water flow scouring intensity and water flow coverage corresponding to each cell according to the simulated washing conditions to obtain washing environment parameters; a calculation step, drawing the corresponding void ratio heat map according to the clothing distribution data, determining the stain residue and fiber damage degree of the clothing according to the simulated washing conditions, and performing weighted calculation according to the stain residue and fiber damage degree to obtain a score; a second determination step, determining the washing environment parameter corresponding to the maximum score as the washing environment parameter corresponding to the void ratio heat map; repeating the simulation step, the first determination step, the calculation step and the second determination step at least once in sequence until the washing environment parameters corresponding to the void ratio heat map corresponding to all preset clothing distribution data are determined; and constructing a second mapping relationship according to the correspondence between the void ratio heat map and the washing environment parameters.

[0009] Optionally, after controlling the corresponding nozzle to spray according to each target control parameter, the method also includes: monitoring the humidity at different positions of the first cell to obtain multiple first target humidity, the first cell being any one cell; when the difference between the maximum and minimum values ​​of any first target humidity is greater than a first threshold, determining the area within a first preset distance of the humidity sensor corresponding to the first target humidity as a flushing blind area; increasing the nozzle flow of the nozzle in the flushing blind area, and adjusting the nozzle angle of the nozzle so that the nozzle is aligned with the flushing blind area; controlling the nozzle to continue spraying according to the corrected nozzle flow and nozzle angle.

[0010] Optionally, controlling the corresponding nozzles to spray according to each target control parameter also includes: dividing the cell into multiple sub-cells according to the nozzles in the cell; determining the void ratio corresponding to each sub-cell to obtain multiple target void ratios; when the target void ratio is greater than a second threshold, reducing the total output flow rate of the nozzles corresponding to the sub-cell; and controlling the nozzles to spray according to the updated total output flow rate.

[0011] Optionally, after determining the proportion of space not occupied by clothes in each cell based on the clothing distribution data and obtaining multiple void ratios, the method also includes: when the void ratio corresponding to any cell is less than a third threshold, controlling the drum to oscillate, wherein the oscillation frequency of the drum is less than or equal to a fourth threshold; when the oscillation is completed, recalculating the void ratio corresponding to each cell.

[0012] Optionally, after controlling the corresponding nozzles to spray according to each target control parameter, the method further includes: obtaining the real-time humidity of each cell for a preset spraying duration to obtain a second target humidity; determining the corresponding water flow coverage range according to the target control parameters to obtain a first target range, and determining the corresponding water flow coverage range according to the second target humidity to obtain a second target range; when the deviation ratio between the second target range and the first target range is greater than or equal to a fifth threshold, updating the third mapping relationship through a calibration experiment.

[0013] According to another aspect of the present application, a washing control device with dynamic water flow regulation is provided, and the device includes: a first acquisition unit, used to acquire image data and ultrasonic monitoring data of clothes in the washing machine drum, model the clothes according to the image data and ultrasonic monitoring data, and obtain clothes distribution data; a first determination unit, used to evenly divide the internal space of the drum to obtain multiple cells, determine the proportion of space not occupied by clothes in each cell according to the clothes distribution data, and obtain multiple void ratios; a first processing unit, used to draw a void ratio heat map according to the multiple void ratios, and query a first mapping relationship according to the void ratio heat map to obtain multiple target control parameters, the first mapping relationship being a mapping relationship between the void ratio distribution heat map and the control parameters corresponding to each nozzle inside the drum, the control parameters including nozzle angle, nozzle flow and total output flow rate; a first control unit, used to control the corresponding nozzle to spray according to each target control parameter.

[0014] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute any one of the methods described above.

[0015] According to another aspect of the present application, a washing machine is provided, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include methods for executing any one of the methods.

[0016] Applying the technical solution of the present application, in the above-mentioned washing control method with dynamic water flow regulation, first, image data and ultrasonic monitoring data of the clothes in the washing machine drum are obtained, and the clothes are modeled based on the image data and ultrasonic monitoring data to obtain clothing distribution data. Then, the internal space of the drum is evenly divided into multiple cells. The proportion of space in each cell not occupied by clothes is determined based on the clothing distribution data to obtain multiple void ratios. Then, a void ratio heat map is drawn based on the multiple void ratios, and a first mapping relationship is queried based on the void ratio heat map to obtain multiple target control parameters. The first mapping relationship is a mapping relationship between the void ratio distribution heat map and the control parameters corresponding to each nozzle in the drum. The control parameters include nozzle angle, nozzle flow rate, and total output flow rate. Finally, the corresponding nozzle is controlled to spray according to each target control parameter. This application uses a camera and an ultrasonic sensor to perform three-dimensional modeling of the clothing distribution state inside the washing machine, and draws a void ratio heat map based on the modeling data to intuitively reflect the distribution of the clothes in the washing machine. Then, the nozzle control parameters are adjusted based on the void ratio heat map to achieve dynamic regulation of the washing water flow. This solves the problem of the lack of dynamic nozzle adjustment during the washing process in the prior art, which causes damage to the clothes. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A hardware structure block diagram of a mobile terminal according to a washing control method with dynamic water flow regulation provided in an embodiment of the present application is shown;

[0018] Figure 2 A schematic flow chart of a washing control method with dynamic water flow regulation according to an embodiment of the present application is shown;

[0019] Figure 3 A structural block diagram of a washing control device with dynamic water flow regulation provided according to an embodiment of the present application is shown.

[0020] The above drawings include the following reference numerals:

[0021] 102. Processor; 104. Memory; 106. Transmission device; 108. Input / output device. DETAILED DESCRIPTION

[0022] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0023] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0024] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0025] As introduced in the background technology, the randomness of the stacking state of clothes inside the drum affects both the washing and the flushing force of the water flow. The existing technology has not made improvements to the above-mentioned shortcomings, and there is still a risk of damaging clothes. In order to solve the problem of lack of dynamic adjustment of the nozzle during the washing process in the existing technology, which leads to damage to clothes, the embodiments of the present application provide a washing control method, device, computer-readable storage medium and washing machine with dynamic water flow adjustment.

[0026] The technical solutions in the embodiments of the present invention will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present invention.

[0027] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 This is a hardware structure block diagram of a mobile terminal for a washing control method with dynamic water flow regulation according to an embodiment of the present invention. Figure 1 As shown, the mobile terminal may include one or more ( Figure 1 Only one is shown) a processor 102 (the processor 102 may include but is not limited to a microprocessor MCU or a programmable logic device FPGA and other processing devices) and a memory 104 for storing data, wherein the mobile terminal may also include a transmission device 106 and an input and output device 108 for communication functions. It will be understood by those skilled in the art that Figure 1The structure shown is only for illustration and does not limit the structure of the mobile terminal. Figure 1 More or fewer components than shown, or with Figure 1 Different configurations shown.

