Washing machine control method, apparatus, washing machine, and medium

Abstract

The present disclosure relates to a washing machine control method, device, washing machine and medium. The washing machine control method comprises: acquiring a sound signal in the washing machine; and determining foam information in the washing machine according to the sound signal. The foam information is determined according to the sound signal, so that the foam adhering to the clothes is reduced by processing the foam, and the overflow of the foam is prevented, thereby improving the cleaning effect of the washing machine and the reliability of the washing machine control. At the same time, since the washing machine does not need to be stationary during the acquisition of the sound signal, the cleaning efficiency of the washing machine is improved. Moreover, since the determination of the foam information by the sound signal is not limited by the liquid level in the washing machine, the foam information cannot be determined due to the excessively high liquid level, thereby improving the effectiveness of the washing machine control.

Description

Technical Field

[0001] This disclosure relates to the field of washing machine technology, and in particular to a washing machine control method, device, washing machine, and medium. Background Technology

[0002] Currently, detergent is added to remove stains from clothes during the washing process in a washing machine. However, if too much detergent is added, a large amount of foam will be produced in the water. This excessive foam may stick to the clothes, resulting in poor cleaning performance. Summary of the Invention

[0003] To overcome the problems existing in related technologies, this disclosure provides a washing machine control method, device, washing machine, and medium.

[0004] According to a first aspect of the present disclosure, a washing machine control method is provided, the washing machine control method comprising:

[0005] Acquire sound signals from the washing machine;

[0006] Based on the sound signal, the foam information in the washing machine is determined.

[0007] In some embodiments of this disclosure, the foam information includes the number of foam particles; determining the foam information in the washing machine based on the sound signal includes:

[0008] Based on the sound signal, determine the first number of foam bursts in the washing machine;

[0009] Obtain the water temperature of the washing machine;

[0010] The number of foams is determined based on the first quantity and the water temperature.

[0011] In some embodiments of this disclosure, determining the first number of foam bursts in the washing machine based on the sound signal includes:

[0012] Based on the multiple amplitude values ​​of the sound signal at different times, determine multiple frequency values ​​of the sound signal;

[0013] The first quantity is determined based on the plurality of frequency values.

[0014] In some embodiments of this disclosure, determining multiple frequency values ​​of the sound signal based on multiple amplitude values ​​of the sound signal at different times includes:

[0015] The multiple amplitude values ​​are grouped;

[0016] Each set of amplitude values ​​is converted to obtain multiple sets of frequency values.

[0017] In some embodiments of this disclosure, determining the first quantity based on the plurality of frequency values ​​includes:

[0018] The maximum value among the frequency values ​​in each group is determined as the maximum frequency value;

[0019] Determine the poles of the frequency signal formed by the maximum frequency values ​​described above;

[0020] The first quantity is determined based on the stated pole.

[0021] In some embodiments of this disclosure, the number of sound signals is multiple; determining the first number based on the poles includes:

[0022] The second quantity is obtained by summing the poles corresponding to each of the aforementioned sound signals;

[0023] The ratio of the second quantity to the quantity of the sound signals is determined to be the third quantity;

[0024] The ratio of the third quantity to the first preset value is determined to be the first quantity.

[0025] In some embodiments of this disclosure, the foam information includes foam distribution; determining the foam information in the washing machine based on the sound signal includes:

[0026] The average value of multiple amplitudes of the sound signal at different times is determined as the average amplitude.

[0027] The foam distribution is determined based on the average amplitude.

[0028] In some embodiments of this disclosure, the number of sound signals is multiple; determining the foam distribution based on the average amplitude includes:

[0029] If the difference between the two average amplitudes is greater than a second preset value, it is determined that the foam distribution is uneven.

[0030] If the difference between any two of the stated average amplitudes is less than or equal to the second preset value, the foam distribution is determined to be uniform; and / or,

[0031] If one of the average amplitudes is greater than the sum of the two average amplitudes, it is determined that the foam distribution of the sound sensor corresponding to the sound signal with the largest average amplitude is greater than the foam distribution of the sound sensors corresponding to the other sound signals.

[0032] If each of the average amplitudes is less than the sum of any two of the average amplitudes, it is determined that the foam distribution of the sound sensor corresponding to each of the sound signals is the same.

[0033] In some embodiments of this disclosure, the foam information includes foam size; determining the foam information in the washing machine based on the sound signal includes:

[0034] The maximum amplitude of the sound signal at different times is determined as the maximum amplitude value.

[0035] Obtain the water level of the washing machine;

[0036] Obtain the water temperature of the washing machine;

[0037] The size of the foam is determined based on the maximum amplitude, the water level, and the water temperature.

[0038] In some embodiments of this disclosure, acquiring the sound signal from the washing machine includes:

[0039] Before the spin-drying program of the washing machine begins, acquire the sound signal from the washing machine; and / or,

[0040] After the spin-drying cycle of the washing machine is completed, the sound signal from the washing machine is acquired.

[0041] In some embodiments of this disclosure, before determining the foam information in the washing machine based on the sound signal, the washing machine control method further includes:

[0042] The sound signal is subjected to high-frequency filtering.

[0043] In some embodiments of this disclosure, after determining the foam information in the washing machine based on the sound signal, the washing machine control method further includes:

[0044] When the foam information meets the preset conditions, the washing machine is controlled to enter the spin-drying process or end the washing process.

[0045] If the foam information does not meet the preset conditions, the foam in the washing machine is eliminated.

[0046] In some embodiments of this disclosure, the foam information includes the number of foams, the distribution of foams, and / or the size of foams; the preset conditions include the number of foams being less than a third preset value, the distribution of foams being uniform, and / or the size of foams being greater than a fourth preset value.

[0047] According to a second aspect of the present disclosure, a washing machine control device is provided, the washing machine control device comprising:

[0048] An acquisition module, configured to acquire sound signals from the washing machine;

[0049] A determining module is configured to determine foam information in the washing machine based on the sound signal.

