Cooking control method, cooking control system and kitchen electric equipment

Abstract

The invention provides a cooking control method, a cooking control system and kitchen electric equipment. The method comprises the following steps: acquiring running state data of the kitchen electric equipment in real time; judging whether the running state data is within a preset running threshold range or not; if the operation state data is not within the preset operation threshold range, determining that the kitchen electric equipment is in a fault state; if the running state data is within the preset running threshold range, inputting the running state data into a pre-trained fault prediction model, and simulating to obtain a fault prediction result; identifying the type of the fault prediction result; if the type of the fault prediction result is that a fault exists, determining that the kitchen electrical equipment is in a fault state; and the rotation angle of the manual-automatic integrated valve is adjusted based on the preset control scheme in the fault state. In the mode, the fault information can be automatically detected under the condition of manual ignition, and the working state of the kitchen electric equipment is automatically adjusted, so that the intelligent response capability of the kitchen electric equipment is improved, and the cooking safety of a user is further improved.

Description

Technical Field

[0001] The present invention relates to the technical field of kitchen appliances, and in particular to a cooking control method, a cooking control system and kitchen appliances. Background Art

[0002] In existing kitchen appliances, after the user manually ignites the appliance, the user needs to manually adjust the knob to control the flame size. However, this method has certain safety hazards, for example, the user may forget to turn off the fire source or fail to turn off the fire source in time when the appliance fails. Summary of the invention

[0003] In view of this, an object of the present invention is to provide a cooking control method, a cooking control system and a kitchen appliance, which can automatically detect fault information and automatically adjust the working state of the kitchen appliance under manual ignition, thereby improving the intelligent response capability of the kitchen appliance and further improving the safety of the user's cooking.

[0004] In a first aspect, an embodiment of the present invention provides a cooking control method, which is applied to a main controller of a kitchen appliance, wherein a manual-automatic valve connected to the main controller is provided in the kitchen appliance; the method comprises: obtaining operating status data of the kitchen appliance in real time; judging whether the operating status data is within a preset operating threshold range; if the operating status data is not within the preset operating threshold range, determining that the kitchen appliance is in a fault state; if the operating status data is within the preset operating threshold range, inputting the operating status data into a pre-trained fault prediction model to simulate and obtain a fault prediction result; identifying the type of the fault prediction result; if the type of the fault prediction result is that a fault exists, determining that the kitchen appliance is in a fault state; and adjusting the rotation angle of the manual-automatic valve based on a preset control scheme under the fault state.

[0005] Furthermore, the method also includes: obtaining the rotation angle of the manual-automatic valve in real time; judging whether the rotation angle is within a preset angle threshold; if the rotation angle is not within the preset angle threshold, controlling the manual-automatic valve to close.

[0006] Furthermore, the operating status data includes temperature data, gas concentration data and pressure data; if the operating status data is not within the preset operating threshold range, the step of determining that the kitchen appliance is in a fault state includes: if the temperature data is not within the preset operating threshold range, determining that the kitchen appliance is in an overheating state; or, if the gas concentration data is not within the preset operating threshold range, determining that the kitchen appliance is in a gas leakage state; or, if the pressure data is not within the preset operating threshold range, determining that the kitchen appliance is in an abnormal gas pressure state.

[0007] Furthermore, the step of adjusting the rotation angle of the manual-automatic valve based on the preset control scheme under the fault state includes: if the fault state is an overheating state, controlling the rotation angle of the manual-automatic valve to decrease according to a preset step size; if the fault state is a gas leakage state or an abnormal gas pressure state, controlling the manual-automatic valve to close.

[0008] Furthermore, the kitchen appliance also includes an alarm device connected to the main controller; the main controller is also connected to the mobile terminal of the peripheral device for communication; after the step of determining that the kitchen appliance is in a fault state; the method also includes: generating an alarm signal according to the fault state, and sending the alarm signal to the alarm device and the mobile terminal respectively.

[0009] Furthermore, before the step of acquiring the operating status data of the kitchen appliance in real time, the method also includes: in response to the user's operation information, controlling the manual-automatic integrated valve to start cooking; the operation information includes start cooking information.

