Heating control method and device for twin-tub washing machine, washing machine

Abstract

The application discloses a heating control method and device of a double-barrel washing machine and the washing machine. The method comprises the following steps: obtaining the washing type, the weight of clothes and the opening time interval of the left barrel and the right barrel of the double-barrel washing machine; obtaining the ambient temperature of the room where the double-barrel washing machine is located; obtaining the initial temperature of the left barrel and the initial temperature of the right barrel according to the washing type, the weight of clothes, the opening time interval and the ambient temperature; determining the total running time of the left barrel and the total running time of the right barrel according to the washing type, the weight of clothes, the opening time interval, the ambient temperature and the initial temperature of the left barrel and the initial temperature of the right barrel; controlling the left barrel to run according to the total running time of the left barrel, and controlling the right barrel to run according to the total running time of the right barrel. The application solves the technical problem that, in the related art, due to the heat interaction characteristics of the double-barrel structure, heat is transferred between the two washing barrels, and the temperatures of the two barrels are influenced by each other.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of home appliance control, in particular to a heating control method and device of a double-barrel washing machine and the washing machine. BACKGROUND

[0002] The double-barrel structure of the double-barrel washing machine brings convenience, but also brings technical challenges, especially in the aspect of heating control. The existing problems in the prior art are as follows:

[0003] 1) Heat transfer problem: In the existing double-barrel washing machine, due to the physical structure between the two washing barrels, heat will be transferred from one barrel to another, making it difficult to accurately control the target temperature and affecting the washing effect.

[0004] 2) Energy consumption problem: Due to heat transfer and temperature interaction, traditional heating control strategies often need to consume more energy to compensate for temperature deviation, which not only increases operating costs, but also does not meet the current environmental protection trend of energy saving and emission reduction.

[0005] 3) User experience problem: Unstable heating temperature and prolonged heating time will reduce the efficiency of the washing machine and affect the user experience, especially in washing large items or specific temperature washing programs.

[0006] In view of the above problems, no effective solution has been proposed so far. SUMMARY

[0007] The embodiments of the present application provide a heating control method and device of a double-barrel washing machine and the washing machine to at least solve the technical problem that in the related art, due to the heat interaction characteristics of the double-barrel structure, heat will be transferred between the two washing barrels, causing mutual influence of the temperatures of the two barrels in the heating mode of the double-barrel washing machine.

[0008] According to an aspect of an embodiment of the present application, a heating control method of a double-barrel washing machine is provided, comprising: when it is detected that both the left barrel and the right barrel of the double-barrel washing machine are opened, obtaining the washing type, the weight of the clothes and the opening time interval of the left barrel and the right barrel of the double-barrel washing machine; obtaining the ambient temperature of the room where the double-barrel washing machine is located; predicting the left barrel initial temperature of the left barrel and the right barrel initial temperature of the right barrel according to the washing type, the weight of the clothes, the opening time interval and the ambient temperature; determining the total running time of the left barrel and the total running time of the right barrel according to the washing type, the weight of the clothes, the opening time interval, the ambient temperature and the left barrel initial temperature and the right barrel initial temperature; controlling the left barrel to run according to the total running time of the left barrel, and controlling the right barrel to run according to the total running time of the right barrel.

[0009] Optionally, the obtaining the clothes weight of the double-barrel washing machine comprises: performing a weighing operation on the left barrel and the right barrel of the double-barrel washing machine after the double-barrel washing machine starts to perform the washing operation, to obtain the clothes weight of the double-barrel washing machine.

[0010] Optionally, the obtaining the opening time interval of the left barrel and the right barrel of the double-barrel washing machine comprises: determining a left barrel opening time of the left barrel and a right barrel opening time of the right barrel; and determining the opening time interval according to the left barrel opening time and the right barrel opening time.

[0011] Optionally, the predicting the left barrel initial temperature of the left barrel and the right barrel initial temperature of the right barrel according to the washing type, the clothes weight, the opening time interval, and the environment temperature comprises: inputting the washing type, the clothes weight, the opening time interval, and the environment temperature into an initial temperature prediction model, to process the washing type, the clothes weight, the opening time interval, and the environment temperature by using the initial temperature prediction model, to obtain the left barrel initial temperature and the right barrel initial temperature.

[0012] Optionally, before the inputting the washing type, the clothes weight, the opening time interval, and the environment temperature into the initial temperature prediction model, the heating control method of the double-barrel washing machine further comprises: obtaining a plurality of groups of first training data comprising sample washing types, sample clothes weights, sample opening time intervals, sample environment temperatures, and corresponding sample left barrel initial temperatures and sample right barrel initial temperatures; and training the plurality of groups of first training data by using a machine learning method, to obtain the initial temperature prediction model.

[0013] Optionally, the determining the left barrel total running time of the left barrel and the right barrel total running time of the right barrel according to the washing type, the clothes weight, the opening time interval, the environment temperature, and the left barrel initial temperature and the right barrel initial temperature comprises: inputting the washing type, the clothes weight, the opening time interval, the environment temperature, and the left barrel initial temperature and the right barrel initial temperature into a total running time prediction model, to process the washing type, the clothes weight, the opening time interval, the environment temperature, and the left barrel initial temperature and the right barrel initial temperature by using the total running time prediction model, to obtain the left barrel total running time and the right barrel total running time.

[0014] Optionally, before determining the total left drum running time of the left drum and the total right drum running time of the right drum according to the washing type, the laundry weight, the opening time interval, the ambient temperature, and the left drum initial temperature and the right drum initial temperature, the heating control method of the dual tub washing machine further comprises: obtaining a plurality of second training data sets comprising sample washing types, sample laundry weights, sample opening time intervals, sample ambient temperatures, and sample left drum initial temperatures and sample right drum initial temperatures, and corresponding sample total left drum running times and total right drum running times; training the plurality of second training data sets in a machine learning manner to obtain the total running time prediction model.

[0015] Optionally, after determining the total left drum running time of the left drum and the total right drum running time of the right drum according to the washing type, the laundry weight, the opening time interval, the ambient temperature, and the left drum initial temperature and the right drum initial temperature, the heating control method of the dual tub washing machine further comprises: displaying the total left drum running time and / or the total right drum running time.

[0016] According to another aspect of the embodiments of the present application, a heating control device of a dual tub washing machine is also provided, comprising: a first obtaining unit configured to, when detecting that both a left drum and a right drum of the dual tub washing machine are opened, obtain a washing type, a laundry weight, and an opening time interval of the left drum and the right drum of the dual tub washing machine; a second obtaining unit configured to obtain an ambient temperature of a room where the dual tub washing machine is located; a third obtaining unit configured to predict a left drum initial temperature of the left drum and a right drum initial temperature of the right drum according to the washing type, the laundry weight, the opening time interval, and the ambient temperature; a determining unit configured to determine a total left drum running time of the left drum and a total right drum running time of the right drum according to the washing type, the laundry weight, the opening time interval, the ambient temperature, and the left drum initial temperature and the right drum initial temperature; and a control unit configured to control the left drum to run according to the total left drum running time, and control the right drum to run according to the total right drum running time.