[0028] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the washing control method for dynamic water flow regulation in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the computer programs stored in the memory 104, that is, implementing the above-mentioned method. The memory 104 may include a high-speed random access memory and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely located relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of the above-mentioned networks include but are not limited to the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof. The transmission device 106 is used to receive or send data via a network. Specific examples of the above-mentioned networks may include wireless networks provided by the mobile terminal's communication provider. In one example, the transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0029] In this embodiment, a washing control method for dynamic adjustment of water flow running on a mobile terminal, a computer terminal or a similar computing device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0030] Figure 2 FIG. 1 is a flow chart of a washing control method for dynamically adjusting water flow according to an embodiment of the present application. Figure 2 As shown, the method includes the following steps:

[0031] Step S201, obtaining image data and ultrasonic monitoring data of clothes in the drum of a washing machine, modeling the clothes based on the image data and ultrasonic monitoring data, and obtaining clothes distribution data;

[0032] Specifically, the washing machine's built-in miniature camera captures the distribution of clothing inside the drum in real time, and computer vision technology identifies the position, shape, and stacking of clothing. Furthermore, an ultrasonic sensor array measures the distances between various areas of clothing. Combined with the total volume of the drum, the actual volume and distribution of clothing are estimated. The image data and ultrasonic monitoring data are then used to interrelate and correct each other, constructing a three-dimensional model of the clothing distribution to generate the aforementioned clothing distribution data.

[0033] Step S202: Evenly divide the internal space of the drum into a plurality of cells, and determine the proportion of space not occupied by clothes in each cell based on the clothes distribution data to obtain a plurality of void ratios;

[0034] Specifically, the internal space of the drum is evenly divided to form a grid cell matrix, and the void ratio (φ) of each cell is calculated, that is, the proportion of the space volume in the area not occupied by clothes, reflecting the possible water flow penetration and cleaning efficiency.

[0035] The calculation formula of the above void ratio is as follows:

[0036]

[0037] in, is the local void fraction, The volume occupied by the local clothing, is the local drum volume within the cell.

[0038] Step S203: Draw a void ratio heat map based on the multiple void ratios, and query a first mapping relationship based on the void ratio heat map to obtain multiple target control parameters. The first mapping relationship is a mapping relationship between the void ratio distribution heat map and the control parameters corresponding to each nozzle inside the drum. The control parameters include nozzle angle, nozzle flow rate, and total output flow rate.

[0039] Specifically, based on the calculated porosity data, a two-dimensional heat map of the drum interior is generated, where colors (e.g., red, yellow, and green) represent the difficulty of water penetration at different porosity levels. Specifically, red areas (φ < 0.2) in the heat map indicate densely packed clothing, making it difficult for water to penetrate; green areas (φ > 0.6) indicate sparsely distributed clothing, allowing for good water penetration. Using a pre-built offline CFD simulation dataset, the flow field characteristics within the drum at different porosity distributions are mapped to the optimal control parameters for each nozzle, forming a mapping table or model, the aforementioned first mapping relationship. Based on the porosity heat map, the system queries this first mapping relationship to determine the target control parameters for each nozzle (nozzle angle θ, flow rate qᵢ, and total output flow rate v).

[0040] Step S204: Control the corresponding nozzles to spray according to the target control parameters.

[0041] Specifically, the adjustment of nozzle angle and flow rate directly affects the nozzle, while the change of total output flow rate is achieved by controlling the water pump power to ensure that each nozzle sprays according to the optimal parameters.

[0042] It can be understood that the above embodiment uses multi-source sensor data (image data and ultrasonic monitoring data) to perform real-time and accurate modeling of the distribution of clothes in the drum, obtains the porosity of each cell by calculation, and dynamically adjusts the control parameters of the nozzle based on the pre-trained CFD working condition library, including the nozzle angle, nozzle flow and the total output flow rate of the water pump, to optimize the water flow coverage and flushing intensity, and achieve efficient and safe washing effects.

[0043] This embodiment first obtains image data and ultrasonic monitoring data of the clothing inside the washing machine drum. Based on the image data and ultrasonic monitoring data, the clothing is modeled to obtain clothing distribution data. The internal space of the drum is then evenly divided into multiple cells. The proportion of space in each cell not occupied by clothing is determined based on the clothing distribution data to obtain multiple void ratios. A void ratio heat map is then plotted based on the multiple void ratios. A first mapping relationship is then queried based on the void ratio heat map to obtain multiple target control parameters. The first mapping relationship is a mapping relationship between the void ratio distribution heat map and control parameters corresponding to each nozzle inside the drum. The control parameters include nozzle angle, nozzle flow rate, and total output flow rate. Finally, the corresponding nozzle is controlled to spray based on each target control parameter. This application uses a camera and ultrasonic sensor to perform three-dimensional modeling of the clothing distribution inside the washing machine. Based on the modeled data, a void ratio heat map is plotted to visually reflect the distribution of clothing inside the washing machine. The nozzle control parameters are then adjusted based on the void ratio heat map to achieve dynamic adjustment of the wash water flow. This solves the problem of the prior art lacking dynamic nozzle adjustment during the washing process, which can lead to clothing damage.

[0044] In order to obtain the target control parameters, in an optional implementation, step S203 includes:

[0045] Step S2031: Querying a second mapping relationship based on the void ratio heat map to obtain multiple target washing parameters. The second mapping relationship is a mapping relationship between the void ratio heat map and the corresponding washing environment parameter with the highest score. The score is determined based on the degree of stain residue and fiber damage on the clothes. The washing environment parameters include water flow rate, water flow intensity, and water flow coverage. There is a one-to-one correspondence between the target washing parameters and the cells.

[0046] Specifically, based on CFD simulation and experimental test data, a database is established to record the optimal washing environment parameters (water flow rate, water flow intensity, and water flow coverage) that can be achieved under different porosity distributions, namely the second mapping relationship mentioned above.

[0047] It is understood that for a given porosity distribution, the system will evaluate multiple possible water flow conditions and give a comprehensive score based on the degree of stain residue and fiber damage on the clothes. A high score means that the damage to the clothes is minimized while ensuring the cleaning effect.