[0010] Furthermore, the fault prediction model is trained in the following manner: the historical operating status in the cooking data sample set is used as input, and the historical fault results in the cooking data sample set are used as output, and the initial neural network model is trained until the preset training conditions are met to obtain a trained fault prediction model.

[0011] In a second aspect, an embodiment of the present invention provides a cooking control system, which is applied to a main controller of a kitchen appliance, wherein a manual-automatic valve connected to the main controller is provided in the kitchen appliance; the system comprises: an operation status data acquisition module, which is used to acquire the operation status data of the kitchen appliance in real time; a fault status judgment module, which is used to judge whether the operation status data is within a preset operation threshold range; the fault status judgment module is also used to determine that the kitchen appliance is in a fault state if the operation status data is not within the preset operation threshold range; the fault status judgment module is also used to input the operation status data into a pre-trained fault prediction model if the operation status data is within the preset operation threshold range, and simulate and obtain a fault prediction result; identify the type of the fault prediction result; if the type of the fault prediction result is that a fault exists, determine that the kitchen appliance is in a fault state; and a control module, which is used to adjust the rotation angle of the manual-automatic valve based on a preset control scheme under the fault state.

[0012] In a third aspect, an embodiment of the present invention provides a kitchen appliance, comprising a housing, a stove, a main controller, a manual-automatic valve and at least one sensor; and also comprising the above-mentioned cooking control system; the cooking control system is arranged in the main controller; the manual-automatic valve is arranged on the housing and connected to the stove; the sensor is arranged on the stove; the manual-automatic valve and the sensor are respectively connected to the main controller.

[0013] Furthermore, the kitchen appliance also includes a gas pipeline; the manual-automatic valve includes: an angle sensor, a knob, a gas valve, a motor and a mechanical linkage structure connected to the knob; the angle sensor is arranged on the knob and connected to the main controller; the gas valve is connected to the gas pipeline; the knob is connected to the gas valve through a mechanical linkage structure; the motor is respectively connected to the main controller and the gas valve.

[0014] The embodiment of the present invention provides a cooking control method, a cooking control system and a kitchen appliance, the method comprising: obtaining the operation status data of the kitchen appliance in real time; judging whether the operation status data is within a preset operation threshold range; if the operation status data is not within the preset operation threshold range, determining that the kitchen appliance is in a fault state; if the operation status data is within the preset operation threshold range, inputting the operation status data into a pre-trained fault prediction model to simulate and obtain a fault prediction result; identifying the type of the fault prediction result; if the type of the fault prediction result is that a fault exists, determining that the kitchen appliance is in a fault state; adjusting the rotation angle of the manual-automatic valve based on the preset control scheme under the fault state. In this method, fault information can be automatically detected and the working state of the kitchen appliance can be automatically adjusted in the case of manual ignition, thereby improving the intelligent response capability of the kitchen appliance and further improving the safety of the user's cooking.

[0015] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0016] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 A flow chart of a cooking control method provided in Embodiment 1 of the present invention;

[0019] Figure 2 A flow chart of a method for controlling closing of a manual-automatic integrated valve provided in Embodiment 1 of the present invention;

[0020] Figure 3 A cooking control system provided in Embodiment 2 of the present invention;

[0021] Figure 4 Another cooking control system is provided for the second embodiment of the present invention;

[0022] Figure 5 A schematic diagram of kitchen appliances provided in Embodiment 3 of the present invention;

[0023] Figure 6 This is a schematic diagram of a manual-automatic integrated valve provided in Embodiment 3 of the present invention.

[0024] Icons: 1-operation status data acquisition module; 2-fault status judgment module; 3-control module; 4-alarm module; 5-start cooking module; 11-housing; 12-stove; 13-main controller; 14-manual and automatic valve; 15-sensor; 16-cooking control system; 141-angle sensor; 142-knob; 143-gas valve; 144-motor; 145-mechanical linkage structure. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0026] To facilitate understanding of this embodiment, the embodiment of the present invention is described in detail below.

