Steaming oven control method and device, steaming oven and storage medium

Abstract

The invention relates to a steaming oven control method and device, a steaming oven and a storage medium. The method comprises the steps that filtering preprocessing is carried out on environment data and operation parameters collected by a steaming oven in a past period of time to reduce noise interference so as to improve data precision, and then a temperature prediction model is utilized to predict the temperature change trend in a future period of time, so that the accuracy of temperature prediction is improved. The operation parameters of the steaming oven are controlled in real time according to the temperature change trend, compared with a PID control algorithm with the slow response speed, the control speed and temperature control precision of the steaming oven are improved, and the problems that an existing steaming oven depends on the PID control algorithm for temperature control, the response speed is low, and the control precision is low are solved.

Description

Technical Field

[0001] The present application relates to the field of household appliance control technology, and in particular to a steam oven control method, device, steam oven and storage medium. Background Art

[0002] With the continuous advancement of modern home appliance technology, steam ovens, as a multifunctional kitchen appliance, are becoming more and more popular among consumers. Steam ovens can provide a more uniform heating effect by combining steam and baking functions. However, during use, the internal temperature of the steam oven varies greatly, and the accuracy of temperature control directly affects the cooking effect of food and user experience. At present, traditional temperature control methods mainly rely on simple PID control algorithms, which have problems such as slow response speed and low control accuracy when dealing with complex temperature changes. Summary of the invention

[0003] The present application provides a steam oven control method, device, steam oven and storage medium to solve the problems of slow response speed and low control accuracy in the existing steam oven which relies on PID control algorithm for temperature control.

[0004] In a first aspect, the present application provides a method for controlling a steam oven, the method comprising:

[0005] Obtaining environmental data and operating parameters of the steam oven in a first time period;

[0006] Performing filtering preprocessing on the environmental data to obtain filtered data;

[0007] Inputting the filtered data and the operating parameters of the steam oven in the first time period into a temperature prediction model, and determining the output of the temperature prediction model as a temperature change trend in a second time period, wherein the second time period is a future time period later than the first time period;

[0008] The operating parameters of the steam oven are controlled according to the temperature change trend.

[0009] Optionally, the filtering preprocessing the environmental data to obtain filtered data includes:

[0010] Performing average value filtering on the environmental data to obtain intermediate data;

[0011] Perform Kalman filtering on the intermediate data to obtain filtered data.

[0012] Optionally, controlling the operating parameters of the steam oven according to the temperature change trend includes:

[0013] The fan speed in the steam oven is controlled according to the temperature change trend, wherein the operating parameters of the steam oven include the fan speed.

[0014] Optionally, controlling the fan speed in the steam oven according to the temperature change trend includes:

[0015] When the temperature change trend indicates that the temperature change rate is greater than or equal to the first change rate, increasing the fan speed;

[0016] When the temperature change trend indicates that the temperature change rate is less than or equal to a second change rate, the fan speed is reduced, wherein the first change rate is greater than the second change rate.

[0017] Optionally, before obtaining the environmental data and operating parameters of the steam oven in the first time period, the method further includes:

[0018] Acquire historical cooking data, wherein the historical cooking data is data that has been pre-processed by filtering, and the historical cooking data includes historical environment data under multiple different cooking modes;

[0019] The preset neural network model is deeply trained using the historical cooking data to obtain the temperature prediction model.

[0020] Optionally, after controlling the operating parameters of the steam oven according to the temperature change trend, the method further includes:

[0021] Obtaining a predicted steaming and baking result corresponding to the temperature change trend and a detected steaming and baking result of the steam oven in the second time period;

[0022] According to the difference between the predicted steaming and baking result and the detected steaming and baking result, the model parameters of the temperature prediction model are adjusted.

[0023] Optionally, adjusting the model parameters of the temperature prediction model according to the difference between the predicted steaming and baking result and the detected steaming and baking result includes:

[0024] When at least one of the following situations occurs: the difference between the predicted environment data and the detected environment data is greater than or equal to the first difference, and the difference between the predicted steam-bake image and the detected steam-bake image is greater than or equal to the second difference, the model parameters of the temperature prediction model are adjusted according to the difference between the predicted environment data and the detected environment data and / or the difference between the predicted steam-bake image and the detected steam-bake image, wherein the predicted steam-bake result includes the predicted environment data and the predicted steam-bake image, and the detected steam-bake result includes the detected environment data and the detected steam-bake image.

