Washing parameter determination method, electronic equipment and clothes treatment equipment

Abstract

The invention relates to a washing parameter determination method, electronic equipment and clothes processing equipment in the technical field of washing methods, and the method comprises the steps that input parameters are obtained, the input parameters comprise water inlet parameters, clothes parameters and mode parameters, and the water inlet parameters comprise the actual water level height and the water supplementing execution frequency; actual washing parameters are determined according to the corresponding relation between the input parameters and the washing parameters; wherein the water inlet parameter is related to the sound frequency; the sound frequency is other washing parameters which are generated by clothes rolling in the running process of the washing drum and are determined by the water level height and the number of times of water replenishing in the water replenishing stage through the random forest model, the optimal washing time, rotating speed, temperature and detergent dosage can be obtained more accurately, and the washing effect is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of washing methods, and in particular to a washing parameter determination method, an electronic device, and a clothing processing device. Background Art

[0002] In the technical field of washing methods, most washing machine parameter settings are determined by weighing the laundry. However, the weighing process can cause the measured weight to differ from the actual laundry weight due to factors such as uneven distribution of the laundry. Consequently, parameters such as the water level, wash time, and detergent dosage set based on this inaccurate weight become inaccurate, resulting in poor washing results or overwashing. Summary of the Invention

[0003] The technical problem to be solved by the present invention is that the weighing link of the washing machine may cause the weight obtained by weighing to be inconsistent with the actual weight of the clothes due to reasons such as uneven distribution of clothes. At this time, setting the washing parameters based on the inaccurate weight is inaccurate, which will lead to poor washing effect or over-washing of the clothes. A washing parameter determination method, electronic device and clothing processing device are provided.

[0004] The present invention aims to provide a washing parameter determination method for a clothes processing device, wherein the clothes processing device includes a washing drum, and the washing parameter determination method includes: Obtaining input parameters, the input parameters including water inlet parameters, clothing parameters, and mode parameters, the water inlet parameters including actual water level height and number of water replenishment executions; determining actual washing parameters according to the corresponding relationship between the input parameters and the washing parameters; Wherein, the water inlet parameter is related to the sound frequency; The sound frequency is the sound frequency generated by the tumbling of clothes during the operation of the washing tub.

[0005] In some embodiments, the number of water replenishment executions is determined based on the magnitude of the water level drop after each water replenishment and the sound frequency.

[0006] In some embodiments, the method comprises: Determine the drop in the water level for soaking clothes; Determine whether to enter the water replenishment phase based on whether the drop in the water level for soaking clothes exceeds a preset value; If the water level for soaking the clothes drops by more than the preset amplitude value, the water replenishment stage is entered; otherwise, whether to enter the water replenishment stage is determined based on whether the sound frequency is within the preset sound frequency range; If the sound frequency is outside the preset sound frequency range, the water replenishment stage is entered, and the number of executions of the water replenishment stage is the water replenishment execution number.

[0007] In some embodiments, the water replenishment stage includes: determining the amount of water replenishment according to the drop in the water level for soaking the clothes, and the greater the drop in the water level for soaking the clothes, the greater the amount of water replenishment.

[0008] In some embodiments, the water level for soaking the clothes drops by an amount A; Where, A=(A1-A2) / A1×100%, A1 is the water level before the basic amount of water is injected into the washing tub to soak the clothes; A2 is the water level after the basic amount of water is injected into the washing tub to soak the clothes; 10%≤A≤15%, the water replenishment amount is 1 to 1.2 times the basic water injection amount; 16%≤A≤20%, the water replenishment amount is 1.5 to 1.7 times the basic water injection amount; A>20%, the water replenishment amount is 2 to 2.2 times the basic water injection amount.

[0009] In some embodiments, the water replenishment stage includes: determining the amount of water replenishment based on the deviation between the sound frequency and the preset sound frequency range, and the greater the deviation between the sound frequency and the preset sound frequency range, the greater the amount of water replenishment.

[0010] In some embodiments, the deviation value between the sound frequency and the preset sound frequency range is B; B=|B1-B2| / B1×100%, B1 is the sound frequency value, and B2 is the maximum value or minimum value in the preset sound frequency range that is closer to B1; 5%≤B≤10%, the water replenishment amount is 0.5 to 0.7 times the basic water injection amount; 11%≤B≤15%, the water replenishment amount is 1 to 1.2 times the basic water injection amount; B>15%, the water replenishment amount is 1.5 to 1.7 times the basic water injection amount.

[0011] In some embodiments, the washing parameter determination method further comprises: a soaking stage; The soaking stage is performed before determining the drop in the water level of the soaked clothes; The soaking stage includes: injecting water into the washing tub to soak the clothes, and driving the washing tub to rotate forward and / or reversely and then leaving it to stand for a preset time.

