Cooking data analysis system and method for intelligent cooking equipment

Abstract

The invention discloses a cooking data analysis system and method for intelligent cooking equipment, and particularly relates to the field of artificial intelligence, and the system comprises a target time division module, a cooking data collection module, a cooking data preprocessing module, a cooking data analysis module, a cooking data comprehensive analysis module, a cooking data judgment module, and a man-machine interaction module. A target time division module is used for determining cooking time of a dish as a target time area, the target time area is divided into sub-time areas in an equal-time division mode, the sub-time areas in the target time area are sequentially numbered as 1, 2,..., i,..., n, and intelligent cooking equipment data are collected, preprocessed and analyzed, so that the cooking time of the dish is obtained. According to the method, the cooking comprehensive evaluation index of the intelligent cooking equipment is obtained, potential problems can be found in time, judgment and early warning can be carried out on the potential problems, and the safety of the intelligent cooking equipment is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and more specifically, to a cooking data analysis system and method for intelligent cooking equipment. Background Art

[0002] With the accelerated pace of life and the pursuit of healthy eating, more and more families are beginning to pay attention to smart cooking equipment. These devices can help families save cooking time, improve cooking efficiency, and meet the needs of healthy eating. At the same time, the catering industry's demand for smart cooking equipment is also increasing. Smart cooking equipment can improve meal delivery efficiency, ensure food quality, and reduce labor costs, bringing new development opportunities to catering companies. With the continuous development of technologies such as the Internet of Things and artificial intelligence, smart cooking equipment will become more intelligent, personalized, and diversified. Therefore, it becomes particularly important to analyze cooking data for smart cooking equipment.

[0003] The existing cooking data analysis system includes an intelligent cooking device, a user terminal and a background management system, wherein the background management system is connected to the intelligent cooking device through a communication connection method; wherein the intelligent cooking device includes a data acquisition module and a controller and a memory arranged inside the intelligent cooking device; the background management system includes a data analysis module and a data storage module; the data analysis module receives a cooking request sent from the user terminal and the collected data of the data acquisition module of the intelligent cooking device for analysis and processing, stores the processed and calculated information in the data storage module, and sends the processed information to the controller; the controller judges the status of the intelligent cooking device based on the processed information.

[0004] However, there are still some shortcomings in its actual use. For example, firstly, the abnormal behavior of intelligent cooking equipment is often caused by the combined effect of multiple factors, such as low smoke exhaust purification efficiency, cooking time and stir-frying frequency not meeting the preset requirements, etc. It is difficult for traditional cooking data analysis systems to conduct comprehensive analysis and evaluation on them. Secondly, traditional cooking data analysis systems lack intelligent early warning and alarm mechanisms, and are unable to detect potential safety hazards in a timely manner, which may lead to serious consequences. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a cooking data analysis system for an intelligent cooking device, which solves the problems raised in the above-mentioned background technology through the following scheme.

[0006] To achieve the above object, the present invention provides the following technical solution: a cooking data analysis system for an intelligent cooking device, comprising:

[0007] The target time division module is used to determine the cooking time of a dish in the intelligent cooking device as a target time zone, divide the target time zone into sub-time zones by equal time division, and number the sub-time zones in the target time zone as 1, 2, ..., i, ..., n in sequence;

[0008] The cooking data collection module includes an ingredient maturity collection unit and an environment safety collection unit, wherein the ingredient maturity collection unit is used to collect ingredient data and maturity data of each sub-time zone in the target time zone, and transmit the collected data to the cooking data preprocessing module, and the environment safety collection unit is used to collect environment safety data of each sub-time zone in the target time zone, and transmit the collected data to the cooking data preprocessing module;

[0009] The cooking data preprocessing module includes an ingredient maturity preprocessing unit and an environmental safety preprocessing unit. The ingredient maturity preprocessing unit is used to preprocess the data transmitted by the cooking data acquisition module to obtain an ingredient processing coefficient and a cooking maturity coefficient, and transmit the preprocessed data to the cooking data analysis module. The environmental safety preprocessing unit preprocesses the data transmitted by the cooking data acquisition module to obtain a smoke concentration fluctuation coefficient and an environmental humidity fluctuation coefficient, and transmits the preprocessed data to the cooking data analysis module.

[0010] The cooking data analysis module includes an ingredient maturity analysis unit and an environmental safety analysis unit. The ingredient maturity analysis unit is used to analyze the data transmitted by the cooking data preprocessing module to obtain an ingredient maturity assessment coefficient, and transmit the analyzed data to the cooking data comprehensive analysis module. The environmental safety analysis unit is used to analyze the data transmitted by the cooking data preprocessing module to obtain an environmental safety assessment coefficient, and transmit the analyzed data to the cooking data comprehensive analysis module.