[0017] Optionally, the first obtaining unit comprises: a weighing module configured to, after the dual tub washing machine starts to perform a washing operation, perform a weighing operation on the left drum and the right drum of the dual tub washing machine to obtain the laundry weight of the dual tub washing machine.

[0018] Optionally, the first obtaining unit comprises: a first determining module configured to determine a left drum opening time of the left drum and a right drum opening time of the right drum; and a second determining module configured to determine the opening time interval according to the left drum opening time and the right drum opening time.

[0019] Optionally, the determining unit comprises a first processing module configured to input the washing type, the clothes weight, the opening time interval and the ambient temperature into an initial temperature prediction model, and process the washing type, the clothes weight, the opening time interval and the ambient temperature by using the initial temperature prediction model to obtain the left drum initial temperature and the right drum initial temperature.

[0020] Optionally, the heating control device of the dual-drum washing machine further comprises a fourth obtaining unit configured to obtain a plurality of groups of first training data comprising sample washing types, sample clothes weights, sample opening time intervals, sample ambient temperatures and corresponding sample left drum initial temperatures and sample right drum initial temperatures before inputting the washing type, the clothes weight, the opening time interval and the ambient temperature into the initial temperature prediction model; and a first training unit configured to train the plurality of groups of first training data by using a machine learning method to obtain the initial temperature prediction model.

[0021] Optionally, the determining unit comprises a second processing module configured to input the washing type, the clothes weight, the opening time interval, the ambient temperature and the left drum initial temperature and the right drum initial temperature into a total running time prediction model, and process the washing type, the clothes weight, the opening time interval, the ambient temperature and the left drum initial temperature and the right drum initial temperature by using the total running time prediction model to obtain the left drum total running time and the right drum total running time.

[0022] Optionally, the heating control device of the dual-drum washing machine further comprises a fifth obtaining unit configured to obtain a plurality of groups of second training data comprising sample washing types, sample clothes weights, sample opening time intervals, sample ambient temperatures and sample left drum initial temperatures and sample right drum initial temperatures and corresponding sample left drum total running times and right drum total running times before determining the left drum total running time of the left drum and the right drum total running time of the right drum according to the washing type, the clothes weight, the opening time interval, the ambient temperature and the left drum initial temperature and the right drum initial temperature; and a second training unit configured to train the plurality of groups of second training data by using a machine learning method to obtain the total running time prediction model.

[0023] Optionally, the heating control device of the dual-drum washing machine further comprises a display unit configured to display the left drum total running time and / or the right drum total running time after determining the left drum total running time of the left drum and the right drum total running time of the right drum according to the washing type, the clothes weight, the opening time interval, the ambient temperature and the left drum initial temperature and the right drum initial temperature.

[0024] According to another aspect of the embodiments of the present application, there is further provided a washing machine using the heating control method of the dual tub washing machine according to any one of the preceding embodiments.

[0025] According to another aspect of the embodiments of the present application, there is further provided a computer readable storage medium comprising a stored program, wherein the program performs the heating control method of the dual tub washing machine according to any one of the preceding embodiments.

[0026] According to another aspect of the embodiments of the present application, there is further provided a processor configured to execute a program, wherein the program performs the heating control method of the dual tub washing machine according to any one of the preceding embodiments when executed.

[0027] According to another aspect of the embodiments of the present application, there is further provided a computer program product comprising computer instructions configured to perform the heating control method of the dual tub washing machine according to any one of the preceding embodiments when executed by a processor.

[0028] In the embodiments of the present application, when it is detected that both the left tub and the right tub of the dual tub washing machine are turned on, the washing type, the weight of the laundry and the opening time interval of the left tub and the right tub of the dual tub washing machine are obtained; the ambient temperature of the room where the dual tub washing machine is located is obtained; the left tub initial temperature of the left tub and the right tub initial temperature of the right tub are predicted according to the washing type, the weight of the laundry, the opening time interval and the ambient temperature; the total running time length of the left tub and the total running time length of the right tub are determined according to the washing type, the weight of the laundry, the opening time interval, the ambient temperature and the left tub initial temperature and the right tub initial temperature; the left tub is controlled to run according to the total running time length of the left tub, and the right tub is controlled to run according to the total running time length of the right tub. Through the above technical solutions provided by the present application, the initial temperatures of the left tub and the right tub are determined by analyzing the heating temperature, the washing time, the weight, the ambient temperature and the interval time of the left tub and the right tub, and then the running time lengths of the left tub and the right tub are determined in combination with the initial temperatures, so that the technical effect of reducing the mutual influence of the left tub and the right tub of the dual tub washing machine is achieved, the total running time of the dual tub washing machine is minimized and the system performance is optimized, and thus the technical problem that in the related art, due to the heat exchange characteristics of the dual tub structure, heat is transferred between the two washing tubs, causing the mutual influence of the temperatures of the two tubs is solved. BRIEF DESCRIPTION OF DRAWINGS

[0029] The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and serve to explain the principles of the application. In the drawings:

[0030] Figure 1A hardware structure block diagram of a mobile terminal of a heating control method of a double tub washing machine according to an embodiment of the present application;

[0031] Figure 2 A flow chart of a heating control method of a double tub washing machine according to an embodiment of the present application;

[0032] Figure 3 A flow chart of an optional heating control method of a double tub washing machine according to an embodiment of the present application;

[0033] Figure 4 A schematic diagram of a neural network model according to an embodiment of the present application;

[0034] Figure 5 A flow chart of yet another optional heating control method of a double tub washing machine according to an embodiment of the present application;

[0035] Figure 6 A schematic diagram of a heating control device of a double tub washing machine according to an embodiment of the present application.

[0036] In the above drawings, reference numerals:

[0037] 102, processor; 104, memory; 106, transmission device; 108, input / output device. DETAILED DESCRIPTION

[0038] In order to make the personnel in the art better understand the present application scheme, the technical scheme in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should belong to the scope of protection of the present application.

[0039] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or a chronological sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0040] As described in the background section, in the heating mode of related twin-tub washing machines, due to the thermal interaction characteristics of the twin-tub structure, heat is transferred between the two washing tubs, causing the temperatures of the two tubs to affect each other. This invention provides a heating control method and apparatus for a twin-tub washing machine, a washing machine, a computer-readable storage medium, a processor, and a computer program product.

[0041] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0042] The methods and embodiments provided in this invention can be executed on a mobile terminal, a computer terminal, or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 This is a hardware structure block diagram of a mobile terminal for a heating control method of a twin-tub washing machine according to an embodiment of the present invention. Figure 1 As shown, a mobile terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. The mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the mobile terminal described above. For example, the mobile terminal may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0043] The memory 104 can be used to store computer programs, such as software programs of application software and modules, such as the computer program corresponding to the heating control method of the dual-tub washing machine in the embodiments of the present application. The processor 102 can execute various functional applications and data processing, i.e., implement the above method, by running the computer program stored in the memory 104. The memory 104 can include a high-speed random access memory, and can further include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some examples, the memory 104 can further include a memory remotely arranged with respect to the processor 102, and the remote memory can be connected to the mobile terminal through a network. Examples of the network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof. The transmission device 106 is used to receive or send data through a network. The specific examples of the network can include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet in a wireless manner.

