Intelligent poultry cooking method and system based on cooking equipment

Abstract

The invention discloses an intelligent poultry cooking method based on cooking equipment and a system thereof. The method comprises the following steps: S1, acquiring original information of poultry food materials to be cooked and performing preprocessing; s2, putting the preprocessed poultry food materials into intelligent cooking equipment, starting a cooking program, and monitoring water content, fat content, protein content and impurity related data of the food materials in a cooking process in real time; s3, analyzing the monitoring data through an intelligent algorithm, and identifying impurity components and content; and S4, automatically adjusting cooking parameters or switching a cooking method according to an impurity identification result. The invention relates to the technical field of intelligent cooking. According to the intelligent poultry cooking method and system based on the cooking equipment, the purpose that the system automatically adjusts the cooking temperature, time and method according to the real-time monitoring result and impurity recognition is achieved, impurities are effectively removed, the cooking process is optimized, and the taste and flavor are improved to the maximum while nutrients of food materials are kept is achieved.

Description

Technical Field

[0001] This invention relates to the field of intelligent cooking, and more specifically, to an intelligent poultry cooking method and system based on cooking equipment. Background Technology

[0002] In traditional poultry cooking, several problems affect the cooking results and the quality of the dishes. First, the setting of cooking parameters often relies on the chef's experience and lacks scientific basis. It is difficult to make precise adjustments based on factors such as the type, weight, and initial component content of different poultry ingredients, resulting in inconsistent nutritional value and taste in the cooked dishes. For example, if the same cooking temperature and time are used for chickens of different weights, some chicken meat may be overcooked and dry, while some may be undercooked.

[0003] Secondly, poultry ingredients may carry impurities during cooking, such as grease and detergent residue. Excessive grease content makes dishes too oily, affecting both taste and health; detergent residue, if not completely removed, may be harmful to the body after consumption. However, traditional cooking methods make it difficult to monitor the content of these impurities in real time, and even more difficult to adjust cooking parameters or take effective removal measures based on the impurities.

[0004] Furthermore, most existing cooking equipment has limited functions, only possessing basic heating and timer functions. It cannot collect and analyze data on the composition of ingredients in real time during the cooking process, nor can it dynamically optimize cooking parameters according to changes in ingredients, making it difficult to meet people's demand for high-quality cooked dishes.

[0005] In summary, traditional poultry cooking methods have significant shortcomings in terms of cooking parameter control, impurity removal, and equipment intelligence. There is an urgent need for a poultry cooking method and system that can intelligently monitor, precisely control, and effectively remove impurities. Summary of the Invention

[0006] The purpose of this invention is to provide an intelligent poultry cooking method and system based on cooking equipment. It solves the problems of existing cooking methods that rely on manual control of cooking time and temperature, making it difficult to accurately control changes in the composition of ingredients and to detect and remove impurities in real time. As a result, the nutritional components and taste of the ingredients are easily affected during the cooking process, and they cannot meet the requirements of use.

[0007] This invention achieves the above objective through the following technical solution: an intelligent poultry cooking method based on cooking equipment, comprising the following steps: S1. Obtain the original information of the poultry ingredients to be cooked and perform preprocessing; S2. Place the pre-treated poultry ingredients into the intelligent cooking equipment, start the cooking program, and monitor the moisture, fat, protein content, and impurities of the ingredients in real time during the cooking process. S3. Analyze monitoring data using intelligent algorithms to identify impurity components and their content; S4. Automatically adjust cooking parameters or switch cooking methods based on impurity identification results; S5. Perform impurity removal operation, continuously optimize cooking parameters until cooking is completed, and output poultry dishes that meet nutritional and taste requirements.

[0008] Further steps include obtaining the original information of the poultry ingredients to be cooked and performing preprocessing, including: Obtain at least one of the following data regarding poultry feed: type, weight, initial moisture content, initial fat content, and initial protein content; Poultry ingredients are processed by at least one of the following methods: washing, cutting into pieces, and draining. The pre-treated poultry ingredients are placed into the cooking cavity of the smart cooking equipment to ensure that the ingredients match the detection range of the monitoring components inside the equipment.