[0050] According to a third aspect of the present disclosure, a washing machine is provided, the washing machine comprising:

[0051] processor;

[0052] Memory used to store the processor's executable instructions;

[0053] The processor is configured to execute the washing machine control method described above.

[0054] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium is provided, wherein when instructions in the storage medium are executed by a processor of a terminal, the terminal is enabled to perform the washing machine control method as described above.

[0055] The technical solutions provided by the embodiments of this disclosure may include the following beneficial effects:

[0056] The system acquires sound signals from within the washing machine to determine the extent of foam breakage. Based on these sound signals, it identifies foam information and processes the foam accordingly. By determining foam information through sound signals and processing the foam, it reduces foam adhering to clothes and prevents foam overflow, thereby improving the washing machine's cleaning effect and control reliability. Furthermore, since the washing machine does not need to be left to stand during sound signal acquisition, washing efficiency is improved. Moreover, because determining foam information using sound signals is not limited by the liquid level in the washing machine, it avoids situations where the liquid level is too high, thus improving the effectiveness of washing machine control.

[0057] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0058] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0059] Figure 1 This is a flowchart illustrating a washing machine control method according to an exemplary embodiment;

[0060] Figure 2 This is a flowchart illustrating a washing machine control method according to another exemplary embodiment;

[0061] Figure 3This is a flowchart illustrating a washing machine control method according to another exemplary embodiment;

[0062] Figure 4 This is a flowchart illustrating a washing machine control method according to another exemplary embodiment;

[0063] Figure 5 This is a flowchart illustrating a washing machine control method according to another exemplary embodiment;

[0064] Figure 6 This is a block diagram of a washing machine control device according to an exemplary embodiment;

[0065] Figure 7 This is a block diagram of a washing machine according to an exemplary embodiment.

[0066] In the picture:

[0067] 100 - Acquisition module; 200 - Determination module; 400 - Washing machine; 402 - Processing component; 404 - Memory; 406 - Power supply component; 408 - Multimedia component; 410 - Audio component; 412 - Input / output interface; 414 - Sensor component; 416 - Communication component; 420 - Processor. Detailed Implementation

[0068] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0069] Currently, detergent is added during the washing process in washing machines to remove stains and improve cleaning performance. However, detergent undergoes a chemical reaction, producing foam in the water, which cannot be immediately eliminated. If too much detergent is added, excessive foam may adhere to the clothes, resulting in poor cleaning performance.

[0070] In related technologies, a washing machine control method is provided, which stops the motor in the washing machine after the washing cycle ends. A liquid level sensor detects the liquid level in the washing machine and detects it again after a certain period of time, determining the amount of foam by the difference in liquid level. If there is a large amount of foam, it is eliminated. While this method can detect the amount of foam on the liquid surface, it is difficult to detect foam adhering to clothes, resulting in poor cleaning performance. Furthermore, the need for the washing machine to stand for a period of time increases the time required to wash clothes, leading to low cleaning efficiency. Moreover, when the liquid level reaches its maximum height, even if the amount of foam decreases, the liquid level may not change, resulting in low control effectiveness.

[0071] To address the aforementioned technical problems, this disclosure provides a washing machine control method that determines foam information by acquiring sound signals from within the washing machine to ascertain the foam's bursting status. Since sound signals can still propagate and reflect foam information even when foam adheres to clothing, the foam can be eliminated, improving the washing machine's cleaning effect. Furthermore, since there is no need to allow the washing machine to settle, the time spent on settling is reduced, thereby improving the washing machine's cleaning efficiency. Moreover, because sound signals are not limited by the liquid level, foam information can still be determined even when the liquid level is at its maximum, thus improving the effectiveness of washing machine control.

[0072] For ease of understanding, the washing machine of this disclosure will first be described. The washing machine is equipped with sound sensors, and the number of sound sensors can be one or more. The sound sensors are located in the space between the inner and outer drums of the washing machine and do not rotate with the rotation of the inner drum. When there are multiple sound sensors, each sound sensor can be located in a different area to accurately detect foam information and locate the foam. The sound signal detected by the sound sensor is a curve showing the amplitude changing over time. After sampling the sound signal, the sampled sound signal consists of multiple discrete amplitudes, and the time interval between each two adjacent amplitudes is the sampling time.

[0073] This disclosure provides a washing machine control method, such as... Figure 1 As shown, the method includes:

[0074] S100: Acquire sound signals from the washing machine.

[0075] S200: Determine the foam information in the washing machine based on the sound signal.

[0076] In this embodiment, sound signals from the washing machine are acquired to determine the foam bursting status. Based on the sound signals, foam information is determined to process the foam. By determining foam information based on sound signals and processing the foam accordingly, foam adhering to clothes is reduced and foam overflow is prevented, thereby improving the washing effect and the reliability of washing machine control. Furthermore, since the washing machine does not need to be left to stand during sound signal acquisition, washing efficiency is improved. Moreover, since determining foam information using sound signals is not limited by the liquid level in the washing machine, it avoids the inability to determine foam information when the liquid level is too high, thus improving the effectiveness of washing machine control.

[0077] In one embodiment, before determining the foam information in the washing machine based on the sound signal in step S200, the washing machine control method further includes:

[0078] High-frequency filtering is applied to the audio signal.

[0079] In this embodiment, noise may exist in the environment where the washing machine is located and inside the washing machine drum, interfering with the sound signal and preventing it from accurately reflecting foam information. Since the sound signal has a high frequency when foam bursts, high-frequency filtering is performed to eliminate mid- and low-frequency noise. By processing the sound signal at high frequencies, environmental noise is prevented from affecting the determination of foam information, thereby improving the accuracy of the foam information.