[0044] Embodiment 1

[0045] According to the embodiments of the present application, a method embodiment of the heating control method of the dual-tub washing machine is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system, such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown herein.

[0046] Figure 2 is a flowchart of the heating control method of the dual-tub washing machine according to the embodiments of the present application, as shown in Figure 2 The heating control method of the dual-tub washing machine includes the following steps:

[0047] In step S202, when it is detected that both the left tub and the right tub of the dual-tub washing machine are opened, the washing type of the dual-tub washing machine, the weight of the clothes, and the opening time interval of the left tub and the right tub are obtained.

[0048] Optionally, the washing types mentioned above represent the operating mode of the washing machine selected by the user, such as standard wash, quick wash, deep clean, wool wash, energy-saving mode, etc. Each type has specific temperature and time settings. Laundry weight refers to the total weight of the clothes placed in the washing machine drum, which is an important factor determining heating time and energy consumption. The opening interval is the time difference between the left and right drums from opening to the execution of the heating or washing program.

[0049] Figure 3 This is a flowchart of an optional heating control method for a twin-tub washing machine according to an embodiment of the present invention, such as... Figure 3 As shown, in this embodiment, both the left and right tubs are turned on, with two scenarios: either both tubs are turned on simultaneously, or one tub is turned on first, followed by the other. If the user turns on both tubs simultaneously, the selected washing types X1 and X2 are recorded; the washing machine weighs the clothes to obtain their weights g1 and g2. In this case, the start time interval (T) = 0. Conversely, if only one tub is turned on, the running tub displays the set total time for the washing cycle.

[0050] Step S204: Obtain the ambient temperature of the room where the twin-tub washing machine is located.

[0051] Optionally, ambient temperature refers to the actual temperature of the environment where the washing machine is located, which has a direct impact on heating efficiency.

[0052] like Figure 3 As shown, after the washing machine weighs the clothes to obtain the weights g1 and g2, the temperature sensor obtains the ambient temperature T_ring.

[0053] Step S206: Based on the washing type, the weight of the clothes, the time interval between start-up and the ambient temperature, predict the initial temperature of the left tub and the initial temperature of the right tub.

[0054] The predicted initial temperature here refers to the expected initial temperature value inside the left and right washing tubs before the twin-tub washing machine starts heating, taking into account factors such as the thermal interaction characteristics of the twin-tub structure and environmental conditions. This prediction is based on machine learning model analysis, which integrates factors such as the user's washing type selection, the actual weight of the clothes, the ambient temperature of the washing machine, and the time interval between the opening of the left and right tubs.

[0055] Specifically, due to the heat transfer between the two washing drums in a double drum washing machine, the efficiency and accuracy of the heating process can be affected. The purpose of predicting the initial temperature is to estimate the actual temperature of the left and right drums at the moment when the heating program starts by modeling and learning these complex factors under the influence of heat interaction. In this way, the control system can adjust the heating power and time according to the predicted initial temperature to ensure that each drum reaches the required heating temperature efficiently and accurately even in the presence of heat interaction.

[0056] Predicting the initial temperature is a key step in the overall control strategy, which helps to plan the heating process in advance, avoid waste of resources, shorten the overall heating time, and achieve the goal of energy saving and efficiency improvement while ensuring washing quality and user experience.

[0057] As shown in Figure 3 The washing type, the weight of the clothes, the opening time interval, and the ambient temperature can be used as the basis for predicting the initial temperature of the left and right drums.

[0058] In step S208, the total running time of the left drum and the total running time of the right drum are determined based on the washing type, the weight of the clothes, the opening time interval, the ambient temperature, and the initial temperature of the left drum and the initial temperature of the right drum.

[0059] In step S210, the left drum is controlled to run for the total running time of the left drum, and the right drum is controlled to run for the total running time of the right drum.

[0060] As can be seen from the above, in the embodiment of the present application, when it is detected that both the left drum and the right drum of the double drum washing machine are opened, the washing type, the weight of the clothes, and the opening time interval of the left drum and the right drum of the double drum washing machine are obtained; the ambient temperature of the room where the double drum washing machine is located is obtained; the initial temperature of the left drum and the initial temperature of the right drum are predicted based on the washing type, the weight of the clothes, the opening time interval, and the ambient temperature; the total running time of the left drum and the total running time of the right drum are determined based on the washing type, the weight of the clothes, the opening time interval, the ambient temperature, and the initial temperature of the left drum and the initial temperature of the right drum; the left drum is controlled to run for the total running time of the left drum, and the right drum is controlled to run for the total running time of the right drum, which realizes the purpose of determining the initial temperature of the left and right drums by analyzing the heating temperature, washing time, weight, ambient temperature, and interval time of the left and right drums, and then determining the running time of the left and right drums in combination with the initial temperature, thereby achieving the technical effect of reducing the mutual influence of the left and right drum temperatures of the double drum washing machine, minimizing the total running time of the double drum washing machine, and optimizing the system performance.

[0061] Therefore, through the above technical solutions provided by the embodiments of the present application, the technical problem that in the related art, in the heating mode, due to the heat exchange characteristics of the double-barrel structure, heat is transferred between the two washing barrels, causing the phenomenon that the temperatures of the two barrels affect each other is solved.

[0062] According to the above embodiments of the present application, the clothes weight of the double-barrel washing machine is obtained, including: after the double-barrel washing machine starts to perform a washing operation, performing a weighing operation on the left barrel and the right barrel of the double-barrel washing machine to obtain the clothes weight of the double-barrel washing machine.

[0063] In this embodiment, after the washing machine starts to perform a washing operation, the system automatically performs a weighing operation on the left barrel and the right barrel. The weighing result is provided as input to the initial temperature prediction model together with the washing type, the opening interval time, and the ambient temperature. This model predicts the initial temperatures of the left and right barrels based on the input data, laying a foundation for subsequent total running time prediction. It also solves the problem that the initial state of the heating process cannot be accurately predicted due to unknown clothes weight. By weighing immediately after the washing operation starts, the accuracy of subsequent prediction is ensured, and misjudgment of the heating time is avoided.

[0064] For example, after the user starts the washing machine, advanced sensors inside the washing machine immediately perform precise weighing on the left barrel and the right barrel. Assuming that in one washing process, 5 summer T-shirts (total weight about 500g) are put into the left barrel, and 2 heavy winter jackets (total weight about 1000g) are put into the right barrel. After weighing, the system inputs this information into the machine learning model together with the user's washing type selection, the opening interval time, and the ambient temperature to predict the initial temperature and optimize the total running time. This process ensures that the washing machine can adjust the heating strategy according to the actual weight of the clothes, prevent unreasonable heating time caused by weight difference, and thus achieve more accurate energy utilization and washing effect.

[0065] Through accurate measurement of the clothes weight, the heating control is more accurate, avoiding excessive or insufficient heating time, which helps to save energy and maintain washing quality. For example, for clothes with large weight difference, such as 500g in the left barrel and 1500g in the right barrel, the model can accurately adjust the heating strategy to ensure that each barrel is heated as needed.