[0009] Furthermore, the steps to start the cooking program and monitor relevant data in real time include: Preset initial cooking parameters, which include at least one of initial temperature, initial time, and initial cooking method; The smart cooking equipment uses built-in multi-dimensional sensors to collect at least one of the following data in real time: moisture content, fat content, protein content, and impurity characteristics of the ingredients. The collected monitoring data is transmitted in real time to the equipment control module for storage and processing.

[0010] Furthermore, the steps of analyzing monitoring data and identifying impurity components and content through intelligent algorithms include: A smart algorithm model for impurity identification is constructed, and the model is trained using impurity characteristics and component content data in historical cooking data as training samples. The real-time monitoring data is input into the trained intelligent algorithm model, and through feature matching and data analysis, the impurity type is identified and the specific impurity content is determined. Set an impurity content threshold. When the detected impurity content exceeds the preset threshold, a parameter adjustment command is triggered.

[0011] Furthermore, the step of automatically adjusting cooking parameters or switching cooking methods based on impurity identification results includes: If excessive levels of oily impurities are detected, adjust at least one of the following: cooking temperature or cooking time, or switch cooking methods. If detergent residue is found to be excessive, maintain the cooking temperature and extend the cooking time, or use a circulating cleaning method to remove the residue.

[0012] Furthermore, the steps of performing impurity removal and continuously optimizing cooking parameters include: According to the parameter adjustment command, the corresponding impurity removal module is activated to remove impurities using at least one of the following methods: physical separation, cyclic cleaning, and high-temperature decomposition. During the impurity removal process, the composition data of the ingredients and the impurity content are continuously monitored, and the monitoring results are updated regularly. Cooking parameters are dynamically optimized based on the updated monitoring results until the impurity content stabilizes below the preset threshold.

[0013] Furthermore, the multi-dimensional sensor includes: Moisture detection module, fat detection module, protein detection module and impurity detection module; The detection error of the sensor meets the preset accuracy requirements.

[0014] Furthermore, the impurity content threshold includes: Thresholds for grease impurities and detergent residues; The threshold for oil impurity content is a preset ratio of the initial fat content of the food. The threshold value for detergent residue content is a preset fixed value.

[0015] Furthermore, the criteria for determining whether cooking is complete are: the impurity content is consistently below a preset threshold, and the moisture, fat, and protein content of the ingredients reach the preset optimal ratio.

[0016] A smart poultry system based on cooking equipment, used to implement the aforementioned smart poultry cooking method, the system comprising: The information acquisition and preprocessing module is used to acquire raw information about poultry ingredients and perform preprocessing operations. The cooking execution module is used to hold the ingredients and execute the cooking program; A multi-dimensional monitoring module is used to collect data on the composition of ingredients and impurities in real time during the cooking process; The intelligent analysis and control module is used to analyze monitoring data and identify impurity information through intelligent algorithms, and adjust cooking parameters, switch cooking methods and control impurity removal operations based on the analysis results. The impurity removal module is used to remove impurities generated during the cooking process using corresponding technical means.

[0017] The beneficial effects of this invention are as follows: 1. Using multi-dimensional sensors to monitor the moisture, fat, protein and impurity content of poultry ingredients in real time, and analyzing this data through intelligent algorithms, it can accurately identify the impurity components and their content in the ingredients, thus improving the level of intelligence in the cooking process.

[0018] 2. Based on real-time monitoring results and impurity identification, the system automatically adjusts the cooking temperature, time, and method to effectively remove impurities and optimize the cooking process, maximizing the taste and flavor of the ingredients while preserving their nutrients.

[0019] 3. When the impurity content exceeds the threshold, the system can automatically start the impurity removal module and remove impurities by means of physical separation, circulation cleaning or high temperature decomposition to ensure that the cooked poultry dishes are both healthy and delicious.

[0020] 4. Through automated monitoring, analysis, and adjustment processes, human intervention and errors are reduced, making the cooking process more efficient, reducing food waste, and saving energy.

