Intelligent detection method and device applied to food processor

Abstract

The invention discloses an intelligent detection method and device applied to a food processor, and the method comprises the steps: obtaining a first parameter of target food in the food processor at a preset target temperature, and determining a second parameter corresponding to the first parameter; comparing the first parameter with the second parameter to obtain a parameter comparison result; and determining a taste detection result of the target food according to a predetermined parameter corresponding relationship and a parameter comparison result. Visibly, by implementing the method and the device, the taste of the food in the food processor can be automatically detected, and the accuracy and intelligence of food taste detection can be improved, so that the overall cooking experience of a user and the convenience of using the food processor are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent detection and control, and particularly relates to an intelligent detection method and device applied to a food processor. Background Art

[0002] With the continuous improvement of people's living standards, different types of food processors such as wall breakers and soymilk makers have emerged in the market, bringing a lot of convenience to people's lives. However, current food processors generally detect the temperature change of food by a temperature sensor after heating the food to achieve the detection of the food taste. However, this method is not applicable to foods that do not require heating (such as fruit juice) at all, resulting in a poor user experience. It can be seen that it is particularly important to provide a new detection method to improve the accuracy and intelligence of food taste detection in a food processor, thereby improving the convenience and comfort of users using the food processor. Summary of the Invention

[0003] The present invention provides an intelligent detection method and device applied to a food processor, which can automatically detect the taste of food in the food processor, is beneficial to improving the accuracy and intelligence of food taste detection, thereby enhancing the overall cooking experience of users and the convenience of using the food processor.

[0004] To solve the above technical problems, in the first aspect of the present invention, an intelligent detection method applied to a food processor is disclosed, and the method includes:

[0005] Obtain a first parameter of a target food in the food processor at a preset target temperature, and determine a second parameter corresponding to the first parameter;

[0006] Perform a comparison operation on the first parameter and the second parameter to obtain a parameter comparison result;

[0007] Determine a taste detection result of the target food according to a pre-determined parameter correspondence and the parameter comparison result.

[0008] As an optional implementation manner, in the first aspect of the present invention, the method further includes:

[0009] Determine a food state of the target food according to the parameter comparison result;

[0010] Obtain food demand information of a target user for the target food, and generate an operation control parameter of the food processor according to the food demand information and the food state;

[0011] Among them, the food demand information includes one or more of the taste demand information, quantity demand information, and temperature demand information of the target user for the target food.

[0012] As an optional implementation manner, in the first aspect of the present invention, after generating the operation control parameters of the food processor according to the food demand information and the food state, the method further includes:

[0013] Determine the real-time state of the food processor according to the parameter comparison result;

[0014] Judge whether the real-time state matches a preset target state;

[0015] When it is judged that the real-time state matches the preset target state, perform an adjustment operation on the operation control parameters according to the real-time state to generate target control parameters;

[0016] Among them, the target control parameters include one or more of reducing the motor speed of the food processor and stopping the motor operation of the food processor.

[0017] As an optional implementation manner, in the first aspect of the present invention, generating the operation control parameters of the food processor according to the food demand information and the food state includes:

[0018] Determine the demand state of the target food according to the food demand information, and determine the state difference parameter between the demand state and the food state;

[0019] Based on the state difference parameter, determine the state regulation parameter that matches the state difference parameter, and generate the operation control parameters of the food processor according to the state regulation parameter.

[0020] As an optional implementation manner, in the first aspect of the present invention, determining the second parameter corresponding to the first parameter includes:

[0021] Determine the second parameter that matches the first parameter in the pre-set parameter storage library according to the first parameter and the pre-determined target association relationship;

[0022] Among them, the pre-set parameter storage library includes several candidate parameters, the target association relationship includes the parameter values corresponding to the target food at each preset temperature, the first parameter includes the first electrode resistance value of the target food at the preset target temperature, and the second parameter includes the second electrode resistance value that matches the first parameter;

[0023] Moreover, the operation of comparing the first parameter with the second parameter to obtain a parameter comparison result includes:

[0024] Performing a comparison operation on the first electrode resistance value and the second electrode resistance value to obtain a comparison difference between the first electrode resistance value and the second electrode resistance value, and using the comparison difference as the parameter comparison result.

[0025] As an optional implementation manner, in the first aspect of the present invention, the determining a state regulation parameter matching the state difference parameter based on the state difference parameter and generating an operation control parameter of the food processor according to the state regulation parameter includes:

[0026] Based on the state difference parameter, analyzing a difference factor between the required state and the food state, and determining a state regulation parameter matching the difference factor according to the difference factor in combination with a pre-determined food characteristic prediction model;

[0027] According to the state regulation parameter, predicting a predicted regulation result after the food processor performs a regulation operation matching the state regulation parameter, and determining whether the predicted regulation result matches the required state;

[0028] When it is determined that the predicted regulation result matches the required state, generating an operation control parameter of the food processor according to the state regulation parameter;

[0029] Wherein, the operation control parameter includes one or more of an operation duration control parameter of the food processor, a motor speed control parameter of the food processor, and a heating power control parameter of the food processor.

[0030] As an optional implementation manner, in the first aspect of the present invention, before generating the operation control parameter of the food processor according to the food requirement information and the food state, the method further includes:

[0031] Obtaining historical record information of the target user for the target food, where the historical record information includes one or more of historical operation record information and historical preference setting information of the target user for the target food within a preset historical time period;

[0032] Performing an information fitting operation on the historical record information and the food requirement information to obtain an information fitting result; the information fitting result at least includes the historical record information and the food requirement information;

[0033] Among them, generating the operation control parameters of the food processor according to the food demand information and the food state includes:

[0034] Generating the operation control parameters of the food processor according to the information fitting result and the food state;

[0035] And, before generating the operation control parameters of the food processor according to the information fitting result and the food state, the method further includes:

[0036] Judging whether the information fitting result meets the preset food processing conditions;

[0037] When it is judged that the information fitting result meets the preset food processing conditions, triggering the operation of generating the operation control parameters of the food processor according to the information fitting result and the food state;

[0038] When it is judged that the information fitting result does not meet the preset food processing conditions, based on the preset food processing conditions, performing an adjustment operation on the information fitting result, and re-triggering the operation of judging whether the information fitting result meets the preset food processing conditions.

[0039] The second aspect of the present invention discloses an intelligent detection device applied to a food processor, and the device includes:

[0040] An acquisition module, configured to acquire a first parameter of a target food in the food processor at a preset target temperature;

[0041] A determination module, configured to determine a second parameter corresponding to the first parameter;

[0042] A comparison module, configured to perform a comparison operation on the first parameter and the second parameter to obtain a parameter comparison result;

[0043] The determination module is further configured to determine a taste detection result of the target food according to a pre-determined parameter correspondence relationship and the parameter comparison result.

[0044] As an optional implementation manner, in the second aspect of the present invention, the determination module is further configured to determine the food state of the target food according to the parameter comparison result;

[0045] The acquisition module is further configured to acquire food demand information of a target user for the target food;

[0046] The device further includes:

[0047] A generation module, configured to generate operation control parameters of the food processor according to the food demand information and the food status;

[0048] Wherein, the food demand information includes one or more of the texture demand information, quantity demand information, and temperature demand information of the target food by the target user.

[0049] As an optional implementation manner, in the second aspect of the present invention, the determination module is further configured to, after the generation module generates the operation control parameters of the food processor according to the food demand information and the food status, determine the real-time status of the food processor according to the parameter comparison result;

[0050] The device further includes:

[0051] A first judgment module, configured to judge whether the real-time status matches a preset target status;

[0052] The generation module is further configured to, when the first judgment module judges that the real-time status matches the preset target status, perform an adjustment operation on the operation control parameters according to the real-time status to generate target control parameters;

[0053] Wherein, the target control parameters include one or more of reducing the motor speed of the food processor and stopping the motor operation of the food processor.