[0027] Embodiment 1:

[0028] Figure 1 This is a flow chart of the cooking control method provided in Example 1 of the present invention.

[0029] The cooking control method is applied to the main controller of the kitchen appliance. The kitchen appliance is provided with a manual-automatic valve connected to the main controller. The manual-automatic valve is connected to the gas pipeline in the kitchen appliance. The manual-automatic valve includes a gas valve, a knob and a motor respectively connected to the gas valve, and the gas valve is connected to the gas pipeline. The user can control the opening or closing of the gas valve by manually turning the knob. The main controller also controls the opening or closing of the gas valve by automatically controlling the motor.

[0030] Reference Figure 1 , a cooking control method, comprising:

[0031] Step S101, obtaining the operating status data of the kitchen appliance in real time.

[0032] Here, the operating status data includes temperature data, gas concentration data and pressure data. The kitchen appliance is also provided with a temperature sensor, a gas concentration sensor and a pressure sensor respectively connected to the main controller. The temperature sensor is used to detect the temperature data of the kitchen appliance, and the main controller obtains the temperature data measured by the temperature sensor. The gas concentration sensor is used to detect the gas concentration of the kitchen appliance, and the main controller obtains the gas concentration data measured by the gas concentration sensor. The pressure sensor is used to detect the gas pressure of the kitchen appliance, and the main controller obtains the pressure data measured by the pressure sensor.

[0033] After the main controller obtains the operating data from each sensor, it uses a filtering algorithm, such as Kalman filtering or sliding average filtering, to remove noise from the data and improve the reliability of the data.

[0034] In one embodiment, before step S101, the method further includes:

[0035] In response to the user's operation information, the manual and automatic integrated valve is controlled to start cooking; the operation information includes start cooking information.

[0036] Here, when the manual-automatic valve is in a closed state, the user can turn the knob of the manual-automatic valve to control the manual-automatic valve to start cooking. The main controller determines the rotation angle of the manual-automatic valve through an angle sensor provided in the manual-automatic valve, thereby determining the working state of the manual-automatic valve. The user can also send a start cooking information to the main controller according to an interactive device provided on the kitchen appliance, so that the main controller controls the manual-automatic valve to start cooking by controlling the motor.

[0037] Step S102, determining whether the operation status data is within a preset operation threshold range.

[0038] In one embodiment, the preset operating threshold range is pre-set according to actual conditions, including a temperature data operating threshold range, a gas concentration data operating threshold range, and a pressure data operating threshold range.

[0039] Step S103: if the operation status data is not within the preset operation threshold range, it is determined that the kitchen appliance is in a fault state.

[0040] In one embodiment, in step S103, if the operating status data is not within a preset operating threshold range, the step of determining that the kitchen appliance is in a fault state includes:

[0041] If the temperature data is not within the preset operating threshold range, it is determined that the kitchen appliance is in an overheating state.

[0042] Here, if the temperature data is not within the temperature data operating threshold range, it is determined that the current temperature is abnormal and the kitchen appliance is in an overheated state.

[0043] Alternatively, if the gas concentration data is not within a preset operating threshold range, it is determined that the kitchen appliance is in a gas leakage state.

[0044] Here, if the gas concentration data is not within the gas concentration data operating threshold range, it is determined that a gas leak has occurred and the kitchen appliance is in a gas leak state.

[0045] Alternatively, if the pressure data is not within a preset operating threshold range, it is determined that the kitchen appliance is in an abnormal gas pressure state.

[0046] Here, if the pressure data is not within the pressure data operating threshold range, it is determined that the current pressure is abnormal and the kitchen appliance is in an abnormal gas pressure state.

[0047] Step S104, if the operating status data is within the preset operating threshold range, the operating status data is input into a pre-trained fault prediction model to simulate and obtain a fault prediction result; the type of the fault prediction result is identified; if the type of the fault prediction result is that a fault exists, it is determined that the kitchen appliance is in a fault state.