[0012] In some embodiments, the clothing parameters include: the water absorption performance of the clothing; The method for judging the water absorption performance of clothing is designed as follows: The shorter the running time of the water replenishment phase is, the stronger the water absorption performance of the clothing is; And / or, the more water is replenished in the replenishment stage, the stronger the water absorption performance of the clothing.

[0013] In some embodiments, determining the actual washing parameters according to the correspondence between the input parameters and the washing parameters includes: The input parameters are input into a random forest model, and the actual washing parameters are output through the random forest model. The random forest model is used to reflect the corresponding relationship between the input parameters and the washing parameters.

[0014] In some embodiments, an electronic device is provided, the electronic device comprising: Memory, which stores computer instructions; A processor is used to call and execute the computer instructions to implement the above-mentioned washing parameter determination method.

[0015] In some embodiments, a laundry processing device is provided, which uses the above-mentioned washing parameter determination method or includes the above-mentioned electronic device.

[0016] The solution provided by the present invention has the following beneficial effects compared with the prior art: The parameters acquired by the method include water inlet parameters, clothing parameters, and mode parameters. The water inlet parameters include the actual water level and the number of water refills. The sound frequency is the frequency of sound generated by the tumbling of clothing during the operation of the washing drum. The actual water level is monitored based on the water level frequency. The actual water level and the number of water refills determined by parameters such as the sound frequency are more reasonable, making the water inlet parameters more comprehensive and accurate. This in turn improves the comprehensiveness and accuracy of the input parameters, ultimately outputting more accurate actual washing parameters, improving the washing effect and providing more precise washing parameters for clothing. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are part of the present invention and are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but do not constitute an undue limitation of the present invention. Obviously, the drawings described below are only some embodiments. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without inventive effort. In the accompanying drawings: Figure 1 This is one of the flow charts of the method for determining washing parameters shown in an embodiment of the present invention; Figure 2 This is the second flow chart of the method for determining washing parameters shown in an embodiment of the present invention; Figure 3 This is the third flow chart of the method for determining washing parameters shown in an embodiment of the present invention; Figure 4 This is the fourth flow chart of the method for determining washing parameters shown in an embodiment of the present invention; Figure 5 is a diagram showing an inverse relationship between water level frequency and water level height, as shown in an embodiment of the present invention; Figure 6 is a random forest model training diagram shown in an embodiment of the present invention; Figure 7 is a curve showing the change of the water level frequency of mixed clothes over time during the water replenishment phase according to an embodiment of the present invention; Figure 8 is a curve showing the change of water level frequency over time for clothes with good water absorption during the water replenishment phase according to an embodiment of the present invention; Figure 9 3 is a curve showing the change of water level frequency over time for clothes with poor water absorption during the water replenishment stage according to an embodiment of the present invention.

[0018] It should be noted that these drawings and textual descriptions are not intended to limit the conceptual scope of the present invention in any way, but rather to illustrate the concept of the present invention for those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0019] In the description of the present invention, it should be noted that the terms "inside" and "outside" etc. indicating orientations or positional relationships are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0020] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," "connected," "in contact," and "connected" should be understood broadly. For example, they may refer to fixed, detachable, or integral connections; mechanical or electrical connections; and direct or indirect connections through an intermediary. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0021] The weighing process of the washing machine may cause the measured weight to be inconsistent with the actual weight of the clothes due to factors such as uneven distribution of clothes. In this case, the water level, wash time, detergent dosage and other parameters set based on the inaccurate weight will become inaccurate, resulting in poor washing results or overwashing of clothes.

[0022] Based on this, the following embodiments are proposed.

[0023] Example 1: like Figure 1 As shown, this embodiment provides a washing parameter determination method for a clothes processing device, wherein the clothes processing device includes a washing tub, and the washing parameter determination method includes: Obtaining input parameters, the input parameters including water inlet parameters, clothing parameters, and mode parameters, the water inlet parameters including actual water level height and number of water replenishment executions; determining actual washing parameters according to the corresponding relationship between the input parameters and the washing parameters; Wherein, the water inlet parameter is related to the sound frequency; The sound frequency is the sound frequency generated by the tumbling of clothes during the operation of the washing tub.

[0024] In this embodiment, the proposed method for determining washing parameters acquires parameters including water inlet parameters, clothing parameters, and mode parameters. The water inlet parameters include the actual water level and the number of water refills. The sound frequency is the frequency of sound generated by the tumbling of clothing in the washing tub during operation. The actual water level is monitored based on the water level frequency. The actual water level and the number of water refills determined based on parameters such as the sound frequency are more reasonable, resulting in more comprehensive and accurate water inlet parameters. This, in turn, improves the comprehensiveness and accuracy of the input parameters, ultimately outputting more accurate actual washing parameters, enhancing washing results and providing more precise washing parameters for clothing.