[0066] According to the above embodiments of the present application, the opening time interval of the left barrel and the right barrel of the double-barrel washing machine is obtained, including: determining the left barrel opening time of the left barrel and the right barrel opening time of the right barrel; and determining the opening time interval according to the left barrel opening time and the right barrel opening time.

[0067] In this embodiment, the system records the time point T1 when the left drum is first opened and the time point T2 when the right drum is opened, and then calculates the time difference between the two, i.e. the opening interval time tint. This time information will be input into the optimal total time prediction model together with other parameters, solving the problem of heating time optimization difficulty in double-drum washing machines due to different opening sequences and times of the drums. By recording the opening interval time, the model can adjust the heating strategy according to the actual situation, avoiding unnecessary heat exchange between the drums and improving efficiency.

[0068] For example, on a Sunday morning, the user plans to wash bed sheets in the left drum, and later in the afternoon, he intends to wash clothes in the right drum. The user starts the left drum for washing at 10:00 am, and then opens the right drum at 1:30 pm (i.e. the opening interval time tint is 195 minutes). The system records this opening time interval and inputs it into the initial temperature prediction model together with the washing type (bed sheets, clothes), the weight of the clothes, the environmental temperature, etc. Through model analysis, the opening interval time of the left drum and the right drum significantly affects the prediction result of the initial temperature, and thus determines the optimal total running time of each drum. This intelligent control enables effective management and adjustment of the heating process even when different drums are started at a long interval, avoiding energy waste and temperature instability caused by heat exchange.

[0069] The accurate determination of the opening interval time helps the model make more reasonable decisions on heating time. For example, if the left drum is opened half an hour before the right drum, the model may appropriately extend the heating time of the left drum to compensate for the heat loss that may occur during this time, while shortening the heating time of the right drum to utilize the residual heat effect of the left drum.

[0070] According to the above embodiment of the present application, the left drum initial temperature and the right drum initial temperature of the left drum and the right drum are predicted according to the washing type, the weight of the clothes, the opening time interval, and the environmental temperature, including: inputting the washing type, the weight of the clothes, the opening time interval, and the environmental temperature into the initial temperature prediction model to process the washing type, the weight of the clothes, the opening time interval, and the environmental temperature by using the initial temperature prediction model, to obtain the left drum initial temperature and the right drum initial temperature.

[0071] In this embodiment, the washing type, the weight of the clothes, the opening interval time, and the environmental temperature are input into the initial temperature prediction model trained by a large amount of data, and the model predicts the initial temperatures TA and TB of the left and right drums by using neural network or other machine learning techniques, solving the problem of poor heating control strategy due to lack of understanding of the initial state in the double-drum washing machine. By predicting the initial temperature, the model can more accurately adjust the heating time and power, reducing energy waste.

[0072] The predicted initial temperature here makes the heating process more personalized and targeted. For example, the left barrel with a predicted initial temperature of 27°C and the right barrel with a predicted initial temperature of 25°C, the model can adjust the heating power accordingly to ensure that each barrel reaches the set heating temperature in the shortest time, while avoiding energy loss caused by excessive heating.

[0073] According to the above embodiment of the present application, before the washing type, the weight of the clothes, the opening time interval and the ambient temperature are input into the initial temperature prediction model, the heating control method of the double-barrel washing machine further comprises: obtaining a plurality of sets of first training data comprising sample washing types, sample weights of clothes, sample opening time intervals, sample ambient temperatures and corresponding sample left barrel initial temperatures and sample right barrel initial temperatures; training the plurality of sets of first training data by machine learning to obtain the initial temperature prediction model.

[0074] In this embodiment, before obtaining the output of the initial temperature prediction model, the system needs to collect a large amount of first training data, including samples of different washing types, samples of different weights of clothes, samples of opening time intervals, samples of ambient temperatures, and corresponding left barrel initial temperature samples and right barrel initial temperature samples. Through these data, the model is trained until the model reaches a satisfactory prediction accuracy, solving the problem of lack of adaptability and prediction ability of the model. Through large-scale training data, the model can learn the characteristics of the initial temperature under various conditions, improving the accuracy and applicability of the prediction.

[0075] Here, the fully trained model has stronger prediction ability and can cope with more complex and variable washing situations, reducing the dependence on specific conditions and enhancing the universality and reliability of the heating control method of the double-barrel washing machine.

[0076] The technical solution provided by the embodiment of the present application can be divided into three stages: parameter collection stage, model training stage and model application stage. Among them, the parameter collection stage is as follows: the washing types X1, X2 selected by the user, the weights of clothes g1, g2, the opening interval time t and the ambient temperature T are the key influencing factors of the initial temperature values tA, tB in the barrel. In addition, the washing types X1, X2, the weights of clothes g1, g2, the opening interval time t and the predicted initial temperature values TA, TB are also important influencing parameters of the optimal total time tA, tB of the left and right barrels, so these key parameters must be fully collected in the parameter collection stage.

[0077] As Figure 3As shown, when a user operates a twin-tub washing machine and simultaneously opens both tubs, the selected washing types X1 and X2 are recorded. The washing times t1 and t2, and the heating temperatures T1 and T2 are obtained from the washing types. At this point, the default interval between the opening of the left and right tubs, tinterval, is 0. Temperature sensors are installed on both sides of the outer tub of the washing machine to obtain the ambient temperature Toven. After the wash begins, the weights g1 and g2 of the clothes in the left and right tubs are weighed. These parameters are input into the initial temperature prediction model to obtain the predicted initial temperature values ​​TA and TB. The washing types X1 and X2, the weights g1 and g2, the opening interval tinterval, and the initial temperature values ​​TA and TB are input into the optimal total time model to obtain the optimal total time tA and tB. After weighing is complete, the optimal total time is displayed to the user.

[0078] Additionally, when a user uses a twin-tub washing machine and only one tub is running, the selected washing type X1 is recorded. The washing time t1 and heating temperature T1 are obtained from the washing type, and the weight of the clothes g1 is measured. The system displays the program time and runs the washing cycle by default. If the other tub is not running during this process, the washing cycle continues until completion. If the other tub starts running, the interval t between the left and right tubs is recorded. The ambient temperature Tring is obtained through a temperature sensor. After the second tub starts washing, the weight of the clothes g2 is measured. The parameters X1, X2, Tring, g1, and g2 are input into the predicted initial temperature model to obtain the predicted initial temperature values ​​TA and TB. The washing type X1, X2, the weights of the clothes g1 and g2, the start-up interval t, and the initial temperature values ​​TA and TB are input into the optimal total time model to obtain the optimal total time tB. After the second tub finishes weighing, the optimal total time will be displayed to the user.