[0054] As an optional implementation manner, in the second aspect of the present invention, the specific manner in which the generation module generates the operation control parameters of the food processor according to the food demand information and the food status includes:

[0055] Determine the demand status of the target food according to the food demand information, and determine the status difference parameter between the demand status and the food status;

[0056] Based on the status difference parameter, determine a status regulation parameter matching the status difference parameter, and generate the operation control parameters of the food processor according to the status regulation parameter.

[0057] As an optional implementation manner, in the second aspect of the present invention, the specific manner in which the determination module determines the second parameter corresponding to the first parameter includes:

[0058] Determine the second parameter matching the first parameter in a preset parameter storage library according to the first parameter and a pre-determined target association relationship;

[0059] Among them, the pre-set parameter repository includes a number of candidate parameters, the target association relationship includes the parameter values corresponding to the target food at each preset temperature, the first parameter includes the first electrode resistance value of the target food at the preset target temperature, and the second parameter includes a second electrode resistance value that matches the first parameter;

[0060] Moreover, the specific way for the comparison module to perform a comparison operation on the first parameter and the second parameter to obtain a parameter comparison result includes:

[0061] Perform a comparison operation on the first electrode resistance value and the second electrode resistance value to obtain a comparison difference between the first electrode resistance value and the second electrode resistance value, and use the comparison difference as the parameter comparison result.

[0062] As an optional implementation manner, in the second aspect of the present invention, the specific way for the generation module to determine a state regulation parameter that matches the state difference parameter based on the state difference parameter and generate an operation control parameter of the food processor according to the state regulation parameter includes:

[0063] Based on the state difference parameter, analyze the difference factor between the required state and the food state, and determine a state regulation parameter that matches the difference factor according to the difference factor in combination with a pre-determined food characteristic prediction model;

[0064] According to the state regulation parameter, predict a predicted regulation result after the food processor performs a regulation operation that matches the state regulation parameter, and determine whether the predicted regulation result matches the required state;

[0065] When it is determined that the predicted regulation result matches the required state, generate an operation control parameter of the food processor according to the state regulation parameter;

[0066] Among them, the operation control parameter includes one or more of an operation duration control parameter of the food processor, a motor speed control parameter of the food processor, and a heating power control parameter of the food processor.

[0067] As an optional implementation manner, in the second aspect of the present invention, the acquisition module is further configured to obtain historical record information of the target user for the target food before the generation module generates an operation control parameter of the food processor according to the food demand information and the food state, where the historical record information includes one or more of historical operation record information and historical preference setting information of the target user for the target food within a preset historical time period;

[0068] The device further includes:

[0069] A fitting module, configured to perform an information fitting operation on the historical record information and the food demand information to obtain an information fitting result; the information fitting result at least includes the historical record information and the food demand information;

[0070] Wherein, the specific manner in which the generating module generates the operation control parameters of the food processor according to the food demand information and the food state includes:

[0071] Generating the operation control parameters of the food processor according to the information fitting result and the food state;

[0072] And, the device further includes:

[0073] A second judgment module, configured to judge whether the information fitting result meets a preset food processing condition before the generating module generates the operation control parameters of the food processor according to the information fitting result and the food state; when it is judged that the information fitting result meets the preset food processing condition, trigger the generating module to execute the operation of generating the operation control parameters of the food processor according to the information fitting result and the food state;

[0074] An adjustment module, configured to, when the second judgment module judges that the information fitting result does not meet the preset food processing condition, perform an adjustment operation on the information fitting result based on the preset food processing condition, and re-trigger the second judgment module to execute the operation of judging whether the information fitting result meets the preset food processing condition.

[0075] A third aspect of the present invention discloses another intelligent detection device applied to a food processor, and the device includes:

[0076] A memory storing executable program code;

[0077] A processor coupled to the memory;

[0078] The processor calls the executable program code stored in the memory and executes the intelligent detection method applied to the food processor disclosed in the first aspect of the present invention.

[0079] A fourth aspect of the present invention discloses a computer storage medium, and the computer storage medium stores computer instructions, which are used to execute the intelligent detection method applied to the food processor disclosed in the first aspect of the present invention when called.

[0080] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0081] In an embodiment of the present invention, a first parameter of a target food in a food processor at a preset target temperature is obtained, and a second parameter corresponding to the first parameter is determined; a comparison operation is performed on the first parameter and the second parameter to obtain a parameter comparison result; according to a pre-determined parameter correspondence and the parameter comparison result, a taste detection result of the target food is determined. It can be seen that implementing the present invention can automatically detect the taste of food in a food processor, which is beneficial to improving the accuracy and intelligence of food taste detection, thereby enhancing the overall cooking experience of users and the convenience of using the food processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0083] Figure 1 is a flowchart of an intelligent detection method applied to a food processor disclosed in an embodiment of the present invention;

[0084] Figure 2 is a flowchart of another intelligent detection method applied to a food processor disclosed in an embodiment of the present invention;

[0085] Figure 3 is a structural schematic diagram of an intelligent detection device applied to a food processor disclosed in an embodiment of the present invention;

[0086] Figure 4 is a structural schematic diagram of another intelligent detection device applied to a food processor disclosed in an embodiment of the present invention;

[0087] Figure 5 is a structural schematic diagram of yet another intelligent detection device applied to a food processor disclosed in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0088] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0089] In the description and claims of the present invention and the above-mentioned drawings, terms such as "first", "second", etc. are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, device, product or terminal comprising a series of steps or units is not limited to the listed steps or units, but may optionally further include unlisted steps or units, or may optionally further include other steps or units inherent to these processes, methods, products or terminals.

[0090] Reference to "embodiment" herein means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present invention. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0091] The present invention discloses an intelligent detection method and device for a food processor, which can automatically detect the taste of food in the food processor, is beneficial to improving the accuracy and intelligence of food taste detection, thereby enhancing the overall cooking experience of users and the convenience of using the food processor. The following will be described in detail separately.

[0092] Embodiment 1

[0093] Please refer to Figure 1 , Figure 1 which is a schematic flowchart of an intelligent detection method for a food processor disclosed in an embodiment of the present invention. Among them, Figure 1 the described intelligent detection method for a food processor can be applied to the intelligent detection device of the food processor or to the food processor itself. Among them, the intelligent detection device for the food processor can be integrated in a cloud server or a local server, and the embodiments of the present invention do not make specific limitations. As Figure 1 shown, the intelligent detection method for a food processor may include the following operations:

[0094] 101. Obtain a first parameter of the target food in the food processor at a preset target temperature, and determine a second parameter corresponding to the first parameter.

[0095] In an embodiment of the present invention, optionally, obtaining the first parameter of the target food in the food processor can be obtained in real time, can be obtained at regular intervals according to a preset time period, or can be obtained when it is necessary to detect the state of the food processor or the state of the food stored in the food processor. The embodiments of the present invention do not make specific limitations.

[0096] In an embodiment of the present invention, optionally, the preset target temperature may be the current temperature of the target food or a preset temperature, such as 30 degrees Celsius, etc. The embodiment of the present invention does not make specific limitations.

[0097] In an embodiment of the present invention, optionally, the second parameter may be a second parameter corresponding to the first parameter for the target food determined in advance at the preset target temperature. Further, the first parameter may be the first electrode resistance value of the target food at the target temperature, and the second parameter may be a second electrode resistance value determined in advance and matching the first electrode resistance value for the target food at the preset target temperature.

[0098] 102. Perform a comparison operation on the first parameter and the second parameter to obtain a parameter comparison result.

[0099] In an embodiment of the present invention, optionally, the parameter comparison result at least includes the difference between the first parameter and the second parameter; further optionally, the difference between the first parameter and the second parameter may include the electrode resistance difference between the first electrode resistance value and the second electrode resistance value.

[0100] 103. Determine the taste detection result of the target food according to the parameter correspondence determined in advance and the parameter comparison result.

[0101] In an embodiment of the present invention, optionally, the parameter correspondence determined in advance may include the correspondence between the electrode resistance values of each specific food and each temperature.

