Laundry machine foam detection method, apparatus, medium, device, and laundry machine

Abstract

The present disclosure relates to a laundry machine foam detection method, device, medium, equipment and laundry machine, the method comprising: acquiring a water level frequency waveform of at least one laundry beat; determining that the foam is excessive when the foam excess condition is met based on the water level frequency waveform of at least one laundry beat. Thus, whether the foam is excessive in the laundry stage can be detected based on at least one complete laundry beat, which not only realizes the detection of the foam in the laundry stage, but also helps to improve the detection accuracy, thereby reducing the risk of foam overflow and improving the user experience.

Description

Technical Field

[0001] This disclosure relates to the field of washing machine technology, and in particular to a method, apparatus, medium, equipment, and washing machine for detecting foam in a washing machine. Background Technology

[0002] In recent years, with rapid economic growth and technological progress, people's living standards have continued to improve, and washing machines have gradually entered people's homes, becoming an indispensable household appliance in people's daily lives.

[0003] Foam may be generated during washing machine use. Typically, foam can be detected during the washing and draining or spin-drying stages by detecting the current. Specifically, the viscosity of foam increases the resistance between the inner and outer tubs, increasing the motor load and consequently the current, allowing for foam detection. However, this method cannot detect foam during the washing stage, and excessive foam during this stage can lead to overflow, resulting in a poor user experience. Summary of the Invention

[0004] In order to solve the above-mentioned technical problems, or at least partially solve the above-mentioned technical problems, this disclosure provides a method, apparatus, medium, equipment and washing machine for detecting foam in a washing machine.

[0005] This disclosure provides a method for detecting foam in a washing machine, the method comprising:

[0006] Obtain the water level frequency waveform for at least one washing cycle;

[0007] Based on the water level frequency waveform of at least one of the washing cycles, if the condition of excessive foam is met, it is determined that there is excessive foam.

[0008] Optionally, determining excessive foam based on the water level frequency waveform of at least one of the washing cycles, when the excessive foam condition is met, includes:

[0009] For any of the aforementioned washing cycles, the maximum and minimum water level ranges are determined based on the water level frequency waveform.

[0010] The characteristic value is determined based on the maximum and minimum water level ranges.

[0011] Determine whether the feature value is equal to or greater than a preset feature value threshold;

[0012] If the feature value is equal to or greater than the preset feature value threshold, then excessive foam is determined.

[0013] Optionally, determining the characteristic value based on the maximum and minimum water level ranges includes:

[0014] The characteristic value is obtained by dividing the maximum water level difference by the minimum water level difference.

[0015] Alternatively, the characteristic value can be obtained by subtracting the minimum water level difference from the maximum water level difference.

[0016] Optionally, determining the maximum and minimum water level ranges based on the water level frequency waveform includes:

[0017] Based on the water level frequency waveform, the first minimum and first maximum extreme values ​​within the initial first time period are determined, and the maximum water level range is obtained by subtracting the first minimum extreme value from the first maximum extreme value; wherein, the initial first time period is within the first one-third period of the water level frequency waveform;

[0018] Based on the water level frequency waveform, the minimum value of the second extreme value and the maximum value of the second extreme value within the last second time period are determined. The minimum value of the water level range is obtained by subtracting the minimum value of the second extreme value from the maximum value of the second extreme value. The last second time period is within the last one-third period of the water level frequency waveform.

[0019] Optionally, determining excessive foam based on the water level frequency waveform of at least one of the washing cycles, when the excessive foam condition is met, includes:

[0020] Based on the water level frequency waveform of three consecutive washing cycles, if the condition of excessive foam is met, it is determined that there is excessive foam.

[0021] Optionally, the method further includes:

[0022] After determining whether the washing machine is in the washing stage or after a preset time since the washing stage has started;

[0023] If it is determined that the washing machine is in the washing stage or after a preset time since the start of the washing stage, the water level sensor is controlled to collect water level data at a certain frequency.

[0024] This disclosure also provides a washing machine foam detection device, the device comprising:

[0025] The data acquisition module is used to acquire the water level frequency waveform of at least one washing cycle;

[0026] The condition judgment module is used to determine that there is excessive foam when the water level frequency waveform of at least one of the washing beats is satisfied.

[0027] This disclosure also provides a computer-readable storage medium having a computer program stored thereon, the computer program being executed by a processor to implement the steps of any of the above methods.