[0048] Here, the fault prediction model can predict possible fault conditions or abnormal trends (such as abnormal increase in gas concentration), such as gas leakage, overheating, sensor failure, etc., and take preventive measures in time to reduce the occurrence of faults.

[0049] In one embodiment, the fault prediction model is trained in the following manner:

[0050] The historical operating status in the cooking data sample set is taken as input, and the historical fault results in the cooking data sample set is taken as output. The initial neural network model is trained until the preset training conditions are met to obtain a trained fault prediction model.

[0051] Here, the data stored in the cooking sample set is historical cooking data, which includes historical operating status and historical fault results. The historical cooking data in the cooking sample set is divided into a training set and a validation set, and the ratio can be set to 80% training set and 20% validation set. The initial neural network model is trained with the data in the training set. After the trained fault prediction model is obtained, the fault prediction model is verified with the data in the validation set to optimize the trained fault prediction model.

[0052] Specifically, the fault prediction result may be no fault, abnormal increase in gas concentration, abnormal increase in temperature, etc. If the fault prediction result is no fault, the type of the fault prediction result is determined to be no fault. If the fault prediction result is a result other than no fault, the type of the fault prediction result is determined to be fault.

[0053] Step S105, adjusting the rotation angle of the manual-automatic valve based on a preset control scheme under a fault state.

[0054] In one embodiment, step S105 includes:

[0055] If the fault state is an overheating state, the rotation angle of the manual-automatic valve is controlled to decrease according to a preset step size.

[0056] Here, the preset step length is pre-set according to the actual situation and can be set to a gear. For example, the current manual-automatic valve is in gear 3, and when the fault state is overheating, the main controller controls the manual-automatic valve to adjust to gear 2. Among them, the firepower of gear 2 is less than that of gear 3.

[0057] If the fault state is a gas leakage state or an abnormal gas pressure state, the manual-automatic valve is controlled to close.

[0058] Here, if the current kitchen appliance is in a gas leakage state or an abnormal gas pressure state, the main control controller drives the motor to close the gas valve to cut off the gas supply, record the fault information, and notify the user.

[0059] In one embodiment, the kitchen appliance is further provided with an alarm device connected to the main controller; the main controller is also communicatively connected to the mobile terminal of the peripheral device.

[0060] Here, the alarm device can be set according to actual conditions and can be an audible and visual alarm device.

[0061] The mobile terminal is pre-installed with preset software that can communicate with the kitchen appliances.

[0062] After determining that the kitchen appliance is in a fault state, the method further includes:

[0063] An alarm signal is generated according to the fault status and sent to the alarm device and the mobile terminal respectively.

[0064] Here, the alarm device makes an audible and visual alarm according to the alarm signal, and at the same time, the mobile terminal displays the fault status according to the alarm signal.

[0065] After the fault is eliminated, the user restarts cooking by manually turning the knob of the manual-automatic valve or controlling the interactive device.

[0066] In one embodiment, referring to Figure 2 , the method further comprises:

[0067] Step S201, obtaining the rotation angle of the manual-automatic valve in real time.

[0068] Here, the rotation angle of the manual-automatic valve sent by the angle sensor of the manual-automatic valve is acquired in real time, and the current cooking gear information is determined according to the angle.

[0069] Step S202, determining whether the rotation angle is within a preset angle threshold.

[0070] Here, the preset angle threshold is pre-set according to the actual situation, and can be set so that 0°<angle threshold<270°. When the rotation angle is 0°, it is determined that the manual-automatic valve is in a closed state. When the rotation angle is greater than or equal to 270°, it is determined that the cooking flame is too large and there is a risk of causing a fire.

[0071] Step S203: If the rotation angle is not within the preset angle threshold, the manual-automatic valve is controlled to close.

[0072] Here, if the rotation angle is not within the range of 0° to 270°, the main controller drives the motor to close the gas valve, cut off the gas supply, and notify the user.