[0102] In an embodiment of the present invention, optionally, the taste detection result of the target food may include one of light taste, rich taste, and moderate taste. For example, if the target food is soy milk, if the parameter comparison result indicates that the difference between the first parameter and the second parameter is greater than the target value corresponding to the parameter correspondence, it is determined that the soy milk has a light taste; if the parameter comparison result indicates that the difference between the first parameter and the second parameter is less than the target value corresponding to the parameter correspondence, it is determined that the soy milk has a rich taste; if the parameter comparison result indicates that the difference between the first parameter and the second parameter is equal to the target value corresponding to the parameter correspondence, it is determined that the soy milk has a moderate taste. Further, for different foods, it is possible that some foods are judged to have a light taste when the difference is less than a certain value and a rich taste when the difference is greater than a certain value; whether it is greater or less needs to be determined according to the specific food, temperature and the parameter correspondence determined in advance.

[0103] It can be seen that the implementation Figure 1The described intelligent detection method applied to a food processor can obtain the first parameter of the target food in the food processor at a preset target temperature and determine the corresponding second parameter, perform a comparison operation on the first parameter and the second parameter to obtain a parameter comparison result, and determine the taste detection result of the target food according to the pre-determined parameter correspondence and the parameter comparison result. It can realize the intelligent detection of the taste of the food in the food processor, achieve the precise quantitative evaluation of the food taste, and judge the food state based on the parameter comparison result to realize the taste detection, making the taste judgment more scientific and accurate, which is beneficial to improving the accuracy and intelligence of the food taste detection, thereby enhancing the overall cooking experience of the user, and also being beneficial to improving the convenience and comfort of the user using the food processor.

[0104] Embodiment 2

[0105] Please refer to Figure 2 , Figure 2 which is a schematic flowchart of another intelligent detection method applied to a food processor disclosed in an embodiment of the present invention. Among them, Figure 2 the described intelligent detection method applied to a food processor can be applied to the intelligent detection device of the food processor or the food processor itself. Among them, the intelligent detection device applied to the food processor can be integrated in a cloud server or a local server, which is not limited in the embodiments of the present invention. As Figure 2 shown, the intelligent detection method applied to the food processor may include the following operations:

[0106] 201. Obtain the first parameter of the target food in the food processor at a preset target temperature and determine the second parameter corresponding to the first parameter.

[0107] 202. Perform a comparison operation on the first parameter and the second parameter to obtain a parameter comparison result.

[0108] 203. Determine the taste detection result of the target food according to the pre-determined parameter correspondence and the parameter comparison result.

[0109] In the embodiments of the present invention, for the detailed description of steps 201-step 203, please refer to the other descriptions of steps 101-step 103 in Embodiment 1, and the embodiments of the present invention will not be repeated.

[0110] 204. Determine the food state of the target food according to the parameter comparison result.

[0111] In the embodiments of the present invention, optionally, the food state of the target food may include the current cooking state of the target food. For example, the food state of the target food may include one or more of the water content state, hardness state, temperature state, quantity state, and quality state of the target food.

[0112] In an embodiment of the present invention, optionally, determining the food state of the target food according to the parameter comparison result may include:

[0113] Determine the parameter difference value between the first parameter and the second parameter according to the parameter comparison result, analyze the correspondence between the parameter difference value and the pre-determined parameter correspondence, and determine the food state of the target food based on the correspondence;

[0114] Among them, the food state of the target food may include one or more of the soft and glutinous state of the target food, the thick state of the target food, and the diluted state of the target food.

[0115] In an embodiment of the present invention, optionally, for example, if the parameter comparison result is used to indicate that the parameter difference value between the first parameter and the second parameter is 1, and the reference parameter value corresponding to the pre-determined parameter correspondence is 2, then the parameter difference value is greater than the reference parameter value, and further determine that the taste of the food state of the target food is a bland state; if the parameter comparison result is used to indicate that the parameter difference value between the first parameter and the second parameter is 5, and the reference parameter value corresponding to the pre-determined parameter correspondence is 2, then the parameter difference value is less than the reference parameter value, and further determine that the taste of the food state of the target food is a strong state.

[0116] 205. Obtain the food demand information of the target user for the target food, and generate the operation control parameters of the food processor according to the food demand information and the food state.

[0117] In an embodiment of the present invention, the food demand information includes one or more of the taste demand information, quantity demand information, and temperature demand information of the target user for the target food.

[0118] In an embodiment of the present invention, optionally, obtaining the food demand information of the target user for the target food may be obtained in real time, or obtained at regular intervals according to a preset time period, or obtained when it is necessary to generate the operation control parameters of the food processor. The embodiment of the present invention does not make specific limitations.

[0119] In an embodiment of the present invention, optionally, obtaining the food demand information of the target user for the target food may be the food demand information obtained by obtaining the voice information, gesture information, action information, text information, image information, etc. of the target user. For example, the target user can input the demand for the target food through voice or text. For example, I need soy milk with a very smooth taste, or I need pure fruit juice.

[0120] In an embodiment of the present invention, optionally, the taste requirement information of the target user for the target food may include one or more of the softness and hardness degree requirement information of the target user for the target food, the taste requirement information of the target user for the target food, and the water content requirement information of the target user for the target food; the quantity requirement information of the target user for the target food may include one or more of the weight requirement information of the target user for the target food and the volume requirement information of the target user for the target food.

[0121] In an embodiment of the present invention, optionally, generating the operation control parameters of the food processor according to the food requirement information and the food state may include:

[0122] Inputting the food requirement information and the food state into a pre-trained deep learning model to obtain a model output result, where the model output result includes one or more of the heating temperature, stirring speed, heating duration, motor speed, and motor rotation duration;

[0123] Generating the operation control parameters of the food processor based on the model output result, where the operation control parameters include one or more of the motor speed control parameter, motor rotation duration control parameter, heating duration control parameter, and heating temperature control parameter of the food processor;

[0124] Among them, the pre-trained deep learning model may be an architecture of Transformer.

[0125] In an embodiment of the present invention, further optionally, inputting the food requirement information and the food state into a pre-trained deep learning model to obtain a model output result may include: performing a multi-objective optimization algorithm on the food requirement information to obtain target food requirement information, and inputting the target food requirement information and the food state into the pre-trained deep learning model to obtain a model output result. Among them, considering that user requirements may include multiple dimensions (such as taste, temperature, quantity), a multi-objective optimization algorithm (such as Pareto optimization) is adopted to balance cooking efficiency and energy consumption while meeting user requirements.

[0126] In an embodiment of the present invention, further optionally, after generating the operation control parameters of the food processor according to the food requirement information and the food state, the method may further include: controlling the food processor to perform an operation control operation matching the operation control parameters.

[0127] It can be seen that implementing Figure 2The described intelligent detection method applied to a food processor can determine the food state of the target food according to the parameter comparison result, obtain the food demand information of the target user for the target food, generate the operation control parameters of the food processor according to the food demand information and the food state, and can comprehensively generate the operation control parameters of the food processor by combining the food state of the target food and the food demand information of the target user, so that the matching degree between the operation process and the operation result of the food processor and the user demand is higher, and it can meet the diverse needs of the user for the target food. And by determining the food state and generating the operation control parameters in combination with the food demand information, the cooking process can be accurately controlled, which is beneficial to improving the accuracy and intelligence of controlling the food processor, and reflects the high intelligent level of the food processor, realizing more accurate control, and further being beneficial to improving the accuracy and intelligence of food taste detection, thereby enhancing the overall cooking experience of the user, and also being beneficial to improving the convenience and comfort of the user using the food processor.

[0128] In an optional embodiment, after generating the operation control parameters of the food processor according to the food demand information and the food state, the method further includes:

[0129] Determine the real-time state of the food processor according to the parameter comparison result;

[0130] Judge whether the real-time state matches the preset target state;

[0131] When it is judged that the real-time state matches the preset target state, perform an adjustment operation on the operation control parameters according to the real-time state to generate target control parameters;

[0132] Wherein, the target control parameters include one or more of reducing the motor speed of the food processor and stopping the motor operation of the food processor.