[0079] For the model training phase, the specific steps are as follows: The inputs to the initial temperature prediction model are the user-selected washing types X1 and X2, laundry weights g1 and g2, start-up interval t, and ambient temperature T. The outputs are the initial temperature values ​​TA and TB. The inputs to the optimal total time model are the user-selected washing types X1 and X2, laundry weights g1 and g2, start-up interval t, and initial temperature values ​​TA and TB. The outputs are the optimal total time tA and tB for the left and right drums. Since the input and output parameters of the two models are similar, and both are multiple-input multiple-output (MIMO) problems, a massive and diverse dataset, covering different washing modes, laundry weight ranges, start-up intervals, ambient temperatures, initial temperature values, and optimal total times, is sent to a remote high-performance computing server via a network transmission protocol. This strategy effectively reduces the processing burden on the local controller, significantly lowers hardware costs, and leverages the powerful computing capabilities of the cloud to accelerate data processing and analysis. Figure 4 This is a schematic diagram of a neural network model according to an embodiment of the present invention, such as... Figure 4As shown, X1 to X7 are the outputs of the input layer, with three hidden layers in between, and the output layer at the end. The output layer includes two layers, namely the optimal total time tA and tB for the left and right buckets.

[0080] On the server side, a machine learning model is deployed to predict the initial temperature. This model uses collected parameters such as the user's selected washing types X1 and X2, laundry weights g1 and g2, start-up interval t, and ambient temperature T as input features to train the model. The core objective of model training is to establish the mapping relationship between the user's selected washing types X1 and X2, laundry weights g1 and g2, start-up interval t, ambient temperature T, and the initial temperature values ​​TA and TB. The optimal total time model follows the same principle.

[0081] The washing types X1 and X2, laundry weights g1 and g2, start-up interval t, and ambient temperature T used in the model training process all originated from the initial parameter acquisition phase. This phase involved numerous repetitive experiments and data recordings, providing a solid data foundation for subsequent model training. Washing types X1 and X2 determine washing times t1 and t2 and heating temperatures T1 and T2. Washing time determines the washing duration for both the left and right tubs, and heating temperature determines the heating requirement for each tub. Laundry weights g1 and g2 affect the heating effect; greater weight requires a longer heating time. Ambient temperature T affects the initial heating temperature. The start-up interval t, combined with the washing time, determines the stage of heating for each tub. These parameters combined can predict the initial temperatures TA and TB of both tubs.

[0082] The initial and heating temperatures of the left and right tubs affect the total running time; the closer the initial temperature is to the heating temperature, the shorter the required heating time. Washing time and the weight of the laundry are also key factors determining the total running time. The start-up interval can determine which tub's total running time needs optimization. When both tubs start simultaneously, the running time of both tubs can be optimized at the same time. If there is a certain time interval between starting one tub and starting the other, the optimization strategy will focus on adjusting the washing time of the tub that starts later. When only one tub is running, no optimization adjustment is needed.

[0083] This process continuously improves the model's prediction accuracy and generalization ability, providing strong support for the practical application of dual-barrel heating control systems.

[0084] According to the above embodiments of the present invention, determining the total operating time of the left tub and the total operating time of the right tub based on the washing type, laundry weight, start-up time interval, ambient temperature, and initial temperatures of the left and right tubs includes: inputting the washing type, laundry weight, start-up time interval, ambient temperature, and initial temperatures of the left and right tubs into the total operating time prediction model, and using the total operating time prediction model to process the washing type, laundry weight, start-up time interval, ambient temperature, and initial temperatures of the left and right tubs to obtain the total operating time of the left and right tubs.

[0085] In this embodiment, after predicting the initial temperatures of the left and right tubs, the model uses washing type, laundry weight, start-up interval, ambient temperature, and the predicted initial temperature as inputs into the total running time prediction model to determine the optimal total running times tA and tB for the left and right tubs. These time values ​​guide the actual heating control process, solving the problem of setting the optimal heating time for a twin-tub washing machine while considering all relevant factors. Through comprehensive analysis, the model ensures that each tub reaches its optimal heating state in the shortest possible time while minimizing energy consumption.

[0086] For example, on a cold winter night, a user needs to wash summer and winter clothes simultaneously in a twin-tub washing machine. Data collected earlier, including clothing weight, washing type, and ambient temperature (summer clothes weigh approximately 500 grams, using the standard wash mode; winter clothes weigh approximately 1000 grams, using the deep clean mode; ambient temperature 10°C, start-up interval t = 0), is input into a total running time prediction model. After analysis, the model determines the optimal total running time for the left tub is 62 minutes and for the right tub, 65 minutes. This decision-making process considers all factors affecting heating and washing time, ensuring each tub completes heating and washing within the most suitable time, saving energy and improving washing efficiency. This demonstrates the significant potential of intelligent control in enhancing the user's laundry experience.

[0087] By determining the optimal total duration, the heating process becomes more efficient and energy-saving. For example, for the left and right tanks, the model might determine the optimal total durations to be 55 minutes and 58 minutes, respectively. By optimizing the heating strategy, a shorter total running time is achieved compared to conventional control methods, while ensuring the heating effect.

[0088] According to the above embodiment of the present application, before determining the left drum total running time of the left drum and the right drum total running time of the right drum according to the washing type, the clothes weight, the opening time interval, the environment temperature, and the left drum initial temperature and the right drum initial temperature, the heating control method of the double-drum washing machine further comprises: obtaining a plurality of second training data sets comprising sample washing types, sample clothes weights, sample opening time intervals, sample environment temperatures, and sample left drum initial temperatures and sample right drum initial temperatures, and corresponding sample left drum total running times and right drum total running times; and training the plurality of second training data sets by means of machine learning to obtain a total running time prediction model.

[0089] In this embodiment, in addition to the parameters required for collecting and training the initial temperature prediction model, a large amount of second training data is also needed, including combinations of different washing types, clothes weights, opening interval times, environment temperatures, initial temperatures, and optimal total running times. By analyzing these data through machine learning techniques, a total running time prediction model is trained, solving the problem of insufficient training data for the total running time prediction model, which leads to poor prediction results. By collecting a variety of real running data, the model can learn more extensive running patterns, improving the accuracy and range of prediction.

[0090] By training a sufficient total running time prediction model, the total running time of each drum can be more accurately predicted, reducing unnecessary waiting time and improving user satisfaction. For example, for the left drum and the right drum, the model may have learned from the training data that under certain conditions, the optimal total time of the left drum is 58 minutes, while that of the right drum is 60 minutes.

[0091] According to the above embodiment of the present application, after determining the left drum total running time of the left drum and the right drum total running time of the right drum according to the washing type, the clothes weight, the opening time interval, the environment temperature, and the left drum initial temperature and the right drum initial temperature, the heating control method of the double-drum washing machine further comprises: displaying the left drum total running time and / or the right drum total running time.

[0092] In this embodiment, once the left drum total running time tA and the right drum total running time tB are determined, the display screen of the double-drum washing machine will display these two time values in real time, providing intuitive information to the user and allowing the user to understand the remaining washing time, enhancing the user experience and solving the problem of the user being unable to understand the progress of the washing process in real time. By displaying the optimal total time, the transparency of the washing machine operation is increased, improving the user experience.