[0080] For example, the high-frequency filtering of the audio signal in the above steps can be implemented by the following algorithm:

[0081] y[i]=α×y[i-1]+α×(x[i]-x[i-1]);

[0082] Where y represents the amplitude of the filtered sound signal, x represents the amplitude of the unfiltered sound signal, α represents the filtering coefficient, i ranges from 1 to n, and n is the total number of amplitudes in the sound signal.

[0083] It is understood that, in addition to the algorithms mentioned above, high-frequency filtering can also be performed using software algorithms such as Butterworth filtering, infinite impulse response filtering, and gradient-based filtering, or corresponding hardware circuits. No limitation is made here.

[0084] In one embodiment, such as Figure 2 As shown, the foam information includes the quantity of foam. The foam information in the washing machine, determined based on the sound signal in step S200, can be determined in the following way:

[0085] S210. Determine the first number of foam bursts in the washing machine based on the sound signal.

[0086] S220: Obtain the water temperature of the washing machine.

[0087] S230. Determine the amount of foam based on the first quantity and water temperature.

[0088] In this embodiment, since the amplitude of the sound signal fluctuates when the foam bursts, a first number of foam bursts in the washing machine is determined based on the sound signal. Because the water temperature of the washing machine affects the number of foam bursts per unit time, the water temperature is obtained, and the number of foams is determined based on the first number of foam bursts and the water temperature. By combining the first number of foam bursts and the water temperature to determine the number of foams, the influence of water temperature on the determination of the foam number is eliminated, thereby improving the accuracy of the foam number determination.

[0089] In one embodiment, the determination of the first number of foam bursts in the washing machine based on the sound signal in step S210 is made in the following manner:

[0090] Multiple frequency values ​​of the sound signal are determined based on the multiple amplitude values ​​of the sound signal at different times.

[0091] The first quantity is determined based on multiple frequency values.

[0092] In this embodiment, since the sound signal when foam bursts has a high frequency, the frequency value of the sound signal can accurately reflect whether the foam has burst and the number of bursts. Therefore, it is necessary to convert the amplitude of the sound signal into a frequency value. Because the sound signal has discrete amplitudes after sampling, multiple discrete frequency values ​​of the sound signal are determined based on the multiple amplitudes of the sound signal at different times. Based on these multiple frequency values, the number of burst foams can be accurately determined, thereby improving the accuracy of the foam count.

[0093] In one embodiment, the determination of multiple frequency values ​​of the sound signal based on multiple amplitude values ​​of the sound signal at different times in the above steps is performed in the following manner:

[0094] Grouping multiple amplitude values.

[0095] Each set of amplitude values ​​is converted to obtain multiple sets of frequency values.

[0096] In this embodiment, since the sound signal is a discrete amplitude after sampling, directly converting it to frequency values ​​would result in a large computational load and inaccurate conversion results. Multiple amplitude values ​​are grouped so that each group reflects the changes in the sound signal over a certain period. Each group of amplitude values ​​is then converted to obtain multiple sets of frequency values ​​to determine the initial number of burst bubbles. By grouping the values ​​before conversion, the error in the converted frequency values ​​is reduced, thereby improving the accuracy of the bubble count.

[0097] For example, grouping multiple amplitude values ​​in the above steps can be done by grouping each preset number of amplitude values ​​into a group according to the chronological order.

[0098] For example, the conversion of each group of amplitude values ​​in the above steps to obtain multiple groups of frequency values ​​can be achieved by converting the amplitude values ​​into frequency values ​​through Fourier transform.

[0099] It is understandable that, in addition to the method of grouping first and then converting to obtain multiple sets of frequency values, the method of converting first and then grouping can also be used to obtain multiple sets of frequency values; no limitation is made here.

[0100] In one embodiment, the determination of the first quantity based on multiple frequency values ​​in the above steps is made in the following manner:

[0101] The maximum value in each group of frequency values ​​is determined as the maximum frequency value.

[0102] Determine the poles of the frequency signal formed by the maximum frequency values.

[0103] Determine the first quantity based on the extreme point.

[0104] In this embodiment, since the maximum value in each group of frequency values ​​reflects the severity of foam bursting over a period of time, the maximum frequency value in each group is determined. Since the first number of foam bursts is related to the poles of the frequency signal composed of the maximum frequency values, the poles of the frequency signal are determined, and the first number is determined based on the poles. By determining the first number by identifying the poles of the frequency signal composed of the maximum frequency values, the accuracy of the foam count is improved, as the poles reflect the number of foam bursts.

[0105] For example, the determination of the poles of the frequency signal composed of the maximum frequency values ​​in the above steps can be calculated using the derivative gradient method.

[0106] In one embodiment, there are multiple sound sensors, each detecting one sound signal. The determination of the first number based on the poles in the above steps is made as follows:

[0107] The second quantity is obtained by summing the poles corresponding to each sound signal.

[0108] The ratio of the second quantity to the number of sound signals is determined as the third quantity.

[0109] The ratio of the third quantity to the first preset value is determined as the first quantity.

[0110] In this embodiment, since there are multiple sound signals, each sound signal reflects the same foam bursting situation within the same time period. The second quantity is obtained by summing the poles corresponding to each sound signal, and the ratio of the second quantity to the number of sound signals is determined as the third quantity. The average of the poles is then used to reduce the error in sound signal acquisition. Because sound needs to travel back and forth to the sound sensor, the ratio of the third quantity to a first preset value is determined as the first quantity to eliminate the influence of sound propagation back and forth. By processing the poles of each sound signal, the error of the first quantity is reduced, thereby improving the accuracy of the foam count.

[0111] For example, the first preset value can be 2.

[0112] It is understandable that, in the above steps, determining the first quantity based on the extreme point can also be done by using the third quantity as the first quantity without performing the above steps to determine the ratio of the third quantity to the first preset value as the first quantity.