[0133] In this optional embodiment, optionally, the real-time state of the food processor may include one or more of a waterless state, a no-food state, a water state, a food state, a start state, and a shutdown state.

[0134] In this optional embodiment, optionally, the preset target state may include a waterless state and / or a no-food state; the above judgment of whether the real-time state matches the preset target state may include: judging whether the real-time state is the same as the preset target state. When it is judged that the real-time state is the same as the preset target state, the real-time state matches the preset target state; when it is judged that the real-time state is different from the preset target state, the real-time state does not match the preset target state.

[0135] In this alternative embodiment, optionally, for example, when it is determined that the real-time state matches the preset target state, it indicates that the food processor is currently in a state without water and / or without food. At this time, the generated target control parameters are used to control the motor speed in the food processor to decrease or stop the motor operation in the food processor. This can reduce the operation sound of the food processor in the state without water and / or without food, enable the food processor to be in a quiet state when the user is not using it, and is beneficial to improving the comfort of the user when using the food processor.

[0136] In this alternative embodiment, further optionally, the above method may further include:

[0137] When it is determined that the real-time state does not match the preset target state, determine whether the real-time state matches the operation control parameters. When it is determined that the real-time state matches the operation control parameters, control the food processor to perform a control operation matching the operation control parameters;

[0138] When it is determined that the real-time state does not match the operation control parameters, determine the predicted operation state of the food processor according to the operation control parameters, analyze the state difference parameter between the real-time state and the predicted operation state, generate the target control parameters of the food processor according to the state difference parameter, and control the food processor to perform a control operation matching the target control parameters.

[0139] In this alternative embodiment, optionally, for example, if it is detected that the real-time state indicates that the food in the food processor is too thick, the operation control parameters indicate that the rotation speed of the food processor is low and the predicted operation state is that the food in the food processor will be predicted to be in a thick state, then it is determined that the real-time state does not match the operation control parameters, and the target control parameters of the food processor are generated according to the state difference parameter. The target control parameters include increasing the rotation speed and rotation duration of the motor in the food processor.

[0140] It can be seen that implementing this optional embodiment can determine the real-time state of the food processor according to the parameter comparison result, and judge whether the real-time state matches the preset target state. If they match, adjust the operation control parameters according to the real-time state to generate target control parameters. By monitoring the operation state of the food processor in real time and comparing it with the preset target state, it can ensure that the cooking process always develops in the direction expected by the user, which is beneficial to improving the operation accuracy and reliability of the food processor, and is also beneficial to improving the operation intelligence of the food processor. And by monitoring and adjusting the parameters in real time, it can achieve dynamic adjustment of the control parameters, and can ensure that the device completes the cooking task in the shortest time, improve the operation efficiency of the device, reduce the waiting time of the user, and thus improve the convenience, efficiency and comfort of the user using the food processor. By detecting whether the food processor is in a state of no water or no food before starting, and monitoring the device state in real time during cooking, it can effectively avoid device damage caused by idling or overload. And by reducing the motor speed or stopping the motor operation, it can reduce the noise and vibration during device operation, improve the user experience, and at the same time extend the service life of the device. The user can set the target state according to their own needs (such as taste, temperature), and the system will automatically adjust the parameters to meet these needs, providing a highly personalized cooking experience. The user does not need to manually adjust the parameters or frequently check the cooking state, and the system will automatically complete the adjustment. The user only needs to wait for the final result, which greatly simplifies the operation process. And by monitoring and dynamically adjusting the parameters in real time, it reflects a high level of intelligence, which is beneficial to improving the accuracy and intelligence of food taste detection, thus enhancing the overall cooking experience of the user, and is also beneficial to improving the convenience and comfort of the user using the food processor.

[0141] In another optional embodiment, the operation control parameters of the food processor are generated according to the food demand information and the food state, including:

[0142] Determine the required state of the target food according to the food demand information, and determine the state difference parameter between the required state and the food state;

[0143] Based on the state difference parameter, determine the state regulation parameter that matches the state difference parameter, and generate the operation control parameters of the food processor according to the state regulation parameter.

[0144] In this optional embodiment, optionally, the required state of the target food is the state required by the target food corresponding to the food demand information.

[0145] In this optional embodiment, optionally, the state difference parameter between the demand state and the food state may include: performing a comparison operation on the demand state and the food state to obtain a state difference value, and generating a state difference parameter between the demand state and the food state based on the state difference value. For example, performing a comparison operation on the demand state and the food state to calculate the hardness difference value, water content difference value, viscosity difference value, mass difference value, quantity difference value, temperature difference value, etc. between the demand state and the food state, and generating a state difference parameter between the demand state and the food state based on all the difference values.

[0146] In this optional embodiment, optionally, determining the state regulation parameter matching the state difference parameter based on the state difference parameter may include: determining at least one regulation parameter matching the state difference parameter from a pre-determined parameter set based on the state difference parameter, and generating a state regulation parameter matching the state difference parameter based on all the regulation parameters. For example, in order to make the soy milk change from thick to smooth, one or more operations such as increasing the water content, increasing the motor speed of the food processor, increasing the motor running duration of the food processor, and increasing the heating time may be selected.

[0147] In this optional embodiment, optionally, the operation control parameters of the food processor may include all the state regulation parameters, and the embodiments of the present invention do not make specific limitations.

[0148] In this optional embodiment, further, the food processor can also detect the state change of the food in real time through a sensor during operation. If the real-time state does not match the target state, the system will dynamically adjust the operation control parameters according to the real-time monitoring data; for example, if it is detected that the food temperature is too high, the system will reduce the heating power; if the stirring is uneven, the system will adjust the stirring speed; when the food state approaches or reaches the target state, the system will adjust the motor speed or stop the motor operation according to the real-time state to prevent over-stirring or over-cooking.

[0149] It can be seen that the implementation of this optional embodiment can determine the demand state of the target food according to the food demand information, and determine the state difference parameters between the demand state and the food state, determine the matching state control parameters based on the state difference parameters, and generate the operation control parameters of the food processor according to the state control parameters, and can ensure that the food reaches the taste and temperature expected by the user through real-time monitoring and dynamic adjustment of parameters, which is beneficial to improving the cooking quality of the food processor, and can reduce unnecessary energy consumption through precise control of the food processor, while avoiding cooking failures caused by improper parameter settings, which is beneficial to improving the accuracy and reliability of controlling the food processor, and can automatically detect the food state and adjust the parameters to avoid cooking failures caused by user misoperation, which is also beneficial to improving the intelligence of controlling the food processor, thereby enhancing the user's overall cooking experience, and can also help improve the convenience and comfort of users using the food processor.

[0150] In yet another optional embodiment, determining a second parameter corresponding to the first parameter includes:

[0151] According to the first parameter and the predetermined target association relationship, determining a second parameter matching the first parameter in a preset parameter storage library;

[0152] The preset parameter storage library includes a plurality of parameters to be selected, the target association relationship includes parameter values ​​corresponding to the target food at each preset temperature, the first parameter includes the first electrode resistance value of the target food at the preset target temperature, and the second parameter includes the second electrode resistance value matching the first parameter;

[0153] And, performing a comparison operation on the first parameter and the second parameter to obtain a parameter comparison result, including:

[0154] A comparison operation is performed on the first electrode resistance value and the second electrode resistance value to obtain a comparison difference between the first electrode resistance value and the second electrode resistance value, and the comparison difference is used as a parameter comparison result.

[0155] In this optional embodiment, optionally, the predetermined target association relationship includes parameter values ​​corresponding to the target food at each preset temperature, and further, the predetermined target association relationship may include electrode resistance values ​​corresponding to several types of target food at each preset temperature; the pre-set parameter storage library includes several parameters to be selected.