[0028] This disclosure also provides an electronic device, including a memory and a processor;

[0029] The memory stores executable programs or instructions;

[0030] The processor executes the program or instructions to implement the steps of any of the above methods.

[0031] This disclosure also provides a washing machine that performs foam detection by applying the steps of any of the above methods.

[0032] The technical solution provided in this disclosure has the following advantages compared with the prior art:

[0033] The washing machine foam detection method disclosed herein includes: acquiring a water level frequency waveform for at least one washing cycle; and determining that excessive foam is present when the water level frequency waveform for at least one washing cycle is met. Thus, during the washing stage, excessive foam can be detected based on at least one complete washing cycle, achieving foam detection during the washing stage. Furthermore, using the water level frequency waveform corresponding to a complete washing cycle to determine excessive foam also helps improve detection accuracy, thereby reducing the risk of overflow and improving user experience. Attached Figure Description

[0034] 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.

[0035] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 This is a schematic flowchart of a foam detection method for a washing machine according to an embodiment of the present disclosure;

[0037] Figure 2 This is a water level frequency waveform diagram under normal foam conditions according to an embodiment of this disclosure;

[0038] Figure 3 This is a water level frequency waveform diagram under excessive foam according to an embodiment of the present disclosure;

[0039] Figure 4 for Figure 1 A detailed flowchart of S120 in the method shown;

[0040] Figure 5 A schematic diagram of a washing machine foam detection method provided in this disclosure, which determines the maximum and minimum water level difference based on the water level frequency waveform;

[0041] Figure 6 This is another water level frequency waveform diagram under normal foam conditions according to an embodiment of this disclosure;

[0042] Figure 7 This is a schematic flowchart of another washing machine foam detection method according to an embodiment of the present disclosure;

[0043] Figure 8 This is a schematic diagram of the structure of a washing machine foam detection device according to an embodiment of the present disclosure;

[0044] Figure 9 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present disclosure. Detailed Implementation

[0045] To better understand the above-mentioned objectives, features, and advantages of this disclosure, the solutions disclosed herein will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0046] Numerous specific details are set forth in the following description in order to provide a full understanding of this disclosure, but this disclosure may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some, and not all, of the embodiments of this disclosure.

[0047] In recent years, with the continuous improvement of people's living standards, washing machines have gradually replaced hand washing, achieving automatic cleaning and bringing convenience to life. Washing machines generally include top-loading washing machines, agitator washing machines, and front-loading washing machines; among them, front-loading washing machines have advantages such as low water consumption, high washing efficiency, and less wear and tear on clothes, and are widely used. However, due to the special structural design of front-loading washing machines, if too much detergent is added, excessive foam may occur during the washing and draining stage, the spin-drying stage, or the washing stage (such as the washing or rinsing process). This can easily cause foam to overflow from the detergent dispenser and door seal, resulting in overflow foam, which causes great annoyance to users and leads to a poor user experience.

[0048] In related technologies, foam detection methods used in drum washing machines mainly target the washing and draining stages and the spin-drying stage. When there is a large amount of foam in the drum, the water level change during drainage will be smaller compared to the water level change when there is normal foam. In addition, due to the viscosity of foam, the resistance between the inner and outer drums will also increase during spin-drying, which will increase the motor load and the current. The amount of foam can be sensed by detecting the current.

[0049] However, the above-mentioned method of sensing foam quantity by current cannot detect the foam situation during the washing and rinsing processes. If there is excessive foam during the washing process and the washing machine continues to heat or spin-dry, or if there is excessive foam during the rinsing process and the washing machine continues to rotate, there will be a greater chance of overflowing foam, resulting in a poor user experience. Therefore, it is necessary to detect foam during the washing and rinsing processes.

[0050] To address this, this disclosure provides a foam detection method, also known as a foam sensing method, for use in drum washing machines or other types of washing machines during the washing and / or rinsing process. This method detects the presence of excessive foam by monitoring the water level frequency waveform during washing or rinsing. When excessive foam is present, the washing machine is promptly instructed to enter a defoaming process, thereby reducing the likelihood of foam overflow and improving the user experience.

[0051] Specifically, when judging excessive foam based on water level frequency waveform, the relative magnitudes of the maximum and minimum water level differences corresponding to any washing cycle can be combined for judgment. Thus, the data basis for judging excessive foam is the data of a complete washing cycle. Compared with the process of judging based on point values, this judgment process has more data and higher accuracy.