[0025] More specifically, obtaining the number of water replenishment times can directly indicate the number of water replenishment stages executed. If the clothes absorb a lot of water during the water replenishment stage and the water level drops significantly, multiple water replenishment stages need to be executed to ensure that the clothes fully absorb water. When the actual water level stabilizes and the clothes basically stop absorbing water, water replenishment is stopped. Therefore, obtaining the number of water replenishment times can reflect information such as the water absorption performance of the clothes and the reasonable water level, making the water inlet parameters more comprehensive and accurate. Combined with obtaining the sound frequency generated by the tumbling of clothes during the operation of the washing drum, it can be further determined whether the clothes are in a reasonable water level condition during the operation of the washing drum. For example, if the clothes are entangled or unevenly distributed, it may cause eccentricity, causing abnormal tumbling sounds of the clothes in the washing drum, affecting the washing effect. Based on the acquisition of the sound frequency of the tumbling of clothes in the washing drum during the operation of the washing drum, the number of water replenishment executions and the actual water level value can be made more accurate, thereby improving the comprehensiveness and accuracy of the input parameters, and ultimately outputting more accurate actual washing parameters, improving the washing effect of the clothes, and providing more precise washing parameters for clothes washing.

[0026] Optionally, in an implementation of this embodiment, as Figure 2 As shown, The number of water replenishment executions is determined according to the magnitude of the water level drop after each water replenishment and the sound frequency.

[0027] Furthermore, the method comprises: Determine the drop in the water level for soaking clothes; Determine whether to enter the water replenishment phase based on whether the drop in the water level for soaking clothes exceeds a preset value; If the water level for soaking the clothes drops by more than the preset amplitude value, the water replenishment stage is entered; otherwise, whether to enter the water replenishment stage is determined based on whether the sound frequency is within the preset sound frequency range; If the sound frequency is outside the preset sound frequency range, the water replenishment stage is entered, and the number of executions of the water replenishment stage is the water replenishment execution number.

[0028] In this embodiment, the proposed method for determining washing parameters is based on monitoring the water level frequency and the sound frequency of the clothes tumbling in the washing drum to determine a more reasonable water level height. More specifically, it is determined whether to enter the water replenishment stage based on whether the amplitude of the drop in the water level for soaking the clothes exceeds a preset amplitude value; if the amplitude of the drop in the water level for soaking the clothes exceeds the preset amplitude value, it indicates that the clothes absorbed more water during the water intake stage and the amplitude of the drop in the water level is large, and the water replenishment stage is entered to replenish water so that the clothes absorb water more fully; if the amplitude of the drop in the water level for soaking the clothes does not exceed the preset amplitude value, it indicates that the current water level is stable and the clothes have basically stopped absorbing water, but it is not enough to ensure the rationality of the water level. If the clothes are entangled or unevenly distributed, it may cause eccentricity, causing abnormal tumbling sound of the clothes in the washing drum, affecting the washing process. The system determines whether to enter the water replenishment phase based on whether the frequency of the sound produced by the tumbling of clothes in the washing drum during operation is within a preset sound frequency range. If the sound frequency is outside this range, the current water level is still insufficient for the clothes to be washed properly. Therefore, the system enters the water replenishment phase, replenishing water to reduce entanglement of clothes and promote more even distribution of clothes within the water, thereby optimizing the actual water level. This water level and the number of water replenishments performed during the water replenishment phase are then used to determine other washing parameters. For example, this reasonable actual water level and number of water replenishments are input into an intelligent optimization model, which then outputs the optimal wash time, speed, temperature, and detergent dosage. This washing parameter determination method accurately identifies the clothing state through multi-dimensional feature fusion, enabling more accurate intelligent optimization of washing parameters and significantly improving washing results. Furthermore, by continuously collecting and analyzing washing data and combining it with an intelligent learning algorithm, the system achieves dynamic performance optimization and improved adaptability.

[0029] The intelligent optimization model can use a random forest model to optimize and control the washing parameters of the washing machine. Random forest is a machine learning algorithm based on ensemble learning. It has nonlinear modeling capabilities, anti-overfitting characteristics, and high generalization capabilities. It is particularly suitable for complex systems with multiple inputs and multiple outputs. During the model construction process, the washing machine operation data is first collected, including input parameters such as water level height, water replenishment frequency, clothing water absorption rate, and user-selected mode. At the same time, the corresponding optimal wash time, speed, temperature, and detergent dosage are recorded as output parameters. After cleaning and preprocessing, the data is used for model training. The nonlinear fitting capability of the random forest model can effectively explore the complex relationship between input parameters and output parameters. Based on the reasonable actual water level height and the number of water replenishment executions in the water replenishment phase obtained by the washing parameter determination method, more reasonable other washing parameters can be output to improve the washing effect.