[0156] In this optional embodiment, optionally, the determining, based on the first parameter and the predetermined target association relationship, a second parameter matching the first parameter in a preset parameter repository may include:

[0157] Determine the parameter values corresponding to the target food at each preset temperature according to the first parameter and the pre-determined target association relationship, and determine the second parameter that matches the first parameter and the preset target temperature in the parameter repository according to the preset target temperature.

[0158] In this optional embodiment, further optionally, if the parameter comparison result is used to indicate a large parameter difference, it is determined that the food processor is currently in a state of no water and / or no food; if the parameter comparison result is greater than the reference parameter value corresponding to the pre-determined parameter correspondence, it is determined that the taste of the target food in the food processor is bland, and if the parameter comparison result is less than the reference parameter value corresponding to the pre-determined parameter correspondence, it is determined that the taste of the target food in the food processor is rich.

[0159] It can be seen that implementing this optional embodiment can determine the second parameter that matches the first parameter in the pre-set parameter repository according to the first parameter and the pre-determined target association relationship. Among them, the first parameter includes the first electrode resistance value of the target food at the preset target temperature, and the second parameter includes the second electrode resistance value that matches the first parameter. Performing a comparison operation on the first electrode resistance value and the second electrode resistance value to obtain a comparison difference and then obtaining a parameter comparison result can facilitate improving the accuracy and reliability of obtaining the parameter comparison result through the difference comparison between the electrode resistance values. Thus, it can achieve more precise control of the food state to improve the cooking quality, and can automatically adjust the parameters according to the change of the resistance value to achieve intelligent cooking. Through real-time monitoring and dynamic adjustment, it can effectively avoid cooking failures caused by improper parameter settings, and can also perform personalized control and adjustment on the food processor according to the needs of the food state, which is beneficial to improving the matching degree between the food state of the target food and the user's needs. Furthermore, it is also beneficial to improve the intelligence of controlling the food processor, thereby enhancing the overall cooking experience of the user, and can also be beneficial to improving the convenience and comfort of the user using the food processor.

[0160] In another optional embodiment, based on the state difference parameter, determine the state regulation parameter that matches the state difference parameter, and generate the operation control parameter of the food processor according to the state regulation parameter, including:

[0161] Based on the state difference parameter, analyze the difference factor between the required state and the food state, and determine the state regulation parameter that matches the difference factor according to the difference factor in combination with the pre-determined food characteristic prediction model;

[0162] According to the state regulation parameter, predict the predicted regulation result after the food processor performs the regulation operation that matches the state regulation parameter, and determine whether the predicted regulation result matches the required state;

[0163] When it is determined that the predicted regulation result matches the demand state, operating control parameters of the food processor are generated according to the state regulation parameters;

[0164] Among them, the operating control parameters include one or more of the operating duration control parameter of the food processor, the motor speed control parameter of the food processor, and the heating power control parameter of the food processor.

[0165] In this optional embodiment, optionally, the difference factors between the demand state and the food state may include one or more of the temperature difference, humidity difference, mass difference, volume difference, water content difference, and thickness difference between the demand state and the food state.

[0166] In this optional embodiment, optionally, the pre-determined food property prediction model is a food property prediction model pre-trained to convergence. For example, through the pre-determined food property prediction model, the state regulation parameters matching the difference factors are calculated; if the goal is to increase the temperature of the food, the model will calculate the heating power that needs to be increased according to the difference between the current temperature and the target temperature; further, the state regulation parameters may include one or more of heating power, stirring speed, running time, etc., and the specific parameters are determined according to the difference factors and the food property model.

[0167] In this optional embodiment, optionally, predicting the predicted regulation result after the food processor performs the regulation operation matching the state regulation parameters according to the state regulation parameters may include: inputting the state regulation parameters and the food state into the pre-determined simulation operation model, and simulating the result after the food processor performs the regulation operation through the simulation operation model to obtain the predicted regulation result. For example, if the heating power is adjusted, predict the change in food temperature.

[0168] In this optional embodiment, optionally, the predicted result is compared with the user demand state to determine whether they match. If the predicted result is consistent with the demand state, it means that the state regulation parameters are reasonable. Then, according to the state regulation parameters, the operating control parameters of the food processor are generated, and the food processor is controlled to perform the operating operation matching the operating control parameters.

[0169] In this optional embodiment, further optionally, when it is determined that the predicted regulation result does not match the demand state, a dynamic adjustment operation or a control mode switching is performed on the state regulation parameters according to the predicted regulation result and the demand state until the predicted regulation result matches the demand state; for example, for harder ingredients, the heating time or stirring intensity can be appropriately increased to make the predicted regulation result match the demand state.

[0170] It can be seen that implementing this optional embodiment can analyze the difference factor between the demand state and the food state based on the state difference parameter, and determine the state regulation parameter matching the difference factor according to the difference factor and the pre-determined food characteristic prediction model. Predict the predicted regulation result after the food processor performs the regulation operation matching the state regulation parameter according to the state regulation parameter and determine whether the predicted regulation result matches the demand state. If they match, generate the operation control parameter according to the state regulation parameter. It can determine the state regulation parameter by analyzing the difference factor between the demand state and the food state and combining the food characteristic prediction model, and can achieve precise cooking control. It can dynamically adjust the operation parameters according to the specific needs of users (such as taste, temperature, quantity), so as to meet the personalized cooking needs of users. And only when the prediction result is consistent with the demand state, the final operation control parameter will be generated. Through this kind of pre-judgment mechanism, cooking failures caused by unreasonable parameter settings can be effectively avoided, the cooking success rate can be improved, and through the combination of intelligent algorithms and real-time monitoring technologies, the full-process automation from state detection to parameter generation is realized, which is beneficial to improving the accuracy and reliability of controlling the food processor, and is beneficial to improving the intelligence of controlling the food processor. During the cooking process, the device can dynamically adjust the operation parameters according to the real-time monitoring data to ensure that the cooking state always meets the expected goal. This kind of dynamic adjustment mechanism not only improves the cooking quality, but also can adapt to the changes of different ingredients and environmental conditions. By precisely controlling the heating power, stirring speed and operation time, the system can optimize the energy use, reduce unnecessary energy consumption, which is beneficial to improving the matching degree between the food state of the target food and the user's needs, and further beneficial to improving the intelligence of controlling the food processor, thus enhancing the overall cooking experience of users, and also beneficial to improving the convenience and comfort of users using the food processor.

[0171] In another optional embodiment, before generating the operation control parameter of the food processor according to the food demand information and the food state, the method further includes:

[0172] Obtain the historical record information of the target user for the target food, where the historical record information includes one or more of the historical operation record information and the historical preference setting information of the target user for the target food within a preset historical time period;

[0173] Perform an information fitting operation on the historical record information and the food demand information to obtain an information fitting result; the information fitting result at least includes the historical record information and the food demand information;

[0174] Wherein, generating the operation control parameter of the food processor according to the food demand information and the food state includes:

[0175] Generate the operation control parameters of the food processor according to the information fitting result and the food state;

[0176] Moreover, before generating the operation control parameters of the food processor according to the information fitting result and the food state, the method further includes:

[0177] Judge whether the information fitting result meets the preset food processing conditions;

[0178] When it is judged that the information fitting result meets the preset food processing conditions, trigger the operation of generating the operation control parameters of the food processor according to the information fitting result and the food state;

[0179] When it is judged that the information fitting result does not meet the preset food processing conditions, based on the preset food processing conditions, perform an adjustment operation on the information fitting result, and re-trigger the operation of judging whether the information fitting result meets the preset food processing conditions.

[0180] In this optional embodiment, optionally, the historical operation record information of the target user for the target food within the preset historical time period includes operation information such as the cooking mode, temperature, time, stirring speed, etc. set by the target user for the target food; the historical preference setting information includes setting information such as the texture preference (such as soft and glutinous, crispy and tender), temperature preference (such as hot, warm, cold), etc. set by the target user for the target food.

