Control method of home appliance and washing machine

Abstract

The present application relates to the technical field of household appliances, and particularly provides a control method of a household appliance and a washing machine. The present application aims to solve the problems of complicated process and time-consuming in confirming the fault components of the household appliance. To this end, the control method comprises: obtaining a first audio signal of noise generated by the household appliance during operation of the household appliance; extracting a first characteristic frequency based on the first audio signal; judging whether a first contribution of the first characteristic frequency to the noise exceeds a first preset value; selectively determining the component that appears to be faulty based on the judgment result; and the first characteristic frequency is a single frequency signal with the largest first contribution to the noise in the first audio signal. The present application can determine the component that appears to be faulty during operation of the household appliance based on the first audio signal of noise collected by the pickup member, without checking one by one by the maintenance personnel, and is simple and fast.

Description

Technical Field

[0001] This invention relates to the field of household appliance technology, specifically providing a control method for household appliances and a washing machine. Background Technology

[0002] As people's living standards improve, the number of household appliances in homes is also increasing. These appliances inevitably generate noise during operation, and the cumulative effect of this noise can be very unpleasant for users. Especially when a component of an appliance malfunctions, the noise it produces can become even louder and more jarring, further impacting the user experience. Therefore, it is essential for users or repair personnel to inspect the appliances, identify the faulty component, and repair it.

[0003] The process of identifying faulty components is quite complicated. It usually requires professional repair personnel to use their experience and specialized equipment to troubleshoot and determine the faulty component. The process is complex and time-consuming.

[0004] Accordingly, a new technical solution is needed in this field to solve the above problems. Summary of the Invention

[0005] To address the aforementioned problems in the prior art, namely the complexity and time-consuming nature of the existing process for identifying faulty components in household appliances, the first aspect of this invention provides a control method for a household appliance. The household appliance is equipped with a sound-collecting component capable of acquiring audio signals of noise generated by the appliance. The control method includes: acquiring a first audio signal of noise generated by the household appliance during operation; extracting a first characteristic frequency based on the first audio signal; determining whether a first contribution of the first characteristic frequency to the noise exceeds a first preset value; and selectively identifying the faulty component based on the determination result; wherein the first characteristic frequency is the single-frequency signal in the first audio signal that has the largest first contribution to the noise.

[0006] In the preferred embodiment of the above control method, the step of "extracting the first feature frequency based on the first audio signal" further includes: converting the first audio signal into a first spectrum; and extracting the first feature frequency based on the first spectrum.

[0007] In the preferred embodiment of the above control method, the step of "selectively determining the faulty component based on the judgment result" further includes: if the first contribution exceeds the first preset value, then comparing the first characteristic frequency with the reference characteristic frequency in the characteristic frequency database; based on the comparison result, determining the reference characteristic frequency with the highest matching degree with the first characteristic frequency as the target characteristic frequency; and based on the target characteristic frequency, determining the faulty component.

[0008] In the preferred embodiment of the above control method, the characteristic frequency database is stored in the household appliance.

[0009] In a preferred embodiment of the above control method, the household appliance includes a display system. After the step of "determining the faulty component", the control method further includes: controlling the display system to display codes related to the faulty component.

[0010] In a preferred embodiment of the above control method, the household appliance is connected to a cloud processing module, and the control method further includes: the cloud processing module acquiring a second audio signal of noise generated by the household appliance based on a received instruction to diagnose the household appliance; the cloud processing module extracting a second characteristic frequency based on the second audio signal; the cloud processing module determining whether the second contribution of the second characteristic frequency to the noise exceeds a second preset value; and based on the determination result, the cloud processing module returning a diagnostic result to the household appliance, wherein the second characteristic frequency is the single-frequency signal with the largest second contribution to the noise in the second audio signal.

[0011] In the preferred embodiment of the above control method, the step of "the cloud processing module returning a diagnostic result to the home appliance based on the judgment result" further includes: if the second contribution exceeds the second preset value, then the diagnostic result of "the home appliance has a fault" is returned to the home appliance.

[0012] In a preferred embodiment of the above control method, the control method further includes: updating the characteristic frequency database when the second contribution exceeds the second preset value.