[0052] In some embodiments, to avoid misjudgment, when judging the relative magnitude of the minimum and maximum water level difference, the judgment can be based on the water level frequency of multiple consecutive washing cycles. Excessive foam is only determined when the water level frequency waveforms corresponding to multiple consecutive washing cycles detect excessive foam, such as two or three consecutive cycles. This avoids misjudgment and further improves the accuracy of judging excessive foam.

[0053] The following description, in conjunction with the accompanying drawings, provides an exemplary account of the washing machine foam detection method, washing machine foam detection device, computer-readable storage medium, electronic device, and washing machine provided in the embodiments of this disclosure.

[0054] For example, Figure 1 This is a schematic flowchart illustrating a foam detection method for a washing machine according to an embodiment of this disclosure. (Refer to...) Figure 1The method may include the following steps:

[0055] S110. Obtain the water level frequency waveform of at least one washing cycle.

[0056] One washing cycle corresponds to the time it takes for the tub to rotate forward once or reverse once during the washing or rinsing process. Since the tub is driven by a motor, one washing cycle also corresponds to the time it takes for the motor to rotate forward or reverse once. The water level frequency fluctuates significantly within one washing cycle, while the fluctuation is smaller during the idle time between two adjacent washing cycles. This will be discussed in conjunction with... Figure 2 and Figure 3 An example is provided.

[0057] The water level frequency is a frequency value used to characterize the water level, and it is a resonant frequency associated with the water level. Specifically, the water level detection inside the washing machine drum can be achieved based on a water level sensor connected to the inside of the drum. The water level sensor's pressure pipe is connected to the drum, and the water level is detected based on the air pressure within the pressure pipe. The higher the water level, the greater the water pressure, and consequently, the greater the inductance of the inductor coil in the sensor. According to the formula for the parallel resonant frequency of inductance and capacitance, the corresponding resonant frequency is lower, and vice versa. Therefore, the water level inside the washing machine drum can be determined based on this resonant frequency, which characterizes the water level frequency.

[0058] Based on this, the water level frequency waveform, also known as the water level waveform, is a curve or broken line showing how the water level frequency changes over time.

[0059] In this embodiment of the disclosure, the water level frequency waveform of a single washing beat, two washing beats, three washing beats, more washing beats, or all washing beats throughout the entire washing stage can be obtained, and is not limited herein.

[0060] Specifically, during the washing or rinsing process, the water level frequency waveform of multiple consecutive washing cycles can be acquired, or the water level frequency waveform of a preset number of washing cycles can be acquired, or the water level frequency waveform of a specified washing cycle can be acquired, which is not limited here.

[0061] In some embodiments, the change in water level in the bucket can be detected by analyzing and judging the frequency waveform of the water level, thereby enabling the judgment of whether there is excessive foam, i.e., foam detection, which will be described in detail later.

[0062] S120. Based on the water level frequency waveform of at least one washing cycle, determine that the foam is excessive when the condition for excessive foam is met.

[0063] The water level frequency waveform when foam is normal is different from the water level frequency waveform when foam is excessive. Therefore, the characteristics of the water level frequency waveform can be used to determine whether there is excessive foam.

[0064] The following is combined Figure 2 and Figure 3 This paper provides an example of how to determine whether there is excessive foam based on the water level frequency waveform.

[0065] For example, Figure 2 This is a water level frequency waveform diagram under normal foam conditions according to an embodiment of this disclosure. Figure 3 This is a water level frequency waveform diagram under excessive foam according to an embodiment of the present disclosure. Figure 2 and Figure 3 In the diagram, the horizontal axis X represents time, which can be expressed in seconds (s); the vertical axis Y represents the water level frequency, which can be expressed in hertz (Hz); L1 represents the water level frequency waveform corresponding to two washing cycles when there is normal foam, and L2 represents the water level frequency waveform corresponding to two washing cycles when there is excessive foam.

[0066] like Figure 2 As shown, the water level frequency waveforms corresponding to two washing cycles are displayed when the foam volume is normal; Figure 2 It can be seen that when the foam is normal, the water level frequency rises and fluctuates significantly during motor rotation. For example... Figure 3 As shown, the specific water level frequency waveforms corresponding to two washing cycles are illustrated when excessive foam is present; Figure 3 It can be seen that during the motor's startup phase, the water level frequency oscillates widely; once the motor stabilizes, the oscillation amplitude of the water level frequency decreases significantly and is smaller than the amplitude during normal foaming. Meanwhile, from Figure 2 and Figure 3 It can be seen that during the idle time between two washing cycles, the fluctuation of water level frequency is small and shows a downward trend.