[0073] The embodiment of the present invention provides a cooking control method, which includes: obtaining the operation status data of the kitchen appliance in real time; judging whether the operation status data is within the preset operation threshold range; if the operation status data is not within the preset operation threshold range, determining that the kitchen appliance is in a fault state; if the operation status data is within the preset operation threshold range, inputting the operation status data into a pre-trained fault prediction model to simulate and obtain a fault prediction result; identifying the type of the fault prediction result; if the type of the fault prediction result is that there is a fault, determining that the kitchen appliance is in a fault state; adjusting the rotation angle of the manual-automatic valve based on the preset control scheme under the fault state. In this method, fault information can be automatically detected and the working state of the kitchen appliance can be automatically adjusted in the case of manual ignition, thereby improving the intelligent response capability of the kitchen appliance and further improving the safety of the user's cooking.

[0074] Embodiment 2:

[0075] Figure 3 This is a cooking control system provided in Embodiment 2 of the present invention.

[0076] The cooking control system is applied to the main controller of the kitchen appliance, and the kitchen appliance is provided with a manual-automatic valve connected to the main controller. Figure 3 , the system includes:

[0077] The operation status data acquisition module 1 is used to acquire the operation status data of the kitchen appliance in real time.

[0078] The fault status judgment module 2 is used to judge whether the operation status data is within a preset operation threshold range.

[0079] The fault state judgment module 2 is also used to determine that the kitchen appliance is in a fault state if the operating state data is not within a preset operating threshold range.

[0080] The fault status judgment module 2 is also used to input the operating status data into a pre-trained fault prediction model if the operating status data is within a preset operating threshold range, and simulate the fault prediction result; identify the type of the fault prediction result; if the type of the fault prediction result is that a fault exists, determine that the kitchen appliance is in a fault state.

[0081] The control module 3 is used to adjust the rotation angle of the manual-automatic valve based on a preset control scheme under a fault state.

[0082] In one embodiment, the control module 3 is further used for:

[0083] Obtain the rotation angle of the manual-automatic valve in real time.

[0084] Determine whether the rotation angle is within a preset angle threshold.

[0085] If the rotation angle is not within the preset angle threshold, the manual and automatic valves are controlled to close.

[0086] In one embodiment, the operating state data includes temperature data, gas concentration data and pressure data. The fault state judgment module 2 is also used for:

[0087] If the operating status data is not within a preset operating threshold range, the step of determining that the kitchen appliance is in a fault state includes:

[0088] If the temperature data is not within the preset operating threshold range, it is determined that the kitchen appliance is in an overheating state.

[0089] or,

[0090] If the gas concentration data is not within the preset operating threshold range, it is determined that the kitchen appliance is in a gas leakage state.

[0091] or,

[0092] If the pressure data is not within the preset operating threshold range, it is determined that the kitchen appliance is in an abnormal gas pressure state.

[0093] In one embodiment, the control module 3 is further used for:

[0094] If the fault state is an overheating state, the rotation angle of the manual-automatic valve is controlled to decrease according to a preset step size.

[0095] If the fault state is a gas leakage state or an abnormal gas pressure state, the manual-automatic valve is controlled to close.

[0096] In one embodiment, the kitchen appliance is further provided with an alarm device connected to the main controller; the main controller is also connected to the mobile terminal of the peripheral device for communication. Figure 4 The system includes an alarm module 4, which is used to:

[0097] An alarm signal is generated according to the fault status and sent to the alarm device and the mobile terminal respectively.

[0098] In one embodiment, referring to Figure 4 The system includes a cooking start module 5, which is used to:

[0099] In response to the user's operation information, the manual and automatic integrated valve is controlled to start cooking; the operation information includes start cooking information.

[0100] In one embodiment, the fault state determination module 2 is further used for:

[0101] The historical operating status in the cooking data sample set is taken as input, and the historical fault results in the cooking data sample set is taken as output. The initial neural network model is trained until the preset training conditions are met to obtain a trained fault prediction model.

[0102] An embodiment of the present invention provides a cooking control system, in which fault information can be automatically detected and the working state of kitchen appliances can be automatically adjusted, thereby improving the intelligent response capability of the kitchen appliances and further improving the safety of users' cooking.