[0013] In the preferred embodiment of the above control method, the step of "selectively determining the faulty component based on the judgment result" further includes: if the first contribution amount does not exceed the first preset value, then the household appliance is controlled to continue operating.

[0014] In a preferred embodiment of the present invention, the household appliance is equipped with a sound-collecting component, which is used to acquire audio signals of noise generated by the household appliance. The control method of the present invention includes: acquiring a first audio signal of noise generated by the household appliance during operation; then, based on the first audio signal, extracting a first characteristic frequency; determining whether the first contribution of the first characteristic frequency to the noise exceeds a first preset value; and, based on the determination result, selectively identifying the faulty component. Wherein, the first characteristic frequency is the single-frequency signal in the first audio signal that has the largest first contribution to the noise. Through this control method, the first audio signal of noise collected by the sound-collecting component can accurately identify components that may malfunction during the operation of the household appliance, eliminating the need for repair personnel to rely on experience and specialized equipment for troubleshooting; the confirmation process is simple and quick.

[0015] Furthermore, the step of "extracting the first characteristic frequency based on the first audio signal" further includes: converting the first audio signal into a first spectrogram, and extracting the first characteristic frequency based on the first spectrogram. When extracting the first characteristic frequency, the first audio signal in the time domain is converted into a first spectrogram in the frequency domain, and then the single-frequency signal that contributes the most to the noise is extracted from the first spectrogram, which is the first characteristic frequency.

[0016] Furthermore, the step of "selectively determining the faulty component based on the judgment result" further includes: if the first contribution exceeds a first preset value, then comparing the first characteristic frequency with a reference characteristic frequency in a characteristic frequency database; based on the comparison result, determining the reference characteristic frequency with the highest matching degree to the first characteristic frequency as the target characteristic frequency; and based on the target characteristic frequency, determining the faulty component. The characteristic frequency database stores reference characteristic frequencies when various components of household appliances malfunction, as well as the components corresponding to those reference characteristic frequencies. Thus, when the first contribution of the first characteristic frequency to noise exceeds the first preset value, it is considered that a component within the household appliance has malfunctioned. At this time, the first characteristic frequency is compared with the reference characteristic frequencies in the characteristic frequency database, and the reference characteristic frequency with the highest matching degree is determined as the target characteristic frequency, thereby identifying the faulty component.

[0017] Furthermore, since the household appliance includes a display system, after the step of "identifying the faulty component," the control method of the present invention further includes: controlling the display system to display codes related to the faulty component. In this way, users or repair personnel can intuitively and conveniently obtain the codes related to the faulty component through the display system. Since the codes related to the component typically correspond one-to-one with the component name, users or repair personnel can accurately identify the specific name of the faulty component. Thus, repair personnel can directly repair the faulty component displayed by the display system without having to troubleshoot each component individually, saving time.

[0018] Furthermore, the home appliance is connected to the cloud processing module. The control method of the present invention includes: the cloud processing module, based on a received instruction to diagnose the home appliance, acquires a second audio signal of the noise generated by the home appliance; extracts a second characteristic frequency based on the second audio signal; then determines whether the second contribution of the second characteristic frequency to the noise exceeds a second preset value; based on the determination result, the cloud processing module returns the diagnosis result to the home appliance, wherein the second characteristic frequency is the single-frequency signal in the second audio signal that has the largest second contribution to the noise. When a user hears abnormal sounds and suspects a possible component malfunction, they can send an instruction to the cloud processing module to diagnose the home appliance. Upon receiving the diagnosis instruction, the cloud processing module acquires the second audio signal of the noise currently generated by the home appliance, extracts the second characteristic frequency based on the second audio signal, determines whether the second contribution of the second characteristic frequency to the noise exceeds a second preset value, and returns the diagnosis result to the home appliance. In this way, the user can know whether there is a faulty component.

[0019] Furthermore, the step of "the cloud processing module returns the diagnostic result to the home appliance based on the judgment result" further includes: if the second contribution exceeds the second preset value, the diagnostic result of "the home appliance is faulty" is returned to the home appliance, so that the user can intuitively know the name of the specific faulty component, which is beneficial to the maintenance work of the maintenance personnel later.