[0067] Therefore, since the water level frequency waveform corresponding to excessive foam is significantly different from the water level frequency waveform corresponding to normal foam, it is possible to base this on... Figure 3 By detecting the water level frequency waveform shown, excessive foam can be determined; in some embodiments, foam can be eliminated immediately, or the washing machine can be stopped from heating and defoamed before spin-drying to reduce the risk of overflow and improve the user experience.

[0068] In this embodiment of the disclosure, a more accurate judgment on whether there is excessive foam can be achieved based on the water level frequency waveform of at least one washing beat, two washing beats, or more washing beats obtained in the foregoing steps.

[0069] For example, when the water level frequency waveform of one washing cycle is obtained in the aforementioned steps, excessive foam can be judged based on the water level frequency waveform of that single washing cycle; when the water level frequency waveform of two washing cycles is obtained in the aforementioned steps, excessive foam can be judged based on the water level frequency waveform of any one of the washing cycles, or simultaneously based on the water level frequency waveforms of both washing cycles; when the water level frequency waveform of three washing cycles is obtained in the aforementioned steps, excessive foam can be judged based on the water level frequency waveform of any one of the washing cycles, or based on the water level frequency waveforms of any two of the washing cycles, or simultaneously based on the water level frequency waveforms of all three washing cycles; and so on, without further elaboration or limitation.

[0070] In this embodiment of the disclosure, it can be determined whether there is excessive foam based on the identification of the water level frequency waveform. In some embodiments, the identification of the water level frequency waveform may include directly identifying the characteristics of the water level frequency waveform, or further processing the water level frequency waveform to identify data characteristics, as detailed below.

[0071] The washing machine foam detection method provided in this disclosure acquires the water level frequency waveform of at least one washing cycle; and determines that excessive foam is present when the condition for excessive foam is met based on the water level frequency waveform of at least one washing cycle. This allows for foam detection during the washing process based on at least one complete washing cycle. Furthermore, when excessive foam is detected, posing a risk of overflow, the washing machine control system can be fed back to perform a defoaming operation, reducing the risk of overflow and improving the user experience. Simultaneously, using the water level frequency waveform corresponding to a complete washing cycle to determine excessive foam increases the amount of basic data used for judging excessive foam compared to methods based on point values, thereby improving detection accuracy, reducing the risk of overflow, and enhancing the user experience.

[0072] What is understandable is that Figure 2 and Figure 3 The example only shows two consecutive washing beats in the washing stage. In other embodiments, washing beats at other times in the washing stage can also be acquired and identified, or all washing beats throughout the entire washing stage can be acquired and identified. This is not limited to this example.

[0073] In some embodiments, Figure 4 for Figure 1 The illustrated flowchart of S120 in the method shows the steps of further data processing based on the water level frequency waveform to obtain characteristic values, and determining whether there is excessive foam based on the judgment of the characteristic values. Figure 1 Based on, refer to Figure 4 In this method, S120 may specifically include the following steps:

[0074] S121. For any washing cycle, determine the maximum and minimum water level difference based on the water level frequency waveform.

[0075] The maximum and minimum water level ranges can be used to characterize the water level frequency waveform, so that subsequent steps can be based on this to determine whether there is excessive foam.

[0076] Specifically, the maximum water level range is the maximum amplitude of water level frequency fluctuation. As mentioned above, the water level frequency fluctuation amplitude is typically large during the motor startup phase; therefore, this maximum water level range can be used to characterize the water level frequency fluctuation during this phase. The minimum water level range is the fluctuation amplitude when the water level frequency fluctuation is relatively stable. As mentioned above, the water level frequency fluctuation amplitude is relatively smaller when the motor is running relatively smoothly; therefore, this minimum water level range can be used to characterize the water level frequency fluctuation during a stable washing process.

[0077] In some embodiments, the step of "extracting the minimum and maximum water level ranges based on the water level frequency waveform" may specifically include the following steps:

[0078] Based on the water level frequency waveform, the first minimum and first maximum extreme values ​​within the initial first time period are determined. The maximum water level range is obtained by subtracting the first minimum extreme value from the first maximum value. The initial first time period includes the motor start-up phase and is usually located within the first third of the water level frequency waveform cycle.