[0181] In this optional embodiment, optionally, performing the information fitting operation on the historical record information and the food demand information to obtain the information fitting result may include: performing the information fitting operation on the historical record information and the food demand information through a pre-set target algorithm to obtain the information fitting result, where the target algorithm may include one or more of a data fusion algorithm, a weighted average algorithm, and a machine learning algorithm, and the obtained information fitting result may include information comprehensively considering the user's historical preferences and current needs. Further optionally, the information fitting result may further include the user's potential preference information derived from historical data.

[0182] In this optional embodiment, optionally, the operation control parameters of the food processor may include one or more of the motor speed, heating power, operation time, etc. of the food processor, and the embodiments of the present invention do not make specific limitations; further, the specific parameters are dynamically adjusted according to the information fitting result and the food state.

[0183] In this optional embodiment, optionally, performing the adjustment operation on the information fitting result based on the preset food processing conditions may include:

[0184] Based on preset food cooking conditions, determine the factors to be adjusted, where the factors to be adjusted include one or more of a food characteristic adjustment factor, a cooking safety adjustment factor, a demand adjustment factor, and a parameter range adjustment factor; determine the factor adjustment parameters corresponding to each factor to be adjusted, and perform an adjustment operation on the information fitting result according to each factor to be adjusted and the factor adjustment parameters corresponding to each factor to be adjusted.

[0185] In this optional embodiment, optionally, for example, if no ingredients are detected or the water volume is insufficient, adjust the information fitting operation to adjust the parameters to avoid the equipment running idly, or if the fitting result may cause the equipment to overheat, adjust the heating parameters to ensure safe operation; after the adjustment is completed, re-determine whether the adjusted information fitting result meets the preset food cooking conditions. If it still does not meet the conditions, repeat the adjustment operation until it meets the conditions.

[0186] It can be seen that implementing this optional embodiment can obtain the historical record information of the target user for the target food and perform an information fitting operation on the historical record information and the food demand information to obtain an information fitting result, generate the operation control parameters of the food processor according to the information fitting result and the food state, and determine whether the information fitting result meets the preset food cooking conditions. If it meets, trigger the operation of generating the operation control parameters of the food processor according to the information fitting result and the food state. If it does not meet, perform an adjustment operation on the information fitting result based on the preset food cooking conditions and re-trigger the operation of determining whether the information fitting result meets the preset food cooking conditions. It can more accurately understand the user's cooking habits and preferences. Combining the current food demand information, it can generate operation control parameters that better meet the user's expectations, which is beneficial to improving the intelligence and convenience of the user using the food processor. And through the verification and adjustment of the preset conditions, it can ensure that the generated operation control parameters are reasonable and feasible, thereby improving the success rate of cooking. Through information fitting and condition judgment, it can automatically optimize the operation control parameters, and can also learn the user's preference changes through machine learning algorithms to further improve the intelligent decision-making ability. During the cooking process, the system can dynamically adjust the operation parameters according to the real-time monitoring data to ensure that the cooking state always meets the expected goal, which is further beneficial to improving the intelligence of controlling the food processor, thereby enhancing the user's overall cooking experience, and is also beneficial to improving the convenience and comfort of the user using the food processor.

[0187] Embodiment III

[0188] Please refer to Figure 3 , Figure 3 which is a schematic structural diagram of an intelligent detection device applied to a food processor disclosed in an embodiment of the present invention. As Figure 3 shown, the intelligent detection device applied to the food processor may include:

[0189] An acquisition module 301, configured to acquire a first parameter of a target food in a food processor at a preset target temperature;

[0190] A determination module 302, configured to determine a second parameter corresponding to the first parameter;

[0191] A comparison module 303, configured to perform a comparison operation on the first parameter and the second parameter to obtain a parameter comparison result;

[0192] The determination module 302 is further configured to determine a taste detection result of the target food according to a pre-determined parameter correspondence and the parameter comparison result.

[0193] It can be seen that implementing Figure 3 The described device can acquire a first parameter of a target food in a food processor at a preset target temperature and determine a corresponding second parameter, perform a comparison operation on the first parameter and the second parameter to obtain a parameter comparison result, and determine a taste detection result of the target food according to a pre-determined parameter correspondence and the parameter comparison result. It can realize intelligent detection of the taste of the food in the food processor, achieve precise quantitative evaluation of the food taste, and judge the food state based on the parameter comparison result to realize taste detection, making the taste judgment more scientific and accurate, which is beneficial to improving the accuracy and intelligence of food taste detection, thereby enhancing the overall cooking experience of users, and can also be beneficial to improving the convenience and comfort of users using the food processor.

[0194] In an alternative embodiment, as Figure 4 shown, the determination module 302 is further configured to determine the food state of the target food according to the parameter comparison result;

[0195] The acquisition module 301 is further configured to acquire food requirement information of the target user for the target food;

[0196] The device further includes:

[0197] A generation module 304, configured to generate operation control parameters of the food processor according to the food requirement information and the food state;

[0198] Wherein, the food requirement information includes one or more of taste requirement information, quantity requirement information, and temperature requirement information of the target user for the target food.

[0199] It can be seen that implementing Figure 4The described device can determine the food state of the target food based on the parameter comparison result, obtain the food demand information of the target user for the target food, and generate the operation control parameters of the food processor according to the food demand information and the food state. It can comprehensively generate the operation control parameters of the food processor by combining the food state of the target food and the food demand information of the target user, so that the matching degree between the operation process and the operation result of the food processor and the user's needs is higher, and it can meet the diverse needs of the user for the target food. And by determining the food state and combining the food demand information to generate the operation control parameters, it can accurately control the cooking process, which is beneficial to improving the accuracy and intelligence of controlling the food processor, and reflects the high level of intelligence of the food processor, achieving more accurate control. Furthermore, it is beneficial to improve the accuracy and intelligence of food taste detection, thereby enhancing the overall cooking experience of the user, and it can also improve the convenience and comfort of the user using the food processor.

[0200] In another optional embodiment, as Figure 4 shown, the determination module 302 is further configured to determine the real-time state of the food processor according to the parameter comparison result after the generation module 304 generates the operation control parameters of the food processor according to the food demand information and the food state;

[0201] The device further includes:

[0202] The first judgment module 305 is configured to judge whether the real-time state matches the preset target state;

[0203] The generation module 304 is further configured to, when the first judgment module 305 judges that the real-time state matches the preset target state, perform an adjustment operation on the operation control parameters according to the real-time state to generate target control parameters;

[0204] Wherein, the target control parameters include one or more of reducing the motor speed of the food processor and stopping the motor operation of the food processor.

[0205] It can be seen that implementing Figure 4The described device can determine the real-time state of the food processor based on the parameter comparison result, and judge whether the real-time state matches the preset target state. If it matches, it can perform an adjustment operation on the operation control parameters according to the real-time state to generate the target control parameters. It can monitor the operation state of the food processor in real time and compare it with the preset target state, which can ensure that the cooking process always develops in the direction expected by the user, is beneficial to improving the operation accuracy and reliability of the food processor, and is beneficial to improving the operation intelligence of the food processor. And by monitoring and adjusting the parameters in real time, it can realize the dynamic adjustment of the control parameters, and can ensure that the device completes the cooking task in the shortest time, improve the operation efficiency of the device, reduce the waiting time of the user, and then improve the convenience, efficiency and comfort of the user using the food processor. By detecting whether the food processor is in a state of no water or no food before starting and monitoring the device state in real time during cooking, it can effectively avoid device damage caused by idling or overload, and by reducing the motor speed or stopping the motor operation, it can reduce the noise and vibration during device operation, improve the user experience, and at the same time extend the service life of the device. The user can set the target state according to their own needs (such as taste, temperature), and the system will automatically adjust the parameters to meet these needs, providing a highly personalized cooking experience. The user does not need to manually adjust the parameters or frequently check the cooking state, and the system will automatically complete the adjustment. The user only needs to wait for the final result, which greatly simplifies the operation process. And by monitoring and dynamically adjusting the parameters in real time, it reflects a high level of intelligence, which is beneficial to improving the accuracy and intelligence of food taste detection, thereby enhancing the overall cooking experience of the user, and is also beneficial to improving the convenience and comfort of the user using the food processor.