[0021] 5. By precisely controlling the moisture, fat, and protein content of poultry ingredients and removing unnecessary impurities, this invention can ensure that the cooked poultry dishes are nutritionally balanced and meet the needs of modern consumers for healthy eating. Attached Figure Description

[0022] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a flowchart of the overall method of the present invention; Figure 2 This is a flowchart of the impurity identification and processing of the present invention; Figure 3 This is a system block diagram of the present invention. Detailed Implementation

[0023] The present application will now be described in further detail with reference to the accompanying drawings. It should be noted that the following specific embodiments are only used to further illustrate the present application and should not be construed as limiting the scope of protection of the present application. Those skilled in the art can make some non-essential improvements and adjustments to the present application based on the above application content.

[0024] Example 1: Please see Figure 1-2 This invention provides a technical solution: an intelligent poultry cooking method based on cooking equipment, the method comprising: S1. Obtain the original information of the poultry ingredients to be cooked and preprocess the poultry ingredients; The original information of poultry ingredients to be cooked refers to the various information that poultry ingredients possess before any processing, such as the type, weight, freshness, and origin of the poultry. This information helps to understand the basic characteristics of the ingredients and provides a basis for subsequent processing and cooking. Pre-processing is a series of preliminary preparations for poultry ingredients to be cooked, which may include cleaning, slaughtering, defecation, internal organ removal, cutting or shaping, etc., with the aim of bringing the ingredients to a state suitable for cooking. S2. Place the pre-treated poultry ingredients into the intelligent cooking equipment, start the cooking program, and monitor the moisture, fat, protein content, and impurities of the ingredients in real time during the cooking process. Intelligent cooking equipment refers to appliances with intelligent functions used for cooking food. They typically integrate multiple sensors, control systems, and cooking programs, automatically adjusting the cooking process based on preset parameters or real-time monitored data to achieve precise cooking. Common intelligent cooking equipment includes intelligent ovens, intelligent steamers, and intelligent stir-fry machines. Cooking programs are a series of pre-set cooking steps and parameter combinations within the intelligent cooking equipment, including cooking temperature, cooking time, and cooking method. Different cooking programs are available for different ingredients and dishes to ensure the food meets the required standards. Real-time monitoring involves continuously collecting various data about the ingredients during the cooking process using sensors and other devices. This allows for timely reflection of changes in the ingredients during cooking, providing a basis for subsequent analysis and adjustments. Moisture content refers to the proportion of water contained in poultry ingredients; moisture content affects the quality of the ingredients. The cooking process involves various factors, including the texture, taste, and cooking time. For example, ingredients with high moisture content may require longer cooking time to evaporate moisture and achieve the desired texture. Fat content refers to the percentage of fat in poultry, which significantly impacts the taste, flavor, and nutritional value of a dish. Different cooking methods affect fat content differently; for instance, roasting may cause some fat to render out, while boiling tends to retain more. Protein content is the amount of protein in poultry. Protein is an essential nutrient for the human body, and understanding its content helps assess the nutritional value of a dish. Furthermore, protein denaturation during cooking affects the texture and taste of the dish. Finally, data on impurities in poultry, including their types, amounts, and distribution, is crucial for ensuring the hygiene, safety, and quality of the food. S3. Through intelligent algorithms, the monitoring data is analyzed to identify the components and content of impurities, including grease and detergent residues. Among them, intelligent algorithms are programs or methods designed based on computer science and mathematical principles that can automatically process and analyze data. In the field of cooking, intelligent algorithms can analyze and judge based on real-time monitored food data using specific logic and models to achieve functions such as identifying impurity components and content. Impurity components and content refer to substances in poultry ingredients other than the main nutrients and their proportions. Common impurities include oil, detergent residues, etc. These impurities may affect the taste, hygiene and safety, and nutritional value of dishes. S4. Based on the impurity identification results, automatically adjust the cooking temperature, cooking time, or switch the cooking method, including steaming, baking, and boiling; Cooking temperature refers to the temperature of the environment in which the ingredients are placed during cooking. Different cooking temperatures will have different effects on the physical and chemical changes of the ingredients, thus affecting the taste, color, and nutrient preservation of the dish. For example, high-temperature roasting can make poultry have a crispy skin, while low-temperature slow cooking can make the meat more tender and juicy. Cooking time is the duration of cooking of ingredients under specific cooking conditions. The length of cooking time directly affects the doneness, taste, and degree of nutrient retention of the ingredients. Cooking time that is too short may result in undercooked ingredients, while cooking time that is too long may result in overcooked ingredients or loss of nutrients. Cooking method refers to the specific method used to prepare the dish. Common cooking methods include steaming, roasting, and boiling. Different cooking methods will bring different flavors and textures to the dish. S5. Perform impurity removal operation, continuously optimize cooking parameters until cooking is completed, and output poultry dishes that meet nutritional and taste requirements. Among them, the impurity removal operation involves taking corresponding measures to remove or reduce impurities in the ingredients to a safe and reasonable level based on the impurity identification results; the cooking parameter optimization involves further adjusting and improving parameters such as cooking temperature and cooking time based on the impurity removal status and real-time monitoring data during the cooking process to achieve the best cooking effect, so that the dish meets the requirements in terms of nutrition and taste; the poultry dishes that meet the requirements of nutrition and taste are dishes made from poultry that meet human nutritional needs and have a good taste after the above series of processing and cooking processes.