[0030] In this embodiment, a sound sensor is used to obtain the sound frequency of the clothes tumbling in the washing drum. The sound sensor is installed between the inner drum and the outer drum of the washing drum and fixed to the clothes stirring area near the middle of the outer drum to capture the sound frequency of the clothes tumbling after being stirred. When obtaining the sound frequency of the clothes tumbling in the washing drum, the driving motor of the clothes processing device runs at a normal washing speed. The sound sensor collects the sound frequency of the clothes tumbling after being stirred when the washing drum is running. Based on whether the sound frequency is within the preset sound frequency range, it is judged whether the water level of the clothes at this time meets the optimal water level for washing.

[0031] The water level frequency can reflect the water level height. That is, by monitoring the water level frequency and comparing the changes in the water level frequency within a certain period of time, the water level drop amplitude and the relationship between the water level frequency and the water level height can be obtained. Figure 5 As shown, the water level frequency value obtained by the water level sensor is inversely proportional to the water level height. Figure 5 In the example, the horizontal axis represents the water level frequency output by the water level sensor, and the vertical axis represents the actual water level. As the actual water level increases, the frequency output by the water level sensor decreases, and vice versa. This inverse relationship can be expressed mathematically as: F = k / H. F is the output frequency of the water level sensor, H is the water level, and k is a constant proportional factor that depends on the size and height of the washing machine's drum. The magnitude of the water level drop in this embodiment can be determined by monitoring the water level frequency value with the water level sensor.

[0032] Optionally, in an implementation of this embodiment, as Figure 3 As shown, The water replenishment stage includes: determining the amount of water replenishment according to the drop in the water level for soaking the clothes, and the greater the drop in the water level for soaking the clothes, the greater the amount of water replenishment.

[0033] Furthermore, the water level for soaking the clothes decreases by an amount A; Where, A=(A1-A2) / A1×100%, A1 is the water level before the basic amount of water is injected into the washing tub to soak the clothes; A2 is the water level after the basic amount of water is injected into the washing tub to soak the clothes; 10%≤A≤15%, the water replenishment amount is 1 to 1.2 times the basic water injection amount; 16%≤A≤20%, the water replenishment amount is 1.5 to 1.7 times the basic water injection amount; A>20%, the water replenishment amount is 2 to 2.2 times the basic water injection amount.

[0034] The water replenishment stage includes: determining the amount of water replenishment according to the deviation between the sound frequency and the preset sound frequency range. The greater the deviation between the sound frequency and the preset sound frequency range, the greater the amount of water replenishment.

[0035] The deviation value between the sound frequency and the preset sound frequency range is B; B=|B1-B2| / B1×100%, B1 is the sound frequency value, and B2 is the maximum value or minimum value in the preset sound frequency range that is closer to B1; 5%≤B≤10%, the water replenishment amount is 0.5 to 0.7 times the basic water injection amount; 11%≤B≤15%, the water replenishment amount is 1 to 1.2 times the basic water injection amount; B>15%, the water replenishment amount is 1.5 to 1.7 times the basic water injection amount.

[0036] In this embodiment, if the water level for soaking clothes drops by more than the preset amplitude value, the water replenishment stage is entered; or if the sound frequency is outside the preset sound frequency range, the water replenishment stage is entered.

[0037] During the water replenishment stage, add an appropriate amount of water, and repeat the operation of driving the washing drum with the driving motor to rotate forward 2 times and reverse 2 times, and then keep it stationary for 1 minute. During this process, the system continuously monitors the change in water level: if the water level does not drop by more than 10%, the sound frequency detection is performed again. If the sound frequency is within the preset sound frequency range, the current actual water level h is recorded as a reference value. If the water level for soaking clothes drops by more than 10% or the sound frequency is outside the preset sound frequency range, the system continues to perform the water replenishment operation until the actual water level and sound frequency meet the requirements. At this time, the actual water level h is recorded as a reference value to provide a basis for the optimization of subsequent washing procedures.

[0038] During the water replenishment stage, the amount of water replenishment is determined based on the extent of the drop in the water level for soaking the clothes.

[0039] When the water level drops by 10% to 15%, the clothes are judged to have absorbed little water, and αL of water will be added first. When the water level drops by 16% to 20%, the clothes are judged to have absorbed moderate water, and 1.5αL of water will be added. When the water level drops by more than 20%, the clothes are judged to have absorbed a lot of water, and 2αL of water will be added. After one water replenishment is completed, let the clothes soak again, and then judge whether to add water again according to the change in water level until the water level meets the requirements; During the water replenishment phase, the amount of water replenishment is determined based on the deviation between the sound frequency and the preset sound frequency range.

[0040] When B is 5% ≤ ≤ 10%, the garment is judged to be slightly dehydrated and 0.5αL of water is added. When B is 11% ≤ ≤ 15%, the garment is judged to be moderately dehydrated and αL of water is added. When B exceeds 15%, the garment is judged to be significantly dehydrated and 1.5αL of water is added. The sound frequency detection cycle is repeated until the sound frequency falls within the preset sound frequency range, and the final number of water additions, n, is recorded, after which the parameter setting phase is entered.