[0079] Based on the water level frequency waveform, the minimum and maximum values ​​of the second extreme values ​​within the last second time period are determined. The minimum water level range is obtained by subtracting the minimum value from the maximum value. The last second time period includes a stable washing process and is usually located within the last third of the water level frequency waveform cycle.

[0080] For example, Figure 5 The washing machine foam detection method provided in this disclosure includes a schematic diagram illustrating the principle of determining the maximum and minimum water level differences based on the water level frequency waveform. This diagram shows the principle of extracting two extreme values ​​within a single washing cycle. Figure 3 Further processing of the water level frequency waveform shown. Figure 5 The physical meaning of the horizontal axis X and the vertical axis Y in the figure can be found in [reference]. Figure 3 I understand, so I won't elaborate further.

[0081] exist Figure 3 Based on, refer to Figure 5The initial first duration range can be 4 seconds, the final second duration range can be 2 seconds, and the duration range between the two duration ranges can be 8 seconds. Specifically, for any washing cycle's water level frequency waveform, based on the water level frequency waveform data after the motor starts for 4 seconds, determine the maximum and minimum values, that is, determine the first extreme maximum value and the first extreme minimum value. The difference between the two is the maximum water level range, that is, the range of this data, shown as "Range 1" in the figure. Then wait for 8 seconds; then based on the water level frequency waveform data for the next 2 seconds, determine the maximum and minimum values, that is, determine the second extreme maximum value and the second extreme minimum value. The difference between the two is the minimum water level range, that is, the range of this data, shown as "Range 2" in the figure.

[0082] This allows for the identification of water level frequency fluctuations during the motor startup phase and the stable washing process, facilitating judgment in subsequent steps.

[0083] In other embodiments, when the duration range corresponding to motor start-up and water level frequency fluctuation is other numerical ranges, the duration of the first and last duration ranges can also be flexibly changed accordingly, which is not limited here.

[0084] In this embodiment of the disclosure, data can be extracted based on the water level frequency waveform of a single washing cycle, for example, data within the first and last two time ranges can be extracted and the range can be calculated. This helps to reduce the amount of data processing, improve the data processing speed, and ensure better detection timeliness.

[0085] In other implementations, the range can be calculated based on all data from a single washing cycle, which can be set according to the requirements of the washing machine foam detection method and is not limited here.

[0086] S122. Determine the characteristic value based on the maximum and minimum water level difference.

[0087] Among them, the eigenvalue is used to characterize the difference between the minimum and maximum water level difference, in order to determine whether there is excessive foam.

[0088] For example, the feature value can be shown as a ratio or a difference, as follows.

[0089] In some embodiments, this step may specifically include:

[0090] The characteristic value is obtained by dividing the maximum water level difference by the minimum water level difference.

[0091] For example, in combination Figure 5 As mentioned earlier, the value of (range 1) ÷ (range 2) can be calculated to obtain the eigenvalue. Furthermore, this eigenvalue can be stored and used for subsequent judgments.

[0092] In some embodiments, this step may specifically include:

[0093] The characteristic value is obtained by subtracting the minimum water level difference from the maximum water level difference.

[0094] For example, in combination Figure 5 As mentioned earlier, the value of (range 1) - (range 2) can be calculated to obtain the eigenvalue. Furthermore, this eigenvalue can be stored and used for subsequent judgments.

[0095] S123. Determine whether the feature value is equal to or greater than the preset feature value threshold.

[0096] The preset feature value threshold is used as a benchmark to determine whether the feature value is too large. When the feature value is too large, it indicates that there may be excessive foam. That is, when the feature value is equal to or greater than the preset feature value threshold, it indicates excessive foam, which corresponds to step S124.

[0097] S124. If the feature value is equal to or greater than the preset feature value threshold, then it is determined that there is excessive foam.

[0098] Among them, the feature value being equal to or greater than the preset feature value threshold is the condition for excessive foam. When the feature value meets the condition for excessive foam, it can be determined that there is excessive foam.

[0099] Otherwise, if the characteristic value does not meet the condition of excessive foam, it indicates that the foam is normal and washing can continue.

[0100] In this embodiment of the disclosure, the maximum and minimum water level difference values ​​are identified based on the water level frequency waveform, and feature values ​​are determined in one step. Then, based on the feature values, it is determined whether there is excessive foam. Thus, foam detection can be performed accurately and in a timely manner, which helps to avoid foam overflow and improve the user experience.