[0113] For example, taking a sound sensor comprising a first sound sensor, a second sound sensor, and a third sound sensor as an example, step S210 will be described. The sound signal detected by the first sound sensor is the first sound signal, the sound signal detected by the second sound sensor is the second sound signal, and the sound signal detected by the third sound sensor is the third sound signal. The amplitude values ​​of the first, second, and third sound signals are grouped, and a Fourier transform is performed on each group of amplitude values ​​to obtain multiple groups of frequency values. The maximum value in each group of frequency values ​​is determined as the maximum frequency value. The maximum frequency values ​​in the first sound signal constitute the first frequency signal, the maximum frequency values ​​in the second sound signal constitute the second frequency signal, and the maximum frequency values ​​in the third sound signal constitute the third frequency signal. The poles in the first, second, and third frequency signals are determined using the derivative gradient method and denoted as env1, env2, and env3, respectively. The sum of env1, env2, and env3 is divided by 6 to obtain the first quantity.

[0114] For example, obtaining the water temperature of the washing machine in step S220 can be done by obtaining the water temperature value detected by the temperature measuring device corresponding to the heating element in the washing machine.

[0115] For example, in step S230, the number of foams is determined based on the first quantity and the water temperature in the following manner:

[0116] The amount of foam is determined based on the first quantity, water temperature, and a first preset relationship.

[0117] Among them, the first preset relationship is used to characterize the relationship between the preset number of ruptures and the preset water temperature and preset number of foams.

[0118] In one embodiment, such as Figure 3 As shown, the foam information includes the foam distribution. The step S200, determining the foam information in the washing machine based on the sound signal, can also be determined in the following way:

[0119] S240. Determine the average value of multiple amplitudes of the sound signal at different times as the average amplitude.

[0120] S250. Determine the foam distribution based on the average amplitude.

[0121] In this embodiment, since the sound signal has discrete amplitudes after sampling, and the average of multiple amplitudes can reflect the foam bursting within a certain time, the average amplitude of the sound signal is determined. Based on the average amplitude, the distance between the foam and the sound sensor detecting the sound signal is determined, thus determining the foam distribution. By determining the foam distribution based on the average amplitude of the sound signal, uneven foam distribution that could lead to overflow or foam sticking to clothes is avoided, thereby improving the reliability of the washing machine control and the washing effect of the washing machine.

[0122] In one embodiment, there are multiple sound sensors, each detecting one sound signal. The determination of the foam distribution based on the average amplitude in step S250 can be achieved as follows:

[0123] If the difference between the two average amplitudes is greater than the second preset value, it is determined that the foam distribution is uneven.

[0124] If the difference between any two average amplitudes is less than or equal to the second preset value, the foam distribution is determined to be uniform.

[0125] In this embodiment, since there are multiple sound sensors detecting sound signals, when the foam distribution is uniform, the average amplitude of each sound signal is approximately the same over a certain period of time. When the foam distribution is uneven, at least one sound signal has a larger average amplitude and at least one sound signal has a smaller average amplitude over a certain period of time. If the difference between two average amplitudes is greater than a second preset value, the foam distribution is biased towards one sound sensor and away from the other, indicating uneven foam distribution. If the difference between any two average amplitudes is less than or equal to the second preset value, the foam distribution is not biased towards any sound sensor, indicating uniform foam distribution. By determining whether the foam distribution is uniform based on the average amplitude of multiple sound signals, foam overflow due to uneven distribution is avoided, thereby improving the reliability of the washing machine control.

[0126] For example, taking a sound sensor comprising a first sound sensor, a second sound sensor, and a third sound sensor as an example, step S250 will be described. The sound signal detected by the first sound sensor is the first sound signal, the sound signal detected by the second sound sensor is the second sound signal, and the sound signal detected by the third sound sensor is the third sound signal. The average value of each amplitude in the first, second, and third sound signals is calculated to obtain a first average amplitude, a second average amplitude, and a third average amplitude. If the absolute value of at least one of the absolute values ​​of the first and second average amplitudes, the second and third average amplitudes, and the difference between the first and third average amplitudes is greater than a second preset value, it is determined that the foam distribution is uneven. If the absolute value of each of the absolute values ​​of the first and second average amplitudes, the second and third average amplitudes, and the difference between the first and third average amplitudes is less than or equal to the second preset value, it is determined that the foam distribution is uniform.

[0127] In one embodiment, there are multiple sound sensors, each detecting one sound signal. The determination of the foam distribution based on the average amplitude in step S250 can also be achieved as follows:

[0128] When an average amplitude is greater than the sum of two average amplitudes, it is determined that the sound sensor corresponding to the sound signal with the largest average amplitude has more foam distribution than the sound sensor corresponding to other sound signals.

[0129] If each average amplitude is less than the sum of any two average amplitudes, it is determined that the foam distribution of the sound sensor corresponding to each sound signal is the same.

[0130] In this embodiment, since there are multiple sound sensors detecting sound signals, the average amplitude of each sound signal is approximately the same over a certain period of time when the foam distribution is not biased towards any one sound sensor. When the foam distribution is biased towards one sound sensor, the average amplitude of that sound sensor is larger over a certain period of time. When one average amplitude is greater than the sum of two average amplitudes, the foam distribution is biased towards the sound sensor corresponding to the sound signal with the larger average amplitude, determining that the sound sensor corresponding to the sound signal with the largest average amplitude has more foam distribution than the sound sensors corresponding to other sound signals. When each average amplitude is less than the sum of any two average amplitudes, the foam distribution is not biased towards any one sound signal, determining that the foam distribution of the sound sensors corresponding to each sound signal is the same. By determining the bias of the foam distribution based on the average amplitude of multiple sound signals, uneven foam distribution and overflow are avoided, thereby improving the reliability of the washing machine control.

[0131] For example, determining that the foam distribution of the sound sensor corresponding to each sound signal is the same in the above steps can mean determining that the foam distribution of the sound sensor corresponding to each sound signal is approximately the same.