[0041] Furthermore, the washing parameter determination method further includes: a soaking stage; The soaking stage is performed before determining the drop in the water level of the soaked clothes; The soaking stage includes: injecting water into the washing tub to soak the clothes, and driving the washing tub to rotate forward and / or reversely and then leaving it to stand for a preset time.

[0042] In this embodiment, after the user puts the clothes to be washed into the washing drum, the water filling stage begins. The control system of the clothes processing equipment injects a basic amount of water αL into the washing drum through a preset basic water filling mode, where α is 8% of the full bucket water volume, and causes the driving motor to drive the washing drum to rotate forward twice and reverse twice, and then remain in a static state for 1 minute, that is, the preset static time is 1 minute, to ensure that the internal state of the washing drum tends to be stable and to give the clothes sufficient time to absorb water. During this process, the system continuously monitors the change in water level: if the water level drops by no more than 10% of the basic water level, that is, the preset amplitude value is 10%; for example, A1 =20cm, A2=19cm, then A=(20-19) / 20×100%=5%, which does not exceed the preset amplitude value of 10%. The system then enters the sound frequency detection phase. Depending on whether the sound frequency of the clothes tumbling in the washing tub during operation is within a preset sound frequency range, the system determines whether to enter the water replenishment phase. If the sound frequency is outside the preset sound frequency range, the system enters the water replenishment phase. Otherwise, if the sound frequency is within the preset sound frequency range, the system records the current actual water level h as a preliminary reference value, and determines the washing parameters based on the actual water level and the number of water replenishment executions in the water replenishment phase.

[0043] Optionally, in one implementation of this embodiment, The clothing parameters include: the water absorption performance of the clothing; The method for judging the water absorption performance of clothing is designed as follows: The shorter the running time of the water replenishment phase is, the stronger the water absorption performance of the clothing is; And / or, the more water is replenished in the replenishment stage, the stronger the water absorption performance of the clothing.

[0044] Furthermore, determining the actual washing parameters according to the correspondence between the input parameters and the washing parameters includes: The input parameters are input into a random forest model, and the actual washing parameters are output through the random forest model. The random forest model is used to reflect the corresponding relationship between the input parameters and the washing parameters.

[0045] In this embodiment, adding input parameters, the strength of the water absorption performance of the clothes and the washing mode, can further provide a calculation basis for the random forest model, making the washing parameters it outputs more accurate.

[0046] The key parameters such as the washing mode selected by the user, the actual water level h, the water absorption performance of the clothes and the number of water replenishment n are recorded and input into the random forest model.

[0047] like Figure 6 As shown in the figure, during model training, the random forest algorithm randomly selects samples and features to construct multiple decision trees. The predictions from each tree are then voted on or averaged to arrive at the final output parameter prediction. During training, model parameters (such as the number of trees and tree depth) are optimized through cross-validation to ensure the model's generalization and prediction accuracy. Furthermore, the random forest model can assess the importance of input parameters, revealing the contribution of each parameter to the output.

[0048] In this embodiment, the water absorption performance of the garment is determined by: the shorter the duration of the water replenishment phase, the greater the water absorption performance of the garment; and / or the greater the amount of water replenished during the water replenishment phase, the greater the water absorption performance of the garment. This allows for accurate determination of the water absorption performance of the garment.

[0049] like Figures 7 to 9 They show the mixing of clothes ( Figure 7 ), clothes with better water absorption performance ( Figure 8 ) and clothing with poor water absorption performance ( Figure 9) The water level frequency variation curves during the water filling and replenishment phases for the three types of clothing. Table 1 details the time spent during the water filling and replenishment phases for these three types of clothing, as well as the final water level frequency values after replenishment. The chart data shows that during the replenishment process, clothing with poor water absorption exhibits longer replenishment times and continuous water level fluctuations, with the smallest water level fluctuations after the water level stabilizes. Clothing with better water absorption exhibits shorter replenishment times and more stable water level fluctuations, with the largest water level fluctuations after stabilization. Mixed clothing falls somewhere in between, with shorter replenishment times, intermittent water level fluctuations, and larger water level fluctuations after stabilization. These characteristics provide an effective basis for distinguishing the water absorption properties of different clothing items.

[0050] Table 1 Changes in time and water level frequency during the water filling and replenishing stages of different clothes

[0051] To optimize the system's accuracy in identifying clothing's water absorption properties, a training dataset based on multiple types of clothing was established. Specifically, a variety of clothing samples of the same weight but different materials and structures were selected and placed in the washing machine. The water level frequency change data for the clothing during the water intake and water replenishment stages were collected in real time, and the time parameters of each stage were recorded. After preprocessing and feature extraction, these data were input into a random forest model, and the water level frequency change characteristics were modeled and trained using the random forest algorithm. After learning and optimizing a large amount of sample data, the model was able to gradually grasp the water level frequency change patterns of different clothing types during the water intake and water replenishment stages, thereby significantly improving the precision and accuracy of identifying clothing's water absorption properties.