[0025] In a second aspect, the present application provides a steam oven control device, the device comprising:

[0026] An acquisition module, used for acquiring environmental data and operating parameters of the steam oven in a first time period;

[0027] A preprocessing module, used for performing filtering preprocessing on the environmental data to obtain filtered data;

[0028] a processing module, configured to input the filtered data and the operating parameters of the steam oven in the first time period into a temperature prediction model, and determine the output of the temperature prediction model as a temperature change trend in a second time period, wherein the second time period is a future time period later than the first time period;

[0029] A control module is used to control the operating parameters of the steam oven according to the temperature change trend.

[0030] In a third aspect, the present application provides a steam oven, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned steam oven control method when executing the computer program.

[0031] In a fourth aspect, the present application further provides a computer storage medium storing computer executable instructions, wherein the computer executable instructions are used to execute the above-mentioned steam oven control method.

[0032] The above-mentioned technical scheme provided by the embodiment of the present application has the following advantages over the prior art: the method provided by the embodiment of the present application obtains the environmental data and operating parameters of the steam oven in a first time period; performs filtering preprocessing on the environmental data to obtain filtered data; inputs the filtered data and the operating parameters of the steam oven in the first time period into a temperature prediction model, and determines the output of the temperature prediction model as the temperature change trend in a second time period, wherein the second time period is a future time period later than the first time period; and controls the operating parameters of the steam oven according to the temperature change trend.

[0033] Based on the above method, the environmental data and operating parameters collected by the steam oven in the past period of time are filtered and preprocessed to reduce noise interference, thereby improving data accuracy. Then, the temperature prediction model is used to predict the temperature change trend in the future period of time. The operating parameters of the steam oven are controlled in real time according to the temperature change trend. Compared with the PID control algorithm with a slower response speed, the control speed and temperature control accuracy of the steam oven are improved, so as to solve the problems of slow response speed and low control accuracy of the existing steam oven that relies on the PID control algorithm for temperature control. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0035] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0036] One or more embodiments are exemplarily described by the images in the corresponding drawings, and these exemplified descriptions do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, and unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0037] Figure 1 A schematic flow chart of a steam oven control method provided in an embodiment of the present application;

[0038] Figure 2 A structural block diagram of a steam oven control device provided in an embodiment of the present application;

[0039] Figure 3 A schematic diagram of the internal structure of a steam oven provided in an embodiment of the present application. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0041] The disclosure below provides many different embodiments or examples to implement different structures of the present invention. In order to simplify the disclosure of the present invention, the parts and settings of specific examples are described below. Of course, they are only examples, and the purpose is not to limit the present invention. In addition, the present invention can repeat reference numbers and / or letters in different examples. This repetition is for the purpose of simplification and clarity, and does not itself indicate the relationship between the various embodiments and / or settings discussed.

[0042] In one embodiment, Figure 1 FIG. 1 is a flow chart of a method for controlling a steam oven in an embodiment, referring to FIG. Figure 1, a steam oven control method is provided. This embodiment mainly uses the method applied to a steam oven control device in a steam oven as an example for illustration, and the steam oven control method specifically includes the following steps:

[0043] Step S210, obtaining environmental data and operating parameters of the steam oven in a first time period.

[0044] Specifically, a high-precision temperature sensor, a humidity sensor, a fan and a steam oven control device are provided in the steam oven. The high-precision temperature sensor is used to collect the temperature inside the steam oven, and the humidity sensor is used to collect the humidity inside the steam oven. The high-precision temperature sensor is arranged at a key position in the steam oven to ensure the representativeness and accuracy of the temperature data. Therefore, the environmental data includes at least temperature and humidity. The first time period refers to the historical time period of the first preset time before the current moment. The operating parameters of the steam oven include fan speed and cooking mode. The cooking mode is used to correspond to different recipes. For example, the cooking mode corresponding to braised fish is different from the cooking mode corresponding to grilled steak. The steam oven can preset cooking modes corresponding to multiple different recipes locally, or the steam oven can obtain cooking modes corresponding to different recipes through a database. Furthermore, the steam oven can operate according to the cooking mode input by the user, and the cooking mode is composed of heating temperature, heating time and space humidity in different heating stages.