[0020] Furthermore, the control method of the present invention further includes: when the second contribution exceeds a second preset value, transmitting the second characteristic frequency and the component corresponding to the second characteristic frequency to the characteristic frequency database, and updating the characteristic frequency database. After the characteristic frequency database is updated, during the operation of the household appliance, as long as the second characteristic frequency is extracted from the audio signal of the current noise, it can be determined that the component corresponding to the second characteristic frequency has malfunctioned. This avoids judgment errors caused by incomplete data in the characteristic frequency database, thereby enabling a better identification of potentially malfunctioning components of the household appliance.

[0021] A second aspect of the present invention provides a washing machine, including a processor and a memory, wherein the memory stores a computer program configured to be executed by the processor to implement the control method described in any of the foregoing embodiments.

[0022] It should be noted that the washing machine has all the technical effects of the aforementioned control method, which will not be repeated here. Attached Figure Description

[0023] The control method of the household appliance of the present invention will now be described with reference to a washing machine and the accompanying drawings. In the drawings:

[0024] Figure 1 This is a flowchart (a) of a control method for a washing machine according to an embodiment of the present invention;

[0025] Figure 2 This is a flowchart (II) of a control method for a washing machine according to an embodiment of the present invention;

[0026] Figure 3 This is a flowchart (III) of a washing machine control method according to an embodiment of the present invention. Detailed Implementation

[0027] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the invention and are not intended to limit the scope of protection of the invention. Although this embodiment uses a washing machine as an example, it is equally applicable to other types of household appliances such as air conditioners and kitchen appliances.

[0028] It should be noted that in the description of this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0029] Currently, when a component inside a washing machine malfunctions, it produces a rather harsh noise, affecting the user experience. Before repair, it's necessary to check all the components of the washing machine, which usually requires experienced repair personnel using specialized equipment to pinpoint the faulty part—a complex and time-consuming process. Therefore, the control method of this invention can identify the faulty component of the washing machine based on the audio signal of the noise, eliminating the need for experienced repair personnel and specialized equipment, making it simple and quick.

[0030] First, refer to Figures 1 to 3 The control method of the washing machine of the present invention will be described. Among them, Figure 1 This is a flowchart (I) of a washing machine control method according to an embodiment of the present invention. Figure 2 This is a flowchart (II) of a washing machine control method according to an embodiment of the present invention. Figure 3 This is a flowchart (III) of a washing machine control method according to an embodiment of the present invention.

[0031] like Figure 1 As shown, in one possible implementation, the control method of the present invention includes:

[0032] Step S100: Acquire the first audio signal of the noise generated by the washing machine;

[0033] In this invention, the washing machine is equipped with a sound pickup component, such as a microphone or a microphone. This sound pickup component can be located inside the washing machine's casing, such as at the front, left, or right side of the casing. During the washing machine's operation, noise is generated, and this sound pickup component can collect the audio signal of this noise.

[0034] In step S100, the first audio signal of the noise generated during the operation of the washing machine is collected by the sound pickup component.

[0035] Step S200: Based on the first audio signal, extract the first feature frequency;

[0036] Among them, the first characteristic frequency is the single-frequency signal that contributes the most to the noise in the first audio signal.

[0037] A washing machine typically contains multiple components that generate noise during operation, such as the noise from the motor and the rotating washing tub. The first audio signal acquired in step S100 is composed of the superposition of single-frequency signals from the noise generated by each component of the washing machine.

[0038] Each component generates a different single-frequency noise signal, and different single-frequency signals contribute different noise levels. Even the same component can contribute different noise levels under different operating conditions. For example, during the washing cycle, the motor contributes 25-40 decibels of noise during normal operation, while during the spin-drying cycle, the motor contributes 40-60 decibels. Similarly, the inlet solenoid valve contributes 30-40 decibels of noise during normal operation, and so on.

[0039] The noise level contributed by a single-frequency signal when the same component malfunctions is different from the noise level contributed by the same component when it is operating normally. For example, when a motor is running normally at 3000 rpm, the noise level it contributes is 40-60 decibels. When a malfunction occurs, the noise level it contributes may reach 65 decibels or even higher, and so on.

