Troubleshooting methods for clothes dryers, troubleshooting devices, clothes dryers and media

Abstract

This invention discloses a fault detection method, a fault detection device, a clothes dryer, and a computer-readable storage medium for a clothes dryer. The fault detection method includes: acquiring a curve showing the change in dehumidification capacity per unit energy consumption of the clothes dryer with ambient temperature within a preset time period; acquiring the dehumidification capacity per unit energy consumption after the preset time period; recording an anomaly when the dehumidification capacity per unit energy consumption exceeds a predetermined range below the curve; and outputting an alarm message when the total number of recorded anomalies meets a preset condition. This fault detection method for clothes dryers makes fault detection more accurate and reduces the occurrence of false alarms.

Description

Technical Field

[0001] This invention relates to the field of household appliance technology, and in particular to a fault detection method, fault detection device, dryer, and computer-readable storage medium for a clothes dryer. Background Technology

[0002] Currently, the operation of a clothes dryer is a typical transient process, with parameters varying greatly under different environmental conditions. Existing fault detection solutions have limited applicability and may lead to false detections. Summary of the Invention

[0003] The present invention provides a method for detecting faults in a clothes dryer, a fault detection device, a clothes dryer, and a computer-readable storage medium.

[0004] A method for detecting faults in a clothes dryer according to an embodiment of the present invention includes:

[0005] Obtain the curve of the unit energy consumption dehumidification capacity of the dryer as a function of ambient temperature within a preset time period;

[0006] The dehumidification capacity per unit energy consumption is obtained after the preset time period;

[0007] If the unit energy consumption dehumidification capacity exceeds a set range below the change curve, an anomaly is recorded.

[0008] If the total number of recorded anomalies meets the preset conditions, an alarm message will be output.

[0009] The above-mentioned fault detection method for clothes dryers obtains the change curve of the unit energy consumption dehumidification capacity of the clothes dryer with ambient temperature within a preset time period and obtains the unit energy consumption dehumidification capacity after the preset time period. If the unit energy consumption dehumidification capacity exceeds the set range below the change curve, an abnormality is recorded. If the total number of recorded abnormalities meets the preset conditions, an alarm message is output, making the fault detection of the clothes dryer more accurate and reducing the occurrence of misjudgments.

[0010] In some implementations, obtaining the curve of the dryer's unit energy consumption dehumidification capacity versus ambient temperature within a preset time period includes:

[0011] Within the preset time period, the ambient temperature, fabric mass at the start of drying, fabric mass at the end of drying, and drying energy consumption are obtained;

[0012] The dehumidification capacity per unit energy consumption is determined based on the fabric mass at the start of drying, the fabric mass at the end of drying, and the drying energy consumption.

[0013] The curve of the dehumidification capacity per unit energy consumption versus the ambient temperature is obtained based on the dehumidification capacity per unit energy consumption and the ambient temperature.

[0014] In some embodiments, determining the dehumidification capacity per unit energy consumption based on the fabric mass at the start of drying, the fabric mass at the end of drying, and the drying energy consumption includes:

[0015] Calculate the mass difference based on the fabric mass at the start of drying and the fabric mass at the end of drying;

[0016] The dehumidification capacity per unit energy consumption is determined based on the mass difference and the drying energy consumption.

[0017] In some embodiments, determining the dehumidification capacity per unit energy consumption based on the mass difference and the drying energy consumption includes:

[0018] The ratio of the mass difference to the drying energy consumption is determined as the dehumidification capacity per unit energy consumption.

[0019] In some embodiments, obtaining the curve of the change of the unit energy consumption dehumidification capacity with ambient temperature based on the unit energy consumption dehumidification capacity and the ambient temperature includes:

[0020] The variation curve is obtained by fitting the dehumidification capacity per unit energy consumption and the ambient temperature.

[0021] In some implementations, if the total number of recorded anomalies meets a preset condition, alarm information is output, including:

[0022] An alarm message is output when the total number of continuously recorded anomalies reaches a first preset number.