[0101] In some embodiments, Figure 1 Based on this, S120 may also include:

[0102] Based on the water level frequency waveform of three consecutive washing cycles, it is determined that there is excessive foam when the condition for excessive foam is met.

[0103] This setting reduces the chance of misjudgment, avoids unnecessarily extending the washing time, and ensures a better user experience.

[0104] Specifically, the water level frequency during the washing process can be collected by a water level sensor and transmitted to a processor for processing. For example, Figure 6 This is another water level frequency waveform diagram under normal foam conditions according to an embodiment of this disclosure. Figure 6As shown, during the washing process, the water level sensor may experience significant measurement errors. This can lead to a situation where, even when the amount of foam is normal, the characteristic value calculated based on the water level frequency waveform is too high, resulting in a misjudgment of excessive foam. Therefore, this misjudgment needs to be eliminated to ensure high accuracy in foam detection. This prevents the misjudgment of excessive foam under normal washing conditions, thus avoiding defoaming and extending the washing time.

[0105] In response to this, this embodiment proposes that when the feature value corresponding to three consecutive washing cycles is greater than a preset feature value threshold, it is determined that there is excessive foam in the washing process, which may lead to the risk of overflow. This setting reduces the probability of false judgment, helps to ensure detection accuracy, and thus improves the user experience.

[0106] In some embodiments, Figure 1 Based on this, before executing S110, the method may further include the following steps:

[0107] After determining whether the washing machine is in the washing stage or after a preset time since the washing stage has started;

[0108] If it is determined that the washing machine is in the washing stage or after a preset time since the start of the washing stage, the water level sensor is controlled to collect water level data at a certain frequency.

[0109] Specifically, the above steps for foam detection can be performed at the beginning of the washing stage to achieve full detection of the washing stage and generate full data corresponding to the washing stage, which is convenient for subsequent data backtracking.

[0110] Alternatively, the above steps for foam detection can be performed after a preset time following the start of the washing machine cycle. This allows for targeted detection of periods where excessive foam may occur, simplifying the complete data processing for the washing machine's operation.

[0111] For example, the specific duration of the preset time can be set based on the type of washing machine and the requirements of the corresponding foam detection method, and is not limited here.

[0112] In some embodiments, Figure 7 This is a schematic flowchart of another washing machine foam detection method according to an embodiment of the present disclosure, showing the combination of... Figure 5 One example of a method. See reference. Figure 7 The method may include the following steps:

[0113] After starting, execute S201.

[0114] S201. Determine whether the washing process is in progress.

[0115] If yes, then execute S202 to further determine the detection time; if no, then execute S211, that is, output the result and end.

[0116] S202. Determine whether the detection time has been reached.

[0117] If yes, then execute S203; if no, continue washing, i.e. execute S214; and return to the judgment of the detection time, i.e. return to execute S202.

[0118] S203, Motor Start.

[0119] S204. Calculate the water level difference in the first four seconds.

[0120] This yields the maximum value of the water level difference.

[0121] S205, wait eight seconds.

[0122] This means that no data processing will be performed within this time frame.

[0123] S206, Calculate the water level difference in the last two seconds.

[0124] This yields the minimum water level difference.

[0125] S207. Calculate and store the feature values.

[0126] That is, by combining the maximum water level difference obtained in S204 and the minimum water level difference obtained in S206, the characteristic value is determined and stored.

[0127] S208. Determine whether the number of feature values ​​is greater than 3.

[0128] If yes, then execute S209; otherwise, return to S203.

[0129] S209. Determine whether all three feature values ​​at the end are greater than the threshold.

[0130] The threshold is the preset feature value threshold mentioned above. This step is to determine whether the three latest feature values ​​in time are all greater than the preset feature value threshold.

[0131] If yes, then execute S210; otherwise, execute S212.

[0132] S210, Determine if it is an overflow bubble and record the time.

[0133] The system determines that there is excessive foam, which may lead to overflow; and records the time corresponding to the excessive foam. For example, this time can be the start time, end time, or any time between the start and end times of the corresponding washing cycle, and is not limited here.

[0134] S212, judged as not overflowing.

[0135] S213. Determine whether the washing process is complete.

[0136] If yes, then execute S211; otherwise, return to S203 until the washing is finished.

[0137] S211, Output Results.