[0040] In step S200, based on the first audio signal obtained in step S100, the first contribution of each single-frequency signal in the first audio signal to the noise is analyzed, and the single-frequency signal with the largest first contribution to the noise is determined as the first characteristic frequency. For example, taking the dehydration stage as an example, the noise value contributed by the single-frequency signal of the noise generated by the motor operation is 55 dB, and the noise values ​​contributed by the single-frequency signals of the noise generated by the operation of other components are all lower than 55 dB. Thus, the single-frequency signal of the noise generated by the motor operation can be determined as the first characteristic frequency.

[0041] Step S300: Determine whether the first contribution of the first characteristic frequency to the noise exceeds a first preset value;

[0042] Step S400: Based on the judgment result, selectively determine the faulty component.

[0043] In step S300, each first characteristic frequency corresponds to a first preset value. The first contribution of the first characteristic frequency to the noise is compared with the first preset value to determine whether the first contribution exceeds the first preset value.

[0044] In step S400, based on the judgment result in step S300, it is determined whether any component of the washing machine is currently malfunctioning. If the first contribution of the first characteristic frequency to the noise exceeds a first preset value, it indicates that the component corresponding to the first characteristic frequency is malfunctioning, thus identifying the malfunctioning component. If the first contribution of the first characteristic frequency to the noise does not exceed the first preset value, it indicates that the component corresponding to the first characteristic frequency is not malfunctioning.

[0045] Taking the motor as an example and the washing machine in the spin-drying stage, the first preset value of the single-frequency signal generated by the motor is 65 decibels. If the contribution of the single-frequency signal generated by the motor to the noise is 58 decibels, it means that the motor is not currently malfunctioning. If the contribution of the single-frequency signal generated by the motor to the noise is 70 decibels, it means that the motor has malfunctioned.

[0046] Obviously, the specific values ​​of the aforementioned first preset value, the noise value contributed by the single-frequency signal generated when the motor is working, the noise value contributed by the single-frequency signal generated when the motor malfunctions, and the noise value contributed when the washing tub is rotating normally are all illustrative descriptions. The noise value contributed by the motor during normal operation and during malfunctions will vary depending on the type of motor, operating frequency, and other parameters. Those skilled in the art can determine the specific value based on experience, experimentation, calculation, etc. Similarly, the noise value contributed by the inlet solenoid valve during normal operation will also vary when the inlet water pressure changes. Those skilled in the art can determine the specific value based on experience, experimentation, calculation, etc. The first preset value will also change accordingly, and those skilled in the art can determine this first preset value based on experience, experimentation, calculation, etc.

[0047] It should be noted that, for ease of explanation, the following description uses the motor as the component corresponding to the first characteristic frequency and the washing machine being in the spin-drying stage to illustrate the control method of the washing machine of the present invention. Obviously, in the control method of the washing machine of the present invention, the component corresponding to the first characteristic frequency can also be other components, such as the washing tub.

[0048] like Figure 2 As shown, in one possible implementation, the control method of the present invention includes:

[0049] Step S100: Acquire the first audio signal of the noise generated by the washing machine;

[0050] Step S201: Convert the first audio signal into a first spectrogram;

[0051] Step S202: Extract the first characteristic frequency based on the first spectrum;

[0052] In step S201, based on the first audio signal obtained in step S100, the first audio signal is converted into a first spectrum diagram, that is, the first audio signal is converted from the time domain to the frequency domain, that is, the first audio signal is converted into a graph showing the amplitude and frequency relationship at different frequencies. In the first spectrum diagram, different frequencies have different amplitudes, and each frequency corresponds to a single-frequency signal. This amplitude is the contribution of the single-frequency signal to the noise, thus allowing us to obtain the contribution of each single-frequency signal to the noise.

[0053] In this invention, the first audio signal can be converted from the time domain to the frequency domain using methods such as Fourier transform. It should be noted that converting the audio signal from the time domain to the frequency domain using Fourier transform is a conventional technique in this field and will not be elaborated upon here.

[0054] In step S202, based on the first spectrum diagram determined in step S201, the contribution of the single-frequency signal of the noise generated by each component to the noise can be obtained. The maximum contribution is the first contribution, and the single-frequency signal corresponding to the first contribution is the first characteristic frequency.

[0055] Step S301: Determine whether the first contribution exceeds the first preset value. If yes, proceed to step S401; otherwise, proceed to step S500.