[0023] In some implementations, if the total number of recorded anomalies meets a preset condition, alarm information is output, including:

[0024] An alarm message will be output if the total number of recorded anomalies reaches the second preset number.

[0025] A fault detection device for a clothes dryer according to an embodiment of the present invention includes:

[0026] Processor, and;

[0027] The memory stores a computer program that, when executed by the processor, implements the steps of the fault detection method for the clothes dryer according to any of the above embodiments.

[0028] A clothes dryer according to an embodiment of the present invention includes the fault detection device described in the above embodiment.

[0029] This invention provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the fault detection method for a clothes dryer according to any of the above embodiments.

[0030] The aforementioned dryer fault detection device, dryer, and computer-readable storage medium acquire the dryer's unit energy consumption dehumidification capacity as a function of ambient temperature within a preset time period, and acquire the unit energy consumption dehumidification capacity after the preset time period. If the unit energy consumption dehumidification capacity exceeds a preset range below the curve, an anomaly is recorded. If the total number of recorded anomalies meets a preset condition, an alarm message is output. This makes dryer fault detection more accurate and reduces false alarms. Furthermore, it avoids potential high energy consumption issues and improves the user experience.

[0031] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0032] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which:

[0033] Figure 1 This is a flowchart illustrating the fault detection method for a clothes dryer according to an embodiment of the present invention.

[0034] Figure 2 This is another flowchart illustrating the fault detection method for a clothes dryer according to an embodiment of the present invention.

[0035] Figure 3 This is a schematic diagram of the change curve of the unit energy consumption dehumidification capacity with ambient temperature in an embodiment of the present invention.

[0036] Figure 4 This is a schematic diagram comparing the curve of the unit energy consumption dehumidification capacity with the ambient temperature and the unit energy consumption dehumidification capacity in an embodiment of the present invention.

[0037] Figure 5 This is a schematic diagram of the modules of the clothes dryer according to an embodiment of the present invention. Detailed Implementation

[0038] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0039] In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified. It should be noted that, unless otherwise explicitly specified and limited, the terms "installed," "connected," and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection. They can be mechanical or electrical connections. They can be direct connections or indirect connections through an intermediate medium, and can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0040] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of the second feature includes the first feature directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0041] This disclosure provides many different embodiments or examples for implementing various structures of the invention. To simplify the disclosure, specific examples of components and arrangements are described herein. These are merely examples and are not intended to limit the invention. Furthermore, reference numerals and / or letters may be repeated in different examples; such repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed. In addition, examples of various specific processes and materials are provided in this invention, but those skilled in the art will recognize the application of other processes and / or the use of other materials.

[0042] Please refer to Figure 1 and Figure 5 A fault detection method for a clothes dryer 100 according to an embodiment of the present invention includes:

[0043] Step 101: Obtain the curve of the unit energy consumption dehumidification capacity of the dryer 100 as a function of ambient temperature within a preset time period.

[0044] Step 103: Obtain the dehumidification capacity per unit of energy consumption after a preset time.

[0045] Step 105: If the dehumidification capacity per unit energy consumption exceeds the set range below the change curve, record an anomaly.

[0046] Step 107: If the total number of recorded anomalies meets the preset conditions, output alarm information.

[0047] The aforementioned fault detection method for the dryer 100 acquires the unit energy consumption dehumidification capacity curve of the dryer as a function of ambient temperature within a preset time period, and acquires the unit energy consumption dehumidification capacity after the preset time period. If the unit energy consumption dehumidification capacity exceeds a set range below the curve, an anomaly is recorded. If the total number of recorded anomalies meets a preset condition, an alarm message is output. This method makes fault detection of the dryer 100 more accurate and reduces false alarms. Furthermore, it avoids potential high energy consumption issues and improves the user experience.