[0052] During the sound frequency detection phase, the degree of eccentricity produced by laundry during the washing process varies due to differences in weight and material. This eccentricity causes variations in the noise level during operation, and the noise level corresponding to the optimal water level for each type of laundry also varies, as shown in Table 2. Therefore, by real-time monitoring the sound frequency of the tumbling laundry within the washing drum, it is possible to effectively determine whether the current water level is within the appropriate range, thereby ensuring a smooth washing process and optimizing the washing effect. During model training, a wash parameter determination method was used to obtain actual water level data under different washing conditions. This enabled the random forest model to comprehensively capture and quantify the corresponding relationship between water level and sound frequency under different conditions. This relationship allowed the random forest model to accurately establish a mapping between water level and noise frequency, providing a solid data foundation for subsequent model training, ensuring that the model can more accurately identify and optimize water level settings for different garments.

[0053] Table 2 Sound frequencies corresponding to different types and weights of clothing

[0054] Model application phase: During the model application phase, the random forest model uses real-time input parameters such as the actual water level, water replenishment frequency, clothing absorbency, and the user's selected mode to perform inference calculations and output the optimal wash time, speed, temperature, and detergent dosage. This method dynamically adjusts wash parameters based on actual operating conditions, significantly improving wash efficiency and results while reducing energy and detergent consumption.

[0055] For example, when the laundry machine is turned on and the user selects wash type X, a base volume of water, αL, is first added to allow the laundry to fully absorb water. If the water level drops by 12%, the water replenishment phase begins. αL of water is added to allow the laundry to fully absorb water. If the drop is less than 10%, the sound frequency detection phase begins. At this point, the sound frequency falls outside the preset frequency range, differing by 8% from the maximum value within the preset frequency range. 0.5αL of water is added. If the sound frequency is re-detected and falls within the preset frequency range, the actual water level, h, and the number of water replenishments, n, are recorded, and the parameter setting phase begins. The water level, h, number of water replenishments, n, the laundry's poor water absorption, and the user's selected wash type, X, are input into the model (a random forest model) to determine the optimal wash parameters for this wash: wash time t, speed r, temperature T, and detergent dosage β. The laundry process then continues.

[0056] Table 3 Parameter comparison example table

[0057] The washing parameter determination method in this embodiment is based on water level frequency and sound frequency. First, the optimal water level is determined by observing the water level frequency changes during the water inlet and water refill phases, and by identifying the sound frequency range. Secondly, the water absorption performance of the clothing, namely the water absorption rate, is determined based on the water level change frequency during the water refill phase. Finally, the water level, water refill frequency, and water absorption rate are input into a model to ultimately determine the optimal washing time, speed, temperature, and detergent dosage. This method determines washing parameters that are more targeted to the clothing being washed, improving washing results and achieving a more precise and optimized washing effect. This not only effectively increases cleaning efficiency but also better protects clothing.

[0058] Example 2 This embodiment provides an electronic device, the electronic device including: Memory, which stores computer instructions; The processor is used to call and execute computer instructions to implement the washing parameter determination method in embodiment one.

[0059] The electronic device monitors the water level frequency and the sound frequency of the clothes tumbling in the washing drum to determine a more reasonable water level height. More specifically, it determines whether to enter the water replenishment stage according to whether the drop amplitude of the water level height for soaking clothes exceeds a preset amplitude value; if the drop amplitude of the water level height for soaking clothes exceeds the preset amplitude value, it indicates that the clothes absorb more water in the water intake stage and the drop amplitude of the water level height is large, and the water replenishment stage is entered to replenish water so that the clothes absorb water more fully; if the drop amplitude of the water level height for soaking clothes does not exceed the preset amplitude value, it indicates that the current water level height is stable and the clothes basically stop absorbing water, but it is not enough to ensure the rationality of the water level. If the clothes are entangled or unevenly distributed, it may cause eccentricity, causing abnormal tumbling sound of the clothes in the washing drum, affecting the washing effect, combined with the basic principle of the invention, the electronic device can be used to monitor the water level frequency and the sound frequency of the clothes tumbling in the washing drum to determine whether to enter the water replenishment stage; During operation, the system determines whether to enter the refill phase based on whether the frequency of the sound produced by the tumbling of clothing within the drum falls within a preset frequency range. If the sound frequency falls outside this range, the current water level is insufficient to properly wash the clothing within the drum. Therefore, the system enters the refill phase, replenishing water to reduce entanglement and promote more even distribution of clothing within the drum, thereby optimizing the actual water level. This water level and the number of refills performed during the refill phase are then used to determine other washing parameters, such as the optimal wash time, speed, temperature, and detergent dosage. This washing parameter determination method accurately identifies clothing status through multi-dimensional feature fusion, enabling more accurate intelligent optimization of washing parameters and significantly improving washing results. Furthermore, by continuously collecting and analyzing washing data and combining it with intelligent learning algorithms, the system achieves dynamic performance optimization and improved adaptability.