[0056] Step S401: Compare the first characteristic frequency with the reference characteristic frequency in the characteristic frequency database;

[0057] Step S402: Based on the comparison results, determine the reference feature frequency that has the highest matching degree with the given first feature frequency as the target feature frequency;

[0058] Step S403: Based on the target characteristic frequency, determine the faulty component;

[0059] Step S404: Control the display system to display codes related to the faulty component;

[0060] Step S500: Control the washing machine to continue running.

[0061] In step S301, based on the first contribution amount of the first characteristic frequency obtained in step S202, the first contribution amount is compared with a first preset value. If the first contribution amount exceeds the first preset value, such as the first contribution amount being 70 dB and the first preset value being 65 dB, it indicates that the component corresponding to the first characteristic frequency has malfunctioned. At this time, the first characteristic frequency is compared with the reference characteristic frequency in the characteristic frequency database, i.e., step S401 is executed.

[0062] If the first contribution level does not exceed the first preset value, such as 58 dB for the first contribution level and 65 dB for the first preset value, it indicates that the component corresponding to the first characteristic frequency is not faulty, which means that the washing machine is not currently malfunctioning and can continue to operate. At this time, the washing machine is controlled to continue operating, i.e., step S500 is executed.

[0063] In this invention, the characteristic frequency database is stored in the washing machine. This allows for the comparison of the first characteristic frequency with each reference characteristic frequency at any time during the washing machine's operation. Obviously, this characteristic frequency database can also be stored in other locations, such as a server connected to the washing machine, a mobile terminal (such as a mobile phone), etc. When it is necessary to compare the first characteristic frequency with each reference characteristic frequency, the first characteristic frequency can be transmitted to the server or mobile terminal.

[0064] In this invention, the characteristic frequency database stores multiple components and multiple reference characteristic frequencies that are present in the washing machine model. The reference characteristic frequencies are the single-frequency signals of the noise emitted by each component during operation.

[0065] In step S401, the first characteristic frequency is compared with multiple reference characteristic frequencies in the characteristic frequency database. The comparison between the first characteristic frequency and the reference characteristic frequencies can be performed using methods such as direct measurement, phase comparison, intermediate frequency substitution, and differential measurement. These comparison methods are all conventional techniques in this field and will not be elaborated here.

[0066] In step S402, based on the comparison results in step S401, the reference feature frequency with the highest matching degree with the first feature frequency is determined as the target feature frequency.

[0067] In step S403, based on the target characteristic frequency and characteristic frequency database determined in step S402, and since there is a one-to-one correspondence between the target characteristic frequency and the component, the component corresponding to the target characteristic frequency can be determined, and thus the component corresponding to the first characteristic frequency can be determined, thereby identifying the component that has malfunctioned.

[0068] In this invention, the washing machine includes a display system, which may be a display screen installed on the control panel of the washing machine.

[0069] In step S404, based on the faulty component identified in step S403, the display system is controlled to display the code related to the faulty component. This allows users or maintenance personnel to intuitively see the code associated with the faulty component through the display system. Since the component-related code usually corresponds one-to-one with the component name, users or maintenance personnel can accurately identify the specific faulty component. Thus, maintenance personnel can directly repair the faulty component displayed by the display system without having to troubleshoot each component individually, saving time.

[0070] like Figure 3 As shown, in one possible implementation, the control method of the present invention includes:

[0071] Step S601: Based on the received instruction to diagnose the household appliances, the cloud processing module acquires the second audio signal of the noise generated by the household appliances;

[0072] In this invention, the washing machine can communicate with the cloud processing module through communication methods such as local area network, wide area network, WiFi, "WiFi + Internet access router", Bluetooth, ZIGBEE, NFC, GPRS, etc. Those skilled in the art can flexibly choose the specific connection method between the washing machine and the cloud processing module according to the specific application scenario.

[0073] In step S601, when the user suspects a possible malfunction in a component inside the washing machine, they can send a diagnostic command to the cloud processing module via the washing machine's control panel, remote control, or mobile app. Based on the received diagnostic command, the cloud processing module acquires the second audio signal of the noise generated by the washing machine.

[0074] It should be noted that, similar to step S100, the second audio signal can be acquired by a pickup component. The washing machine then transmits the second audio signal to the cloud processing module.