[0045] The steam oven obtains cooking modes corresponding to different recipes through a database. The cooking modes corresponding to the recipes in the database may be cooking modes provided by professional chefs, or cooking modes customized by users in different regions according to their own tastes. When obtaining the cooking mode corresponding to a specified recipe, the steam oven may obtain the cooking mode with the highest number of visits, or may obtain the top N cooking modes in order of the number of visits for the same recipe.

[0046] Step S220, performing filtering preprocessing on the environmental data to obtain filtered data.

[0047] Specifically, the steam oven control device first performs filtering preprocessing on the acquired environmental data to reduce noise interference in the environmental data and make the data smoother, thereby improving data accuracy to facilitate subsequent precise control of the steam oven. The filtered data is the environmental data that has been filtered preprocessing, and the filtered data also includes the temperature and humidity that have been filtered.

[0048] Step S230, inputting the filtered data and the operating parameters of the steam oven in the first time period into a temperature prediction model, and determining the output of the temperature prediction model as the temperature change trend in a second time period, wherein the second time period is a future time period later than the first time period.

[0049] Specifically, the filtering data and operating parameters are input as input parameters into the temperature prediction model. The temperature prediction model learns and outputs the corresponding temperature change trend based on the filtering data and the operating parameters. The temperature change trend can be specifically represented by a temperature curve or a string of temperature values. That is, the temperature change trend is used to indicate the temperature change in the second time period in the future. The second time period refers to the time period of the second preset time length after the current moment. The second time period is the future time period after the current moment.

[0050] Step S240: controlling the operating parameters of the steam oven according to the temperature change trend.

[0051] Specifically, the operating parameters of the steam oven are controlled in real time according to the predicted future temperature change trend of the steam oven to meet the expected effect corresponding to the temperature change trend. Compared with the PID control algorithm with a slower response speed, the control speed and temperature control accuracy of the steam oven are improved to solve the problems of slow response speed and low control accuracy of the existing steam oven that relies on the PID control algorithm for temperature control.

[0052] In one embodiment, the filtering preprocessing the environmental data to obtain filtered data includes:

[0053] Performing average value filtering on the environmental data to obtain intermediate data;

[0054] Perform Kalman filtering on the intermediate data to obtain filtered data.

[0055] Specifically, the moving average filtering algorithm is used to perform average filtering on the environmental data, and the moving average filtering algorithm smoothes the data by calculating the average value of the environmental data in the first time period to obtain intermediate data. The Kalman filtering algorithm is used to perform Kalman filtering on the intermediate data, and the Kalman filtering algorithm reduces noise through two steps of prediction and updating to obtain filtered data.

[0056] In one embodiment, controlling the operating parameters of the steam oven according to the temperature change trend includes:

[0057] The fan speed in the steam oven is controlled according to the temperature change trend, wherein the operating parameters of the steam oven include the fan speed.

[0058] Specifically, the fan speed in the steam oven is controlled according to the temperature change trend, and the temperature and humidity in the steam oven are changed by changing the fan speed to meet the expected steaming and baking effect corresponding to the temperature change trend. For example, the fan speed can be increased or decreased according to the temperature change direction of the temperature change trend to comply with the temperature change trend. If the temperature change trend is a temperature increase, the fan speed is decreased to maintain the temperature increase effect; if the temperature change trend is a temperature decrease, the fan speed is decreased to maintain the temperature decrease effect. Conversely, the fan speed can also be increased or decreased in the opposite direction of the temperature change trend to balance the temperature environment inside the steam oven. If the temperature change trend is an increase, the fan speed is increased to speed up the heat dissipation speed; if the temperature change trend is a temperature decrease, the fan speed is decreased to slow down the heat dissipation speed.

[0059] In one embodiment, controlling the fan speed in the steam oven according to the temperature change trend includes:

[0060] When the temperature change trend indicates that the temperature change rate is greater than or equal to the first change rate, increasing the fan speed;

[0061] When the temperature change trend indicates that the temperature change rate is less than or equal to a second change rate, the fan speed is reduced, wherein the first change rate is greater than the second change rate.

[0062] Specifically, the temperature change rate within the second time period is determined according to the temperature change trend. The first change rate is a preset change rate indicated by any positive number, and the second change rate is a preset change rate indicated by any negative number. If the temperature change rate is greater than or equal to the first change rate, it means that the temperature change trend corresponding to the temperature change rate is on an upward trend, and the temperature rises too fast. In order to maintain the stability of the internal temperature of the steam oven, the fan speed is increased to speed up the heat dissipation inside the steam oven.