[0048] Step S2032: query the third mapping relationship according to each target washing parameter to obtain the corresponding target control parameter. The third mapping relationship is a mapping relationship between the washing environment parameter and the control parameter.

[0049] Specifically, based on historical data and empirical formulas, a set of conversion rules from washing environment parameters to specific working parameters of the nozzle and water pump (nozzle angle, flow rate, water pump power, etc.) were established, namely the third mapping relationship mentioned above.

[0050] The above embodiment intelligently adjusts washing and control parameters through real-time analysis of the distribution of clothing within the drum, ensuring optimal washing performance while minimizing fiber damage. The core of this approach is the multi-level mapping of void ratio heat maps, guided by a pre-set scoring mechanism to select optimal washing environment parameters. These parameters are then used to adjust the operating conditions of the nozzles and water pump, achieving refined washing control.

[0051] In order to construct the second mapping relationship, in an optional embodiment, before querying the second mapping relationship according to the porosity heat map to obtain a plurality of target washing parameters, the method further includes:

[0052] Step S301, a simulation step, using any preset clothing distribution data as a boundary condition, and using the nozzle angle, nozzle flow rate, and total output flow rate as input variables, adjusting the input variables and performing simulation under each input variable to obtain multiple simulated washing conditions;

[0053] Step S302, a first determination step, determines the water flow rate, water flow intensity, and water flow coverage corresponding to each cell according to the simulated washing conditions to obtain washing environment parameters;

[0054] Step S303, a calculation step, plotting a corresponding porosity heat map based on the clothing distribution data, determining the degree of stain residue and fiber damage of the clothing based on the simulated washing conditions, and performing a weighted calculation based on the degree of stain residue and fiber damage to obtain a score;

[0055] Step S304, a second determination step, determining the washing environment parameter corresponding to the maximum score as the washing environment parameter corresponding to the porosity heat map;

[0056] Step S305, repeating the simulation step, the first determination step, the calculation step, and the second determination step at least once in sequence until the washing environment parameters corresponding to the void ratio heat maps corresponding to all preset clothing distribution data are determined;

[0057] Specifically, a series of typical clothing stacking configurations were selected as boundary conditions, representing different void fraction distributions. The nozzle angle θ, nozzle flow rate qᵢ, and total output flow rate v were used as CFD simulation input variables. By varying these parameters, multiple simulation rounds were conducted to explore washing conditions under different combinations. Each simulation round outputs data on the water flow rate, water flow intensity, and water flow coverage within the drum, based on the current input variable combination, generating multiple simulated washing conditions. After each simulation round, the washing environment parameters matching the preset clothing distribution data were determined, including the specific water flow rate, water flow intensity, and water flow coverage. Based on the actual or preset clothing distribution data, a corresponding void fraction heat map φ was calculated. The results of each simulation were analyzed to quantify the degree of soiling and fiber damage. For example, the impact of the water flow on the clothing surface and the material properties of the clothing were analyzed to estimate the likelihood of fiber damage. A weighted algorithm was used to calculate a score for each condition, combining the degree of soiling and fiber damage. A high score indicates that the clothes are cleaned with minimal damage to the fibers. From the simulation results of multiple iterations, the washing environment parameters with the highest scores were selected and used as the optimal parameter configuration corresponding to the void ratio heat map.

[0058] Step S306 : constructing a second mapping relationship based on the correspondence between the porosity thermal map and the washing environment parameters.

[0059] Specifically, the above steps are repeated at least once for all preset clothing distribution data until the highest-scoring washing environment parameter combination is found for each typical void ratio distribution. All void ratio heat maps are associated with their corresponding high-scoring washing environment parameters to form a second mapping relationship.

[0060] Through the above embodiment, computational fluid dynamics (CFD) simulation technology is used to predict and optimize the washing effect of the drum washing machine under different clothing distribution conditions. Through multiple rounds of iterative simulation, combined with the porosity heat map and the quantitative evaluation of stain residue and fiber damage degree, an efficient and safe mapping relationship between washing environment parameters and control parameters is finally established.

[0061] In order to prevent poor washing effects in some blind areas, in an optional embodiment, after controlling the corresponding nozzles to spray according to each target control parameter, the method further includes:

[0062] Step S402, monitoring the humidity at different positions of a first cell to obtain a plurality of first target humidity, where the first cell is any cell;

[0063] Specifically, the humidity sensor installed inside the drum can monitor the humidity at different positions of the first cell (ie, any divided unit area) to obtain a series of first target humidity values.

[0064] Step S403: when the difference between the maximum and minimum values ​​of any first target humidity is greater than a first threshold, determining an area within a first preset distance of the humidity sensor corresponding to the first target humidity as a flushing blind area;

[0065] Specifically, the system uses the collected humidity data to calculate the difference between the maximum and minimum humidity values ​​within a cell and determines whether it exceeds a preset first threshold. This threshold is used to identify the presence of a blind flushing zone. If the difference exceeds the first threshold, the system deems the blind flushing zone to be present—the area with the lowest humidity. The humidity sensor's location information can be used to determine the specific location of this blind flushing zone within the drum.

[0066] Step S404, increasing the nozzle flow rate of the nozzle in the flushing blind area, and adjusting the nozzle angle of the nozzle so that the nozzle is aligned with the flushing blind area;

[0067] Specifically, after identifying the flushing blind area, the nozzle flow rate qᵢ of the nozzle in this area is automatically increased, and the nozzle angle θ is fine-tuned to ensure that the water flow can accurately and powerfully impact the blind area, increasing the water's penetration and coverage.

[0068] Step S405: Control the nozzle to continue spraying according to the corrected nozzle flow and nozzle angle.

[0069] Specifically, based on the adjusted flow rate and angle, the system recalculates the spray control strategy to ensure that the water flow can effectively cover and flush the blind spots.

[0070] The above-described embodiment intelligently detects and eliminates potential blind spots during the wash process by monitoring humidity changes in each cell within the drum in real time, ensuring that all areas of clothing receive even and adequate water flow. This technology relies on high-precision humidity sensors and the ability to dynamically adjust nozzle angle and flow rate based on these monitoring results to achieve effective localized rinsing.

[0071] In order to prevent damage to clothing, in an optional embodiment, the above step S204 further includes:

[0072] Step S2041 , dividing the cell into multiple sub-cells according to the nozzles in the cell;

[0073] Specifically, in addition to the original uniform division, this solution further subdivides the cell containing the nozzle into multiple smaller sub-cells to facilitate more precise control of the water flow.