[0103] Embodiment three:

[0104] Figure 5 This is a schematic diagram of kitchen appliances provided in Embodiment 3 of the present invention.

[0105] Reference Figure 5 The kitchen appliance includes a housing 11, a stove 12, a main controller 13, a manual-automatic valve 14 and at least one sensor 15; it also includes the above-mentioned cooking control system 16; the cooking control system 16 is arranged in the main controller 13; the manual-automatic valve 14 is arranged on the housing 11 and connected to the stove 12; the sensor 15 is arranged on the stove 12; the manual-automatic valve 14 and the sensor 15 are respectively connected to the main controller 13.

[0106] Here, the sensor 15 includes a temperature sensor, a gas concentration sensor and a pressure sensor. The gas concentration sensor is used to detect gas leakage. The temperature sensor is used to detect overheating, and can be an NTC (Negative Temperature Coefficient) thermistor, a PTC (Positive Temperature Coefficient) thermistor and a thermocouple. The pressure sensor is used to detect abnormal gas pressure, and can be a MEMS (Micro Electro Mechanical System) pressure sensor.

[0107] The gas concentration sensor can be set at a low point near the stove, because gas is generally heavier than air. The temperature sensor can be set at a key part of the stove, such as near the burner. The pressure sensor can be set in the gas pipeline, near the gas valve.

[0108] The kitchen appliance also includes an alarm device, and the main controller 13 is connected to the alarm device. The alarm device is installed in a conspicuous position to ensure that the user can see and hear the alarm in time.

[0109] In one embodiment, referring to Figure 6 The kitchen appliance also includes a gas pipeline; the manual-automatic valve 14 includes: an angle sensor 141, a knob 142, a gas valve 143, a motor 144 and a mechanical linkage structure 145 connected to the knob 142.

[0110] The angle sensor 141 is arranged on the knob 142 and connected to the main controller 13; the gas valve 143 is connected to the gas pipeline; the knob 142 is connected to the gas valve 143 through the mechanical linkage structure 145; the motor 144 is connected to the main controller 13 and the gas valve 143 respectively.

[0111] Here, the main controller 13 detects the rotation angle of the knob 142 manually rotated by the user through the angle sensor 141. The angle sensor 141 can be a potentiometer or a photoelectric encoder to monitor the rotation angle of the knob 142 in real time.

[0112] The main controller 13 has a built-in microprocessor and a storage unit to store control logic and algorithms. After receiving the operating status data sent by the sensor 15, it is determined whether the kitchen appliance is in a fault state. According to the rotation angle sent by the angle sensor 141 obtained in real time, it is determined whether the kitchen appliance needs to be shut down.

[0113] When the main controller 13 detects that the kitchen appliance is in a fault state or needs to be shut down, it sends a control signal to the motor 144. The motor 144 automatically returns to its original position through the gear transmission control knob 142, and adjusts the gas valve 143 at the same time to ensure safety.

[0114] An embodiment of the present invention provides a kitchen appliance that can automatically detect fault information after a user manually ignites the appliance, and automatically adjust the working state of the kitchen appliance, thereby improving the intelligent response capability of the kitchen appliance and further improving the safety of cooking for the user.

[0115] An embodiment of the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the path planning method for autonomous driving provided in the above embodiment are implemented.

[0116] An embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the path planning method for autonomous driving of the above embodiment are executed.

[0117] The computer program product provided in the embodiment of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the method described in the previous method embodiment. The specific implementation can be found in the method embodiment and will not be repeated here.

[0118] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system and device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0119] In addition, in the description of the embodiments of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0120] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0121] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0122] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A cooking control method, characterized in that: A main controller applied to a kitchen appliance, wherein the kitchen appliance is provided with a manual-automatic integrated valve connected to the main controller; the method comprises: Acquire the operating status data of the kitchen appliance in real time; Determining whether the operating status data is within a preset operating threshold range; If the operating status data is not within the preset operating threshold range, determining that the kitchen appliance is in a fault state; If the operation status data is within the preset operation threshold range, inputting the operation status data into a pre-trained fault prediction model to simulate and obtain a fault prediction result; identifying the type of the fault prediction result; if the type of the fault prediction result is that a fault exists, determining that the kitchen appliance is in a fault state; The rotation angle of the manual-automatic valve is adjusted based on a preset control scheme under a fault state.

