Self-learning method of food processor
By introducing self-learning methods in the food processor to record and analyze user usage parameters and fault information, the problem of poor user experience in the prior art is solved, and the convenience and convenience of the machine are improved.
Patent Information
- Application Number
- CN202310817193.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-07-04
- Publication Date
- 2025-01-07
AI Technical Summary
Existing food processing machines such as wall breakers cannot learn user preferences and machine failure parameters, resulting in poor user experience.
By introducing a self-learning method in the food processor, using the main control module, storage module and fault alarm module, repeatedly obtaining usage parameters and analyzing them, recording user habitual parameters and equipment fault parameters, and feedback to users in real time to improve user experience.
It realizes parameter memory and fault analysis, improves user experience, simplifies the use process, and enhances the convenience of the food processor.
Smart Images
Figure CN119257455A_ABST
Abstract
Description
Technical Field
[0001] The invention relates to the field of food processing, and in particular to a self-learning method for a food processing machine. Background Art
[0002] In recent years, as people's living standards have improved, their requirements for food processors have also increased.
[0003] However, in the food processing machines such as blenders currently on the market, the electronic control system does not memorize or self-learn the user's various usage parameters (such as function, capacity, reservation time, speed gear, etc.) and various machine fault alarm parameters, and is unable to know the user's usage preferences. As a result, users need to spend a lot of time selecting their favorite parameters every time they turn on the machine, and there are no prompts during use, resulting in a poor user experience. At the same time, users are unable to know the specific reasons and improvement measures when the machine alarms, further resulting in a poor user experience.
[0004] Therefore, food processing machines such as blenders are unable to learn user preferences and machine fault parameters, resulting in poor user experience, which has become a technical problem that needs to be solved urgently. Summary of the invention
[0005] The present application provides a self-learning method for a food processing machine to solve the technical problem in the prior art that food processing machines such as blenders cannot learn user usage preferences and machine fault parameters, resulting in a poor user experience.
[0006] The present application provides a self-learning method for a food processing machine, wherein the food processing machine comprises a machine body, a grinding cup and a cup cover installed on the machine body, wherein the machine body comprises a main control module, a storage module and a fault alarm module connected to each other; the self-learning method comprises: repeatedly acquiring the usage parameters of the food processing machine in a working state; storing the usage parameters of the food processing machine in a working state in the storage module; analyzing the usage parameters of the food processing machine in a working state to obtain the habit parameters and equipment fault parameters of the food processing machine; and controlling the main control module to call the food processing machine according to the habit parameters and equipment fault parameters.
[0007] As an optional embodiment, the food processing machine also includes an electric temperature sensor, and the equipment fault parameters include an electric temperature control alarm temperature value; the repeated acquisition of the usage parameters of the food processing machine under the working state includes: controlling the electric temperature sensor to obtain the electric temperature value when the fault alarm module outputs an electric temperature control alarm signal.
[0008] As an optional implementation, the controlling the main control module to call the food processing machine according to the habit parameters and the equipment fault parameters includes: determining whether the electric heating temperature value is higher than the electric heating temperature control alarm temperature value; if the electric heating temperature value is higher than the electric heating temperature control alarm temperature value, controlling the main control module to output a signal for reminding the user to clean the cooking materials.
[0009] As an optional implementation, the equipment fault parameter includes a material overflow alarm voltage value; and the repeatedly obtaining the usage parameters of the food processor in the working state includes: obtaining the current voltage when the fault alarm module outputs a material overflow alarm signal.
[0010] As an optional embodiment, the food processor also includes an anti-overflow electrode for detecting the material overflow status, and the controlling the main control module to call the food processor according to the custom parameters and equipment fault parameters includes: comparing the current voltage with the material overflow alarm voltage value; if the current voltage is greater than the material overflow alarm voltage value, obtaining the current working state of the food processor; if the current working state is after the drainage stage, controlling the main control module to output a signal for reminding the user to further drain the remaining water; if the current working state is before the drainage stage, controlling the main control module to output a signal for reminding the user to clean the anti-overflow electrode.