[0011] The cooking data comprehensive analysis module is used to establish a cooking data comprehensive analysis model, import the food maturity assessment coefficient and the environmental safety assessment coefficient into the cooking data comprehensive analysis model, calculate the cooking comprehensive assessment index, and transmit the data to the cooking data judgment module;

[0012] The cooking data judgment module is used to establish a preset value of the cooking comprehensive evaluation index, judge the cooking comprehensive evaluation index of the target time zone according to the preset value of the cooking comprehensive evaluation index, and send a signal to the human-computer interaction module according to the judgment result;

[0013] The human-computer interaction module is used to receive and judge the signal transmitted by the cooking data judgment module. If the signal transmitted in the cooking data judgment module is signal a, the system will maintain data collection, preprocessing and analysis of the intelligent cooking equipment. If the signal transmitted in the cooking data judgment module is signal b, the system will warn the management personnel and display abnormal data on the terminal display screen to remind the management personnel of the intelligent cooking equipment with abnormal behavior. The management personnel will handle and repair the type of intelligent cooking equipment with abnormal behavior.

[0014] Preferably, the cooking time of the dish is determined by pre-setting different cooking times according to different cooking types. For example, the frying time of vegetable ingredients is shorter, approximately between a few minutes and more than ten minutes, while meat ingredients require a longer frying time; cooking types include steaming, frying, braising, etc.; the time interval is preset by installing a counter on the intelligent cooking equipment, and the appropriate time division accuracy is selected according to actual needs, including every minute, every half minute, every second and every half second.

[0015] Preferably, the food material data include food portion, food internal temperature, food external temperature and food water content, respectively recorded as Tq, Tc, To and Tw, and the maturity data include food cooking time, stir-frying frequency and steam volume, respectively recorded as Mt, Mp and Mw; the environmental safety collection unit includes environmental safety data, including smoke concentration, ambient humidity, smoke exhaust purification volume, respectively recorded as Ec, Ew and Eo.

[0016] Preferably, the food ripening preprocessing unit is used to establish a food ripening preprocessing model, import the food data and ripening data transmitted by the cooking data acquisition module into the food ripening preprocessing model, obtain the food processing coefficient and the cooking ripening coefficient, and the calculation formula of the cooking food coefficient is:

[0017]

[0018] where Ft i represents the food processing coefficient of the ith sub-time zone, Tc max Indicates the maximum internal temperature of food within the target time zone, Tc i represents the internal temperature of the food in the i-th sub-time zone, To max Indicates the maximum external temperature of food within the target time zone, To i represents the external temperature of the food in the ith sub-time zone, Tw i-1 represents the water content of food in the i-1th sub-time zone, Tw i represents the water content of food in the ith sub-time zone, Tq i Represents the food portion in the i-th sub-time period.

[0019] Preferably, the calculation formula of the cooking maturity coefficient is:

[0020]

[0021] Among them, Fm i represents the cooking maturity coefficient of the ith sub-time zone, Mt i represents the food cooking time in the ith sub-time zone, Mt 预 Indicates the preset food cooking time, Mp i represents the frequency of stir-frying in the ith sub-time zone, Mp max Indicates the maximum frequency of stir-frying in the target time zone, Mw i Represents the steam volume in the i-th time sub-zone.

[0022] Preferably, the environmental safety preprocessing unit is used to establish an environmental safety preprocessing model, import the environmental safety data transmitted by the cooking data acquisition module into the environmental safety preprocessing model, and obtain the smoke concentration fluctuation coefficient and the environmental humidity fluctuation coefficient. The calculation formula of the smoke concentration fluctuation coefficient is:

[0023]

[0024] Among them, Ml i represents the smoke fluctuation coefficient of the ith sub-time zone, Ec i represents the smoke density in the ith sub-time zone, Eo i It represents the smoke purification amount in the ith sub-time zone; the calculation formula of the ambient humidity fluctuation coefficient is:

[0025]

[0026] Among them, Mh i represents the environmental humidity coefficient of the i-th sub-time zone, Ew i Represents the ambient humidity of the i-th sub-time zone.

[0027] Preferably, the food maturity analysis unit is used to establish a food maturity analysis model, import the food maturity preprocessing data transmitted by the cooking data preprocessing module into the food maturity analysis model, and obtain the food maturity evaluation coefficient. The specific analysis formula of the food maturity evaluation coefficient is:

[0028]

[0029] where φ i represents the food maturity assessment coefficient of the i-th sub-time zone, Ft i represents the food processing coefficient of the ith sub-time zone, Fm i represents the cooking maturity coefficient of the i-th sub-time zone.

[0030] Preferably, the environmental safety analysis unit is used to establish an environmental safety analysis model, import the environmental safety preprocessing data transmitted by the cooking data preprocessing module into the environmental safety analysis model, and obtain an environmental safety assessment coefficient. The specific analysis formula of the environmental safety assessment coefficient is:

[0031]

[0032] where ψ i represents the environmental safety assessment coefficient of the ith sub-time zone, Ml i represents the smoke fluctuation coefficient of the ith sub-time zone, Mh i Represents the ambient humidity coefficient of the i-th sub-time zone.

[0033] Preferably, the specific analysis formula of the cooking comprehensive evaluation index is:

[0034]

[0035] Where η represents the comprehensive evaluation index of cooking in the target time zone, φ i represents the food maturity assessment coefficient of the sub-time zone, ψ i represents the environmental safety assessment coefficient of the sub-time zone, λ1 and λ2 represent the factors affecting the food maturity assessment coefficient and the environmental safety assessment coefficient, respectively.