[0075] Step S602: The cloud processing module extracts the second feature frequency based on the second audio signal;

[0076] In step S602, similar to step S200, based on the second audio signal obtained in step S601, the second audio signal is converted into a second spectrum diagram through Fourier transform or other methods. Based on the second spectrum diagram, the second contribution of each single-frequency signal to the noise in the second spectrum diagram is analyzed, and the single-frequency signal with the largest second contribution to the noise is determined as the second characteristic frequency.

[0077] Step S603: The cloud processing module determines whether the second contribution of the second characteristic frequency to the noise exceeds the second preset value;

[0078] Step S604: Based on the judgment result, the cloud processing module returns the diagnostic result to the washing machine.

[0079] In step S603, based on the second characteristic frequency extracted in step S602, the cloud processing module compares the second contribution of the second characteristic frequency to the noise with a second preset value to determine whether the second contribution exceeds the second preset value.

[0080] In step S604, based on the judgment result of step S603, the cloud processing module returns the diagnostic result to the washing machine. If the second contribution of the second characteristic frequency to the noise exceeds the second preset value, taking the component corresponding to the second characteristic frequency as the motor and the washing machine in the spin-drying stage as an example, if the second contribution is 70 decibels and the second preset value is 65 decibels, it indicates that the washing machine is faulty. At this time, the diagnostic result "the washing machine is faulty" is returned to the washing machine.

[0081] Similar to step S404, after identifying the faulty component, the cloud processing module can return the code related to that component to the washing machine and control the washing machine's display system to display the code, allowing the user or repair personnel to intuitively understand the name of the faulty component. Obviously, the cloud processing module could also simply return the diagnostic result of "washing machine malfunction" to the washing machine.

[0082] In this invention, the cloud processing module stores all components of various types of washing machines and the single-frequency signals generated by each component during operation. When the second contribution of the second characteristic frequency to the noise exceeds a second preset value, after determining that the washing machine has malfunctioned, the second characteristic frequency can be compared with each single-frequency signal in the cloud processing module. The single-frequency signal with the highest matching degree is determined as the target single-frequency signal, and thus the component corresponding to the target single-frequency signal can be identified as the malfunctioning component.

[0083] Of course, engineers can also update the components in the cloud processing module and the single-frequency signals generated by each component in real time in the background, so as to more accurately determine whether the washing machine has malfunctioned and the malfunctioning component.

[0084] In one possible implementation, the control method of the present invention further includes updating the characteristic frequency database when the second contribution exceeds a second preset value.

[0085] When a user sends a diagnostic report for their washing machine to the cloud processing module, the machine may be malfunctioning, but the system may not identify the faulty component. This could be due to incomplete data in the characteristic frequency database, which stores the necessary components and reference characteristic frequencies. Therefore, when the second contribution exceeds a second preset value, the second characteristic frequency and its corresponding component are transmitted to the characteristic frequency database to update it. After the database is updated, during washing machine operation, extracting the second characteristic frequency from the current noise audio signal allows identification of the faulty component. This avoids errors caused by incomplete data in the characteristic frequency database, enabling better diagnosis of washing machine malfunctions and, when a malfunction occurs, identification of the faulty component.

[0086] After updating the characteristic frequency database, in step S604 above, after the cloud processing module returns the diagnosis result of "the washing machine is faulty" to the washing machine, the washing machine determines the faulty component based on the updated characteristic frequency database.

[0087] If the second contribution of the second characteristic frequency to the noise does not exceed the second preset value, taking the motor and the washing machine in the spin-drying stage as examples, if the second contribution is 58 dB and the second preset value is 65 dB, then the washing machine is not faulty. In this case, the diagnostic result "no fault in the washing machine" is returned to the washing machine.

[0088] Obviously, the specific value of the second preset value mentioned above is merely an exemplary description, and those skilled in the art can determine the second preset value based on experience, experimentation, calculation, and other methods.

[0089] Using the above control method, if the user notices abnormal noise from the washing machine during operation, they can send a diagnostic command to the cloud processing module. Upon receiving the command, the cloud processing module extracts a second characteristic frequency based on the second audio signal of the noise generated by the washing machine. Then, it compares the second contribution of this second characteristic frequency to the noise with a second preset value. If the second contribution exceeds the second preset value, it indicates a malfunction in the washing machine; otherwise, it indicates no malfunction.