[0206] In another optional embodiment, as Figure 4 shown, the specific manner in which the generation module 304 generates the operation control parameters of the food processor according to the food demand information and the food state includes:

[0207] Determine the required state of the target food according to the food demand information, and determine the state difference parameter between the required state and the food state;

[0208] Based on the state difference parameter, determine the state regulation parameter that matches the state difference parameter, and generate the operation control parameter of the food processor according to the state regulation parameter.

[0209] It can be seen that implementing Figure 4The described device can determine the demand status of the target food based on the food demand information, determine the status difference parameter between the demand status and the food status, determine the matching status adjustment parameter based on the status difference parameter, and generate the operation control parameter of the food processor according to the status adjustment parameter. It can ensure that the food reaches the desired taste and temperature of the user through real-time monitoring and dynamic parameter adjustment, which is beneficial to improving the cooking quality of the food processor. And it can reduce unnecessary energy consumption through precise control of the food processor, while avoiding cooking failures caused by improper parameter settings, which is beneficial to improving the accuracy and reliability of controlling the food processor. In addition, it can automatically detect the food status and adjust the parameters to avoid cooking failures caused by user misoperations, which is further beneficial to improving the intelligence of controlling the food processor, thereby enhancing the overall cooking experience of the user. It can also be beneficial to improve the convenience and comfort of the user when using the food processor.

[0210] In another optional embodiment, as Figure 4 shown, the specific manner in which the determination module 302 determines the second parameter corresponding to the first parameter includes:

[0211] Determine the second parameter that matches the first parameter in the pre-set parameter repository according to the first parameter and the pre-determined target association relationship;

[0212] Among them, the pre-set parameter repository includes a number of candidate parameters, the target association relationship includes the parameter values corresponding to the target food at each preset temperature, the first parameter includes the first electrode resistance value of the target food at the preset target temperature, and the second parameter includes the second electrode resistance value that matches the first parameter;

[0213] And, the specific manner in which the comparison module 303 performs a comparison operation on the first parameter and the second parameter to obtain the parameter comparison result includes:

[0214] Perform a comparison operation on the first electrode resistance value and the second electrode resistance value to obtain the comparison difference between the first electrode resistance value and the second electrode resistance value, and use the comparison difference as the parameter comparison result.

[0215] It can be seen that implementing Figure 4The described device can determine a second parameter that matches the first parameter in a preset parameter repository according to the first parameter and a pre-determined target association relationship. Among them, the first parameter includes the first electrode resistance value of the target food at a preset target temperature, and the second parameter includes the second electrode resistance value that matches the first parameter. By performing a comparison operation on the first electrode resistance value and the second electrode resistance value to obtain a comparison difference, and then obtaining a parameter comparison result, it is beneficial to improve the accuracy and reliability of the parameter comparison result through the difference comparison between the electrode resistance values. Thus, it can more precisely control the food state to improve the cooking quality, and can automatically adjust parameters according to the change of the resistance value to achieve intelligent cooking. Through real-time monitoring and dynamic adjustment, it can effectively avoid cooking failures caused by improper parameter settings. It can also perform personalized control and adjustment on the food processor according to the requirements of the food state, which is beneficial to improve the matching degree between the food state of the target food and the user's needs. Furthermore, it is beneficial to improve the intelligence of controlling the food processor, thereby enhancing the overall cooking experience of the user. It is also beneficial to improve the convenience and comfort of the user when using the food processor.

[0216] In yet another alternative embodiment, as Figure 4 shown, the specific manner in which the generation module 304 determines a state regulation parameter that matches the state difference parameter based on the state difference parameter and generates an operation control parameter for the food processor according to the state regulation parameter includes:

[0217] Based on the state difference parameter, analyze the difference factors between the required state and the food state, and determine a state regulation parameter that matches the difference factors in combination with a pre-determined food characteristic prediction model;

[0218] According to the state regulation parameter, predict the predicted regulation result after the food processor performs a regulation operation that matches the state regulation parameter, and determine whether the predicted regulation result matches the required state;

[0219] When it is determined that the predicted regulation result matches the required state, generate an operation control parameter for the food processor according to the state regulation parameter;

[0220] Among them, the operation control parameter includes one or more of the operation duration control parameter of the food processor, the motor speed control parameter of the food processor, and the heating power control parameter of the food processor.

[0221] It can be seen that implementing Figure 4The described device can analyze the difference factor between the demand state and the food state based on the state difference parameter, and determine the state regulation parameter matching the difference factor according to the difference factor and the pre-determined food characteristic prediction model. Predict the predicted regulation result after the food processor performs the regulation operation matching the state regulation parameter according to the state regulation parameter and determine whether the predicted regulation result matches the demand state. If it matches, generate the operation control parameter according to the state regulation parameter. It can determine the state regulation parameter by analyzing the difference factor between the demand state and the food state and combining the food characteristic prediction model, and can achieve precise cooking control. It can dynamically adjust the operation parameters according to the specific needs of users (such as taste, temperature, quantity), so as to meet the personalized cooking needs of users. And only when the prediction result is consistent with the demand state, will the final operation control parameter be generated. Through this kind of pre-judgment mechanism, it can effectively avoid cooking failures caused by unreasonable parameter settings, improve the cooking success rate, and through the combination of intelligent algorithms and real-time monitoring technologies, realize the full-process automation from state detection to parameter generation, which is beneficial to improving the accuracy and reliability of controlling the food processor, and is beneficial to improving the intelligence of controlling the food processor. During the cooking process, the device can dynamically adjust the operation parameters according to the real-time monitoring data to ensure that the cooking state always meets the expected goal. This kind of dynamic adjustment mechanism not only improves the cooking quality, but also can adapt to the changes of different ingredients and environmental conditions. By precisely controlling the heating power, stirring speed and operation time, the system can optimize the energy use, reduce unnecessary energy consumption, which is beneficial to improving the matching degree between the food state of the target food and the user's needs, and further beneficial to improving the intelligence of controlling the food processor, thereby enhancing the overall cooking experience of users, and also beneficial to improving the convenience and comfort of users using the food processor.

[0222] In another alternative embodiment, as Figure 4 shown, the obtaining module 301 is further configured to obtain the historical record information of the target user for the target food before the generating module 304 generates the operation control parameter of the food processor according to the food demand information and the food state, where the historical record information includes one or more of the historical operation record information and the historical preference setting information of the target user for the target food within the preset historical time period;

[0223] The device further includes:

[0224] The fitting module 306 is configured to perform an information fitting operation on the historical record information and the food demand information to obtain an information fitting result; the information fitting result at least includes the historical record information and the food demand information;

[0225] Wherein, the specific manner in which the generating module 304 generates the operation control parameter of the food processor according to the food demand information and the food state includes:

[0226] Generate the operation control parameters of the food processor according to the information fitting result and the food state;

[0227] Moreover, the device further includes:

[0228] A second judgment module 307, configured to judge whether the information fitting result meets the preset food processing conditions before the generation module 304 generates the operation control parameters of the food processor according to the information fitting result and the food state; when it is judged that the information fitting result meets the preset food processing conditions, trigger the generation module 304 to perform the operation of generating the operation control parameters of the food processor according to the information fitting result and the food state;

[0229] An adjustment module 308, configured to, when the second judgment module 307 judges that the information fitting result does not meet the preset food processing conditions, perform an adjustment operation on the information fitting result based on the preset food processing conditions, and re-trigger the second judgment module 307 to perform the operation of judging whether the information fitting result meets the preset food processing conditions.