[0093] For example, during a routine laundry cycle, the washing machine screen displays the optimal total running time tA for the left tub as 55 minutes and tB for the right tub as 58 minutes. Before starting the washing machine, users clearly understand the time required for each tub to complete the wash cycle. This not only helps users manage their personal time effectively but also enhances their confidence in the washing machine's performance, making the entire washing experience more transparent and controllable.

[0094] By displaying the total time in real time, users can manage their time effectively, reducing waiting anxiety and increasing their trust and satisfaction with the washing machine's performance.

[0095] Figure 5 This is a flowchart of another optional heating control method for a twin-tub washing machine according to an embodiment of the present invention, such as... Figure 5 As shown, for the system model, before the start of this wash cycle, the user selected washing mode X1 for the left tub and washing mode X2 for the right tub, with corresponding washing times t1 and t2, and heating temperatures T1 and T2. The start-up interval is t_interval. After the wash cycle starts, the weight of the clothes in the left tub (g1) and the weight of the clothes in the right tub (g2) are obtained, and the ambient temperature T_ring is measured. X1, X2, g1, g2, t_interval, and T_ring are input into the initial temperature prediction model. The model calculates the initial temperatures TA and TB of the left and right tubs through learning. X1, X2, g1, g2, TA, TB, and T_ring are input into the optimal total time model. The model calculates the optimal total time tA and tB of the left and right tubs through learning, as shown in Tables 1 and 2 below:

[0096] Table 1

[0097]

[0098] Table 2

[0099]

[0100] The technical solution provided by this invention first analyzes parameters such as the heating temperature, washing time, weight, ambient temperature, and the interval between the opening of the left and right tubs. These parameters are input into the model, and a machine learning algorithm is used to comprehensively analyze and optimize each variable, outputting the predicted initial temperature under the mutual influence of the left and right tubs. Then, the washing type, weight of the clothes, the opening interval between the left and right tubs, and the predicted initial temperature value are input into the model, ultimately outputting the optimal heating control strategy to minimize the total time and optimize system performance. This solves the problem that in existing twin-tub washing machines, the two tubs operate independently during normal washing, without affecting each other. However, in heating mode, due to the thermal interaction characteristics of the twin-tub structure, heat is transferred between the two tubs, causing their temperatures to influence each other. By adopting effective heating control methods, energy saving and consumption reduction can be achieved, ensuring efficient and stable system operation.

[0101] Specifically, it is based on the washing type of left and right barrels, the weight of clothes, the opening interval time and the predicted initial temperature. The method first constructs an optimization model by taking the heating temperature of left and right barrels, the washing time, the weight, the environmental temperature and the opening interval time as input variables, and uses machine learning algorithm to comprehensively analyze and optimize each variable to predict the initial temperature under the interaction of left and right barrels. Then, the washing type of left and right barrels, the weight of clothes, the opening interval time and the predicted initial temperature are input into the model to further calculate the total running time, so as to minimize the total time and optimize the performance. The heating temperature of left and right barrels, the washing time, the weight of clothes, the environmental temperature and the opening interval time of left and right barrels are input into the remote system, and the model predicts the initial temperature value under the mutual influence of left and right barrels. 2, the washing type of left and right barrels, the weight of clothes, the opening interval time of left and right barrels, the predicted initial temperature value are input into the remote system before washing starts, and the model obtains the optimal total time through machine learning.

[0102] It should be noted that, for the foregoing method embodiments, in order to simply describe, they are all expressed as a series of action combinations, but those skilled in the art should know that the present application is not limited by the action sequence described, because according to the present application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification all belong to preferred embodiments, and the actions and modules involved are not necessarily essential to the present application.

[0103] From the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be realized by means of software and the necessary general hardware platform, and of course it can also be realized by hardware, but in many cases the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes a plurality of instructions for making a terminal device (which can be a mobile phone, computer, server or network device) execute the methods described in the embodiments of the present application.

[0104] Embodiment 2

[0105] According to the embodiments of the present application, a heating control device of a double-barrel washing machine for implementing the heating control method of the double-barrel washing machine is also provided, Figure 6 is a schematic diagram of a heating control device of a double-barrel washing machine according to an embodiment of the present application, like Figure 6As shown, the heating control device of the double-barrel washing machine comprises a first obtaining unit 601, a second obtaining unit 603, a third obtaining unit 605, a determining unit 607 and a control unit 609. The heating control device of the double-barrel washing machine will be described below.

[0106] The first obtaining unit 601 is configured to obtain the washing type, the weight of clothes and the opening time interval of the left barrel and the right barrel of the double-barrel washing machine when it is detected that both the left barrel and the right barrel are opened.

[0107] The second obtaining unit 603 is configured to obtain the ambient temperature of the room where the double-barrel washing machine is located.

[0108] The third obtaining unit 605 is configured to predict the left barrel initial temperature of the left barrel and the right barrel initial temperature of the right barrel according to the washing type, the weight of clothes, the opening time interval and the ambient temperature.

[0109] The determining unit 607 is configured to determine the total running time of the left barrel and the total running time of the right barrel according to the washing type, the weight of clothes, the opening time interval, the ambient temperature, the left barrel initial temperature and the right barrel initial temperature.

[0110] The control unit 609 is configured to control the left barrel to run according to the total running time of the left barrel and control the right barrel to run according to the total running time of the right barrel.

[0111] It should be noted that the first obtaining unit 601, the second obtaining unit 603, the third obtaining unit 605, the determining unit 607 and the control unit 609 correspond to steps S202 to S210 in the above embodiment, and the five units have the same instances and application scenarios as the corresponding steps, but are not limited to the contents disclosed in the above embodiment.

[0112] From the above, in the scheme described in the above embodiments of the present application, the first acquisition unit can be used to acquire the washing type, the weight of clothes and the opening time interval of the left barrel and the right barrel of the double-barrel washing machine when it is detected that both the left barrel and the right barrel of the double-barrel washing machine are opened, the second acquisition unit is used to acquire the ambient temperature of the room where the double-barrel washing machine is located, the third acquisition unit is used to predict the left barrel initial temperature of the left barrel and the right barrel initial temperature of the right barrel according to the washing type, the weight of clothes, the opening time interval and the ambient temperature, the determination unit is used to determine the total running time of the left barrel and the total running time of the right barrel according to the washing type, the weight of clothes, the opening time interval, the ambient temperature and the left barrel initial temperature and the right barrel initial temperature, and the control unit is used to control the left barrel to run according to the total running time of the left barrel and control the right barrel to run according to the total running time of the right barrel, which realizes the purpose of determining the initial temperature of the left barrel and the right barrel by analyzing the heating temperature, the washing time, the weight, the ambient temperature and the interval time of the opening of the left barrel and the right barrel, and then determining the running time of the left barrel and the right barrel in combination with the initial temperature, and achieves the technical effect of reducing the mutual influence of the left barrel temperature and the right barrel temperature of the double-barrel washing machine, so that the total running time of the double-barrel washing machine is minimized and the system performance is optimized.

[0113] Therefore, by the above technical scheme provided by the embodiments of the present application, the technical problem that in the related art, in the heating mode of the double-barrel washing machine, due to the heat exchange characteristics of the double-barrel structure, heat is transferred between the two washing barrels, causing the phenomenon of mutual influence of the temperatures of the two barrels, is solved.