2. The cooking control method according to claim 1, characterized in that: The method further comprises: Acquiring the rotation angle of the manual-automatic valve in real time; Determining whether the rotation angle is within a preset angle threshold; If the rotation angle is not within the preset angle threshold, the manual-automatic valve is controlled to be closed.

3. The cooking control method according to claim 1, characterized in that: The operating status data includes temperature data, gas concentration data and pressure data; The step of determining that the kitchen appliance is in a fault state if the operating status data is not within the preset operating threshold range comprises: If the temperature data is not within the preset operating threshold range, determining that the kitchen appliance is in an overheated state; or, If the gas concentration data is not within the preset operating threshold range, it is determined that the kitchen appliance is in a gas leakage state; or, If the pressure data is not within the preset operating threshold range, it is determined that the kitchen appliance is in an abnormal gas pressure state.

4. The cooking control method according to claim 3, characterized in that: The step of adjusting the rotation angle of the manual-automatic valve based on the preset control scheme under the fault state includes: If the fault state is the overheat state, controlling the rotation angle of the manual-automatic valve to decrease according to a preset step length; If the fault state is the gas leakage state or the abnormal gas pressure state, the manual-automatic valve is controlled to be closed.

5. The cooking control method according to claim 1, characterized in that: The kitchen appliance is also provided with an alarm device connected to the main controller; the main controller is also connected to the mobile terminal of the peripheral device for communication; After determining that the kitchen appliance is in a fault state, the method further comprises: An alarm signal is generated according to the fault state, and the alarm signal is sent to the alarm device and the mobile terminal respectively.

6. The cooking control method according to claim 1, characterized in that: Before the step of acquiring the operating status data of the kitchen appliance in real time, the method further includes: In response to user operation information, the manual-automatic integrated valve is controlled to start cooking; the operation information includes start cooking information.

7. The cooking control method according to claim 1, characterized in that: The fault prediction model is trained in the following way: The historical operating status in the cooking data sample set is used as input, and the historical fault results in the cooking data sample set are used as output, and the initial neural network model is trained until the preset training conditions are met to obtain a trained fault prediction model.

8. A cooking control system, characterized in that: A main controller applied to a kitchen appliance, wherein the kitchen appliance is provided with a manual-automatic integrated valve connected to the main controller; the system comprises: An operation status data acquisition module, used to acquire the operation status data of the kitchen appliance in real time; A fault status judgment module is used to judge whether the operation status data is within a preset operation threshold range; The fault state judgment module is further used to determine that the kitchen appliance is in a fault state if the operation state data is not within the preset operation threshold range; The fault state judgment module is further used to input the running state data into a pre-trained fault prediction model to simulate and obtain a fault prediction result if the running state data is within the preset running threshold range; identify the type of the fault prediction result; and determine that the kitchen appliance is in a fault state if the type of the fault prediction result is that a fault exists; A control module is used to adjust the rotation angle of the manual-automatic valve based on a preset control scheme under a fault state.

9. A kitchen appliance, characterized in that: It includes a housing, a stove, a main controller, a manual-automatic valve and at least one sensor; it also includes the cooking control system described in claim 8; the cooking control system is arranged in the main controller; the manual-automatic valve is arranged on the housing and connected to the stove; the sensor is arranged on the stove; the manual-automatic valve and the sensor are respectively connected to the main controller.

10. The kitchen appliance according to claim 9, characterized in that: The kitchen appliance also includes a gas pipeline; the manual-automatic valve includes: an angle sensor, a knob, a gas valve, a motor and a mechanical linkage structure connected to the knob; The angle sensor is arranged on the knob and connected to the main controller; the gas valve is connected to the gas pipeline; the knob is connected to the gas valve through the mechanical linkage structure; and the motor is connected to the main controller and the gas valve respectively.

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