[0230] It can be seen that implementing Figure 4 The described device can obtain the historical record information of the target user for the target food, perform an information fitting operation on the historical record information and the food demand information to obtain an information fitting result, generate the operation control parameters of the food processor according to the information fitting result and the food state, and judge whether the information fitting result meets the preset food processing conditions. If it meets, it triggers the execution of the operation of generating the operation control parameters of the food processor according to the information fitting result and the food state. If it does not meet, it performs an adjustment operation on the information fitting result based on the preset food processing conditions and re-triggers the execution of the operation of judging whether the information fitting result meets the preset food processing conditions. It can more accurately understand the user's cooking habits and preferences, and combined with the current food demand information, can generate operation control parameters that better meet the user's expectations, which is beneficial to improving the intelligence and convenience of the user's use of the food processor. And through the verification and adjustment of the preset conditions, it can ensure that the generated operation control parameters are reasonable and feasible, thereby improving the success rate of cooking. Through information fitting and condition judgment, it can automatically optimize the operation control parameters, and can also learn the user's preference changes through machine learning algorithms to further improve the intelligent decision-making ability. During the cooking process, the system can dynamically adjust the operation parameters according to the real-time monitoring data to ensure that the cooking state always meets the expected goal, which is further beneficial to improving the intelligence of controlling the food processor, thereby enhancing the user's overall cooking experience, and is also beneficial to improving the convenience and comfort of the user's use of the food processor.

[0231] Embodiment 4

[0232] Please refer toFigure 5 , Figure 5 is a schematic structural diagram of another intelligent detection device applied to a food processor disclosed in an embodiment of the present invention. As Figure 5 shown, the intelligent detection device applied to a food processor may include:

[0233] a memory 401 storing executable program codes;

[0234] a processor 402 coupled to the memory 401;

[0235] The processor 402 calls the executable program codes stored in the memory 401 and executes the steps in the intelligent detection method applied to a food processor described in Embodiment 1 or Embodiment 2 of the present invention.

[0236] Embodiment 5

[0237] An embodiment of the present invention discloses a computer storage medium storing computer instructions, which are used to execute the steps in the intelligent detection method applied to a food processor described in Embodiment 1 or Embodiment 2 of the present invention when the computer instructions are called.

[0238] Embodiment 6

[0239] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute the steps in the intelligent detection method applied to a food processor described in Embodiment 1 or Embodiment 2.

[0240] The device embodiments described above are only illustrative. The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed to multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative labor.

[0241] Through the specific descriptions of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the above technical solutions, in essence, or the part that contributes to the prior art can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, and the storage medium includes read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc memories, magnetic disk memories, tape memories, or any other computer-readable medium capable of carrying or storing data.

[0242] Finally, it should be noted that: the intelligent detection method and device for a food processor disclosed in the embodiments of the present invention only disclose the preferred embodiments of the present invention, which are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments or perform equivalent replacements on some of the technical features; and these modifications 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.

Claims

1. An intelligent detection method applied to a food processor, characterized in that: The method comprises: Acquire a first parameter of a target food in the food processor at a preset target temperature, and determine a second parameter corresponding to the first parameter; Performing a comparison operation on the first parameter and the second parameter to obtain a parameter comparison result; The taste detection result of the target food is determined according to the predetermined parameter correspondence and the parameter comparison result.

2. The intelligent detection method for a food processor according to claim 1, characterized in that: The method further comprises: Determining the food state of the target food according to the parameter comparison result; Acquiring food demand information of a target user for the target food, and generating operation control parameters of the food cooking machine according to the food demand information and the food state; The food demand information includes one or more of the target user's taste demand information, quantity demand information, and temperature demand information for the target food.

3. The intelligent detection method for a food processor according to claim 2, characterized in that: After generating the operation control parameters of the food processor according to the food demand information and the food status, the method further includes: Determining the real-time status of the food processor according to the parameter comparison result; Determining whether the real-time state matches a preset target state; When it is determined that the real-time state matches the preset target state, an adjustment operation is performed on the operation control parameter according to the real-time state to generate a target control parameter; The target control parameter includes one or more of reducing the motor speed of the food processor and stopping the motor of the food processor.

4. The intelligent detection method for a food processor according to claim 2, characterized in that: The step of generating the operation control parameters of the food processor according to the food demand information and the food state includes: Determining a demand state of the target food according to the food demand information, and determining a state difference parameter between the demand state and the food state; Based on the state difference parameter, a state control parameter matching the state difference parameter is determined, and according to the state control parameter, an operation control parameter of the food processor is generated.

5. The intelligent detection method for a food processor according to claim 3, characterized in that: The determining a second parameter corresponding to the first parameter includes: Determining, in a preset parameter repository, a second parameter matching the first parameter according to the first parameter and the predetermined target association relationship; The preset parameter storage library includes a plurality of parameters to be selected, the target association relationship includes parameter values ​​corresponding to the target food at each preset temperature, the first parameter includes a first electrode resistance value of the target food at the preset target temperature, and the second parameter includes a second electrode resistance value matching the first parameter; And, performing a comparison operation on the first parameter and the second parameter to obtain a parameter comparison result includes: A comparison operation is performed on the first electrode resistance value and the second electrode resistance value to obtain a comparison difference between the first electrode resistance value and the second electrode resistance value, and the comparison difference is used as a parameter comparison result.

6. The intelligent detection method for a food processor according to claim 4, characterized in that: The determining, based on the state difference parameter, a state control parameter matching the state difference parameter, and generating an operation control parameter of the food processor according to the state control parameter, includes: Based on the state difference parameter, analyzing the difference factor between the demand state and the food state, and determining the state control parameter matching the difference factor according to the difference factor combined with a predetermined food characteristic prediction model; According to the state control parameter, predicting a predicted control result after the food processor performs a control operation matching the state control parameter, and determining whether the predicted control result matches the required state; When it is determined that the prediction and control result matches the demand state, generating an operation control parameter of the food processor according to the state control parameter; The operation control parameters include one or more of an operation time control parameter of the food processor, a motor speed control parameter of the food processor, and a heating power control parameter of the food processor.

7. The intelligent detection method for a food processor according to claim 2, characterized in that: Before generating the operation control parameters of the food processor according to the food demand information and the food status, the method further includes: Acquire the target user's historical record information on the target food, wherein the historical record information includes one or more of the target user's historical operation record information and historical preference setting information on the target food within a preset historical time period; Performing an information fitting operation on the historical record information and the food demand information to obtain an information fitting result; the information fitting result at least includes the historical record information and the food demand information; The step of generating the operation control parameters of the food processor according to the food demand information and the food status includes: generating operation control parameters of the food processor according to the information fitting result and the food state; Furthermore, before generating the operation control parameters of the food processor according to the information fitting result and the food state, the method further includes: Determining whether the information fitting result meets the preset food cooking conditions; When it is determined that the information fitting result satisfies the preset food cooking condition, the operation of generating the operation control parameters of the food cooking machine according to the information fitting result and the food state is triggered; When it is determined that the information fitting result does not meet the preset food cooking conditions, an adjustment operation is performed on the information fitting result based on the preset food cooking conditions, and the operation of determining whether the information fitting result meets the preset food cooking conditions is re-triggered.

8. An intelligent detection device for a food processor, characterized in that: The device comprises: An acquisition module, used for acquiring a first parameter of a target food in the food processor at a preset target temperature; A determination module, used to determine a second parameter corresponding to the first parameter; A comparison module, used for performing a comparison operation on the first parameter and the second parameter to obtain a parameter comparison result; The determination module is further used to determine the taste detection result of the target food according to the predetermined parameter correspondence and the parameter comparison result.

9. An intelligent detection device for a food processor, characterized in that: The device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the intelligent detection method applied to a food processor as described in any one of claims 1-7.

10. A computer storage medium, characterized in that: The computer storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the intelligent detection method applied to the food processing machine as described in any one of claims 1-7.

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