[0036] Preferably, the preset value of the cooking comprehensive evaluation index is marked as η D , when η D ≤η, it means that the cooking comprehensive evaluation index of the target time zone is greater than or equal to the preset value of the cooking comprehensive evaluation index, indicating that the cooking ability of the intelligent cooking device is in a normal state, and a signal a is sent. When η D >η, it means that the cooking comprehensive evaluation index of the target time zone is less than the preset value of the cooking comprehensive evaluation index, indicating that the cooking ability of the intelligent cooking device is in an abnormal state, and a signal b is sent.

[0037] Preferably, the human-computer interaction module of the cooking data analysis system for the intelligent cooking device is also used to receive alarm feedback information issued by the user terminal, the alarm feedback information includes a response to the early warning of the judgment result transmitted by the cooking data judgment module, the response result includes the existence of cooking abnormalities in the equipment and the normal cooking of the equipment. When the response result is that the equipment has cooking abnormalities, the human-computer interaction module is also used to call the specific process of judging the current cooking process, and based on the analysis model of the cooking data comprehensive analysis module and the cooking data judgment module, determine the potential risks of the intelligent cooking equipment, and display the potential risk judgment results through the terminal display screen for the user to inspect and repair the intelligent cooking equipment.

[0038] Specifically, the potential risk judgment results may include intelligent cooking device failure and environmental failure, the intelligent cooking device failure may include heating source failure and flip part failure, and the environmental failure may include exhaust failure and power failure. In this way, the cooking data analysis system for the intelligent cooking device can provide feedback on the failure of the intelligent cooking device periodically or in real time, which is convenient for users to maintain the intelligent cooking device in time, which can extend the service life of the intelligent cooking device, improve cooking quality, and reduce the probability of dangerous accidents.

[0039] The present invention also provides a cooking data analysis method for an intelligent cooking device, which is applied to the cooking data analysis system for the intelligent cooking device, comprising:

[0040] S1: Dividing the target time zone: determining the cooking time of a dish in the intelligent cooking device as the target time zone, dividing the target time zone into sub-time zones by equal time division, and numbering the sub-time zones in the target time zone as 1, 2, ..., i, ..., n in sequence;

[0041] S2: Collecting cooking data: The food ripening collection unit of the cooking data collection module collects food data and ripening data of each sub-time zone in the target time zone, and transmits the collected data to the cooking data preprocessing module; the environment safety collection unit of the cooking data collection module collects environment safety data of each sub-time zone in the target time zone, and transmits the collected data to the cooking data preprocessing step;

[0042] S3: Preprocessing cooking data: The food preparation preprocessing unit of the cooking data preprocessing module preprocesses the data transmitted by the cooking data acquisition module to obtain food preparation coefficients and cooking preparation coefficients, and transmits the preprocessed data to the cooking data analysis module; the environmental safety preprocessing unit of the cooking data preprocessing module preprocesses the data transmitted by the cooking data acquisition module to obtain smoke concentration fluctuation coefficients and environmental humidity fluctuation coefficients, and transmits the preprocessed data to the cooking data analysis step;

[0043] S4: Analyze cooking data: The food maturity analysis unit of the cooking data analysis module analyzes the data transmitted by the cooking data preprocessing module to obtain the food maturity assessment coefficient, and transmits the analyzed data to the cooking data comprehensive analysis module; the environmental safety analysis unit of the cooking data analysis module analyzes the data transmitted by the cooking data preprocessing module to obtain the environmental safety assessment coefficient, and transmits the analyzed data to the comprehensive cooking data analysis step;

[0044] S5: Comprehensive analysis of cooking data: The cooking data comprehensive analysis module establishes a cooking data comprehensive analysis model, imports the food maturity assessment coefficient and the environmental safety assessment coefficient into the cooking data comprehensive analysis model, calculates the cooking comprehensive assessment index, and transmits the data to the cooking data judgment step;

[0045] S6: judging cooking data: the cooking data judging module establishes a preset value of the cooking comprehensive evaluation index, judges the cooking comprehensive evaluation index of the target time zone according to the preset value of the cooking comprehensive evaluation index, and sends a signal to the human-computer interaction module according to the judgment result;

[0046] S7: Human-computer interaction: The human-computer interaction module receives and judges the signal transmitted by the cooking data judgment module. The system warns the management personnel and displays abnormal data on the terminal display screen to remind the management personnel of the intelligent cooking equipment with abnormal behavior. The management personnel will handle the intelligent cooking equipment with abnormal behavior.

[0047] Technical effects and advantages of the present invention:

[0048] 1. The present invention divides the cooking time of a dish into multiple sub-time zones through the target time division module, which can realize the refined analysis of the intelligent cooking equipment. The data analysis of each sub-time zone can be carried out independently, so that the system can more accurately capture the subtle changes of the intelligent cooking equipment in different time periods, and provide more accurate data support for subsequent judgment and early warning; the food material data, maturity data and environmental safety data of the intelligent cooking equipment are collected in real time through the cooking data collection module, which provides an important basis for the status and safety evaluation of the intelligent cooking equipment, and grasps the operation status of the intelligent cooking equipment in real time; the collected data is pre-processed through the cooking data pre-processing module, so that the data processing is more perfect, and support is provided for the cooking data analysis module; the pre-processed data is further processed through the cooking data analysis module, and it is imported into the analysis model to calculate the food maturity evaluation coefficient and environmental safety evaluation coefficient of the intelligent cooking equipment, which can intuitively reflect the operation status of the intelligent cooking equipment in different time zones, and provide an important reference basis for the judgment and decision-making of the system;