[0090] Although the steps in the above embodiments are described in the above order, those skilled in the art will understand that in order to achieve the effect of this embodiment, different steps do not need to be executed in such an order. They can be executed simultaneously (in parallel) or in a reverse order. These simple variations are all within the protection scope of this invention.

[0091] In summary, in the preferred embodiment of the present invention, based on the first audio signal collected by the sound pickup component, a first characteristic frequency is extracted, and it is determined whether the first contribution of the first characteristic frequency to the noise exceeds a first preset value. Based on the determination result, the faulty component is selectively identified. Thus, based on the first audio signal of noise collected by the sound pickup component, the components that may malfunction during the operation of household appliances can be accurately identified without the need for repair personnel to check each component individually, making it simple and quick. By comparing the first characteristic frequency with the reference characteristic frequencies in the characteristic frequency database, the faulty component can be accurately identified. After identifying the faulty component, the display system displays the code related to the faulty component, allowing users or repair personnel to intuitively and conveniently identify the faulty component. When a user hears an abnormal sound and suspects a possible component malfunction, they can send a diagnostic command to the cloud processing module. The cloud processing module determines whether the washing machine is malfunctioning based on the second audio signal of noise emitted by the washing machine. When the second contribution exceeds a second preset value, the diagnostic result "washing machine malfunctions" is returned to the washing machine, and the characteristic frequency database is updated simultaneously.

[0092] Of course, the alternative implementation methods described above, as well as the alternative implementation methods and preferred implementation methods, can be used in combination to create new implementation methods that are suitable for more specific application scenarios.

[0093] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A method for controlling a household appliance, characterized in that, The household appliance is equipped with a sound pickup component, which is capable of acquiring the audio signal of the noise generated by the household appliance. The control method includes: During the operation of the household appliance, a first audio signal of the noise generated by the household appliance is acquired; Based on the first audio signal, extract the first feature frequency; Determine whether the first contribution of the first characteristic frequency to the noise exceeds a first preset value; Based on the judgment results, the faulty components are selectively identified; Wherein, the first characteristic frequency is the single-frequency signal that contributes the most to the noise in the first audio signal; The home appliance is connected to the cloud processing module, and the control method further includes: The cloud processing module acquires a second audio signal of the noise generated by the home appliance based on the received instruction to diagnose the home appliance. The cloud processing module extracts a second feature frequency based on the second audio signal; The cloud processing module determines whether the second contribution of the second characteristic frequency to the noise exceeds a second preset value; Based on the judgment result, the cloud processing module returns the diagnostic result to the home appliance. The second characteristic frequency is the single-frequency signal that contributes the most to the second noise in the second audio signal.

2. The control method according to claim 1, characterized in that, The step of "extracting the first feature frequency based on the first audio signal" further includes: The first audio signal is converted into a first spectrogram; Based on the first spectrum, the first characteristic frequency is extracted.

3. The control method according to claim 1, characterized in that, The step of "selectively identifying the faulty component based on the judgment result" further includes: If the first contribution exceeds the first preset value, then the first feature frequency is compared with the reference feature frequency in the feature frequency database. Based on the comparison results, the reference feature frequency with the highest matching degree to the first feature frequency is determined as the target feature frequency; Based on the target characteristic frequency, the faulty component is identified.

4. The control method according to claim 3, characterized in that, The characteristic frequency database is stored in the household appliance.

5. The control method according to claim 3, characterized in that, The household appliance includes a display system. After the step of "identifying the faulty component", the control method further includes: The display system is controlled to display codes related to the malfunctioning component.

6. The control method according to claim 1, characterized in that, The step of "based on the judgment result, the cloud processing module returns the diagnostic result to the home appliance" further includes: If the second contribution exceeds the second preset value, a diagnostic result of "the home appliance is faulty" is returned to the home appliance.

7. The control method according to claim 1, characterized in that, The control method further includes: When the second contribution exceeds the second preset value, the feature frequency database is updated.

8. The control method according to claim 1, characterized in that, The step of "selectively identifying the faulty component based on the judgment result" further includes: If the first contribution does not exceed the first preset value, then the household appliance is controlled to continue operating.

9. A washing machine, characterized in that, include: processor; A memory storing a computer program configured to be executed by the processor to implement the control method of any one of claims 1 to 8.

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