[0132] For example, taking a sound sensor comprising a first sound sensor, a second sound sensor, and a third sound sensor as an example, step S250 will be described. The sound signal detected by the first sound sensor is the first sound signal, the sound signal detected by the second sound sensor is the second sound signal, and the sound signal detected by the third sound sensor is the third sound signal. The average values ​​of each of the first, second, and third sound signals are calculated to obtain a first average amplitude, a second average amplitude, and a third average amplitude. If the first average amplitude is greater than the sum of the second and third average amplitudes, the foam distribution is biased towards the first sound sensor. If the second average amplitude is greater than the sum of the first and third average amplitudes, the foam distribution is biased towards the second sound sensor. If the third average amplitude is greater than the sum of the first and second average amplitudes, the foam distribution is biased towards the third sound sensor. If the first average amplitude is less than or equal to the sum of the second and third average amplitudes, and the second average amplitude is less than or equal to the sum of the first and third average amplitudes and the third average amplitude is less than or equal to the sum of the first and second average amplitudes, then the degree to which the foam distribution is biased towards the first, second, and third sound sensors is approximately the same.

[0133] In one embodiment, such as Figure 4 As shown, the foam information includes foam size. The step S200, which determines the foam information in the washing machine based on the sound signal, can also be determined in the following ways:

[0134] S260. Determine the maximum value of multiple amplitude values ​​of the sound signal at different times as the maximum amplitude value.

[0135] S270, Obtain the water level of the washing machine.

[0136] S280, Obtain the water temperature of the washing machine.

[0137] S290. Determine the foam size based on the maximum amplitude, water level, and water temperature.

[0138] In this embodiment, since the amplitude of the sound signal changes differently when bubbles of different sizes burst, the maximum value of multiple amplitude values ​​of the sound signal at different times is determined as the maximum amplitude value, so as to determine the amplitude change caused by the largest bubble bursting within a certain time period. Since the water level and temperature of the washing machine affect the size of the foam, the water level and temperature of the washing machine are obtained, and the foam size is determined based on the maximum amplitude value, water level, and water temperature. By combining the maximum amplitude value, water level, and water temperature to determine the foam size, the foam size can correspond to the water temperature, thereby improving the accuracy of foam size determination.

[0139] For example, obtaining the water level of the washing machine in step S270 can be done by obtaining the water level value detected by the water level sensor in the washing machine.

[0140] For example, obtaining the water temperature of the washing machine in step S280 can be done by obtaining the water temperature value detected by the temperature measuring device corresponding to the heating element in the washing machine.

[0141] For example, in step S290, the foam size is determined based on the maximum amplitude, water level, and water temperature in the following manner:

[0142] The size of the foam is determined based on the maximum amplitude, water level, water temperature, and a second preset relationship.

[0143] The second preset relationship is used to characterize the relationship between preset amplitude, preset water level, preset water temperature and preset foam size.

[0144] It is understood that steps S210-S230, S240-S250, and S260-S290 can be executed sequentially, or only one or more of them can be executed in parallel; no restrictions are imposed here.

[0145] In one embodiment, the acquisition of the sound signal from the washing machine in step S100 can be determined in the following way:

[0146] Acquire the sound signals from the washing machine before the spin cycle begins.

[0147] In this embodiment, if a certain amount of foam remains in the washing machine during the spin-drying process, the foam may adhere to the clothes. By acquiring sound signals before the spin-drying program begins, foam information is determined and foam is eliminated to reduce foam adhesion to clothes, thereby improving the washing machine's cleaning effect.

[0148] In one embodiment, the acquisition of the sound signal from the washing machine in step S100 can also be determined in the following way:

[0149] After the washing machine's spin cycle ends, acquire the sound signal from the washing machine.

[0150] In this embodiment, during the spin-drying process, the washing machine may generate new foam on the clothes, causing the foam to adhere to the clothes. By acquiring sound signals after the spin-drying cycle ends, foam information can be identified and eliminated to reduce foam adhesion to clothes, thereby improving the washing machine's cleaning effect.

[0151] It is understood that the acquisition of the washing machine's sound signal in step S100 can be performed not only before the start of the washing machine's spin cycle and / or after the spin cycle ends, but also at any time when the inner drum of the washing machine stops rotating; there is no limitation here.

[0152] In one embodiment, after determining the foam information in the washing machine based on the sound signal in step S200, the washing machine control method further includes:

[0153] When the foam information meets the preset conditions, control the washing machine to enter the spin-drying process or end the washing cycle.

[0154] If the foam information does not meet the preset conditions, eliminate the foam in the washing machine.

[0155] In this embodiment, when the foam information meets preset conditions, the foam information in the washing machine can meet the requirements of dehydration or ending the wash cycle without causing clothes to stick together with foam, thus controlling the washing machine to enter the dehydration process or end the wash cycle. When the foam information does not meet the preset conditions, the foam information in the washing machine cannot meet the requirements of dehydration, causing clothes to stick together with foam, thus eliminating the foam in the washing machine. By determining whether to eliminate foam based on the foam information in the washing machine, the problem of clothes sticking together with foam is avoided, thereby improving the washing effect of the washing machine.

[0156] In one embodiment, the foam information includes the number of foam particles. A preset condition includes the number of foam particles being less than a third preset value.

[0157] In this embodiment, the amount of foam is used as a preset condition to determine whether the foam in the washing machine needs to be eliminated, thus avoiding excessive foam from sticking to the clothes and improving the washing effect of the washing machine.

[0158] In one embodiment, the foam information includes foam distribution. A preset condition includes uniform foam distribution.

[0159] In this embodiment, the foam distribution is used as a preset condition to determine whether it is necessary to eliminate the foam in the washing machine, thereby avoiding uneven foam distribution that would stick to the clothes and improving the washing machine's cleaning effect.

[0160] In one embodiment, the foam information includes foam size. A preset condition includes a foam size greater than a fourth preset value.