[0074] Step S2042, determining the void ratio corresponding to each sub-cell to obtain multiple target void ratios;

[0075] Specifically, the void ratio φ of each sub-cell is calculated in real time, where φ reflects the proportion of space in the area not occupied by clothes.

[0076] Step S2043: when the target void ratio is greater than the second threshold, reducing the total output flow rate of the nozzle corresponding to the sub-cell;

[0077] Specifically, when the target void ratio is greater than or equal to the second threshold value (0.8), the total output flow rate of the corresponding nozzle is reduced to prevent the local impact from being too strong and damaging the clothes.

[0078] Step S2044: Control the nozzle to spray according to the updated total output flow rate.

[0079] Specifically, based on the adjusted flow rate, the system recalculates the sprinkler control strategy to ensure appropriate water flow.

[0080] Through the above embodiments, more refined water flow control is performed based on the porosity of the sub-cells, aiming to avoid excessive water flow in areas where clothes are sparsely distributed, thereby reducing damage to clothes while ensuring the washing effect.

[0081] To improve the washing effect, in an optional embodiment, after determining the proportion of space not occupied by clothes in each cell based on the clothes distribution data to obtain multiple void ratios, the method further includes:

[0082] Step S501: When the void ratio corresponding to any cell is less than a third threshold, the drum is controlled to oscillate, wherein the oscillation frequency of the drum is less than or equal to a fourth threshold;

[0083] Specifically, after generating the porosity heat map, if a cell's porosity φ is found to be below a third threshold (for example, set to 0.2), it indicates that the clothes are stacked too tightly, hindering water penetration. The drum's oscillation mechanism is then activated, using a built-in vibration motor or adjusting the drum's rotation mode to oscillate at a frequency less than or equal to a fourth threshold. The fourth threshold (for example, set to 5 Hz) ensures that the drum's vibration is not too intense, preventing damage to clothing fibers or the washing machine's structure.

[0084] Step S502: After the oscillation is completed, the void ratio corresponding to each cell is recalculated.

[0085] Specifically, after the drum oscillates, the system recalculates the porosity of each cell. This rebalancing improves the distribution of tightly packed clothing, potentially raising the porosity to a level more conducive to water penetration.

[0086] Through the above-mentioned embodiments, during the operation of a drum washing machine, the distribution of clothing within the drum directly affects water permeability and washing efficiency. When clothing is too dense, that is, when the porosity of a cell is below the third threshold, water cannot fully penetrate the clothing, resulting in poor washing results. This solution introduces a drum oscillation mechanism to improve clothing distribution and increase porosity while ensuring that clothing fibers are not damaged, thereby optimizing water coverage and cleaning efficiency during the washing process. The oscillation frequency is designed to be below the fourth threshold to prevent adverse effects on clothing or the washing machine structure.

[0087] In order to ensure the accuracy of the above target control parameters, after controlling the corresponding nozzles to spray according to each target control parameter, the above method further includes:

[0088] Step S601: obtain the real-time humidity of each cell for a preset spraying time to obtain a second target humidity;

[0089] Specifically, during the spraying process of the drum washing machine, the humidity sensor measures and records the real-time humidity of each cell every preset spraying time (for example, every 2 minutes) to obtain the second target humidity H2.

[0090] Step S602: determining a corresponding water flow coverage range according to the target control parameter to obtain a first target range, and determining a corresponding water flow coverage range according to the second target humidity to obtain a second target range;

[0091] Specifically, based on the current target control parameters, the system can calculate the theoretically achievable water flow coverage, i.e., the first target range C1. Based on the distribution of the second target humidity H2, the system can estimate the actual achievable water flow coverage, i.e., the second target range C2.

[0092] Step S603 : When the deviation ratio between the second target range and the first target range is greater than or equal to a fifth threshold, the third mapping relationship is updated through a calibration experiment.

[0093] Specifically, the system calculates the deviation ratio ΔC between the second target range C2 and the first target range C1 to assess the degree of match between the actual moisture distribution and the theoretical coverage range. If the deviation ratio ΔC is greater than or equal to a fifth threshold (assuming 10%), the system deems that there is a significant mismatch between the current nozzle control parameters and the actual water flow distribution, and a calibration experiment is required to update the third mapping relationship.

[0094] Through the above-described embodiment, by monitoring real-time humidity during the spraying process and comparing the preset water flow coverage with the actual humidity coverage, the nozzle control parameters are dynamically adjusted to achieve optimal water flow distribution. If a significant deviation between the actual humidity coverage and the preset range is detected, i.e., the deviation ratio is greater than or equal to the fifth threshold, the system will initiate a calibration experiment and update the third mapping relationship, i.e., the mapping table between nozzle control parameters and water flow coverage, to more accurately guide subsequent spray control.

[0095] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0096] The embodiment of the present application also provides a washing control device for dynamic water flow regulation. It should be noted that the washing control device for dynamic water flow regulation of the embodiment of the present application can be used to execute the washing control method for dynamic water flow regulation provided by the embodiment of the present application. The device is used to implement the above-mentioned embodiments and preferred embodiments, and the details that have been described will not be repeated here. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived.

[0097] The following introduces the washing control device with dynamic water flow regulation provided in the embodiment of the present application.

[0098] Figure 3 : is a structural block diagram of a washing control device for dynamic water flow regulation according to an embodiment of the present application. Figure 3 As shown, the device includes:

[0099] A first acquisition unit 10 is configured to acquire image data and ultrasonic monitoring data of clothes in the drum of the washing machine, model the clothes based on the image data and ultrasonic monitoring data, and obtain clothes distribution data;

[0100] Specifically, the washing machine's built-in miniature camera captures the distribution of clothing inside the drum in real time, and computer vision technology identifies the position, shape, and stacking of clothing. Furthermore, an ultrasonic sensor array measures the distances between various areas of clothing. Combined with the total volume of the drum, the actual volume and distribution of clothing are estimated. The image data and ultrasonic monitoring data are then used to interrelate and correct each other, constructing a three-dimensional model of the clothing distribution to generate the aforementioned clothing distribution data.

[0101] The first determining unit 20 is configured to evenly divide the internal space of the drum into a plurality of cells, and determine the proportion of space not occupied by clothes in each cell according to the clothes distribution data to obtain a plurality of void ratios;

[0102] Specifically, the internal space of the drum is evenly divided to form a grid cell matrix, and the void ratio (φ) of each cell is calculated, that is, the proportion of the space volume in the area not occupied by clothes, reflecting the possible water flow penetration and cleaning efficiency.

[0103] The calculation formula of the above void ratio is as follows:

[0104]

[0105] in, is the local void fraction, The volume occupied by the local clothing, is the local drum volume within the cell.