[0011] As an optional implementation, the equipment fault parameter includes a cup lid switch signal value; the repeatedly obtaining the usage parameters of the food processor in the working state includes: obtaining the cup lid switch signal value when the fault alarm module outputs a lid opening alarm signal.
[0012] As an optional implementation, the controlling the main control module to call the food processing machine according to the habit parameters and the equipment fault parameters includes: determining whether the cup cover switch signal value is abnormal; if the cup cover switch signal value is abnormal, controlling the main control module to output a signal for reminding the user to tighten the cup cover.
[0013] As an optional implementation, the habit parameters include habit function parameters, and controlling the main control module to call the food processing machine according to the habit parameters and equipment fault parameters includes: controlling the main control module to obtain a signal from a user selecting a function; and controlling the main control module to select a system function corresponding to the habit function parameters.
[0014] As an optional implementation, the customary parameters include customary capacity parameters, and the controlling the main control module to call the food processing machine according to the customary parameters and equipment fault parameters includes: obtaining the current system function; and controlling the main control module to select the customary capacity parameters corresponding to the current system function.
[0015] As an optional implementation, the habit parameters include reservation duration habit parameters, and controlling the main control module to call the food processor according to the habit parameters and equipment fault parameters includes: controlling the main control module to obtain a signal from a user making a reservation for cooking; and controlling the main control module to select the reservation duration habit parameters.
[0016] Due to the adoption of the above technical solution, the technical effects achieved by this application are:
[0017] In the present application, the self-learning method includes storing the usage parameters of the food processor in the working state into the storage module, analyzing the usage parameters of the food processor in the working state, obtaining the habit parameters and equipment fault parameters of the food processor; and controlling the main control module to call the food processor according to the habit parameters and equipment fault parameters. That is, it includes three steps: parameter memory, parameter analysis and learning, and user feedback. The function of parameter memory is to record various parameters of the user, store them locally or in the cloud, and by analyzing and learning the user's usage parameters, it is possible to obtain various usage habits of the user, and provide real-time feedback to the user when the user uses the food processor to improve the user experience; by analyzing and learning the user's alarm parameters, it is possible to analyze the cause of the alarm, and provide real-time feedback to the user to improve the user experience. It solves the technical problem that food processors such as wall breaking machines in the prior art cannot learn the user's usage preferences and machine fault parameters, resulting in poor user experience, and improves the convenience of using the food processor. BRIEF DESCRIPTION OF THE DRAWINGS
[0018] 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.
[0019] 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.
[0020] Figure 1 It is a flow chart of a self-learning method for a food processing machine provided according to an embodiment of the present application. DETAILED DESCRIPTION
[0021] In order to enable those skilled in the art to better understand the solution of the present application, 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 only 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 creative work should fall within the scope of protection of the present application.
[0022] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.
[0023] Referring to the background technology, in the food processing machines such as blenders currently on the market, the electronic control system does not memorize or self-learn the user's various usage parameters (such as function, capacity, reservation time, speed gear, etc.) and various machine fault alarm parameters, and is unable to know the user's usage preferences. As a result, users need to spend a lot of time selecting their favorite parameters every time they turn on the machine, and there are no prompts during use, resulting in a poor user experience. At the same time, users cannot know the specific reasons and improvement measures when the machine alarms, further resulting in a poor user experience.
[0024] Based on this, Figure 1 As shown, the present application provides a self-learning method for a food processing machine, the food processing machine comprising a machine body, a grinding cup and a cup cover installed on the machine body, the machine body comprising a main control module, a storage module and a fault alarm module connected to each other; the self-learning method comprises:
[0025] S1 repeatedly obtains the usage parameters of the food processing machine in a working state;
[0026] S2: storing the usage parameters of the food processor in the working state into the storage module;
[0027] S3 analyzes the usage parameters of the food processing machine in the working state to obtain the customary parameters and equipment failure parameters of the food processing machine;
[0028] S4 controls the main control module to call the food processing machine according to the custom parameters and equipment fault parameters.