[0114] Optionally, the first acquisition unit comprises a weighing module configured to perform a weighing operation on the left barrel and the right barrel of the double-barrel washing machine after the double-barrel washing machine starts to perform a washing operation, to obtain the weight of clothes of the double-barrel washing machine.

[0115] Optionally, the first acquisition unit comprises a first determination module configured to determine the left barrel opening time of the left barrel and the right barrel opening time of the right barrel, and a second determination module configured to determine the opening time interval according to the left barrel opening time and the right barrel opening time.

[0116] Optionally, the determination unit comprises a first processing module configured to input the washing type, the weight of clothes, the opening time interval and the ambient temperature into an initial temperature prediction model, to process the washing type, the weight of clothes, the opening time interval and the ambient temperature by using the initial temperature prediction model, to obtain the left barrel initial temperature and the right barrel initial temperature.

[0117] Optionally, the heating control device of the dual-tank washing machine further comprises: a fourth acquisition unit, configured to acquire a plurality of sets of first training data comprising sample washing types, sample laundry weights, sample opening time intervals, sample ambient temperatures, and corresponding sample left-tank initial temperatures and sample right-tank initial temperatures, before inputting the washing type, the laundry weight, the opening time interval, and the ambient temperature into the initial temperature prediction model; and a first training unit, configured to train the plurality of sets of first training data by means of machine learning to obtain the initial temperature prediction model.

[0118] Optionally, the determining unit comprises: a second processing module, configured to input the washing type, the laundry weight, the opening time interval, the ambient temperature, and the left-tank initial temperature and the right-tank initial temperature into the total running time prediction model, to process the washing type, the laundry weight, the opening time interval, the ambient temperature, and the left-tank initial temperature and the right-tank initial temperature by means of the total running time prediction model, and to obtain the left-tank total running time and the right-tank total running time.

[0119] Optionally, the heating control device of the dual-tank washing machine further comprises: a fifth acquisition unit, configured to acquire a plurality of sets of second training data comprising sample washing types, sample laundry weights, sample opening time intervals, sample ambient temperatures, and sample left-tank initial temperatures and sample right-tank initial temperatures, and corresponding sample left-tank total running times and sample right-tank total running times, before determining the left-tank total running time of the left tank and the right-tank total running time of the right tank according to the washing type, the laundry weight, the opening time interval, the ambient temperature, and the left-tank initial temperature and the right-tank initial temperature; and a second training unit, configured to train the plurality of sets of second training data by means of machine learning to obtain the total running time prediction model.

[0120] Optionally, the heating control device of the dual-tank washing machine further comprises: a display unit, configured to display the left-tank total running time and / or the right-tank total running time after determining the left-tank total running time of the left tank and the right-tank total running time of the right tank according to the washing type, the laundry weight, the opening time interval, the ambient temperature, and the left-tank initial temperature and the right-tank initial temperature.

[0121] According to another aspect of the embodiments of the present application, a washing machine is also provided, which uses the heating control method of the dual-tank washing machine according to any one of the above.

[0122] According to another aspect of the embodiments of the present application, a processor is also provided, which is configured to run a program, wherein the program performs the heating control method of the dual-tank washing machine according to any one of the above when running.

[0123] According to another aspect of the embodiments of the present application, a computer program product is provided, which includes computer instructions for performing the heating control method of the double-barrel washing machine according to any one of the above embodiments when executed by a processor.

[0124] According to another aspect of the embodiments of the present application, a computer readable storage medium is provided, which includes a stored program for performing the heating control method of the double-barrel washing machine according to any one of the above embodiments.

[0125] Optionally, in the embodiment, the computer readable storage medium can be located in any one of the computer terminals in a computer terminal group in a computer network, or in any one of the communication devices in a communication device group.

[0126] Optionally, in the embodiment, the computer readable storage medium is configured to store program code for performing the following steps: obtaining the washing type, the weight of the clothes, and the opening time interval of the left barrel and the right barrel of the double-barrel washing machine when it is detected that both the left barrel and the right barrel of the double-barrel washing machine are opened; obtaining the ambient temperature of the room where the double-barrel washing machine is located; predicting the left barrel initial temperature of the left barrel and the right barrel initial temperature of the right barrel according to the washing type, the weight of the clothes, the opening time interval, and the ambient temperature; determining the total running time of the left barrel and the total running time of the right barrel according to the washing type, the weight of the clothes, the opening time interval, the ambient temperature, and the left barrel initial temperature and the right barrel initial temperature; controlling the left barrel to run according to the total running time of the left barrel, and controlling the right barrel to run according to the total running time of the right barrel.

[0127] Optionally, in the embodiment, the computer readable storage medium is configured to store program code for performing the following steps: performing a weighing operation on the left barrel and the right barrel of the double-barrel washing machine to obtain the weight of the clothes of the double-barrel washing machine after the double-barrel washing machine starts to perform a washing operation.

[0128] Optionally, in the embodiment, the computer readable storage medium is configured to store program code for performing the following steps: determining the left barrel opening time of the left barrel and the right barrel opening time of the right barrel; and determining the opening time interval according to the left barrel opening time and the right barrel opening time.

[0129] Optionally, in the embodiment, the computer readable storage medium is configured to store program code for performing the following steps: inputting the washing type, the weight of the clothes, the opening time interval, and the ambient temperature into an initial temperature prediction model to process the washing type, the weight of the clothes, the opening time interval, and the ambient temperature by using the initial temperature prediction model to obtain the left barrel initial temperature and the right barrel initial temperature.

[0130] Optionally, in the embodiment, the computer readable storage medium is configured to store program code for performing the following steps: obtaining a plurality of first training data sets comprising sample washing types, sample laundry weights, sample opening time intervals, sample ambient temperatures, and corresponding sample left drum initial temperatures and sample right drum initial temperatures, before inputting the washing type, the laundry weight, the opening time interval, and the ambient temperature into the initial temperature prediction model; and training the plurality of first training data sets by means of machine learning to obtain the initial temperature prediction model.

[0131] Optionally, in the embodiment, the computer readable storage medium is configured to store program code for performing the following steps: inputting the washing type, the laundry weight, the opening time interval, the ambient temperature, and the left drum initial temperature and the right drum initial temperature into the total running time prediction model, to process the washing type, the laundry weight, the opening time interval, the ambient temperature, and the left drum initial temperature and the right drum initial temperature by means of the total running time prediction model, to obtain the left drum total running time and the right drum total running time.

[0132] Optionally, in the embodiment, the computer readable storage medium is configured to store program code for performing the following steps: obtaining a plurality of second training data sets comprising sample washing types, sample laundry weights, sample opening time intervals, sample ambient temperatures, and sample left drum initial temperatures and sample right drum initial temperatures, and corresponding sample left drum total running times and sample right drum total running times, before determining the left drum total running time of the left drum and the right drum total running time of the right drum according to the washing type, the laundry weight, the opening time interval, the ambient temperature, and the left drum initial temperature and the right drum initial temperature; and training the plurality of second training data sets by means of machine learning to obtain the total running time prediction model.