[0048] Specifically, the dryer 100 may include a heat pump system 12 or a drying system. During prolonged operation, the heat pump system 12 or the drying system may malfunction. The fault detection method of this invention can detect faults in the heat pump system 12 or the drying system, such as refrigerant leakage, heat exchanger blockage, or duct system malfunctions. These faults may cause a decrease in the performance of the dryer 100. The dryer 100 may also include a control board or computer board, which can control the overall operation of the dryer 100.

[0049] Please refer to Figure 2 In some implementations, step 101 includes:

[0050] Step 1011: Within a preset time period, obtain the ambient temperature, fabric quality at the start of drying, fabric quality at the end of drying, and drying energy consumption.

[0051] Step 1013: Determine the dehumidification capacity per unit of energy consumption based on the fabric mass at the start of drying, the fabric mass at the end of drying, and the drying energy consumption.

[0052] Step 1015: Obtain the curve of the change of the unit energy consumption dehumidification capacity with the ambient temperature based on the unit energy consumption dehumidification capacity and the ambient temperature.

[0053] In this way, we can obtain the curve of dehumidification capacity per unit energy consumption as a function of ambient temperature.

[0054] Specifically, the ambient temperature can be obtained by the dryer 100 through an ambient temperature sensor or through a network. Fabric quality can be recorded at the start and end of drying to obtain the fabric quality at the start and end of drying. In one embodiment, the fabric quality can be obtained using a quality sensor.

[0055] In one implementation, the drying energy consumption can be obtained by integrating the power collected at each sampling moment during the drying stage. It is understood that in other implementations, the drying energy consumption can be directly obtained through sensors.

[0056] The preset duration can be a period of time after the dryer 100 is installed, for example, within two weeks after installation. Step 101 is equivalent to the learning phase of the dryer 100. This results in a curve that more closely reflects the operating conditions of the dryer 100, improving the accuracy of fault detection. By obtaining multiple unit energy consumption dehumidification values ​​and multiple ambient temperatures over a period of time, the curve showing the change in unit energy consumption dehumidification value with ambient temperature can better reflect the actual operating conditions of the dryer 100, further improving the accuracy of fault detection. It is understood that the preset duration is not limited to two weeks; other durations are also possible and are not specifically limited here.

[0057] In some implementations, step 1013 includes:

[0058] Calculate the mass difference based on the fabric mass at the start and end of drying;

[0059] The dehumidification capacity per unit of energy consumption is determined based on the quality difference and the energy consumption of drying clothes.

[0060] In this way, the dehumidification capacity per unit of energy consumption can be specifically determined.

[0061] Specifically, the mass difference can be the difference between the fabric mass at the start of drying and the fabric mass at the end of drying, indicating how much moisture was removed by the dryer during the drying stage. The dehumidification capacity per unit of energy consumption is then determined based on the mass difference and the drying energy consumption.

[0062] Generally, under the same drying energy consumption, a larger quality difference indicates a greater dehumidification capacity per unit of energy consumption, signifying better dryer performance. Conversely, a smaller quality difference indicates a smaller dehumidification capacity per unit of energy consumption, signifying poorer dryer performance. In other words, dehumidification capacity per unit of energy consumption is positively correlated with quality difference and negatively correlated with drying energy consumption. Dehumidification capacity per unit of energy consumption is an indicator for evaluating dryer performance.

[0063] In some implementations, determining the dehumidification capacity per unit energy consumption based on the mass difference and drying energy consumption includes:

[0064] The ratio of the quality difference to the drying energy consumption is determined as the dehumidification capacity per unit of energy consumption.

[0065] In this way, the calculation method for dehumidification capacity per unit of energy consumption is simple and easy to implement, which improves the efficiency of fault detection methods.

[0066] Specifically, the fabric mass at the start of drying is denoted as M0, the fabric mass at the end of drying is denoted as M1, the drying energy consumption is denoted as W, and the dehumidification capacity per unit energy consumption is denoted as SMER. Then, the dehumidification capacity per unit energy consumption is SMER = (M0 - M1) / W.