[0161] In this embodiment, the size of the foam is used as a preset condition to determine whether the foam in the washing machine needs to be eliminated, so as to avoid the foam being too small and sticking to the clothes, thereby improving the washing effect of the washing machine.

[0162] For example, the process of eliminating foam in the washing machine in the above steps can be done by water inlet and outlet, by spraying, or by adding defoamer; there is no limitation here.

[0163] For example, the process of eliminating foam in the washing machine in the above steps can be achieved by combining the amount of foam, the distribution of foam and / or the size of foam to determine the water inlet and outlet flow rate and its rate, the spray location and its rate, and the amount of defoamer added.

[0164] For example, the first preset relationship, the second preset relationship, the second preset value, the third preset value, and the fourth preset value can be determined experimentally before the washing machine leaves the factory.

[0165] This disclosure provides a washing machine control method, such as... Figure 5 As shown, the method includes:

[0166] S300: Before the spin cycle of the washing machine begins, acquire various sound signals from the washing machine.

[0167] S310 performs high-frequency filtering on each audio signal.

[0168] S320: Group the multiple amplitude values ​​of each sound signal at different times.

[0169] S330: Convert each group of amplitude values ​​in each sound signal to obtain multiple groups of frequency values.

[0170] S340. Determine the maximum value in each group of frequency values ​​as the maximum frequency value.

[0171] S350. Determine the poles of the frequency signal formed by the maximum frequency values ​​in each sound signal.

[0172] S360. Summing the poles corresponding to each sound signal yields the second quantity.

[0173] S370. Determine the ratio of the second quantity to the number of sound signals as the third quantity.

[0174] S380. Determine the ratio of the third quantity to the first preset value as the first quantity.

[0175] S390, Obtain the water temperature of the washing machine.

[0176] S400. Determine the amount of foam based on the first quantity and water temperature.

[0177] S410. Determine the average value of multiple amplitudes of each sound signal at different times as the average amplitude.

[0178] S420. If the difference between the two average amplitudes is greater than the second preset value, it is determined that the foam distribution is uneven.

[0179] S430. When the difference between any two average amplitudes is less than or equal to the second preset value, the foam distribution is determined to be uniform.

[0180] S440. Determine the maximum value of multiple amplitude values ​​of each sound signal at different times as the maximum amplitude value.

[0181] S450: Obtain the water level of the washing machine.

[0182] S460: Obtain the water temperature of the washing machine.

[0183] S470. Determine the foam size based on the maximum amplitude, water level, and water temperature.

[0184] S480: When the number of foams is less than the third preset value, the foams are evenly distributed, and the foam size is greater than the fourth preset value, control the washing machine to enter the spin-drying process.

[0185] S490. When the number of foams is greater than or equal to a third preset value, the foam distribution is uneven, and / or the foam size is less than or equal to a fourth preset value, eliminate the foam in the washing machine.

[0186] In this embodiment, before the washing machine's spin-drying cycle begins, sound signals from the washing machine are acquired to determine foam information. High-frequency filtering is applied to the sound signals to eliminate noise interference from the washing machine's environment, improving the accuracy of the foam information. Since the sampled sound signals include multiple discrete amplitudes, these amplitudes are grouped, and each group is converted into a frequency value. The poles of the frequency signals formed by the maximum values ​​in each group are determined, and the average of these poles is divided by a first preset value to reduce errors in the initial number of foam bursts. Because the washing machine's water temperature affects the number of foam bursts per unit time, the water temperature is acquired and combined with the initial number of bursts to determine the number of foam bursts. Since the amplitude change of the sound signal caused by foam bursts over a certain time is related to the foam distribution, the average amplitude of the sound signal is determined. When the difference between two average amplitudes is large, the foam distribution is biased towards the sound sensor with the larger average amplitude and away from the sound sensor with the smaller average amplitude, indicating uneven foam distribution. When the difference between any two average amplitudes is less than or equal to a second preset value, the foam distribution is not biased towards either sound sensor, indicating uniform foam distribution. Because the amplitude of the sound signal caused by the bursting of the largest foam changes significantly, the maximum amplitude of the sound signal is determined to determine the size of the largest foam. Since the water level and temperature of the washing machine affect the size of the largest foam, the water level and temperature are obtained and combined with the maximum amplitude to determine the foam size. When the number of foams is less than a third preset value, the foam distribution is uniform, and the foam size is greater than a fourth preset value, the washing machine will not allow foam to stick to the clothes or overflow during the spin-drying process, thus controlling the washing machine to enter the spin-drying process. When the number of foams is greater than or equal to the third preset value, the foam distribution is uneven, and / or the foam size is less than or equal to the fourth preset value, the washing machine will allow foam to stick to the clothes and / or overflow during the spin-drying process, thus eliminating the foam in the washing machine. By determining foam information based on the sound signal, foam processing is performed to reduce foam sticking to clothes and prevent foam overflow, thereby improving the washing machine's cleaning effect and the reliability of its control. Furthermore, since the washing machine does not need to be left to stand during the sound signal acquisition process, the washing efficiency is improved. Furthermore, since determining foam information using sound signals is not limited by the liquid level in the washing machine, it avoids the inability to determine foam information when the liquid level is too high, thereby improving the effectiveness of washing machine control.

[0187] In one exemplary embodiment, a washing machine control device is provided for implementing the method described above. (Reference) Figure 6 As shown, the washing machine control device may include an acquisition module 100 and a determination module 200, wherein, during the implementation of the above method,

[0188] Acquisition module 100 is configured to acquire sound signals from the washing machine.

[0189] The determination module 200 is configured to determine foam information in the washing machine based on sound signals.

[0190] In one exemplary embodiment, a washing machine control device is provided, wherein an acquisition module 100 is configured to:

[0191] Acquire the sound signals from the washing machine before the spin cycle begins.

[0192] In one exemplary embodiment, a washing machine control device is provided, wherein an acquisition module 100 is configured to:

[0193] After the washing machine's spin cycle ends, acquire the sound signal from the washing machine.