[0063] If the temperature change trend is less than or equal to the second change rate, it means that the temperature change trend corresponding to the temperature change rate is decreasing and the temperature is dropping too fast. In order to maintain the stability of the internal temperature of the steam oven, the fan speed is reduced to slow down the heat dissipation speed inside the steam oven.

[0064] Among them, the fan speed adjustment method of increasing the fan speed and decreasing the fan speed includes: superimposing or reducing the current fan speed according to the preset step length, that is, increasing or reducing the fan operation gear by one gear, and the speed change of one gear corresponds to the preset step length, so as to achieve rapid adjustment of the fan speed. Alternatively, according to the change rate interval to which the difference between the actual temperature change rate and the first change rate or the second change rate belongs, the corresponding adjustment speed is determined; the adjustment speed is superimposed or reduced on the basis of the current fan speed to obtain the adjusted target fan speed; the fan operation is controlled according to the target fan speed, so as to achieve personalized adjustment of the fan speed in combination with different actual temperature change rates.

[0065] In one embodiment, before obtaining the environmental data and operating parameters of the steam oven in the first time period, the method further includes:

[0066] Acquire historical cooking data, wherein the historical cooking data is data that has been pre-processed by filtering, and the historical cooking data includes historical environment data under multiple different cooking modes;

[0067] The preset neural network model is deeply trained using the historical cooking data to obtain the temperature prediction model.

[0068] Specifically, the historical cooking data may be the historical operation data of multiple different steam ovens, including the historical environmental data of different steam ovens under different cooking modes. The historical environmental data includes the temperature, humidity, heating time, etc. of the steam ovens in different cooking modes in the past, and the historical cooking data is the data that has been filtered and preprocessed to ensure the reliability and accuracy of the data. The historical cooking data is used to perform deep learning training on the preset neural network model. The preset neural network model is any deep neural network model. The deep neural network model can use a structure suitable for time series prediction such as LSTM (long short-term memory network) to improve the prediction accuracy. The input of the deep neural network model is the historical cooking data, and the output is the temperature change trend within a certain period of time in the future. During the training process, the supervised learning method is used, and the actual temperature change data is used as the training label to optimize the model parameters so that it can accurately predict the temperature change trend. The training process can use the gradient descent algorithm to adjust the network weights through back propagation, so as to obtain a temperature prediction model that can output the future temperature change trend based on the cooking data.

[0069] In one embodiment, after controlling the operating parameters of the steam oven according to the temperature variation trend, the method further includes:

[0070] Obtaining a predicted steaming and baking result corresponding to the temperature change trend and a detected steaming and baking result of the steam oven in the second time period;

[0071] According to the difference between the predicted steaming and baking result and the detected steaming and baking result, the model parameters of the temperature prediction model are adjusted.

[0072] Specifically, the steam-baking oven control device can predict the temperature change trend in a future period of time based on the environmental data and operating parameters of the steam-baking oven in different time periods, and the temperature change trend also corresponds to a corresponding predicted steaming and baking result. The predicted steaming and baking result is used to indicate the steaming and baking effect that the steam-baking object in the steam-baking oven will present under the steaming and baking of the temperature change trend in the future time period, and the detected steaming and baking result is used to indicate the actual steaming and baking effect of the steam-baking oven in the second time period based on the temperature change trend. By comparing the predicted steaming and baking effect with the actual steaming and baking effect of the steam-baking oven in the second time period, it is determined whether the steaming and baking effect of the steam-baking oven meets the expected requirements, and then the model parameters of the temperature prediction model can be dynamically adjusted according to the difference between the predicted steaming and baking result and the detected steaming and baking result.

[0073] It can be understood that the steam oven cooks the steaming and baking object according to the temperature change trend output by the temperature prediction model. However, there is an error between the actual detected steaming and baking result and the predicted steaming and baking result, indicating that there is an error in the matching degree between the predicted temperature change trend and the corresponding predicted steaming and baking result. It is necessary to adjust the model parameters of the temperature prediction model to output a temperature change trend with a higher matching degree with the predicted steaming and baking result, so as to ensure the real-time and accuracy of the temperature control of the steam oven. The steam oven system is fully tested and optimized to ensure that the temperature control effect meets the expectations under different cooking modes and environmental conditions. Through feedback and actual usage, the control algorithm and model parameters are continuously optimized to improve the stability and reliability of the steam oven system.