[0067] It is understood that in other implementations, the dehumidification capacity per unit energy consumption can also be calculated using other formulas, and is not limited to the ratio mentioned above.

[0068] In some implementations, step 1015 includes:

[0069] The curve of dehumidification capacity per unit energy consumption versus ambient temperature was obtained by fitting the data with the ambient temperature.

[0070] Thus, obtaining the curve of unit energy consumption dehumidification capacity changing with ambient temperature is simple and easy, improving the efficiency of fault detection methods.

[0071] Specifically, please refer to Figure 3 By calculating the unit energy consumption dehumidification capacity based on ambient temperature, fabric mass at the start of drying, and fabric mass at the end of drying, and by obtaining the ambient temperature, the relationship between unit energy consumption dehumidification capacity and ambient temperature is obtained. A coordinate system is established with ambient temperature (T) on the horizontal axis and unit energy consumption dehumidification capacity (SMER) on the vertical axis. Data points showing the relationship between unit energy consumption dehumidification capacity and ambient temperature can be obtained. By fitting multiple data points, a curve showing the change of unit energy consumption dehumidification capacity with ambient temperature is obtained. Figure 3 In the figure, as an illustration, the curve A1 of the unit energy consumption dehumidification capacity as a function of ambient temperature is a straight line. As the ambient temperature T increases, the unit energy consumption dehumidification capacity SMER also increases.

[0072] It is understood that in other implementations, the curve of the dehumidification capacity per unit energy consumption changing with ambient temperature is not limited to the form of a fitted curve, but can also be in other functional forms, such as a quadratic curve, a multivariate polynomial, etc., which are not specifically limited here.

[0073] In step 103, the preset duration can be a period of time two weeks after the dryer is installed. In one example, it could be within one month after two weeks of installation, to calculate the newly collected dehumidification capacity per unit of energy consumption. It is understood that the newly collected dehumidification capacity per unit of energy consumption is not limited to one month and can be for other durations; no specific limitation is made here.

[0074] In step 105, the dehumidification capacity per unit of energy consumption exceeds the set range below the change curve; that is, the dehumidification capacity per unit of energy consumption is less than the value corresponding to the change curve and is outside the set range. In one example, the set range can be within 5% below the change curve, and the set range is the range between the change curve and the curve formed by shifting the overall change curve down by 5%. Please refer to... Figure 4 The curve showing the change in dehumidification capacity per unit energy consumption with ambient temperature is A1. The curve formed by shifting A1 downward by 5% is A2. The dehumidification capacities per unit energy consumption are B1 and B2, respectively. The set range is defined by curves A1 and A2. If the dehumidification capacity per unit energy consumption B1 is within the set range, no abnormality is recorded. If the dehumidification capacity per unit energy consumption B2 exceeds the set range, an abnormality is recorded.

[0075] It is understandable that in other examples, the set range is not limited to the 5% range below the change curve, but can be other ranges, which are not specifically limited here.

[0076] Steps 103 to 107 can be the application stage after learning.

[0077] In some implementations, step 107 includes:

[0078] An alarm message is output when the total number of continuously recorded anomalies reaches a first preset number.

[0079] This makes the fault detection of the dryer 100 more accurate and reduces the occurrence of misjudgments.

[0080] Specifically, if the recorded anomaly is determined to be a malfunction of dryer 100, then the possibility of this misjudgment is relatively high, because dryer 100 may encounter certain external factors, such as sudden changes in ambient temperature, or unstable power supply leading to abnormal energy consumption, causing the unit energy consumption dehumidification amount to exceed the set range below the change curve.

[0081] In this embodiment of the invention, when the total number of continuously recorded anomalies reaches a first preset number, an alarm message is output, indicating that the drying system or heat pump system 12 of the dryer 100 is faulty, which can greatly reduce the occurrence of misjudgment.

[0082] In one example, the first preset number of attempts can be 3. If the total number of connection record anomalies reaches 3, an alarm message will be output. After outputting the alarm message, the total number of anomalies can be reset to zero.