[0049] 2. The results of the cooking data analysis module are imported into the comprehensive analysis model through the cooking data comprehensive analysis module to calculate the cooking comprehensive evaluation index, which can comprehensively reflect the overall operating status of the intelligent cooking equipment and provide a decision-making basis for the cooking data judgment module; the preset value of the cooking comprehensive evaluation index is set through the cooking data judgment module. When the cooking comprehensive evaluation index exceeds the preset value, the system will automatically issue a warning signal to remind the management personnel to deal with it in time; the warning signal is displayed on the terminal display screen through the human-computer interaction module, providing data support and judgment basis for the management personnel to deal with the intelligent cooking equipment in abnormal state, and providing important guarantee for taking timely measures to avoid the occurrence of safety accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a schematic diagram of the overall structure of the present invention.

[0051] Figure 2 The present invention is a system operation flow chart. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] As attached Figure 1 A cooking data analysis system for an intelligent cooking device is shown, comprising a target time division module, a cooking data acquisition module, a cooking data preprocessing module, a cooking data analysis module, a cooking data comprehensive analysis module, a cooking data judgment module, and a human-computer interaction module.

[0054] The output end of the target time division module is connected to the input end of the cooking data acquisition module, the output end of the cooking data acquisition module is connected to the input end of the cooking data preprocessing module, the output end of the cooking data preprocessing module is connected to the input end of the cooking data analysis module, the output end of the cooking data analysis module is connected to the input end of the cooking data comprehensive analysis module, the output end of the cooking data comprehensive analysis module is connected to the input end of the cooking data judgment module, and the output end of the cooking data judgment module is connected to the input end of the human-computer interaction module.

[0055] The target time division module is used to determine the cooking time of a dish in the intelligent cooking device as a target time area, divide the target time area into sub-time areas by equal time division, and number the sub-time areas in the target time area as 1, 2, ..., i, ..., n in sequence.

[0056] In this embodiment, it should be specifically explained that the cooking time of a dish is determined by pre-setting different cooking times according to different cooking types. For example, the frying time of vegetable ingredients is shorter, approximately between a few minutes and more than ten minutes, while meat ingredients require a longer frying time; cooking types include steaming, frying, and braising; time intervals are preset by installing a counter on the intelligent cooking device, and the appropriate time division accuracy is selected according to actual needs, including every minute, every half minute, every second, and every half second.

[0057] The cooking data collection module includes an ingredient maturity collection unit and an environmental safety collection unit, wherein the ingredient maturity collection unit is used to collect ingredient data and maturity data of each sub-time zone in the target time zone, and transmit the collected various types of data to the cooking data preprocessing module, and the environmental safety collection unit is used to collect environmental safety data of each sub-time zone in the target time zone, and transmit the collected various types of data to the cooking data preprocessing module.

[0058] In this embodiment, it should be specifically noted that the food material data includes food portion, food internal temperature, food external temperature and food water content, which are respectively recorded as Tq, Tc, To and Tw, and the maturity data includes food cooking time, stir-frying frequency and steam volume, which are respectively recorded as Mt, Mp and Mw.

[0059] In this embodiment, it should be specifically explained that the food portion is connected to the smart device through a weight sensor to measure it in real time; the internal and external temperatures of the food are measured during the food preparation process by a probe-type temperature measuring instrument; the water content of the food is measured by combining a spectral sensor with a machine learning model to measure the absorption and reflection characteristics of the food to light, and the spectral data is analyzed and classified using the machine learning model to measure the water content of the food; the food cooking time is measured by a timer installed in the system; the stir-frying frequency is set by the smart cooking device during cooking; the steam volume is measured by combining a steam sensor in the cooking chamber with a machine learning model to measure the steam concentration and temperature when making food and convert them into electrical signals, and the machine learning model is used to convert the electrical signals into digital signals to obtain the steam volume.

[0060] In this embodiment, it should be specifically explained that the environmental safety collection unit includes environmental safety data, including smoke concentration, environmental humidity, and smoke exhaust purification amount, which are respectively recorded as Ec, Ew, and Eo.

[0061] In this embodiment, it should be specifically explained that the smoke concentration is detected accurately and quickly by the oil fume concentration detector; the ambient humidity during the cooking process is measured by the humidity sensor; the exhaust purification amount is scanned by setting a professional particle scanner to scan the number of particles entering and leaving the oil fume purifier.

[0062] The cooking data preprocessing module includes an ingredient maturity preprocessing unit and an environmental safety preprocessing unit. The ingredient maturity preprocessing unit is used to preprocess the data transmitted by the cooking data acquisition module to obtain an ingredient processing coefficient and a cooking maturity coefficient, and transmit the preprocessed data to the cooking data analysis module. The environmental safety preprocessing unit preprocesses the data transmitted by the cooking data acquisition module to obtain a smoke concentration fluctuation coefficient and an environmental humidity fluctuation coefficient, and transmits the preprocessed data to the cooking data analysis module.