[0074] Specifically, the control parameters and model structure of the temperature prediction model can be adjusted according to user feedback to meet the steaming and baking needs of different users.

[0075] In one embodiment, adjusting the model parameters of the temperature prediction model according to the difference between the predicted steaming and baking result and the detected steaming and baking result includes:

[0076] When at least one of the following situations occurs: the difference between the predicted environment data and the detected environment data is greater than or equal to the first difference, and the difference between the predicted steam-bake image and the detected steam-bake image is greater than or equal to the second difference, the model parameters of the temperature prediction model are adjusted according to the difference between the predicted environment data and the detected environment data and / or the difference between the predicted steam-bake image and the detected steam-bake image, wherein the predicted steam-bake result includes the predicted environment data and the predicted steam-bake image, and the detected steam-bake result includes the detected environment data and the detected steam-bake image.

[0077] Specifically, the predicted steaming and baking result includes the predicted environmental data and the predicted steaming and baking image, and the detected steaming and baking result includes the detected environmental data and the detected steaming and baking image. The predicted environmental data is compared with the actual detected environmental data to determine whether the environmental data controlled based on the temperature change trend is consistent with the predicted environmental data. If the difference between the predicted environmental data and the detected environmental data is greater than or equal to the first difference, it means that the environmental data controlled based on the temperature change trend is inconsistent with the predicted environmental data. Then, it is necessary to use the difference between the predicted environmental data and the detected environmental data to adjust the model parameters of the temperature prediction model, so that the temperature change trend output by the temperature prediction model subsequently controls the detected steaming and baking result after the steam oven is operated to be consistent with the predicted steaming and baking result, that is, to improve the accuracy of the output content of the temperature prediction model.

[0078] The predicted steaming and baking image is compared with the actual detected steaming and baking image to determine whether the steaming and baking effect of the steaming and baking object after being controlled based on the temperature change trend is consistent with the predicted steaming and baking effect. If the difference between the predicted steaming and baking image and the detected steaming and baking image is greater than or equal to the second difference, it means that the steaming and baking effect of the steaming and baking object after being controlled based on the temperature change trend is inconsistent with the predicted steaming and baking effect. Then, the model parameters of the temperature prediction model are adjusted using the difference between the predicted steaming and baking image and the detected steaming and baking image. That is, a camera for collecting steaming and baking images is also provided in the steaming and baking oven, and the steaming and baking oven control device also has an image recognition function. The steaming and baking images at different steaming and baking stages can be used to reflect the steaming and baking effects of the steaming and baking object at different steaming and baking stages. For example, when grilling steaks at different steaming and baking stages, the color changes of the steaks can be identified by identifying the steaming and baking images, so as to determine whether the steaming and baking effects meet the expected effects.

[0079] In actual use, the current temperature data and related parameters are input into the trained deep neural network model in real time to predict the future temperature change trend. The temperature prediction results will be used as the basis for fan control. According to the predicted temperature change trend, the fan speed is dynamically adjusted to achieve more accurate temperature control. Specifically, the fan speed can be adjusted according to the predicted temperature change rate and trend using a fuzzy control algorithm or an adaptive control algorithm. For example, when the predicted temperature rises too fast, the fan speed can be appropriately increased to speed up the heat dissipation; when the predicted temperature drops too fast, the fan speed can be reduced to slow down the heat dissipation and keep the temperature inside the steam oven stable. The dynamic adjustment of the fan should take into account the cooking mode and the temperature set by the user to ensure the heat dissipation effect.

[0080] The data collected by the temperature sensor is preprocessed through a digital filtering algorithm to reduce noise interference, make the temperature data smoother and more reliable, effectively improve the accuracy of the temperature data, and avoid control errors caused by noise. A deep neural network model is designed and trained to use a large amount of historical temperature data and related environmental parameters of the steam oven to predict the temperature change trend in the future. In this way, temperature changes can be predicted in advance, so that temperature control can be performed more accurately. According to the temperature change trend predicted by the deep neural network, the speed of the fan in the steam oven is dynamically adjusted. In order to more efficiently control the internal temperature of the steam oven and improve the cooking effect, it can significantly improve the temperature control accuracy and response speed of the steam oven, improve the cooking effect and user experience, and has broad application prospects and market value.