[0106] A first processing unit 30 is configured to draw a void ratio heat map based on the plurality of void ratios, and query a first mapping relationship based on the void ratio heat map to obtain a plurality of target control parameters. The first mapping relationship is a mapping relationship between the void ratio distribution heat map and control parameters corresponding to each nozzle in the drum. The control parameters include nozzle angle, nozzle flow rate, and total output flow rate.

[0107] Specifically, based on the calculated porosity data, a two-dimensional heat map of the drum interior is generated, where colors (e.g., red, yellow, and green) represent the difficulty of water penetration at different porosity levels. Specifically, red areas (φ < 0.2) in the heat map indicate densely packed clothing, making it difficult for water to penetrate; green areas (φ > 0.6) indicate sparsely distributed clothing, allowing for good water penetration. Using a pre-built offline CFD simulation dataset, the flow field characteristics within the drum at different porosity distributions are mapped to the optimal control parameters for each nozzle, forming a mapping table or model, the aforementioned first mapping relationship. Based on the porosity heat map, the system queries this first mapping relationship to determine the target control parameters for each nozzle (nozzle angle θ, flow rate qᵢ, and total output flow rate v).

[0108] The first control unit 40 is used to control the corresponding nozzles to spray according to each target control parameter.

[0109] Specifically, the adjustment of nozzle angle and flow rate directly affects the nozzle, while the change of total output flow rate is achieved by controlling the water pump power to ensure that each nozzle sprays according to the optimal parameters.

[0110] It can be understood that the above embodiment uses multi-source sensor data (image data and ultrasonic monitoring data) to perform real-time and accurate modeling of the distribution of clothes in the drum, obtains the porosity of each cell by calculation, and dynamically adjusts the control parameters of the nozzle based on the pre-trained CFD working condition library, including the nozzle angle, nozzle flow and the total output flow rate of the water pump, to optimize the water flow coverage and flushing intensity, and achieve efficient and safe washing effects.

[0111] In this embodiment, a first acquisition unit acquires image data and ultrasonic monitoring data of clothing within the washing machine drum, models the clothing based on the image data and ultrasonic monitoring data, and obtains clothing distribution data. A first determination unit evenly divides the internal space of the drum into multiple cells, determines the proportion of space in each cell not occupied by clothing based on the clothing distribution data, and obtains multiple void ratios. A first processing unit draws a void ratio heat map based on the multiple void ratios, and queries a first mapping relationship based on the void ratio heat map to obtain multiple target control parameters. The first mapping relationship is a mapping relationship between the void ratio distribution heat map and control parameters corresponding to each nozzle within the drum, including nozzle angle, nozzle flow rate, and total output flow rate. The first control unit controls the corresponding nozzle to spray based on each target control parameter. This application uses a camera and an ultrasonic sensor to perform three-dimensional modeling of the clothing distribution state within the washing machine, and draws a void ratio heat map based on the modeling data to intuitively reflect the distribution of clothing within the washing machine. The nozzle control parameters are then adjusted based on the void ratio heat map, achieving dynamic adjustment of the wash water flow. This solves the problem of the prior art lack of dynamic nozzle adjustment during the washing process, which causes clothing damage.

[0112] In order to obtain the target control parameter, in an optional embodiment, the first processing unit includes:

[0113] a first query module configured to query a second mapping relationship based on the void ratio heat map to obtain a plurality of target washing parameters, wherein the second mapping relationship is a mapping relationship between the void ratio heat map and the corresponding washing environment parameter with the highest score, where the score is determined based on the degree of stain residue and fiber damage on the clothing. The washing environment parameters include water flow rate, water flow intensity, and water flow coverage, and there is a one-to-one correspondence between the target washing parameters and the cells;

[0114] Specifically, based on CFD simulation and experimental test data, a database is established to record the optimal washing environment parameters (water flow rate, water flow intensity, and water flow coverage) that can be achieved under different porosity distributions, namely the second mapping relationship mentioned above.

[0115] It is understood that for a given porosity distribution, the system will evaluate multiple possible water flow conditions and give a comprehensive score based on the degree of stain residue and fiber damage on the clothes. A high score means that the damage to the clothes is minimized while ensuring the cleaning effect.

[0116] The second query module is used to query the third mapping relationship according to each target washing parameter to obtain the corresponding target control parameter. The third mapping relationship is a mapping relationship between the washing environment parameter and the control parameter.

[0117] Specifically, based on historical data and empirical formulas, a set of conversion rules from washing environment parameters to specific working parameters of the nozzle and water pump (nozzle angle, flow rate, water pump power, etc.) were established, namely the third mapping relationship mentioned above.

[0118] The above embodiment intelligently adjusts washing and control parameters through real-time analysis of the distribution of clothing within the drum, ensuring optimal washing performance while minimizing fiber damage. The core of this approach is the multi-level mapping of void ratio heat maps, guided by a pre-set scoring mechanism to select optimal washing environment parameters. These parameters are then used to adjust the operating conditions of the nozzles and water pump, achieving refined washing control.

[0119] In order to construct the second mapping relationship, in an optional implementation manner, the apparatus further includes:

[0120] a simulation unit configured to, before querying the second mapping relationship based on the void ratio heat map to obtain a plurality of target washing parameters, execute a simulation step, using any preset clothing distribution data as a boundary condition, the nozzle angle, the nozzle flow rate, and the total output flow rate as input variables, adjust the input variables, and perform simulation under each input variable to obtain a plurality of simulated washing conditions;

[0121] a second determining unit, configured to execute the first determining step, determine the water flow rate, water flow intensity, and water flow coverage corresponding to each cell according to the simulated washing condition, and obtain washing environment parameters;

[0122] a calculation unit, configured to execute a calculation step, draw a corresponding porosity heat map based on the clothing distribution data, determine the degree of stain residue and fiber damage of the clothing based on a simulated washing condition, and perform a weighted calculation based on the degree of stain residue and fiber damage to obtain a score;

[0123] a third determining unit, configured to execute the second determining step, and determine the washing environment parameter corresponding to the maximum score as the washing environment parameter corresponding to the porosity heat map;

[0124] a repeating unit, configured to sequentially repeat the simulation step, the first determination step, the calculation step, and the second determination step at least once until the washing environment parameters corresponding to the void ratio heat maps corresponding to all preset clothing distribution data are determined;