[0025] It should be noted that during use, the system acquires and preprocesses raw information, enabling targeted preparation based on the characteristics of poultry, laying the foundation for subsequent cooking. Real-time monitoring of moisture, fat content, and impurities allows for precise control of ingredient changes during cooking, preventing errors due to a lack of understanding of their condition. Intelligent algorithms analyze and identify impurities, promptly detecting potential hygiene and safety hazards to ensure food safety. The system automatically adjusts temperature, time, or switches methods based on impurity results, flexibly responding to different situations, effectively removing impurities, and improving dish quality. Executing removal operations and continuously optimizing parameters allows for constant adjustment and improvement of the cooking process. The final poultry dishes output meet nutritional requirements and have excellent taste, satisfying consumers' dual pursuit of health and deliciousness, improving cooking efficiency and dish quality, and enhancing market competitiveness.

[0026] In one embodiment, the raw information of the poultry ingredients to be cooked is obtained, and the poultry ingredients are pre-processed, including: Obtain data on the type, weight, initial moisture content, initial fat content, and initial protein content of the poultry ingredients to be cooked; Clean, cut, and drain the poultry ingredients to remove visible impurities from the surface. The pre-treated poultry ingredients are evenly placed into the cooking cavity of the intelligent cooking equipment, ensuring that the ingredients match the detection range of the monitoring components inside the equipment.

[0027] This design acquires raw information such as the type, weight, and initial nutrient content of poultry ingredients, performs pre-treatments such as washing, chopping, and draining, and finally places the ingredients evenly into the cooking cavity and matches the monitoring range. This comprehensive understanding of the ingredients' characteristics provides a foundation for precise cooking. Pre-treatment removes surface impurities, improves the hygiene quality of the dishes, ensures that the ingredients are in the appropriate monitoring position, and accurately acquires data on the ingredients during cooking. This allows for precise control of the subsequent cooking process based on the true state of the ingredients, ensuring cooking results, improving dish quality, and meeting consumers' demand for healthy and delicious dishes.

[0028] In one embodiment, the cooking program is initiated and data related to the moisture, fat, protein content, and impurities of the ingredients are monitored in real time during the cooking process, including: Preset initial cooking parameters, including initial temperature, initial time, and initial cooking method; The intelligent cooking device uses built-in multi-dimensional sensors to collect real-time data on the moisture content, fat content, protein content, and impurity characteristics of the ingredients during the cooking process. Moisture content is calculated using the Karl Fischer method, with the following formula:

[0029] in, Moisture content (%) The volume (mL) of Karl Fischer reagent consumed in the titration. The titer of Karl Fischer reagent is given in mg / mL. Sample weight (mg) of poultry ingredients; Fat content was calculated using the Soxhlet extraction method, and the formula is as follows:

[0030] in, Fat content (%) Mass of the extraction bottle (g). The total mass (g) of the extraction bottle and fat. Sample weight (g) of poultry ingredients; Protein content was calculated using the Kjeldahl method, and the formula is as follows:

[0031] in, Protein content (%) This represents the concentration (mol / L) of the hydrochloric acid standard solution. The volume (mL) of hydrochloric acid standard solution consumed in the titration. The protein conversion factor is 6.25 for poultry meat. Sample weight (g) of poultry ingredients; The sensor collects data every 10-30 seconds and transmits the collected monitoring data to the equipment control module in real time for storage and processing.