[0063] In this embodiment, it should be specifically explained that the food maturity preprocessing unit is used to establish a food maturity preprocessing model, import the food data and maturity data transmitted by the cooking data acquisition module into the food maturity preprocessing model, and obtain the food processing coefficient and the cooking maturity coefficient. The calculation formula of the cooking food coefficient is:

[0064]

[0065] Where Ft i represents the food processing coefficient of the ith sub-time zone, Tc max Indicates the maximum internal temperature of food within the target time zone, Tc i represents the internal temperature of the food in the i-th sub-time zone, To max Indicates the maximum external temperature of food within the target time zone, To i represents the external temperature of the food in the ith sub-time zone, Tw i-1 represents the water content of food in the i-1th sub-time zone, Tw i represents the water content of food in the ith sub-time zone, Tq i represents the food portion in the i-th sub-time zone; the calculation formula of the cooking maturity coefficient is:

[0066]

[0067] Among them, Fm i represents the cooking maturity coefficient of the ith sub-time zone, Mt i represents the food cooking time in the ith sub-time zone, Mt 预 Indicates the preset food cooking time, Mp i represents the frequency of stir-frying in the ith sub-time zone, Mp max Indicates the maximum frequency of stir-frying within the target time zone, Mw i Represents the steam volume in the i-th time sub-zone.

[0068] In this embodiment, it should be specifically explained that the environmental safety preprocessing unit is used to establish an environmental safety preprocessing model, import the environmental safety data transmitted by the cooking data acquisition module into the environmental safety preprocessing model, and obtain the smoke concentration fluctuation coefficient and the environmental humidity fluctuation coefficient. The calculation formula of the smoke concentration fluctuation coefficient is:

[0069]

[0070] Among them, Ml i represents the smoke fluctuation coefficient of the ith sub-time zone, Ec i represents the smoke density in the ith sub-time zone, Eo i It represents the smoke purification amount in the ith sub-time zone; the calculation formula of the ambient humidity fluctuation coefficient is:

[0071]

[0072] Among them, Mh i represents the environmental humidity coefficient of the i-th sub-time zone, Ew i Represents the ambient humidity of the i-th sub-time zone.

[0073] The cooking data analysis module includes an ingredient maturity analysis unit and an environmental safety analysis unit. The ingredient maturity analysis unit is used to analyze the data transmitted by the cooking data preprocessing module to obtain an ingredient maturity assessment coefficient, and transmit the analyzed data to the cooking data comprehensive analysis module. The environmental safety analysis unit is used to analyze the data transmitted by the cooking data preprocessing module to obtain an environmental safety assessment coefficient, and transmit the analyzed data to the cooking data comprehensive analysis module.

[0074] In this embodiment, it should be specifically explained that the food maturity analysis unit is used to establish a food maturity analysis model, import the food maturity preprocessing data transmitted by the cooking data preprocessing module into the food maturity analysis model, and obtain the food maturity evaluation coefficient. The specific analysis formula of the food maturity evaluation coefficient is:

[0075]

[0076] where φ i represents the food maturity assessment coefficient of the i-th sub-time zone, Ft i represents the food processing coefficient of the ith sub-time zone, Fm i represents the cooking maturity coefficient of the i-th sub-time zone.

[0077] In this embodiment, it should be specifically explained that the environmental safety analysis unit is used to establish an environmental safety analysis model, import the environmental safety preprocessing data transmitted by the cooking data preprocessing module into the environmental safety analysis model, and obtain the environmental safety assessment coefficient. The specific analysis formula of the environmental safety assessment coefficient is:

[0078]

[0079] where ψ i represents the environmental safety assessment coefficient of the ith sub-time zone, Ml i represents the smoke fluctuation coefficient of the ith sub-time zone, Mh i Represents the ambient humidity coefficient of the i-th sub-time zone.

[0080] The cooking data comprehensive analysis module is used to establish a cooking data comprehensive analysis model, import the food maturity assessment coefficient and the environmental safety assessment coefficient into the cooking data comprehensive analysis model, calculate the cooking comprehensive assessment index, and transmit the data to the cooking data judgment module.

[0081] In this embodiment, it should be specifically explained that the specific analysis formula of the cooking comprehensive evaluation index is:

[0082]

[0083] Where η represents the comprehensive evaluation index of cooking in the target time zone, φ i represents the food maturity assessment coefficient of the i-th sub-time zone, ψ i represents the environmental safety assessment coefficient of the ith sub-time zone, λ1 and λ2 represent the factors that affect the food maturity assessment coefficient and the environmental safety assessment coefficient, respectively, such as the amount of seasoning added during cooking that does not match the preset amount and the freshness of the food.

[0084] The cooking data judgment module is used to establish a preset value of the cooking comprehensive evaluation index, judge the cooking comprehensive evaluation index of the target time zone according to the preset value of the cooking comprehensive evaluation index, and send a signal to the human-computer interaction module according to the judgment result.