[0081] Figure 1 FIG. 1 is a flow chart of a method for controlling a steam oven in one embodiment. It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0082] In one embodiment, Figure 2 As shown, a steam oven control device is provided, comprising:

[0083] An acquisition module 310 is used to acquire environmental data and operating parameters of the steam oven in a first time period;

[0084] A preprocessing module 320 is used to perform filtering preprocessing on the environmental data to obtain filtered data;

[0085] A processing module 330 is used to input the filtered data and the operating parameters of the steam oven in the first time period into a temperature prediction model, and determine the output of the temperature prediction model as a temperature change trend in a second time period, wherein the second time period is a future time period later than the first time period;

[0086] The control module 340 is used to control the operating parameters of the steam oven according to the temperature change trend.

[0087] In one embodiment, the preprocessing module 320 is further configured to:

[0088] Performing average value filtering on the environmental data to obtain intermediate data;

[0089] Perform Kalman filtering on the intermediate data to obtain filtered data.

[0090] In one embodiment, the control module 340 is further configured to:

[0091] The fan speed in the steam oven is controlled according to the temperature change trend, wherein the operating parameters of the steam oven include the fan speed.

[0092] In one embodiment, the control module 340 is further configured to:

[0093] When the temperature change trend indicates that the temperature change rate is greater than or equal to the first change rate, increasing the fan speed;

[0094] When the temperature change trend indicates that the temperature change rate is less than or equal to a second change rate, the fan speed is reduced, wherein the first change rate is greater than the second change rate.

[0095] In one embodiment, the processing module 330 is further configured to:

[0096] Acquire historical cooking data, wherein the historical cooking data is data that has been pre-processed by filtering, and the historical cooking data includes historical environment data under multiple different cooking modes;

[0097] The preset neural network model is deeply trained using the historical cooking data to obtain the temperature prediction model.

[0098] In one embodiment, the processing module 330 is further configured to:

[0099] Obtaining a predicted steaming and baking result corresponding to the temperature change trend and a detected steaming and baking result of the steam oven in the second time period;

[0100] According to the difference between the predicted steaming and baking result and the detected steaming and baking result, the model parameters of the temperature prediction model are adjusted.

[0101] In one embodiment, the processing module 330 is further configured to:

[0102] When at least one of the following situations occurs: the difference between the predicted environment data and the detected environment data is greater than or equal to the first difference, and the difference between the predicted steam-bake image and the detected steam-bake image is greater than or equal to the second difference, the model parameters of the temperature prediction model are adjusted according to the difference between the predicted environment data and the detected environment data and / or the difference between the predicted steam-bake image and the detected steam-bake image, wherein the predicted steam-bake result includes the predicted environment data and the predicted steam-bake image, and the detected steam-bake result includes the detected environment data and the detected steam-bake image.

[0103] like Figure 3 As shown, the embodiment of the present application provides a steam oven, including a processor 711, a communication interface 712, a memory 713 and a communication bus 714, wherein the processor 711, the communication interface 712, and the memory 713 communicate with each other through the communication bus 714;

[0104] Memory 713, used for storing computer programs;

[0105] The processor 711 is used to implement the steam oven control method provided by any one of the aforementioned method embodiments when executing the program stored in the memory 713.

[0106] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the present application scheme, and does not constitute a limitation on the steam oven to which the present application scheme is applied. The specific steam oven may include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0107] In one embodiment, the steam oven control device provided in the present application can be implemented in the form of a computer program. The computer program can be Figure 3 The memory of the steam oven can store various program modules constituting the steam oven control device, for example, Figure 2 The acquisition module 310, pre-processing module 320, processing module 330 and control module 340 are shown. The computer program composed of various program modules enables the processor to execute the steam oven control method of each embodiment of the present application described in this specification.

[0108] Figure 3 The steam oven shown can be Figure 2The acquisition module 310 in the steam oven control device shown acquires the environmental data and operating parameters of the steam oven in the first time period. The steam oven can perform filtering preprocessing on the environmental data through the preprocessing module 320 to obtain filtered data. The steam oven can input the filtered data and the operating parameters of the steam oven in the first time period into the temperature prediction model through the processing module 330, and determine the output of the temperature prediction model as the temperature change trend in the second time period, wherein the second time period is a future time period later than the first time period. The steam oven can control the operating parameters of the steam oven according to the temperature change trend through the control module 340.