[0138] That is, output the judgment result obtained in S213 corresponding to the end of washing; or output the result obtained in S210 corresponding to overflow and its associated time; or output the judgment result obtained in S201 corresponding to the non-washing stage.

[0139] In the entire determination process proposed in this embodiment, the overflow determination process is entered at the preset detection time of the washing stage, starting from S203. After the motor starts, the feature value calculation step is entered, starting from S204. That is, the data of the corresponding water level frequency waveform is captured, the feature value is calculated and stored. When the stored feature value is greater than or equal to three, the last three feature values ​​are counted. If the last three feature values ​​are all greater than the set threshold, it is determined to be an overflow situation, and the determination result and determination time are output. If one of the last three feature values ​​is less than the set threshold, that is, it does not meet the above determination conditions, it is temporarily determined to be no overflow. If it is still in the washing stage, it returns to the feature value calculation process, calculates the feature value of the next washing cycle, and enters the determination step again, thereby completing the cycle process until the washing is finished.

[0140] The foam detection method in this embodiment is based on the fluctuation characteristics of the water level frequency waveform rising sharply downwards during the motor start-up phase, and the subsequent water level frequency oscillation decreasing, to identify excessive foam. Specifically, the feature value can be determined by the multiple of the range between the data before and after a single washing cycle, and it is judged whether the above fluctuation characteristics are met to achieve the identification of excessive foam. In some embodiments, the feature values ​​of three consecutive washing cycles are detected and compared with a set threshold to avoid misjudgment and ensure detection accuracy.

[0141] Based on the above embodiments, this disclosure also provides a washing machine foam detection device, which can be used to perform the steps of any of the washing machine foam detection devices in the above embodiments to achieve the corresponding beneficial effects, such as accurately detecting whether there is excessive foam during the washing stage. This can be understood with reference to the above text and will not be repeated here.

[0142] For example, Figure 8 This is a schematic diagram of the structure of a washing machine foam detection device according to an embodiment of this disclosure. (Refer to...) Figure 8The device 3 may include: a data acquisition module 310, used to acquire the water level frequency waveform of at least one washing cycle; and a condition judgment module 320, used to determine that the foam is excessive when the water level frequency waveform of at least one washing cycle meets the condition of excessive foam.

[0143] The washing machine foam detection device provided in this embodiment, through the synergistic effect of the aforementioned functional modules, can detect whether there is excessive foam during the washing stage based on at least one complete washing cycle, thus achieving foam detection during the washing stage. Furthermore, when excessive foam is detected, posing a risk of overflow, the device can feed back to the washing machine control system to perform defoaming operations, reducing the risk of overflow and improving the user experience. Simultaneously, using the water level frequency waveform corresponding to a complete washing cycle to determine whether there is excessive foam, compared to a point-value-based method, increases the amount of basic data used to determine whether there is excessive foam, thereby improving detection accuracy, reducing the risk of overflow, and enhancing the user experience.

[0144] What is understandable is that Figure 8 The provided washing machine foam detection device can perform the steps of any of the methods described above and achieve the corresponding beneficial effects, which will not be elaborated here.

[0145] Based on the above embodiments, this disclosure also provides a computer-readable storage medium storing a computer program thereon, which is executed by a processor to implement the steps of any of the methods in the above embodiments and achieve the corresponding beneficial effects.

[0146] Based on the above embodiments, this disclosure also provides an electronic device, including a memory and a processor; the memory stores an executable program or instructions; the processor runs the program or instructions to implement the steps of any of the methods in the above embodiments and achieve the corresponding beneficial effects.

[0147] For example, such as Figure 9 The diagram shown is a structural schematic of an electronic device provided in an embodiment of this disclosure. (Refer to...) Figure 9 The electronic device 4 includes a memory 41 and a processor 42; the memory 41 stores executable programs or instructions; the processor 42 runs the programs or instructions to implement the steps of any of the methods in the above embodiments, and has corresponding beneficial effects. The similarities can be understood with reference to the above text, and will not be repeated here.

[0148] For example, the electronic device may be an electronic device built into the washing machine, or an electronic device connected to the washing machine. The specific connection method may be a wired connection or a wireless connection, which is not limited here.

[0149] Based on the above embodiments, this disclosure also provides a washing machine that applies the steps of any of the methods in the above embodiments to achieve foam detection.

[0150] In some embodiments, the washing machine may be a specific implementation of the electronic device described above. For example, the washing machine may be a drum washing machine or other types of washing machines, which are not limited herein.