[0194] In one exemplary embodiment, a washing machine control device is provided, wherein a determining module 200 is configured to:

[0195] Determine the first number of foam bursts in the washing machine based on the sound signals.

[0196] Get the water temperature of the washing machine.

[0197] Determine the amount of foam based on the initial quantity and water temperature.

[0198] In one exemplary embodiment, a washing machine control device is provided, wherein a determining module 200 is configured to:

[0199] Multiple frequency values ​​of the sound signal are determined based on the multiple amplitude values ​​of the sound signal at different times.

[0200] The first quantity is determined based on multiple frequency values.

[0201] In one exemplary embodiment, a washing machine control device is provided, wherein a determining module 200 is configured to:

[0202] Grouping multiple amplitude values.

[0203] Each set of amplitude values ​​is converted to obtain multiple sets of frequency values.

[0204] In one exemplary embodiment, a washing machine control device is provided, wherein a determining module 200 is configured to:

[0205] The maximum value in each group of frequency values ​​is determined as the maximum frequency value.

[0206] Determine the poles of the frequency signal formed by the maximum frequency values.

[0207] Determine the first quantity based on the extreme point.

[0208] In one exemplary embodiment, a washing machine control device is provided, wherein a determining module 200 is configured to:

[0209] The second quantity is obtained by summing the poles corresponding to each sound signal.

[0210] The ratio of the second quantity to the number of sound signals is determined as the third quantity.

[0211] The ratio of the third quantity to the first preset value is determined as the first quantity.

[0212] In one exemplary embodiment, a washing machine control device is provided, wherein a determining module 200 is configured to:

[0213] The average amplitude is determined by averaging the multiple amplitudes of the sound signal at different times.

[0214] The distribution of foam is determined based on the average amplitude.

[0215] In one exemplary embodiment, a washing machine control device is provided, wherein a determining module 200 is configured to:

[0216] If the difference between the two average amplitudes is greater than the second preset value, it is determined that the foam distribution is uneven.

[0217] If the difference between any two average amplitudes is less than or equal to the second preset value, the foam distribution is determined to be uniform.

[0218] In one exemplary embodiment, a washing machine control device is provided, wherein a determining module 200 is configured to:

[0219] When an average amplitude is greater than the sum of two average amplitudes, it is determined that the sound sensor corresponding to the sound signal with the largest average amplitude has more foam distributions than the sound sensors corresponding to other sound signals.

[0220] If each average amplitude is less than the sum of any two average amplitudes, it is determined that the foam distribution of the sound sensor corresponding to each sound signal is the same.

[0221] In one exemplary embodiment, a washing machine control device is provided, wherein a determining module 200 is configured to:

[0222] The maximum amplitude of a sound signal at different times is determined as the maximum amplitude value.

[0223] Get the water level in the washing machine.

[0224] Get the water temperature of the washing machine.

[0225] The size of the foam is determined based on the maximum amplitude, water level, and water temperature.

[0226] In one exemplary embodiment, a washing machine control device is provided, the device further comprising:

[0227] The filtering module is configured to perform high-frequency filtering on audio signals.

[0228] In one exemplary embodiment, a washing machine control device is provided, the device further comprising:

[0229] The control module is configured to control the washing machine to enter the spin-drying process or end the washing process when the foam information meets preset conditions.

[0230] The foam elimination module is configured to eliminate foam in the washing machine when the foam information does not meet preset conditions.

[0231] In one exemplary embodiment, a washing machine is provided, such as a single-drum washing machine, a multi-drum washing machine, and a pulsator washing machine.

[0232] refer to Figure 7 As shown, the washing machine 400 may include one or more of the following components: a processing component 402, a memory 404, a power supply component 406, a multimedia component 408, an audio component 410, an input / output (I / O) interface 412, a sensor component 414, and a communication component 416.

[0233] Processing component 402 typically controls the overall operation of washing machine 400, including operations associated with display, telephone calls, data communication, camera operation, and recording. Processing component 402 may include one or more processors 420 to execute instructions to complete all or part of the steps of the methods described above. Furthermore, processing component 402 may include one or more modules to facilitate interaction between processing component 402 and other components. For example, processing component 402 may include a multimedia module to facilitate interaction between multimedia component 408 and processing component 402.

[0234] Memory 404 is configured to store various types of data to support the operation of washing machine 400. Examples of this data include instructions for any application or method used to operate on washing machine 400, contact data, phonebook data, messages, pictures, videos, etc. Memory 404 can be implemented by any type of volatile or non-volatile storage terminal or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0235] The power supply assembly 406 provides power to the various components of the washing machine 400. The power supply assembly 406 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the washing machine 400.

[0236] Multimedia component 408 includes a screen that provides an output interface between washing machine 400 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of touch or swipe actions but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 408 includes a front-facing camera module and / or a rear-facing camera module. When washing machine 400 is in an operating mode, such as a shooting mode or video mode, the front-facing camera module and / or rear-facing camera module may receive external multimedia data. Each front-facing camera module and rear-facing camera module may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0237] Audio component 410 is configured to output and / or input audio signals. For example, audio component 410 includes a microphone (MIC) configured to receive external audio signals when washing machine 400 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 404 or transmitted via communication component 416. In some embodiments, audio component 410 also includes a speaker for outputting audio signals.

[0238] I / O interface 412 provides an interface between processing component 402 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0239] Sensor assembly 414 includes one or more sensors for providing state assessments of various aspects of washing machine 400. For example, sensor assembly 414 may detect the on / off state of washing machine 400, the relative positioning of components such as the display and keypad of washing machine 400, changes in the position of washing machine 400 or one of its components, the presence or absence of user contact with washing machine 400, the orientation or acceleration / deceleration of washing machine 400, and temperature changes of washing machine 400. Sensor assembly 414 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 414 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 414 may also include an accelerometer, gyroscope, magnetometer, pressure sensor, or temperature sensor.