[0109] An embodiment of the present application further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steam oven control method provided in any of the aforementioned method embodiments is implemented.

[0110] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0111] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a general hardware platform, or of course by hardware. Based on this understanding, the above technical solution, in essence or in other words, the part that contributes to the relevant technology, can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a steam oven (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0112] It should be understood that the terms used herein are only for the purpose of describing specific example embodiments and are not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms "one", "an" and "said" as used herein may also be meant to include plural forms. The terms "include", "comprise", "contain", and "have" are inclusive, and therefore specify the existence of stated features, steps, operations, elements and / or parts, but do not exclude the existence or addition of one or more other features, steps, operations, elements, parts, and / or combinations thereof. The method steps, processes, and operations described herein are not interpreted as necessarily requiring them to be performed in the specific order described or illustrated, unless the execution order is clearly indicated. It should also be understood that additional or alternative can be used.

[0113] The foregoing is merely a specific embodiment of the present invention, which enables those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A steam oven control method, It is characterized in that The method comprises: Obtaining environmental data and operating parameters of the steam oven in a first time period; Performing filtering preprocessing on the environmental data to obtain filtered data; Inputting the filtered data and the operating parameters of the steam oven in the first time period into a temperature prediction model, and determining the output of the temperature prediction model as a temperature change trend in a second time period, wherein the second time period is a future time period later than the first time period; The operating parameters of the steam oven are controlled according to the temperature change trend.

2. The method according to claim 1, It is characterized in that The filtering preprocessing of the environmental data to obtain filtered data includes: Performing average value filtering on the environmental data to obtain intermediate data; Perform Kalman filtering on the intermediate data to obtain filtered data.

3. The method according to claim 1, It is characterized in that The controlling the operating parameters of the steam oven according to the temperature change trend includes: The fan speed in the steam oven is controlled according to the temperature change trend, wherein the operating parameters of the steam oven include the fan speed.

4. The method according to claim 3, It is characterized in that The controlling the fan speed in the steam oven according to the temperature change trend comprises: When the temperature change trend indicates that the temperature change rate is greater than or equal to the first change rate, increasing the fan speed; When the temperature change trend indicates that the temperature change rate is less than or equal to a second change rate, the fan speed is reduced, wherein the first change rate is greater than the second change rate.

5. The method according to claim 1, It is characterized in that Before obtaining the environmental data and operating parameters of the steam oven in the first time period, the method further includes: Acquire historical cooking data, wherein the historical cooking data is data that has been pre-processed by filtering, and the historical cooking data includes historical environment data under multiple different cooking modes; The preset neural network model is deeply trained using the historical cooking data to obtain the temperature prediction model.

6. The method according to claim 1, It is characterized in that After controlling the operating parameters of the steam oven according to the temperature change trend, the method further includes: Obtaining a predicted steaming and baking result corresponding to the temperature change trend and a detected steaming and baking result of the steam oven in the second time period; According to the difference between the predicted steaming and baking result and the detected steaming and baking result, the model parameters of the temperature prediction model are adjusted.

7. The method according to claim 6, It is characterized in that According to the difference between the predicted steaming and baking result and the detected steaming and baking result, adjusting the model parameters of the temperature prediction model includes: When at least one of the following situations occurs: the difference between the predicted environment data and the detected environment data is greater than or equal to the first difference, and the difference between the predicted steam-bake image and the detected steam-bake image is greater than or equal to the second difference, the model parameters of the temperature prediction model are adjusted according to the difference between the predicted environment data and the detected environment data and / or the difference between the predicted steam-bake image and the detected steam-bake image, wherein the predicted steam-bake result includes the predicted environment data and the predicted steam-bake image, and the detected steam-bake result includes the detected environment data and the detected steam-bake image.

8. A steam oven control device, It is characterized in that The device comprises: An acquisition module, used for acquiring environmental data and operating parameters of the steam oven in a first time period; A preprocessing module, used for performing filtering preprocessing on the environmental data to obtain filtered data; a processing module, configured to input the filtered data and the operating parameters of the steam oven in the first time period into a temperature prediction model, and determine the output of the temperature prediction model as a temperature change trend in a second time period, wherein the second time period is a future time period later than the first time period; A control module is used to control the operating parameters of the steam oven according to the temperature change trend.

9. A steam oven, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, It is characterized in that When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, It is characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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