[0029] Specifically, the parameters selected by the user are recorded when the user uses the food processor, and the working status of the food processor is recorded when the food processor fails; and multiple acquisitions are performed, that is, the use parameters of the food processor are recorded multiple times, and multiple sets of use parameters are saved to the storage module, so that the use parameters of the food processor in the working state can be analyzed, and then the main control module is controlled to call the food processor according to the habit parameters and equipment failure parameters. The self-learning method includes storing the use parameters of the food processor in the working state in the storage module, that is: the food processor memorizes the user's use parameters and equipment failure parameters, and analyzes and learns the obtained parameters, so as to obtain various types of user habits and analyze the cause of the alarm; and then feedback is given to the user based on the analysis and learning results to improve the user experience. It solves the technical problem that food processors such as wall breaking machines in the prior art cannot learn user usage preferences and machine failure parameters, resulting in poor user experience.
[0030] It should be understood that the present application does not limit the specific number of times the usage parameters of the food processor in working condition are repeatedly obtained, but the number of usage parameters obtained must be able to meet the requirements of analyzing the usage parameters and deriving habitual parameters and equipment fault parameters, for example, each usage parameter is obtained 30 times or more.
[0031] Moreover, exemplary, after repeatedly acquiring a sufficient number of usage parameters, the usage parameters of the food processor in the working state can be continuously acquired, and the acquired usage parameters can be continuously memorized, analyzed and learned to obtain the habit parameters and equipment fault parameters of the food processor, so that when the user changes the habit parameters, the food processor can timely acquire the user's changed habit parameters, and control the main control module to call the food processor according to the user's new habit parameters. This further improves the convenience of using the food processor and improves the user experience.
[0032] In addition, the present application does not limit the specific types of the custom parameters and the equipment fault parameters obtained by the food processing machine through analysis and learning of the use parameters. To analyze and obtain the custom parameters, the function selection, capacity selection, reservation time selection, start time, gear selection, switch time and other use parameters of the food processing machine can be obtained for memory and analysis; to analyze and obtain the custom parameters, the electric heating temperature value can be obtained when the food processing machine has an electric heating temperature control alarm, the current voltage can be obtained when the material overflow alarm occurs, the cup cover switch signal value can be obtained when the cover is opened, the current mains voltage value can be obtained when the high and low voltage alarm occurs, the number of data packet loss can be obtained when the communication abnormality alarm occurs, the motor temperature control temperature and current value can be obtained when the motor temperature control alarm occurs, the residual water box detection voltage value can be obtained when the residual water box overflows, and the current step can be recorded; when the pulp cup alarm occurs, the pulp cup detection voltage value can be obtained and the current step can be recorded; when the water tank is short of water, the current step can be obtained; when the rotary valve abnormality alarm occurs, the rotary valve position information can be obtained, etc. The following embodiments are specific self-learning methods according to different custom parameters and equipment fault parameters.
[0033] As an optional embodiment, the food processing machine also includes an electric temperature sensor, and the equipment fault parameters include an electric temperature control alarm temperature value; the repeated acquisition of the usage parameters of the food processing machine under the working state includes: controlling the electric temperature sensor to obtain the electric temperature value when the fault alarm module outputs an electric temperature control alarm signal.
[0034] As an optional implementation, the controlling the main control module to call the food processing machine according to the habit parameters and the equipment fault parameters includes: determining whether the electric heating temperature value is higher than the electric heating temperature control alarm temperature value; if the electric heating temperature value is higher than the electric heating temperature control alarm temperature value, controlling the main control module to output a signal for reminding the user to clean the cooking materials.