[0125] Specifically, a series of typical clothing stacking configurations were selected as boundary conditions, representing different void fraction distributions. The nozzle angle θ, nozzle flow rate qᵢ, and total output flow rate v were used as CFD simulation input variables. By varying these parameters, multiple simulation rounds were conducted to explore washing conditions under different combinations. Each simulation round outputs data on the water flow rate, water flow intensity, and water flow coverage within the drum, based on the current input variable combination, generating multiple simulated washing conditions. After each simulation round, the washing environment parameters matching the preset clothing distribution data were determined, including the specific water flow rate, water flow intensity, and water flow coverage. Based on the actual or preset clothing distribution data, a corresponding void fraction heat map φ was calculated. The results of each simulation were analyzed to quantify the degree of soiling and fiber damage. For example, the impact of the water flow on the clothing surface and the material properties of the clothing were analyzed to estimate the likelihood of fiber damage. A weighted algorithm was used to calculate a score for each condition, combining the degree of soiling and fiber damage. A high score indicates that the clothes are cleaned with minimal damage to the fibers. From the simulation results of multiple iterations, the washing environment parameters with the highest scores were selected and used as the optimal parameter configuration corresponding to the void ratio heat map.

[0126] A construction unit is used to construct a second mapping relationship according to the corresponding relationship between the porosity thermal map and the washing environment parameters.

[0127] Specifically, the above steps are repeated at least once for all preset clothing distribution data until the highest-scoring washing environment parameter combination is found for each typical void ratio distribution. All void ratio heat maps are associated with their corresponding high-scoring washing environment parameters to form a second mapping relationship.

[0128] Through the above embodiment, computational fluid dynamics (CFD) simulation technology is used to predict and optimize the washing effect of the drum washing machine under different clothing distribution conditions. Through multiple rounds of iterative simulation, combined with the porosity heat map and the quantitative evaluation of stain residue and fiber damage degree, an efficient and safe mapping relationship between washing environment parameters and control parameters is finally established.

[0129] In order to prevent poor washing effect in some blind areas, in an optional embodiment, the above device further includes:

[0130] a second acquisition unit, configured to monitor the humidity at different positions of the first cell after controlling the corresponding nozzle to spray according to each target control parameter, to obtain a plurality of first target humidity, where the first cell is any one cell;

[0131] Specifically, the humidity sensor installed inside the drum can monitor the humidity at different positions of the first cell (ie, any divided unit area) to obtain a series of first target humidity values.

[0132] a fourth determining unit, configured to determine, when a difference between a maximum value and a minimum value of any first target humidity is greater than a first threshold, an area within a first preset distance from the humidity sensor corresponding to the first target humidity as a flushing blind area;

[0133] Specifically, the system uses the collected humidity data to calculate the difference between the maximum and minimum humidity values ​​within a cell and determines whether it exceeds a preset first threshold. This threshold is used to identify the presence of a blind flushing zone. If the difference exceeds the first threshold, the system deems the blind flushing zone to be present—the area with the lowest humidity. The humidity sensor's location information can be used to determine the specific location of this blind flushing zone within the drum.

[0134] a second processing unit for increasing the nozzle flow rate of the nozzle in the flushing blind area and adjusting the nozzle angle of the nozzle so that the nozzle is aligned with the flushing blind area;

[0135] Specifically, after identifying the flushing blind area, the nozzle flow rate qᵢ of the nozzle in this area is automatically increased, and the nozzle angle θ is fine-tuned to ensure that the water flow can accurately and powerfully impact the blind area, increasing the water's penetration and coverage.

[0136] The second control unit is used to control the nozzle to continue spraying according to the corrected nozzle flow and nozzle angle.

[0137] Specifically, based on the adjusted flow rate and angle, the system recalculates the spray control strategy to ensure that the water flow can effectively cover and flush the blind spots.

[0138] The above-described embodiment intelligently detects and eliminates potential blind spots during the wash process by monitoring humidity changes in each cell within the drum in real time, ensuring that all areas of clothing receive even and adequate water flow. This technology relies on high-precision humidity sensors and the ability to dynamically adjust nozzle angle and flow rate based on these monitoring results to achieve effective localized rinsing.

[0139] In order to prevent damage to clothing, in an optional embodiment, the first control unit further includes:

[0140] a processing module, for dividing a cell into a plurality of sub-cells according to the nozzles in the cell;

[0141] Specifically, in addition to the original uniform division, this solution further subdivides the cell containing the nozzle into multiple smaller sub-cells to facilitate more precise control of the water flow.

[0142] A determination module is used to determine the void ratio corresponding to each sub-cell to obtain multiple target void ratios;

[0143] Specifically, the void ratio φ of each sub-cell is calculated in real time, where φ reflects the proportion of space in the area not occupied by clothes.

[0144] an adjusting module, configured to reduce a total output flow rate of the nozzles corresponding to the sub-cells when the target void ratio is greater than a second threshold value;

[0145] Specifically, when the target void ratio is greater than or equal to the second threshold value (0.8), the total output flow rate of the corresponding nozzle is reduced to prevent the local impact from being too strong and damaging the clothes.

[0146] The control module is used for controlling the nozzles to spray according to the updated total output flow rate.

[0147] Specifically, based on the adjusted flow rate, the system recalculates the sprinkler control strategy to ensure appropriate water flow.

[0148] Through the above embodiments, more refined water flow control is performed based on the porosity of the sub-cells, aiming to avoid excessive water flow in areas where clothes are sparsely distributed, thereby reducing damage to clothes while ensuring the washing effect.

[0149] In order to improve the washing effect, in an optional embodiment, the above device further includes:

[0150] a third control unit, configured to determine, based on the clothing distribution data, a ratio of space not occupied by clothing in each cell to obtain a plurality of void ratios, and, if the void ratio corresponding to any cell is less than a third threshold, control the drum to oscillate, wherein the oscillation frequency of the drum is less than or equal to a fourth threshold;

[0151] Specifically, after generating the porosity heat map, if a cell's porosity φ is found to be below a third threshold (for example, set to 0.2), it indicates that the clothes are stacked too tightly, hindering water penetration. The drum's oscillation mechanism is then activated, using a built-in vibration motor or adjusting the drum's rotation mode to oscillate at a frequency less than or equal to a fourth threshold. The fourth threshold (for example, set to 5 Hz) ensures that the drum's vibration is not too intense, preventing damage to clothing fibers or the washing machine's structure.

[0152] The update unit is used to recalculate the void ratio corresponding to each cell when the oscillation is completed.

[0153] Specifically, after the drum oscillates, the system recalculates the porosity of each cell. This rebalancing improves the distribution of tightly packed clothing, potentially raising the porosity to a level more conducive to water penetration.