[0083] In some implementations, step 107 includes:

[0084] An alarm message will be output if the total number of recorded anomalies reaches the second preset number.

[0085] This makes the fault detection of the dryer 100 more accurate and reduces the occurrence of misjudgments.

[0086] Specifically, if the recorded anomaly is determined to be a malfunction of dryer 100, then the possibility of this misjudgment is relatively high, because dryer 100 may encounter certain external factors, such as sudden changes in ambient temperature, or unstable power supply leading to abnormal energy consumption, causing the unit energy consumption dehumidification amount to exceed the set range below the change curve.

[0087] In this embodiment of the invention, when the total number of recorded anomalies reaches a second preset number, an alarm message is output, indicating that the drying system or heat pump system 12 of the dryer 100 is faulty, which can greatly reduce the occurrence of misjudgment.

[0088] In one example, the second preset number of occurrences can be 5. An alarm is output when the total number of recorded anomalies reaches 5. After outputting the alarm, the total number of anomalies can be reset to zero. In one implementation, the second preset number of occurrences is typically greater than the first preset number of occurrences.

[0089] The dryer 100 may include an alarm device that can emit alarm information, which may be audible and / or visual. For example, the alarm device may include a speaker, through which the alarm information (audible information) can be broadcast, such as the voice message "Dryer 100 malfunction, please check" or a similar message.

[0090] The alarm device includes a display screen, through which alarm information (light information) can be displayed. For example, the display screen may show text such as "Dryer 100 Malfunction, please check" or similar text, or images, etc.

[0091] In some implementations, the fault detection method further includes:

[0092] Send alarm information to a preset terminal to trigger a dryer 100 fault alarm on the preset terminal.

[0093] In this way, users can be notified of a 100 malfunction in the dryer in a timely manner.

[0094] Specifically, the preset terminal includes, but is not limited to, mobile phones, tablets, personal computers, wearable smart devices, etc. The preset terminal can be pre-bound to the dryer 100. The dryer 100 can send alarm information to the preset terminal, and the preset terminal can provide audible and / or visual alerts. For details on audible and visual alerts, please refer to the explanation of the above embodiments.

[0095] When the preset terminal receives an alarm message, it can display a prompt on the human-machine interface of the preset terminal so that the user can promptly obtain the fault status of the dryer 100 and notify the maintenance personnel for inspection.

[0096] Please refer to Figure 5A fault detection device 200 for a clothes dryer 100 according to an embodiment of the present invention includes a processor 14 and a memory 16. The memory 16 stores a computer program, which, when executed by the processor 14, implements the steps of the fault detection method for the clothes dryer 100 according to any of the above embodiments.

[0097] Please refer to Figure 5 A clothes dryer 100 according to an embodiment of the present invention includes the fault detection device 200 of the above embodiment.

[0098] Specifically, the fault detection device 200 may include a control board or a computer board, or an additional fault detection device 200, which may be communicatively connected to the control board or computer board. Figure 5 In the illustrated embodiment, the dryer 100 further includes a heat pump system 12, and a fault detection device 200 is electrically connected to the heat pump system 12 and used to detect faults in the heat pump system 12. It is understood that in other embodiments, the dryer 100 may also include a drying system, and the fault detection device 200 is electrically connected to the drying system and used to detect faults in the drying system; this is not specifically limited here.

[0099] This invention provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor 14, it implements the steps of the fault detection method for the dryer 100 according to any of the above embodiments.

[0100] In one embodiment, the fault detection method for the dryer 100 implemented by the computer program when executed by the processor 14 includes:

[0101] Step 101: Obtain the curve of the unit energy consumption dehumidification capacity of the dryer 100 as a function of ambient temperature within a preset time period.

[0102] Step 103: Obtain the dehumidification capacity per unit of energy consumption after a preset time.

[0103] Step 105: If the dehumidification capacity per unit energy consumption exceeds the set range below the change curve, record an anomaly.