[0035] Specifically, first, when an electric heating temperature control alarm occurs in a food processing machine, electric heating temperature values are obtained multiple times, and multiple electric heating temperature values and the current state of the food processing machine when the alarm occurs are analyzed and learned to obtain the electric heating temperature control alarm temperature value; and the electric heating temperature control alarm temperature value is stored in a storage module. When an electric heating temperature control alarm occurs in the food processing machine again, it is determined whether the electric heating temperature value is higher than the electric heating temperature control alarm temperature value; if the electric heating temperature value is higher than the electric heating temperature control alarm temperature value, it means that the current step is in a fast heating stage, and it is believed that the material has a burnt bottom and the heat is not easy to dissipate, causing the thermostat to alarm. At this time, the user is reminded to clean the material, place normal materials according to the recipe, and start the production again.
[0036] As an optional implementation, the equipment fault parameter includes a material overflow alarm voltage value; and the repeatedly obtaining the usage parameters of the food processor in the working state includes: obtaining the current voltage when the fault alarm module outputs a material overflow alarm signal.
[0037] As an optional embodiment, the food processor also includes an anti-overflow electrode for detecting the material overflow status, and the controlling the main control module to call the food processor according to the custom parameters and equipment fault parameters includes: comparing the current voltage with the material overflow alarm voltage value; if the current voltage is greater than the material overflow alarm voltage value, obtaining the current working state of the food processor; if the current working state is after the drainage stage, controlling the main control module to output a signal for reminding the user to further drain the remaining water; if the current working state is before the drainage stage, controlling the main control module to output a signal for reminding the user to clean the anti-overflow electrode.
[0038] Specifically, first, when a material overflow alarm occurs in the food processing machine, the current voltage is obtained multiple times, and the multiple current voltage values and the current state of the food processing machine when the alarm occurs are analyzed and learned to obtain the material overflow alarm voltage value; and the material overflow alarm voltage value is stored in the storage module, and when a material overflow alarm occurs in the food processing machine again, the current voltage is compared with the material overflow alarm voltage value; if the current voltage is greater than the material overflow alarm voltage value, and the current working state is after the drainage stage, then it means that the cause of the alarm may be that the user has not drained the water in the mixing cup, and the main control module is controlled to output a signal for reminding the user to further drain the remaining water; if the current working state is before the drainage stage, then it means that the cause of the alarm may be that the anti-overflow electrode is dirty, and the main control module is controlled to output a signal for reminding the user to clean the anti-overflow electrode.
[0039] As an optional implementation, the equipment fault parameter includes a cup lid switch signal value; the repeatedly obtaining the usage parameters of the food processor in the working state includes: obtaining the cup lid switch signal value when the fault alarm module outputs a lid opening alarm signal.
[0040] As an optional implementation, the controlling the main control module to call the food processing machine according to the habit parameters and the equipment fault parameters includes: determining whether the cup cover switch signal value is abnormal; if the cup cover switch signal value is abnormal, controlling the main control module to output a signal for reminding the user to tighten the cup cover.
[0041] Specifically, first, when a lid opening alarm occurs in the food processing machine, the cup lid switch signal value is obtained multiple times, and it is determined whether the cup lid switch signal value is abnormal; if the cup lid switch signal value is abnormal, it means that the cup lid is in an open state, and the main control module is controlled to output a signal to remind the user to tighten the cup lid.