[0240] Communication component 416 is configured to facilitate wired or wireless communication between washing machine 400 and other terminals. Washing machine 400 can access wireless networks based on communication standards, such as WiFi, 2G, 3G, 4G, 5G, or combinations thereof. In one exemplary embodiment, communication component 416 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 416 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0241] In an exemplary embodiment, the washing machine 400 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing terminals (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.

[0242] In one exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 404 including instructions, which can be executed by a processor 420 of the washing machine 400 to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage terminal, etc. When the instructions in the storage medium are executed by the terminal's processor, the terminal is able to perform the method shown in the above embodiments.

[0243] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the claims.

[0244] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A washing machine control method, characterized in that, The washing machine control method includes: Acquire sound signals from the washing machine; Based on the sound signal, determine the foam information in the washing machine; Wherein, the foam information includes the number of foams; determining the foam information in the washing machine based on the sound signal includes: Based on the multiple amplitude values ​​of the sound signal at different times, determine multiple frequency values ​​of the sound signal; Based on the multiple frequency values, a first number of foam bursts in the washing machine is determined; Obtain the water temperature of the washing machine; The number of bubbles is determined based on the first quantity, the water temperature, and the first preset relationship, wherein the first preset relationship is used to characterize the relationship between the preset number of bubbles and the preset water temperature and the preset number of bubbles.

2. The washing machine control method according to claim 1, characterized in that, Determining multiple frequency values ​​of the sound signal based on multiple amplitude values ​​of the sound signal at different times includes: The multiple amplitude values ​​are grouped; Each set of amplitude values ​​is converted to obtain multiple sets of frequency values.

3. The washing machine control method according to claim 2, characterized in that, Determining the first quantity based on the plurality of frequency values ​​includes: The maximum value among the frequency values ​​in each group is determined as the maximum frequency value; Determine the poles of the frequency signal formed by the maximum frequency values ​​described above; The first quantity is determined based on the stated pole.

4. The washing machine control method according to claim 3, characterized in that, The number of sound signals is multiple; determining the first number based on the poles includes: The second quantity is obtained by summing the poles corresponding to each of the aforementioned sound signals; The ratio of the second quantity to the quantity of the sound signals is determined to be the third quantity; The ratio of the third quantity to the first preset value is determined to be the first quantity.

5. The washing machine control method according to claim 1, characterized in that, The foam information includes foam distribution; determining the foam information in the washing machine based on the sound signal includes: The average value of multiple amplitudes of the sound signal at different times is determined as the average amplitude. The foam distribution is determined based on the average amplitude.

6. The washing machine control method according to claim 5, characterized in that, The number of sound signals is multiple; determining the foam distribution based on the average amplitude includes: If the difference between the two average amplitudes is greater than a second preset value, it is determined that the foam distribution is uneven. If the difference between any two of the stated average amplitudes is less than or equal to the second preset value, the foam distribution is determined to be uniform; and / or, If one of the average amplitudes is greater than the sum of the two average amplitudes, it is determined that the foam distribution of the sound sensor corresponding to the sound signal with the largest average amplitude is greater than the foam distribution of the sound sensors corresponding to the other sound signals. If each of the average amplitudes is less than the sum of any two of the average amplitudes, it is determined that the foam distribution of the sound sensor corresponding to each of the sound signals is the same.

7. The washing machine control method according to claim 1, characterized in that, The foam information includes foam size; determining the foam information in the washing machine based on the sound signal includes: The maximum amplitude of the sound signal at different times is determined as the maximum amplitude value. Obtain the water level of the washing machine; Obtain the water temperature of the washing machine; The size of the foam is determined based on the maximum amplitude, the water level, and the water temperature.

8. The washing machine control method according to claim 1, characterized in that, The acquisition of sound signals from the washing machine includes: Before the spin-drying program of the washing machine begins, acquire the sound signal from the washing machine; and / or, After the spin-drying cycle of the washing machine is completed, the sound signal from the washing machine is acquired.

9. The washing machine control method according to claim 1, characterized in that, Before determining the foam information in the washing machine based on the sound signal, the washing machine control method further includes: The sound signal is subjected to high-frequency filtering.

10. The washing machine control method according to any one of claims 1 to 9, characterized in that, After determining the foam information in the washing machine based on the sound signal, the washing machine control method further includes: When the foam information meets the preset conditions, the washing machine is controlled to enter the spin-drying process or end the washing process. If the foam information does not meet the preset conditions, the foam in the washing machine is eliminated.

11. The washing machine control method according to claim 10, characterized in that, The foam information includes the number of foams, the distribution of foams, and / or the size of foams; the preset conditions include the number of foams being less than a third preset value, the distribution of foams being uniform, and / or the size of foams being greater than a fourth preset value.

12. A washing machine control device, characterized in that, The washing machine control device includes: An acquisition module, configured to acquire sound signals from the washing machine; A determining module is configured to determine foam information in the washing machine based on the sound signal, the foam information including the number of foams; The determining module is further configured to determine multiple frequency values ​​of the sound signal based on multiple amplitude values ​​of the sound signal at different times; Based on the multiple frequency values, a first number of foam bursts in the washing machine is determined; Obtain the water temperature of the washing machine; The number of bubbles is determined based on the first quantity, the water temperature, and the first preset relationship, wherein the first preset relationship is used to characterize the relationship between the preset number of bubbles and the preset water temperature and the preset number of bubbles.

13. A washing machine, characterized in that, The washing machine includes: processor; Memory used to store the processor's executable instructions; The processor is configured to perform the washing machine control method as described in any one of claims 1 to 11.

14. A non-transitory computer-readable storage medium, characterized in that, When the instructions in the storage medium are executed by the processor of the terminal, the terminal is able to perform the washing machine control method as described in any one of claims 1 to 11.

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