[0154] Through the above-mentioned embodiments, during the operation of a drum washing machine, the distribution of clothing within the drum directly affects water permeability and washing efficiency. When clothing is too dense, that is, when the porosity of a cell is below the third threshold, water cannot fully penetrate the clothing, resulting in poor washing results. This solution introduces a drum oscillation mechanism to improve clothing distribution and increase porosity while ensuring that clothing fibers are not damaged, thereby optimizing water coverage and cleaning efficiency during the washing process. The oscillation frequency is designed to be below the fourth threshold to prevent adverse effects on clothing or the washing machine structure.

[0155] In order to ensure the accuracy of the above target control parameters, the above device also includes:

[0156] A third acquisition unit is configured to acquire the real-time humidity of each cell for a preset spraying time after controlling the corresponding nozzle to spray according to each target control parameter, thereby obtaining a second target humidity;

[0157] Specifically, during the spraying process of the drum washing machine, the humidity sensor measures and records the real-time humidity of each cell every preset spraying time (for example, every 2 minutes) to obtain the second target humidity H2.

[0158] a fifth determining unit, configured to determine a corresponding water flow coverage range according to the target control parameter to obtain a first target range, and determine a corresponding water flow coverage range according to the second target humidity to obtain a second target range;

[0159] Specifically, based on the current target control parameters, the system can calculate the theoretically achievable water flow coverage, i.e., the first target range C1. Based on the distribution of the second target humidity H2, the system can estimate the actual achievable water flow coverage, i.e., the second target range C2.

[0160] The correction unit is configured to update the third mapping relationship through a calibration experiment when a deviation ratio between the second target range and the first target range is greater than or equal to a fifth threshold.

[0161] Specifically, the system calculates the deviation ratio ΔC between the second target range C2 and the first target range C1 to assess the degree of match between the actual moisture distribution and the theoretical coverage range. If the deviation ratio ΔC is greater than or equal to a fifth threshold (assuming 10%), the system deems that there is a significant mismatch between the current nozzle control parameters and the actual water flow distribution, and a calibration experiment is required to update the third mapping relationship.

[0162] Through the above-described embodiment, by monitoring real-time humidity during the spraying process and comparing the preset water flow coverage with the actual humidity coverage, the nozzle control parameters are dynamically adjusted to achieve optimal water flow distribution. If a significant deviation between the actual humidity coverage and the preset range is detected, i.e., the deviation ratio is greater than or equal to the fifth threshold, the system will initiate a calibration experiment and update the third mapping relationship, i.e., the mapping table between nozzle control parameters and water flow coverage, to more accurately guide subsequent spray control.

[0163] The washing control device with dynamic water flow adjustment includes a processor and memory. The first acquisition unit, first determination unit, first processing unit, and first control unit are all stored as program units in the memory. The processor executes the program units stored in the memory to implement the corresponding functions. All of the above modules are located in the same processor; alternatively, the above modules can be located in different processors in any combination.

[0164] The processor contains a kernel, which retrieves the corresponding program unit from the memory. One or more kernels can be set, and the kernel parameters can be adjusted to reduce clothing damage.

[0165] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0166] An embodiment of the present invention provides a computer-readable storage medium, which includes a stored program. When the program is run, the device where the computer-readable storage medium is located is controlled to execute the washing control method with dynamic water flow regulation.

[0167] An embodiment of the present invention provides a processor, which is used to run a program, wherein the washing control method of dynamic water flow regulation is executed when the program is run.

[0168] An embodiment of the present invention provides a washing machine, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, at least a washing control step of dynamically adjusting the water flow is implemented.

[0169] The present application also provides a computer program product which, when executed on a data processing device, is adapted to execute a program of steps for initializing a washing control with at least a dynamic regulation of the water flow.

[0170] Obviously, those skilled in the art will appreciate that the various modules or steps of the present invention described above can be implemented using a general-purpose computing device, can be centralized on a single computing device, or can be distributed across a network of multiple computing devices. They can be implemented using program code executable by the computing device, and thus, can be stored in a storage device and executed by the computing device. In some cases, the steps shown or described herein can be performed in a different order than that shown, or can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0171] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0172] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of 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 device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing 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.

[0173] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0174] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0175] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0176] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0177] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can be implemented using any method or technology for information storage. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change RAM (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media, such as modulated data signals and carrier waves.

[0178] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0179] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0180] From the above description, it can be seen that the above embodiments of the present application achieve the following technical effects:

[0181] 1) The present invention relates to a washing control method for dynamic water flow regulation. First, image data and ultrasonic monitoring data of the clothing within the washing machine drum are acquired. The clothing is modeled based on the image data and ultrasonic monitoring data to obtain clothing distribution data. Then, the internal space of the drum is evenly divided into multiple cells. The proportion of space in each cell not occupied by clothing is determined based on the clothing distribution data to obtain multiple void ratios. A void ratio heat map is then drawn based on the multiple void ratios. A first mapping relationship is queried based on the void ratio heat map to obtain multiple target control parameters. The first mapping relationship is a mapping relationship between the void ratio distribution heat map and control parameters corresponding to each nozzle within the drum. The control parameters include nozzle angle, nozzle flow rate, and total output flow rate. Finally, the corresponding nozzle is controlled to spray based on each target control parameter. This invention uses a camera and an ultrasonic sensor to perform three-dimensional modeling of the clothing distribution within the washing machine. Based on the modeling data, a void ratio heat map is drawn to intuitively reflect the distribution of clothing within the washing machine. The nozzle control parameters are then adjusted based on the void ratio heat map to achieve dynamic regulation of the washing water flow. This solves the problem of the prior art that the lack of dynamic nozzle adjustment during the washing process causes damage to clothing.

[0182] 2) The present invention relates to a washing control device with dynamic water flow regulation. The first acquisition unit acquires image data and ultrasonic monitoring data of the clothes in the washing machine drum, models the clothes based on the image data and ultrasonic monitoring data, and obtains clothing distribution data. The first determination unit evenly divides the internal space of the drum into multiple cells, determines the proportion of space in each cell not occupied by clothes based on the clothing distribution data, and obtains multiple void ratios. The first processing unit draws a void ratio heat map based on the multiple void ratios and queries a first mapping relationship based on the void ratio heat map to obtain multiple target control parameters. The first mapping relationship is a mapping relationship between the void ratio distribution heat map and control parameters corresponding to each nozzle in the drum. The control parameters include nozzle angle, nozzle flow rate, and total output flow rate. The first control unit controls the corresponding nozzle to spray according to each target control parameter. The present invention uses a camera and an ultrasonic sensor to perform three-dimensional modeling of the clothing distribution state inside the washing machine, and draws a void ratio heat map based on the modeling data to intuitively reflect the distribution of the clothes in the washing machine. The nozzle control parameters are then adjusted based on the void ratio heat map to achieve dynamic regulation of the washing water flow. This solves the problem of the prior art that lacks dynamic nozzle adjustment during the washing process, which causes damage to the clothes.