[0032] This design presets initial cooking parameters, uses built-in multi-dimensional sensors to collect data on the components and impurities of ingredients in real time during cooking, clarifies the calculation method for the content of each component, sets the collection frequency and data transmission processing method, preset parameters provide initial direction for cooking, multi-dimensional sensors comprehensively monitor and accurately grasp changes in ingredients during the cooking process, clear calculation methods ensure data accuracy and reliability, reasonable collection frequency provides timely data feedback, and real-time transmission and processing facilitates rapid adjustments to cooking, ensuring a scientific and reasonable cooking process and improving the quality and stability of dishes.

[0033] In one embodiment, the analysis of monitoring data using an intelligent algorithm to identify the components and content of impurities includes: A smart algorithm model for impurity identification was constructed. The model was trained using impurity characteristics and component content data from historical cooking data as training samples. Real-time monitoring data is input into the trained intelligent algorithm model. Through feature matching and data analysis, the types of impurities generated during the current cooking process are identified, and the specific content of impurities such as grease and detergent residue is determined. The formula for calculating the grease impurity content is as follows:

[0034] in, The percentage of oil impurities that separate out during cooking. The fat content (%) is monitored in real time. The initial fat content of the food (%). Detergent residue content was calculated using high-performance liquid chromatography combined with the external standard method. The calculation formula is as follows:

[0035] in, This refers to the detergent residue content (mg / kg). This represents the peak area of ​​detergent residue in the sample solution. The concentration (mg / L) of detergent residue in the standard solution. The sample volume (L) is the fixed volume. The peak area of ​​detergent residue in the standard solution. Sample weight (kg) of poultry ingredients; Set an impurity content threshold. When the detected impurity content exceeds the preset threshold, a parameter adjustment command is triggered.

[0036] This design constructs and trains an intelligent algorithm model for impurity identification. It inputs real-time data to identify the type and content of impurities, clarifies the calculation method for oil and detergent residue content, and sets impurity content thresholds to trigger parameter adjustment commands. The intelligent algorithm model can quickly and accurately identify impurities, improving the efficiency and accuracy of impurity detection. The clarified calculation method provides a scientific basis for judging impurity content, and the set thresholds can promptly detect situations where impurities exceed the standard. The triggered commands adjust cooking parameters in a timely manner, effectively removing impurities, ensuring the hygiene and safety of dishes, and improving the quality of dishes.

[0037] In one embodiment, automatically adjusting the cooking temperature, cooking time, or switching the cooking method based on the impurity identification result includes: If the impurities are identified as primarily oils and their content exceeds the standard, calculate the temperature adjustment range:

[0038] in, The temperature adjustment range (°C) is the maximum temperature. This is the temperature adjustment coefficient for oil impurities, with a value ranging from 3 to 5. This represents the actual oil and fat impurity content (%). The threshold (%) for oil impurity content, adjusted by temperature. And the lowered temperature is not lower than 80℃; Simultaneously calculate the time adjustment range:

[0039] in, Extend the time by (minutes). This is a time adjustment coefficient for oil impurities, with a value of 5-8. After extending the time... ; Or switch directly to the steaming cooking method; If the impurities are identified as primarily detergent residue and the levels exceed the standard, maintain the cooking temperature and calculate the additional stewing time:

[0040] in, For additional stewing time (minutes). This is a time adjustment factor for detergent residue, with a value ranging from 8 to 12. This represents the actual detergent residue content (mg / kg). The threshold for detergent residue content (mg / kg) is the total cooking time. Residues are removed through water circulation; The adjustment range is dynamically adjusted based on changes in impurity content to ensure that the impurity content gradually decreases to below the preset threshold.

[0041] This design provides specific calculation methods and operational strategies for adjusting cooking temperature, time, or switching cooking methods for different types of excessive impurities. The adjustment range is dynamically adjusted based on changes in impurity content, and targeted treatment measures are taken for different impurities to improve impurity removal efficiency. The specific calculation methods make the adjustment more precise and scientific, avoiding over- or under-adjustment. Dynamic adjustment allows for flexible responses to actual conditions, ensuring that impurity content gradually decreases below the threshold, guaranteeing stable food quality, and meeting consumers' demands for high-quality dishes.