[0085] In this embodiment, it should be specifically noted that the preset value of the cooking comprehensive evaluation index is marked as η D , when η D ≤η, it means that the cooking comprehensive evaluation index of the target time zone is greater than the preset value of the cooking comprehensive evaluation index, indicating that the cooking ability of the intelligent cooking device is in a normal state, and a signal a is sent. When η D >η, it means that the comprehensive cooking evaluation index of the target time zone is less than the preset value of the comprehensive cooking evaluation index, indicating that the cooking ability of the intelligent cooking device is in an abnormal state, and a signal b is sent to transmit the sent signal to the human-computer interaction module.

[0086] The human-computer interaction module is used to receive and judge the signal transmitted by the cooking data judgment module. If the signal transmitted in the cooking data judgment module is signal a, the system will maintain data collection, preprocessing and analysis of the intelligent cooking equipment. If the signal transmitted in the cooking data judgment module is signal b, the system will warn the management personnel and display abnormal data on the terminal display screen to remind the management personnel of the intelligent cooking equipment with abnormal behavior, and the management personnel will handle and repair the intelligent cooking equipment with abnormal behavior.

[0087] The present invention divides the cooking time of a dish into multiple sub-time zones through the target time division module, which can realize the refined analysis of the intelligent cooking equipment. The data analysis of each sub-time zone can be carried out independently, so that the system can more accurately capture the subtle changes of the intelligent cooking equipment in different time periods, and provide more accurate data support for subsequent judgment and early warning; the food material data, maturity data and environmental safety data of the intelligent cooking equipment are collected in real time through the cooking data collection module, which provides an important basis for the status and safety evaluation of the intelligent cooking equipment, and grasps the operating status of the intelligent cooking equipment in real time; the collected data are pre-processed through the cooking data pre-processing module, so that the data processing is more perfect, and support is provided for the cooking data analysis module; the pre-processed data are further processed through the cooking data analysis module, and the data are imported into the analysis model to calculate the intelligent cooking The food maturity assessment coefficient and environmental safety assessment coefficient of the cooking equipment can intuitively reflect the operating status of the intelligent cooking equipment in different time zones, providing an important reference basis for the judgment and decision-making of the system; the results of the cooking data analysis module are imported into the comprehensive analysis model through the cooking data comprehensive analysis module to calculate the cooking comprehensive evaluation index, which can comprehensively reflect the overall operating status of the intelligent cooking equipment and provide a decision-making basis for the cooking data judgment module; the preset value of the cooking comprehensive evaluation index is set through the cooking data judgment module. When the cooking comprehensive evaluation index is lower than the preset value, the system will automatically issue an early warning signal to remind the management personnel to deal with it in time; the early warning signal is displayed on the terminal display screen through the human-computer interaction module, providing data support and judgment basis for the management personnel to deal with the intelligent cooking equipment with abnormal behavior, and providing important guarantee for taking timely measures to avoid the occurrence of safety accidents.

[0088] like Figure 2 As shown, the present invention also provides a cooking data analysis method for an intelligent cooking device, which is applied to the cooking data analysis system for the intelligent cooking device, comprising:

[0089] S1: Dividing the target time zone: determining the cooking time of a dish in the intelligent cooking device as the target time zone, dividing the target time zone into sub-time zones by equal time division, and numbering the sub-time zones in the target time zone as 1, 2, ..., i, ..., n in sequence;

[0090] S2: Collecting cooking data: The food ripening collection unit of the cooking data collection module collects food data and ripening data of each sub-time zone in the target time zone, and transmits the collected data to the cooking data preprocessing module; the environment safety collection unit of the cooking data collection module collects environment safety data of each sub-time zone in the target time zone, and transmits the collected data to the cooking data preprocessing step;

[0091] S3: Preprocessing cooking data: The food preparation preprocessing unit of the cooking data preprocessing module preprocesses the data transmitted by the cooking data acquisition module to obtain food preparation coefficients and cooking preparation coefficients, and transmits the preprocessed data to the cooking data analysis module; the environmental safety preprocessing unit of the cooking data preprocessing module preprocesses the data transmitted by the cooking data acquisition module to obtain smoke concentration fluctuation coefficients and environmental humidity fluctuation coefficients, and transmits the preprocessed data to the cooking data analysis step;

[0092] S4: Analyze cooking data: The food maturity analysis unit of the cooking data analysis module analyzes the data transmitted by the cooking data preprocessing module to obtain the food maturity assessment coefficient, and transmits the analyzed data to the cooking data comprehensive analysis module; the environmental safety analysis unit of the cooking data analysis module analyzes the data transmitted by the cooking data preprocessing module to obtain the environmental safety assessment coefficient, and transmits the analyzed data to the comprehensive cooking data analysis step;

[0093] S5: Comprehensive analysis of cooking data: The cooking data comprehensive analysis module establishes a cooking data comprehensive analysis model, imports the food maturity assessment coefficient and the environmental safety assessment coefficient into the cooking data comprehensive analysis model, calculates the cooking comprehensive assessment index, and transmits the data to the cooking data judgment step;

[0094] S6: judging cooking data: the cooking data judging module establishes a preset value of the cooking comprehensive evaluation index, judges the cooking comprehensive evaluation index of the target time zone according to the preset value of the cooking comprehensive evaluation index, and sends a signal to the human-computer interaction step according to the judgment result;

[0095] S7: Human-computer interaction: The human-computer interaction module receives and judges the signal transmitted by the cooking data judgment module. The system warns the management personnel and displays abnormal data on the terminal display screen to remind the management personnel of the intelligent cooking equipment with abnormal behavior. The management personnel will handle the intelligent cooking equipment with abnormal behavior.