[0042] In addition, if high or low voltage alarms occur during the use of the food processor, the food processor can record the voltage values in real time and learn the voltage trend. When the voltage trend is voltage fluctuation, the user can be informed of unstable voltage without any operation. Food processing will be automatically resumed after the voltage stabilizes. When the voltage trend does not change, the user is prompted to try again after powering off. If a motor temperature control alarm occurs during use, the data of the motor temperature sensor and the current working step are obtained and analyzed. If the temperature of the temperature sensor is higher than the preset temperature and the current step is in the high-speed crushing stage, it is considered that the material is too thick, causing the thermostat to operate. At this time, the user is prompted to place normal materials according to the recipe and prepare again; if the temperature of the temperature sensor is higher than the preset temperature value and the current step is in the boiling stage, it means that hard ingredients are stuck in the crushing blade. At this time, the user is prompted to clean the ingredients and do not place hard ingredients; during use, a residual water box alarm may also occur, then the residual water box sensor voltage value, the current working menu and working steps are obtained and analyzed, if the alarm occurs during the preparation of ingredients, it means that the user has not dumped the residual water box, the user is prompted to dump the residual water box and continue food processing; during use, if a slurry cup alarm occurs, the slurry cup sensor voltage value can be obtained and analyzed, and the user is prompted to place the slurry cup correctly; if a water tank water shortage alarm occurs, the system obtains and analyzes the current water tank liquid level and working steps. If the water tank liquid level matches the working steps, it means that the water tank placement problem prevents water from entering the pipeline, and the user is prompted to place the water tank correctly; if the water tank liquid level does not match the working steps, it means that the water tank is short of water, and the user is prompted to add water to the water tank before the work can continue. During use, if a rotary valve alarm occurs, the trajectory of the rotary valve Hall sensor information during the rotation of the rotary valve is obtained and analyzed. If there is a movement trajectory but it does not reach the target position, it means that the material may be stuck. The voice prompts the user to check whether the rotary valve port is blocked by material, which can be cleaned by themselves. If there is no movement trajectory, it means that the rotary valve has a hardware failure, and the user is prompted to send it to after-sales repair.
[0043] As an optional implementation, the habit parameters include habit function parameters, and controlling the main control module to call the food processing machine according to the habit parameters and equipment fault parameters includes: controlling the main control module to obtain a signal from a user selecting a function; and controlling the main control module to select a system function corresponding to the habit function parameters.
[0044] Specifically, first, the functions selected by the user can be repeatedly obtained, and analyzed and learned to form habitual function parameters; then when the user selects a function, the system function corresponding to the habitual function parameters can be directly selected. Among them, the signal of the user selecting a function can be obtained by repeatedly obtaining the user's cooking time in advance, and forming a habitual cooking time parameter, and automatically turning on the food processor at the cooking time corresponding to the habitual cooking time parameter, and selecting the function according to the habitual function parameters; or the system function corresponding to the habitual function parameters can be directly selected when the user manually turns on the food processor.
[0045] As an optional implementation, the customary parameters include customary capacity parameters, and the controlling the main control module to call the food processing machine according to the customary parameters and equipment fault parameters includes: obtaining the current system function; and controlling the main control module to select the customary capacity parameters corresponding to the current system function.
[0046] Specifically, first, the capacity selected by the user for each function can be repeatedly obtained, and analyzed and learned to form habitual capacity parameters; then when the user selects capacity, the main control module can be controlled to obtain the habitual capacity parameters corresponding to the function selected by the user, and select the capacity corresponding to the habitual capacity parameters.
[0047] As an optional implementation, the habit parameters include reservation duration habit parameters, and controlling the main control module to call the food processor according to the habit parameters and equipment fault parameters includes: controlling the main control module to obtain a signal from a user making a reservation for cooking; and controlling the main control module to select the reservation duration habit parameters.
[0048] Specifically, first, the reservation duration selected by the user can be repeatedly obtained, and the reservation duration can include different reservation durations under different functions, different capacities, etc., and multiple acquired data of the reservation duration can be analyzed and studied to form a reservation duration habit parameter; then when the user needs to make a reservation, the main control module can be controlled to directly select the reservation duration corresponding to the reservation duration habit parameter.
[0049] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.
[0050] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.
[0051] In several embodiments provided in the present application, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. There may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. The units described as separate components may or may not be physically separated, and the components displayed 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 units may be selected according to actual needs to achieve the purpose of the solution provided in this embodiment.
[0052] So far, the technical solution of the present application has been described in combination with the above multiple embodiments, but it is easy for those skilled in the art to understand that the protection scope of the present application is not limited to these specific embodiments. Without departing from the technical principles of the present application, those skilled in the art can split and combine the technical solutions in the above-mentioned various embodiments, and can also make equivalent changes or replacements to the relevant technical features. Any changes, equivalent replacements, improvements, etc. made within the technical concept and / or technical principles of the present application will fall within the protection scope of the present application.