[0060] Example 3 This embodiment provides a clothes processing device, which uses the washing parameter determination method in the first embodiment, or includes the electronic device in the second embodiment.

[0061] The clothes processing device monitors the water level frequency and the sound frequency of the clothes tumbling in the washing drum to determine a more reasonable water level height. More specifically, it determines whether to enter the water replenishment stage according to whether the amplitude of the drop in the water level height for soaking the clothes exceeds a preset amplitude value; if the amplitude of the drop in the water level height for soaking the clothes exceeds the preset amplitude value, it indicates that the clothes absorb more water in the water intake stage and the amplitude of the drop in the water level height is large, and the water replenishment stage is entered to replenish water so that the clothes absorb water more fully; if the amplitude of the drop in the water level height for soaking the clothes does not exceed the preset amplitude value, it indicates that the current water level height is stable and the clothes basically stop absorbing water, but it is not enough to ensure the rationality of the water level. If the clothes are entangled or unevenly distributed, it may cause eccentricity, causing abnormal tumbling sound of the clothes in the washing drum, affecting the washing effect, combined with The decision to enter the refill phase is based on whether the frequency of the sound produced by the tumbling of clothing within the washing drum during operation falls within a preset frequency range. If the sound frequency falls outside this range, the current water level is insufficient to properly wash the clothing within the washing drum. Therefore, the refill phase begins. By adding water to the washing drum, the entanglement of clothing within the washing drum is reduced, resulting in a more even distribution of clothing within the water, thereby optimizing the actual water level. This water level and the number of refills performed during the refill phase are used to determine other washing parameters, such as the optimal washing time, speed, temperature, and detergent dosage. This washing parameter determination method accurately identifies clothing status through multi-dimensional feature fusion, enabling more accurate intelligent optimization of washing parameters and significantly improving washing results. Furthermore, by continuously collecting and analyzing washing data and combining it with intelligent learning algorithms, the system achieves dynamic performance optimization and improved adaptability.

[0062] In summary, the ingenious idea of the method for determining washing parameters lies in: By monitoring the water level frequency and the frequency of the sound of the clothes tumbling in the washing drum, a more reasonable water level height is determined. Whether to enter the water replenishment stage is determined based on whether the drop in the water level for soaking the clothes exceeds the preset amplitude value; if the drop in the water level for soaking the clothes exceeds the preset amplitude value, it indicates that the clothes absorbed a lot of water during the water intake stage and the water level dropped significantly, and the water replenishment stage is entered to replenish water so that the clothes can absorb water more fully; if the drop in the water level for soaking the clothes does not exceed the preset amplitude value, it indicates that the current water level is stable and the clothes have basically stopped absorbing water, but it is not enough to ensure the rationality of the water level. If the clothes are entangled or unevenly distributed, it may cause eccentricity, causing abnormal tumbling sounds of the clothes in the washing drum. , affecting the washing effect. Whether the sound frequency of the clothes tumbling in the washing drum during operation is within the preset sound frequency range is determined to determine whether to enter the water replenishment stage. If the sound frequency is outside the preset sound frequency range, it indicates that the current water level is still unable to allow the clothes to be washed in the washing drum in a suitable posture. Therefore, in this state, the water replenishment stage is entered. By replenishing water into the washing drum, the entanglement of clothes in the washing drum is reduced, and the clothes are distributed more evenly in the water, so that the actual water level height is more reasonable. The water level height and the number of water replenishments in the water replenishment stage are used to determine other washing parameters through the random forest model to more accurately obtain the optimal washing time, speed, temperature and detergent dosage. This washing parameter determination method accurately judges the clothing state through multi-dimensional feature fusion, can more accurately realize the intelligent optimization of washing parameters, and significantly improve the washing effect.

[0063] It is further understood that in this disclosure, "many" refers to two or more than two, and other quantifiers are similar. "And / or" describes the association relationship of related objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the related objects before and after are in an "or" relationship. The singular forms "a", "the" and "the" are also intended to include the plural forms, unless the context clearly indicates otherwise.

[0064] It will be further understood that the terms "first," "second," and the like are used to describe various types of information, but such information should not be limited to these terms. These terms are used solely to distinguish information of the same type from one another and do not indicate a particular order or level of importance. In fact, the terms "first," "second," and the like are fully interchangeable. For example, first information could be referred to as second information, and similarly, second information could be referred to as first information without departing from the scope of this disclosure.