[0096] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0097] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A cooking data analysis system for intelligent cooking equipment, characterized in that: include: Target time division module: used to determine the cooking time of a dish in the intelligent cooking device as a target time zone, divide the target time zone into sub-time zones by equal time division, and number the sub-time zones in the target time zone as 1, 2, ..., i, ..., n in sequence; The cooking data collection module includes a food maturity collection unit and an environment safety collection unit, wherein the food maturity collection unit is used to collect food data and maturity data of each sub-time zone in the target time zone, and transmit the collected data to the cooking data preprocessing module, and the environment safety collection unit is used to collect environment safety data of each sub-time zone in the target time zone, and transmit the collected data to the cooking data preprocessing module; The cooking data preprocessing module includes a food ripening preprocessing unit and an environmental safety preprocessing unit. The food ripening preprocessing unit is used to preprocess the data transmitted by the cooking data acquisition module to obtain a food processing coefficient and a cooking ripening coefficient, and transmit the preprocessed data to the cooking data analysis module. The environmental safety preprocessing unit preprocesses the data transmitted by the cooking data acquisition module to obtain a smoke concentration fluctuation coefficient and an environmental humidity fluctuation coefficient, and transmits the preprocessed data to the cooking data analysis module. Cooking data analysis module: including a food maturity analysis unit and an environmental safety analysis unit. The food maturity analysis unit is used to analyze the data transmitted by the cooking data preprocessing module to obtain a food maturity assessment coefficient, and transmit the analyzed data to the cooking data comprehensive analysis module. The environmental safety analysis unit is used to analyze the data transmitted by the cooking data preprocessing module to obtain an environmental safety assessment coefficient, and transmit the analyzed data to the cooking data comprehensive analysis module. Cooking data comprehensive analysis module: used to establish a cooking data comprehensive analysis model, import the food maturity assessment coefficient and environmental safety assessment coefficient into the cooking data comprehensive analysis model, calculate the cooking comprehensive assessment index, and transmit the data to the cooking data judgment module; Cooking data judgment module: used to establish a preset value of the cooking comprehensive evaluation index, judge the cooking comprehensive evaluation index of the target time zone according to the preset value of the cooking comprehensive evaluation index, and send a signal to the human-computer interaction module according to the judgment result; Human-computer interaction module: used to receive and judge the signals transmitted by the cooking data judgment module. The system will warn the management personnel and display abnormal data on the terminal display screen to remind the management personnel of the intelligent cooking equipment with abnormal behavior. The management personnel will handle the intelligent cooking equipment with abnormal behavior.

2. The cooking data analysis system for intelligent cooking equipment according to claim 1, characterized in that: The food material data include food portion, food internal temperature, food external temperature and food moisture content, respectively recorded as Tq, Tc, To and Tw; the maturity data include food cooking time, stir-frying frequency and steam volume, respectively recorded as Mt, Mp and Mw; the environmental safety data include smoke concentration, environmental humidity and smoke exhaust purification volume, respectively recorded as Ec, Ew and Eo.

3. The cooking data analysis system for intelligent cooking equipment according to claim 1, characterized in that: The food material maturity preprocessing unit is used to establish a food material maturity preprocessing model, import the food material data and maturity data transmitted by the cooking data acquisition module into the food material maturity preprocessing model, and obtain the food material processing coefficient and the cooking maturity coefficient. The calculation formula of the cooking food material coefficient is: where Ft i represents the food processing coefficient of the i-th sub-time zone, Tc max Indicates the maximum internal temperature of food within the target time zone, Tc i represents the internal temperature of the food in the i-th sub-time zone, To max Indicates the maximum external temperature of food within the target time zone, To i represents the external temperature of the food in the ith sub-time zone, Tw i-1 represents the water content of food in the i-1th sub-time zone, Tw i represents the water content of food in the ith sub-time zone, Tq i Represents the food portion in the i-th sub-time period.

4. The cooking data analysis system for intelligent cooking equipment according to claim 3, characterized in that: The calculation formula of the cooking maturity coefficient is: Among them, Fm i represents the cooking maturity coefficient of the ith sub-time zone, Mt i represents the food cooking time in the ith sub-time zone, Mt 预 Indicates the preset food cooking time, Mp i represents the frequency of stir-frying in the ith sub-time zone, Mp max Indicates the maximum frequency of stir-frying within the target time zone, Mw i Represents the steam volume in the i-th time sub-zone.

5. The cooking data analysis system for intelligent cooking equipment according to claim 1, characterized in that: The environmental safety preprocessing unit is used to establish an environmental safety preprocessing model, import the environmental safety data transmitted by the cooking data acquisition module into the environmental safety preprocessing model, and obtain the smoke concentration fluctuation coefficient and the environmental humidity fluctuation coefficient. The calculation formula of the smoke concentration fluctuation coefficient is: Among them, Ml i represents the smoke fluctuation coefficient of the ith sub-time zone, Ec i represents the smoke density in the ith sub-time zone, Eo i It represents the smoke exhaust purification amount in the ith sub-time zone; the calculation formula of the ambient humidity fluctuation coefficient is: Among them, Mh i represents the environmental humidity coefficient of the i-th sub-time zone, Ew i Represents the ambient humidity of the i-th sub-time zone.