[0053] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.
[0054] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.
Claims
1. A self-learning method for a food processing machine, characterized in that: The food processor comprises a body, a grinding cup and a cup cover installed on the body, the body comprises a main control module, a storage module and a fault alarm module connected to each other; the self-learning method comprises: Repeatedly obtaining the usage parameters of the food processing machine in a working state; storing the usage parameters of the food processing machine in the working state in the storage module; Analyzing the usage parameters of the food processing machine in the working state to obtain the customary parameters and equipment failure parameters of the food processing machine; The main control module is controlled to call the food processing machine according to the custom parameters and equipment fault parameters.
2. The self-learning method for a food processing machine according to claim 1, characterized in that: The food processing machine further comprises an electric heating temperature sensor, and the equipment fault parameter comprises an electric heating temperature control alarm temperature value; The repeatedly obtaining the usage parameters of the food processor in the working state comprises: When the fault alarm module outputs an electric heating temperature control alarm signal, the electric heating temperature sensor is controlled to obtain an electric heating temperature value.
3. The self-learning method for a food processing machine according to claim 2, characterized in that: The controlling the main control module to call the food processing machine according to the habit parameters and the equipment fault parameters comprises: Determine whether the electric heating temperature value is higher than the electric heating temperature control alarm temperature value; If the electric heating temperature value is higher than the electric heating temperature control alarm temperature value, the main control module is controlled to output a signal for reminding the user to clean the cooking materials.
4. The self-learning method for a food processing machine according to claim 1, characterized in that: The equipment failure parameters include a material overflow alarm voltage value; The repeatedly obtaining the usage parameters of the food processor in the working state comprises: The current voltage is obtained when the fault alarm module outputs a material overflow alarm signal.
5. The self-learning method for a food processing machine according to claim 4, characterized in that: The food processing machine further includes an anti-overflow electrode for detecting a material overflow state, and the controlling the main control module to call the food processing machine according to the habit parameters and the equipment fault parameters includes: Comparing the current voltage with the material overflow alarm voltage value; If the current voltage is greater than the material overflow alarm voltage value, obtaining the current working state of the food processing machine; If the current working state is after the drainage stage is finished, the main control module is controlled to output a signal for reminding the user to further drain the remaining water; If the current working state is before the drainage stage, the main control module is controlled to output a signal for reminding the user to clean the anti-overflow electrode.
6. The self-learning method for a food processing machine according to claim 1, characterized in that: The equipment fault parameter includes a cup cover switch signal value; The repeatedly obtaining the usage parameters of the food processor in the working state comprises: The cup cover switch signal value is obtained when the fault alarm module outputs a cover opening alarm signal.
7. The self-learning method for a food processing machine according to claim 6, characterized in that: The controlling the main control module to call the food processing machine according to the habit parameters and the equipment fault parameters comprises: Determining whether the cup cover switch signal value is abnormal; If the cup cover switch signal value is abnormal, the main control module is controlled to output a signal for reminding the user to tighten the cup cover.
8. The self-learning method for a food processing machine according to claim 1, characterized in that: The habit parameters include habit function parameters, and the controlling the main control module to call the food processing machine according to the habit parameters and the equipment fault parameters includes: Controlling the main control module to obtain a signal indicating that a user has selected a function; Control the main control module to select the system function corresponding to the customary function parameter.
9. The self-learning method for a food processing machine according to claim 8, characterized in that: The habit parameters include habit capacity parameters, and the controlling the main control module to call the food processing machine according to the habit parameters and the equipment fault parameters includes: Get the current system capabilities; Control the main control module to select the custom capacity parameters corresponding to the current system function.
10. The self-learning method for a food processing machine according to claim 1, characterized in that: The habit parameter includes a reservation duration habit parameter, and the controlling the main control module to call the food processing machine according to the habit parameter and the equipment fault parameter includes: Control the main control module to obtain a signal from the user for making a reservation for cooking; Control the main control module to select the reservation duration habit parameter.