[0151] In some embodiments, the washing machine may further include a water level sensor for acquiring water level frequency and transmitting it to a processor so that the processor can execute the steps of any of the methods described above to achieve foam detection.

[0152] In other embodiments, the washing machine may also include other mechanical or functional structures, which are not described in detail or are not limited herein.

[0153] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0154] The above description is merely a specific embodiment of this disclosure, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to the embodiments described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for detecting foam in a washing machine, characterized in that, include: Obtain the water level frequency waveform for at least one washing cycle; Based on the water level frequency waveform of at least one of the washing cycles, if the condition of excessive foam is met, it is determined that there is excessive foam. The determination of excessive foam based on the water level frequency waveform of at least one of the washing cycles, when the condition for excessive foam is met, includes: For any of the aforementioned washing cycles, the maximum and minimum water level ranges are determined based on the water level frequency waveform. The characteristic value is determined based on the maximum and minimum water level ranges. Determine whether the feature value is equal to or greater than a preset feature value threshold; If the feature value is equal to or greater than the preset feature value threshold, then excessive foam is determined. The step of determining the characteristic value based on the maximum and minimum water level ranges includes: The characteristic value is obtained by dividing the maximum water level difference by the minimum water level difference. Alternatively, the characteristic value can be obtained by subtracting the minimum water level difference from the maximum water level difference. The step of determining the maximum and minimum water level ranges based on the water level frequency waveform includes: Based on the water level frequency waveform, the first minimum and first maximum extreme values ​​within the initial first time period are determined, and the maximum water level range is obtained by subtracting the first minimum extreme value from the first maximum extreme value; wherein, the initial first time period is within the first one-third period of the water level frequency waveform; Based on the water level frequency waveform, the minimum value of the second extreme value and the maximum value of the second extreme value within the last second time period are determined. The minimum value of the water level range is obtained by subtracting the minimum value of the second extreme value from the maximum value of the second extreme value. The last second time period is within the last one-third period of the water level frequency waveform.

2. The method according to claim 1, characterized in that, The determination of excessive foam based on the water level frequency waveform of at least one of the washing cycles, when the condition for excessive foam is met, includes: Based on the water level frequency waveform of three consecutive washing cycles, if the condition of excessive foam is met, it is determined that there is excessive foam.

3. The method according to any one of claims 1-2, characterized in that, Also includes: After determining whether the washing machine is in the washing stage or after a preset time since the washing stage has started; If it is determined that the washing machine is in the washing stage or after a preset time since the start of the washing stage, the water level sensor is controlled to collect water level data at a certain frequency.

4. A foam detection device for a washing machine, characterized in that, include: The data acquisition module is used to acquire the water level frequency waveform of at least one washing cycle; The condition judgment module is used to determine excessive foam when the excessive foam condition is met based on the water level frequency waveform of at least one of the washing cycles. Specifically, it includes: for any washing cycle, determining the maximum and minimum water level ranges based on the water level frequency waveform; determining a feature value based on the maximum and minimum water level ranges; determining whether the feature value is equal to or greater than a preset feature value threshold; and determining excessive foam if the feature value is equal to or greater than the preset feature value threshold. The step of determining the feature value based on the maximum and minimum water level ranges includes: dividing the maximum water level range by the minimum water level range to obtain the feature value; or subtracting the minimum water level range from the maximum water level range. The minimum value is obtained to obtain the characteristic value; wherein, determining the maximum and minimum water level range based on the water level frequency waveform includes: determining the first minimum and first maximum extreme values ​​within an initial first time period based on the water level frequency waveform, and subtracting the first minimum extreme value from the first maximum extreme value to obtain the maximum water level range; wherein, the initial first time period is within the first one-third period of the water level frequency waveform; determining the second minimum and second maximum extreme values ​​within a final second time period based on the water level frequency waveform, and subtracting the second minimum extreme value from the second maximum extreme value to obtain the minimum water level range; wherein, the final second time period is within the last one-third period of the water level frequency waveform.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that, The computer program is executed by a processor to implement the steps of the method as described in any one of claims 1-3.

6. An electronic device, characterized in that, Including memory and processor; The memory stores executable programs or instructions; The processor executes the program or instructions to implement the steps of the method as described in any one of claims 1-3.

7. A washing machine, characterized in that, Foam detection is achieved by applying the steps of the method as described in any one of claims 1-3.

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