6. The cooking data analysis system for intelligent cooking equipment according to claim 1, characterized in that: The food maturity analysis unit is used to establish a food maturity analysis model, import the food maturity preprocessing data transmitted by the cooking data preprocessing module into the food maturity analysis model, and obtain the food maturity evaluation coefficient. The specific analysis formula of the food maturity evaluation coefficient is: where φ i represents the food maturity assessment coefficient of the i-th sub-time zone, Ft i represents the food processing coefficient of the ith sub-time zone, Fm i represents the cooking maturity coefficient of the i-th sub-time zone.

7. The cooking data analysis system for intelligent cooking equipment according to claim 1, characterized in that: The environmental safety analysis unit is used to establish an environmental safety analysis model, import the environmental safety preprocessing data transmitted by the cooking data preprocessing module into the environmental safety analysis model, and obtain the environmental safety assessment coefficient. The specific analysis formula of the environmental safety assessment coefficient is: where ψ i represents the environmental safety assessment coefficient of the ith sub-time zone, Ml i represents the smoke fluctuation coefficient of the ith sub-time zone, Mh i Represents the ambient humidity coefficient of the i-th sub-time zone.

8. The cooking data analysis system for intelligent cooking equipment according to claim 1, characterized in that: The expression of the cooking data comprehensive analysis model is: Among them, η represents the comprehensive evaluation index of cooking in the target time zone, φ i represents the food maturity assessment coefficient of the i-th sub-time zone, ψ i represents the environmental safety assessment coefficient of the i-th sub-time zone, λ1 and λ2 represent the factors affecting the food maturity assessment coefficient and the environmental safety assessment coefficient, respectively.

9. The cooking data analysis system for intelligent cooking equipment according to claim 1, characterized in that: The preset value of the cooking comprehensive evaluation index is marked as η D The cooking data judgment module is used when n D ≤η, it means that the cooking comprehensive evaluation index of the target time zone is greater than or equal to the preset value of the cooking comprehensive evaluation index, indicating that the cooking ability of the intelligent cooking device is in a normal state, and a signal a is sent. When η D >η, it means that the cooking comprehensive evaluation index of the target time zone is less than the preset value of the cooking comprehensive evaluation index, indicating that the cooking ability of the intelligent cooking device is in an abnormal state, and a signal b is sent.

10. A cooking data analysis method for an intelligent cooking device, characterized in that: A cooking data analysis system for an intelligent cooking device as claimed in any one of claims 1 to 9, comprising: S1: Dividing the target time zone: determining the cooking time of a dish in the intelligent cooking device as the target time zone, dividing the target time zone into sub-time zones by equal time division, and numbering the sub-time zones in the target time zone as 1, 2, ..., i, ..., n in sequence; S2: Collecting cooking data: The food ripening collection unit of the cooking data collection module collects food data and ripening data of each sub-time zone in the target time zone, and transmits the collected data to the cooking data preprocessing module; the environment safety collection unit of the cooking data collection module collects environment safety data of each sub-time zone in the target time zone, and transmits the collected data to the cooking data preprocessing step; S3: Preprocessing cooking data: The food preparation preprocessing unit of the cooking data preprocessing module preprocesses the data transmitted by the cooking data acquisition module to obtain food preparation coefficients and cooking preparation coefficients, and transmits the preprocessed data to the cooking data analysis module; the environmental safety preprocessing unit of the cooking data preprocessing module preprocesses the data transmitted by the cooking data acquisition module to obtain smoke concentration fluctuation coefficients and environmental humidity fluctuation coefficients, and transmits the preprocessed data to the cooking data analysis step; S4: Analyze cooking data: The food maturity analysis unit of the cooking data analysis module analyzes the data transmitted by the cooking data preprocessing module to obtain the food maturity assessment coefficient, and transmits the analyzed data to the cooking data comprehensive analysis module; the environmental safety analysis unit of the cooking data analysis module analyzes the data transmitted by the cooking data preprocessing module to obtain the environmental safety assessment coefficient, and transmits the analyzed data to the comprehensive cooking data analysis step; S5: Comprehensive analysis of cooking data: The cooking data comprehensive analysis module establishes a cooking data comprehensive analysis model, imports the food maturity assessment coefficient and the environmental safety assessment coefficient into the cooking data comprehensive analysis model, calculates the cooking comprehensive assessment index, and transmits the data to the cooking data judgment step; S6: judging cooking data: the cooking data judging module establishes a preset value of the cooking comprehensive evaluation index, judges the cooking comprehensive evaluation index of the target time zone according to the preset value of the cooking comprehensive evaluation index, and sends a signal to the human-computer interaction module according to the judgment result; S7: Human-computer interaction: The human-computer interaction module receives and judges the signal transmitted by the cooking data judgment module. The system warns the management personnel and displays abnormal data on the terminal display screen to remind the management personnel of the intelligent cooking equipment with abnormal behavior. The management personnel will handle the intelligent cooking equipment with abnormal behavior.

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