[0065] It is further understood that although operations are described in a particular order in the drawings in the embodiments of the present disclosure, this should not be construed as requiring that the operations be performed in the particular order shown or in a serial order, or that all of the operations shown be performed to obtain the desired results. In certain circumstances, multitasking and parallel processing may be advantageous.

[0066] Other embodiments of the present disclosure will readily occur to those skilled in the art after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow from the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the following claims.

[0067] It should be understood that the present disclosure is not limited to the exact structures described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the scope of the appended claims.

Claims

1. A method for determining washing parameters, used in a clothes processing device, wherein the clothes processing device includes a washing tub, characterized in that: The washing parameter determination method comprises: Obtaining input parameters, the input parameters including water inlet parameters, clothing parameters, and mode parameters, the water inlet parameters including actual water level height and number of water replenishment executions; determining actual washing parameters according to the corresponding relationship between the input parameters and the washing parameters; Wherein, the water inlet parameter is related to the sound frequency; The sound frequency is the sound frequency generated by the tumbling of clothes during the operation of the washing tub.

2. The method for determining washing parameters according to claim 1, wherein: The number of water replenishment executions is determined according to the magnitude of the water level drop after each water replenishment and the sound frequency.

3. The method for determining washing parameters according to claim 2, wherein: The method comprises: Determine the drop in the water level for soaking clothes; Determine whether to enter the water replenishment phase based on whether the drop in the water level for soaking clothes exceeds a preset value; If the water level for soaking the clothes drops by more than the preset amplitude value, the water replenishment stage is entered; otherwise, whether to enter the water replenishment stage is determined based on whether the sound frequency is within the preset sound frequency range; If the sound frequency is outside the preset sound frequency range, the water replenishment stage is entered, and the number of executions of the water replenishment stage is the water replenishment execution number.

4. The method for determining washing parameters according to claim 3, The water replenishment stage includes: The amount of water to be replenished is determined according to the amplitude of the drop in the water level for soaking the clothes. The greater the amplitude of the drop in the water level for soaking the clothes, the greater the amount of water to be replenished.

5. The method for determining washing parameters according to claim 4, The water level for soaking clothes drops by A; in, A=(A1-A2) / A1×100%, A1 is the water level before the basic amount of water is injected into the washing tub to soak the clothes; A2 is the water level after the basic amount of water is injected into the washing tub to soak the clothes; 10%≤A≤15%, the water replenishment amount is 1 to 1.2 times the basic water injection amount; 16%≤A≤20%, the water replenishment amount is 1.5 to 1.7 times the basic water injection amount; A>20%, the water replenishment amount is 2 to 2.2 times the basic water injection amount.

6. The method for determining washing parameters according to claim 5, The water replenishment stage includes: The amount of water replenishment is determined according to the deviation between the sound frequency and the preset sound frequency range. The greater the deviation between the sound frequency and the preset sound frequency range, the greater the amount of water replenishment.

7. The method for determining washing parameters according to claim 6, The deviation value between the sound frequency and the preset sound frequency range is B; B=|B1-B2| / B1×100%, B1 is the value of the sound frequency, and B2 is the maximum value or minimum value in the preset sound frequency range that is closer to B1; 5%≤B≤10%, the water replenishment amount is 0.5 to 0.7 times the basic water injection amount; 11%≤B≤15%, the water replenishment amount is 1 to 1.2 times the basic water injection amount; B>15%, the water replenishment amount is 1.5 to 1.7 times the basic water injection amount.

8. The method for determining washing parameters according to claim 3, wherein: The washing parameter determination method further comprises: a soaking stage; The soaking stage is performed before determining the drop in the water level of the soaked clothes; The soaking stage includes: injecting water into the washing tub to soak the clothes, and driving the washing tub to rotate forward and / or reversely and then leaving it to stand for a preset time.

9. The method for determining washing parameters according to any one of claims 3 to 8, characterized in that: The clothing parameters include: the water absorption performance of the clothing; The method for judging the water absorption performance of clothing is designed as follows: The shorter the running time of the water replenishment phase is, the stronger the water absorption performance of the clothing is; And / or, the more water is replenished in the replenishment stage, the stronger the water absorption performance of the clothing.

10. The method for determining washing parameters according to claim 1, wherein: Determining the actual washing parameters according to the correspondence between the input parameters and the washing parameters includes: The input parameters are input into a random forest model, and the actual washing parameters are output through the random forest model. The random forest model is used to reflect the corresponding relationship between the input parameters and the washing parameters.

11. An electronic device, characterized in that: The electronic device comprises: Memory, which stores computer instructions; A processor is configured to call and execute the computer instructions to implement the washing parameter determination method according to any one of claims 1 to 10.

12. A clothes processing device, characterized in that: The laundry processing device uses the washing parameter determination method according to any one of claims 1 to 10, or includes the electronic device according to claim 11.

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