[0104] Step 107: If the total number of recorded anomalies meets the preset conditions, output alarm information.

[0105] The aforementioned fault detection device 200, dryer 100, and computer-readable storage medium of dryer 100 acquire the change curve of the dryer's unit energy consumption dehumidification capacity with ambient temperature within a preset time period and acquire the unit energy consumption dehumidification capacity after the preset time period. If the unit energy consumption dehumidification capacity exceeds a preset range below the change curve, an anomaly is recorded. If the total number of recorded anomalies meets a preset condition, an alarm message is output, making fault detection of dryer 100 more accurate and reducing false alarms. Furthermore, it avoids potential high energy consumption issues and improves the user experience.

[0106] It should be noted that the above explanation of the implementation method and beneficial effects of the fault detection method also applies to the fault detection device 200, dryer 100 and computer-readable storage medium of the present invention. To avoid redundancy, they will not be elaborated in detail here.

[0107] It is understood that a computer program includes computer program code. Computer program code can be in the form of source code, object code, executable files, or certain intermediate forms. Computer-readable storage media can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, external hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), and software distribution media, etc. The processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0108] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with an embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0109] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A method for detecting faults in a clothes dryer, characterized in that, include: Obtain the curve of the unit energy consumption dehumidification capacity of the dryer as a function of ambient temperature within a preset time period; The dehumidification capacity per unit energy consumption is obtained after the preset time period; If the unit energy consumption dehumidification capacity exceeds a set range below the change curve, an anomaly is recorded. If the total number of recorded anomalies meets the preset conditions, an alarm message will be output. The curves showing the change in dehumidification capacity per unit energy consumption of the dryer with ambient temperature over a preset time period include: Within the preset time period, the ambient temperature, fabric mass at the start of drying, fabric mass at the end of drying, and drying energy consumption are obtained; The dehumidification capacity per unit energy consumption is determined based on the fabric mass at the start of drying, the fabric mass at the end of drying, and the drying energy consumption. The curve of the dehumidification capacity per unit energy consumption versus the ambient temperature is obtained based on the dehumidification capacity per unit energy consumption and the ambient temperature. The curve of the dehumidification capacity per unit energy consumption versus the ambient temperature, obtained based on the dehumidification capacity per unit energy consumption and the ambient temperature, includes: The variation curve is obtained by fitting the dehumidification capacity per unit energy consumption and the ambient temperature.

2. The fault detection method for a clothes dryer according to claim 1, characterized in that, The unit energy consumption dehumidification capacity is determined based on the fabric mass at the start of drying, the fabric mass at the end of drying, and the drying energy consumption, including: Calculate the mass difference based on the fabric mass at the start of drying and the fabric mass at the end of drying; The dehumidification capacity per unit energy consumption is determined based on the mass difference and the drying energy consumption.

3. The fault detection method for a clothes dryer according to claim 2, characterized in that, Determining the dehumidification capacity per unit energy consumption based on the mass difference and the drying energy consumption includes: The ratio of the mass difference to the drying energy consumption is determined as the dehumidification capacity per unit energy consumption.

4. The fault detection method for a clothes dryer according to claim 1, characterized in that, If the total number of recorded anomalies meets the preset conditions, the alarm information output includes: An alarm message is output when the total number of continuously recorded anomalies reaches a first preset number.

5. The fault detection method for a clothes dryer according to claim 1, characterized in that, If the total number of recorded anomalies meets the preset conditions, the alarm information output includes: An alarm message will be output if the total number of recorded anomalies reaches the second preset number.

6. A fault detection device for a clothes dryer, characterized in that, include: Processor, and; A memory storing a computer program that, when executed by the processor, implements the steps of the fault detection method for a clothes dryer according to any one of claims 1-5.

7. A clothes dryer, characterized in that, Includes the fault detection device as described in claim 6.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the fault detection method for the clothes dryer according to any one of claims 1-5.

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