[0183] The above description is merely a preferred embodiment of the present application and is not intended to limit the present application. Various modifications and variations are possible for those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present application shall be included within the scope of protection of the present application.

Claims

1. A washing control method with dynamic water flow regulation, characterized in that: include: Acquire image data and ultrasonic monitoring data of clothes in the drum of the washing machine, model the clothes according to the image data and ultrasonic monitoring data, and obtain clothes distribution data; Evenly dividing the internal space of the drum to obtain a plurality of cells, and determining the proportion of space not occupied by clothes in each cell according to the clothes distribution data to obtain a plurality of void ratios; A void ratio heat map is drawn based on the plurality of void ratios, and a first mapping relationship is queried based on the void ratio heat map to obtain a plurality of target control parameters, wherein the first mapping relationship is a mapping relationship between the void ratio distribution heat map and control parameters corresponding to each nozzle inside the drum, wherein the control parameters include nozzle angle, nozzle flow rate, and total output flow rate; The corresponding nozzle is controlled to spray according to each target control parameter.

2. The method according to claim 1, characterized in that The first mapping relationship is queried according to the porosity heat map to obtain multiple target control parameters, including: querying a second mapping relationship based on the porosity heat map to obtain a plurality of target washing parameters, wherein the second mapping relationship is a mapping relationship between the porosity heat map and the washing environment parameter with the highest corresponding score, wherein the score is determined based on the degree of stain residue and fiber damage on the clothes, and the washing environment parameters include water flow rate, water flow intensity, and water flow coverage, and the target washing parameters correspond one-to-one to the cells; The third mapping relationship is queried according to each of the target washing parameters to obtain the corresponding target control parameters. The third mapping relationship is a mapping relationship between the washing environment parameters and the control parameters.

3. The method according to claim 2, characterized in that Before querying the second mapping relationship according to the porosity heat map to obtain a plurality of target washing parameters, the method further includes: a simulation step, taking any preset clothing distribution data as a boundary condition, the nozzle angle, the nozzle flow rate, and the total output flow rate as input variables, adjusting the input variables, and performing simulation under each input variable to obtain multiple simulated washing conditions; A first determining step is to determine the water flow rate, the water flow intensity, and the water flow coverage corresponding to each cell according to the simulated washing condition to obtain the washing environment parameters; a calculation step of drawing the corresponding porosity heat map based on the clothing distribution data, determining the stain residue and the degree of fiber damage of the clothing based on the simulated washing conditions, and performing a weighted calculation based on the stain residue and the degree of fiber damage to obtain the score; A second determining step is to determine the washing environment parameter corresponding to the maximum score as the washing environment parameter corresponding to the porosity heat map; Repeating the simulation step, the first determination step, the calculation step, and the second determination step at least once in sequence until the washing environment parameters corresponding to the void ratio heat map corresponding to all the preset clothing distribution data are determined; The second mapping relationship is constructed according to the corresponding relationship between the porosity thermal map and the washing environment parameters.

4. The method according to claim 1, wherein After controlling the corresponding nozzle to spray according to each target control parameter, the method further includes: monitoring humidity at different positions of a first cell to obtain a plurality of first target humidity levels, where the first cell is any one of the cells; When the difference between the maximum value and the minimum value of any one of the first target humidity values ​​is greater than a first threshold, determining an area within a first preset distance of the humidity sensor corresponding to the first target humidity as a flushing blind area; increasing the nozzle flow rate of the nozzle in the flushing blind area, and adjusting the nozzle angle of the nozzle so that the nozzle is aligned with the flushing blind area; The nozzle is controlled to continue spraying according to the corrected nozzle flow and the nozzle angle.

5. The method according to claim 1, wherein Controlling the corresponding nozzle to spray according to each target control parameter also includes: dividing the cell into a plurality of sub-cells according to the nozzles in the cell; Determining the void ratio corresponding to each of the sub-cells to obtain a plurality of target void ratios; When the target void ratio is greater than a second threshold, reducing the total output flow rate of the nozzle corresponding to the sub-cell; The nozzle is controlled to spray according to the updated total output flow rate.

6. The method according to claim 1, characterized in that After determining the proportion of space not occupied by clothes in each cell according to the clothes distribution data to obtain a plurality of void ratios, the method further includes: When the void ratio corresponding to any one of the cells is less than a third threshold, controlling the drum to oscillate, wherein the oscillation frequency of the drum is less than or equal to a fourth threshold; When the shaking is completed, the void ratio corresponding to each cell is recalculated.

7. The method according to claim 2, characterized in that After controlling the corresponding nozzle to spray according to each target control parameter, the method further includes: Each spraying is performed for a preset time, and the real-time humidity of each cell is obtained to obtain a second target humidity; Determine the corresponding water flow coverage range according to the target control parameter to obtain a first target range, and determine the corresponding water flow coverage range according to the second target humidity to obtain a second target range; When the deviation ratio between the second target range and the first target range is greater than or equal to a fifth threshold, the third mapping relationship is updated through a calibration experiment.

8. A washing control device with dynamic water flow regulation, characterized in that: The device comprises: a first acquiring unit, configured to acquire image data and ultrasonic monitoring data of clothes in the drum of the washing machine, model the clothes according to the image data and ultrasonic monitoring data, and obtain clothes distribution data; a first determining unit, configured to evenly divide the internal space of the drum into a plurality of cells, and determine a proportion of space not occupied by clothes in each cell according to the clothes distribution data, to obtain a plurality of void ratios; a first processing unit, configured to draw a void ratio heat map based on the plurality of void ratios, and query a first mapping relationship based on the void ratio heat map to obtain a plurality of target control parameters, wherein the first mapping relationship is a mapping relationship between the void ratio distribution heat map and control parameters corresponding to each nozzle inside the drum, the control parameters including nozzle angle, nozzle flow rate, and total output flow rate; The first control unit is used to control the corresponding nozzle to spray according to each target control parameter.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 7.

10. A washing machine, characterized in that: include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for executing the method of any one of claims 1 to 7.

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