[0133] Optionally, in the embodiment, the computer readable storage medium is configured to store program code for performing the following steps: displaying the left drum total running time and / or the right drum total running time, after determining the left drum total running time of the left drum and the right drum total running time of the right drum according to the washing type, the laundry weight, the opening time interval, the ambient temperature, and the left drum initial temperature and the right drum initial temperature.

[0134] The above-mentioned serial numbers of the embodiments of the application are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0135] In the above-mentioned embodiments of the application, the description of each embodiment has its own emphasis, and the parts not described in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0136] In several embodiments provided in the present application, it should be understood that the disclosed technical contents can be implemented by other manners. Among them, the above-described device embodiments are only illustrative, for example, the division of the units can be a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units or modules shown or discussed can be indirect coupling or communication connection between the units or modules through some interfaces, and can be electrical or other forms.

[0137] The technical features of the above-described embodiments can be combined arbitrarily. In order to make the description simple, all possible combinations of the technical features in the above-described embodiments are not described, however, as long as the combination of the technical features does not exist contradictory, it should be considered as the scope of the present disclosure.

[0138] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or they can be distributed to multiple units. Part or all of the units can be selected according to actual needs to achieve the purpose of the present embodiment.

[0139] In addition, the functional units in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0140] The integrated unit, if realized in the form of a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a plurality of instructions to make a computer device (which can be a personal computer, a server or a network device, etc.) execute all or part of the steps of the method described in each embodiment of the present application. The foregoing storage medium includes: a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic disk or an optical disk, and various program code storage media.

[0141] The above merely describes the preferred embodiments of the present application, and it should be pointed out that, for those skilled in the art, several improvements and refinements can be made without departing from the principles of the present application, and these improvements and refinements should also be considered as falling within the protection scope of the present application.

Claims

1. A heating control method for a twin-tub washing machine, characterized in that, include: When it is detected that both the left and right tubs of the twin-tub washing machine are turned on, the washing type, the weight of the clothes, and the time interval between the opening of the left and right tubs are obtained. The washing type can determine the washing time and the heating temperature. The washing time can determine the washing duration of the left tub and the washing duration of the right tub. The heating temperature is used to determine the heating requirements of the left and right tubs. Obtain the ambient temperature of the room where the twin-tub washing machine is located; The initial temperature of the left tub and the initial temperature of the right tub are predicted based on the washing type, the weight of the clothes, the opening time interval, and the ambient temperature. The total running time of the left tub and the total running time of the right tub are determined based on the washing type, the weight of the clothes, the start-up time interval, the ambient temperature, the initial temperature of the left tub, and the initial temperature of the right tub. The left bucket is controlled to run for the total running time of the left bucket, and the right bucket is controlled to run for the total running time of the right bucket.

2. The heating control method for a twin-tub washing machine according to claim 1, characterized in that, Obtaining the weight of clothes in the twin-tub washing machine includes: After the twin-tub washing machine starts washing, a weighing operation is performed on the left and right tubs of the twin-tub washing machine to obtain the weight of the clothes in the twin-tub washing machine.

3. The heating control method for a twin-tub washing machine according to claim 1, characterized in that, Obtaining the opening time interval between the left and right tubs of the twin-tub washing machine includes: Determine the opening time of the left bucket and the opening time of the right bucket; The opening time interval is determined based on the opening time of the left bucket and the opening time of the right bucket.

4. The heating control method for a twin-tub washing machine according to claim 1, characterized in that, The initial temperatures of the left tub and the right tub are predicted based on the washing type, the weight of the laundry, the start-up time interval, and the ambient temperature, including: The washing type, the weight of the clothes, the start-up time interval, and the ambient temperature are input into the initial temperature prediction model. The initial temperature prediction model is then used to process the washing type, the weight of the clothes, the start-up time interval, and the ambient temperature to obtain the initial temperature of the left tub and the initial temperature of the right tub.

5. The heating control method for a twin-tub washing machine according to claim 4, characterized in that, Before inputting the washing type, the weight of the clothes, the start-up time interval, and the ambient temperature into the initial temperature prediction model, the method further includes: Acquire multiple sets of first training data, including sample washing type, sample clothing weight, sample opening time interval, sample ambient temperature, and the corresponding initial temperatures of the left and right buckets of the sample. The initial temperature prediction model is obtained by training the multiple sets of first training data using machine learning.

6. The heating control method for a twin-tub washing machine according to claim 1, characterized in that, The total operating time of the left tub and the total operating time of the right tub are determined based on the washing type, the weight of the clothes, the start-up time interval, the ambient temperature, and the initial temperatures of the left and right tubs, including: The washing type, the weight of the clothes, the start-up time interval, the ambient temperature, and the initial temperatures of the left and right tubs are input into the total running time prediction model. The total running time prediction model is then used to process the washing type, the weight of the clothes, the start-up time interval, the ambient temperature, and the initial temperatures of the left and right tubs to obtain the total running time of the left tub and the total running time of the right tub.

7. The heating control method for a twin-tub washing machine according to claim 6, characterized in that, Before determining the total operating time of the left tub and the total operating time of the right tub based on the washing type, the weight of the clothes, the start-up time interval, the ambient temperature, and the initial temperatures of the left and right tubs, the method further includes: Acquire multiple sets of second training data, including sample washing type, sample clothing weight, sample opening time interval, sample ambient temperature, sample initial temperature of the left and right tubs, and the corresponding total running time of the left and right tubs. The total running time prediction model is obtained by training the multiple sets of second training data using machine learning.

8. The heating control method for a twin-tub washing machine according to claim 1, characterized in that, After determining the total operating time of the left tub and the total operating time of the right tub based on the washing type, the weight of the clothes, the start-up time interval, the ambient temperature, and the initial temperatures of the left and right tubs, the process further includes: Display the total running time of the left bucket and / or the total running time of the right bucket.

9. A heating control device for a twin-tub washing machine, characterized in that, include: The first acquisition unit is used to acquire the washing type, the weight of the clothes, and the time interval between the opening of the left and right tubs of the twin-tub washing machine when it is detected that both the left and right tubs of the twin-tub washing machine are open. The washing type can determine the washing time and the heating temperature, the washing time can determine the washing duration of the left tub and the washing duration of the right tub, and the heating temperature is used to determine the heating requirements of the left and right tubs. The second acquisition unit is used to acquire the ambient temperature of the room where the twin-tub washing machine is located. The third acquisition unit is used to predict the initial temperature of the left tub and the initial temperature of the right tub based on the washing type, the weight of the clothes, the opening time interval and the ambient temperature. The determining unit is used to determine the total running time of the left tub and the total running time of the right tub based on the washing type, the weight of the clothes, the opening time interval, the ambient temperature, the initial temperature of the left tub, and the initial temperature of the right tub. The control unit is used to control the left bucket to run for the total running time of the left bucket, and to control the right bucket to run for the total running time of the right bucket.

10. A washing machine, characterized in that, The washing machine uses the heating control method of the twin-tub washing machine according to any one of claims 1 to 8.

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