[0042] In one embodiment, performing an impurity removal operation to continuously optimize cooking parameters includes: Based on the parameter adjustment instructions, the intelligent cooking device activates the corresponding impurity removal module. Oily impurities are physically separated and removed by the device's built-in oil separation unit. Separation efficiency:

[0043] in, The percentage of oil and grease impurity separation efficiency. The percentage of oil impurities before separation. The percentage of oil impurities after separation; Detergent residue is removed through a combination of circulating washing and high-temperature decomposition, with a removal efficiency of:

[0044] in, Detergent residue removal efficiency (%) To determine the amount of detergent residue (mg / kg) before removal. The amount of detergent residue after removal (mg / kg); During the impurity removal process, the composition data and impurity content of the ingredients are continuously monitored, and the monitoring results are updated every 5-10 seconds. Based on the updated monitoring results, the cooking temperature, time, or cooking method is dynamically optimized using intelligent algorithms until the impurity content stabilizes below a preset threshold, and the moisture, fat, and protein content of the ingredients reach the optimal ratio. The optimal ratio satisfies the following:

[0045] in, The optimal moisture content (%). The optimal fat content (%). The optimal protein content (%).

[0046] This design activates the corresponding impurity removal module based on parameter adjustment commands, clearly defining the removal methods and efficiency calculations for grease and detergent residues. It continuously monitors and dynamically optimizes cooking parameters until the optimal ratio is achieved. The targeted removal module effectively removes impurities, improving the hygiene quality of the dishes. The clear calculation method for removal efficiency allows for the evaluation of removal effects. Continuous monitoring and dynamic optimization ensure that the cooking process is constantly adjusted and improved, so that the ingredients reach the optimal ratio, enhancing the nutritional value and taste of the dishes and meeting consumers' demand for healthy and delicious food.

[0047] In one embodiment, the multi-dimensional sensor includes a moisture sensor, a fat sensor, a protein sensor, and a high-performance liquid chromatography detector, which respectively perform the detection and data calculation of the content of moisture, fat, protein, and detergent residue. The detection accuracy of the sensor is: Moisture content detection error ≤ ±0.5%, fat content detection error ≤ ±0.3%, protein content detection error ≤ ±0.2%, detergent residue detection error ≤ 0.1 mg / kg.

[0048] This design allows multiple sensors to comprehensively detect the content of various components and impurities in the ingredients, providing rich and accurate data for cooking control. High-precision detection ensures data reliability, making the adjustment of cooking parameters more precise and scientific, avoiding cooking errors caused by data mistakes, improving the stability of dish quality, and enhancing consumer satisfaction with the dishes.

[0049] In one embodiment, setting the impurity content threshold includes: Threshold for oil impurity content The value is taken as 30%-40% of the initial fat content of the food, and the threshold for detergent residue content. The value ranges from 0.5 mg / kg to 1.0 mg / kg. or When this happens, the parameter adjustment command is immediately triggered.

[0050] This design clearly defines the threshold range for the content of grease impurities and detergent residues, specifies the conditions for triggering parameter adjustment commands, and provides a scientific standard for judging whether impurities exceed the limit by reasonably setting the threshold range, ensuring the hygiene and safety of dishes. The clear trigger conditions enable timely response to situations where impurities exceed the limit, and rapid adjustment of cooking parameters to remove impurities, preventing impurities from adversely affecting the quality of dishes, ensuring that dishes meet hygiene and quality requirements, and enhancing market competitiveness.

[0051] Example 2: Please see Figure 3 A smart poultry system based on cooking equipment, used to implement the aforementioned smart poultry cooking method, the system comprising: The information acquisition and preprocessing module is used to acquire raw information about poultry ingredients and perform preprocessing operations. The cooking execution module is used to hold the ingredients and execute the cooking program; A multi-dimensional monitoring module is used to collect data on the composition of ingredients and impurities in real time during the cooking process; The intelligent analysis and control module is used to analyze monitoring data and identify impurity information through intelligent algorithms, and adjust cooking parameters, switch cooking methods and control impurity removal operations based on the analysis results. The impurity removal module is used to remove impurities generated during the cooking process using corresponding technical means.

[0052] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0053] The above embodiments provide a detailed description of the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A smart poultry cooking method based on cooking equipment, characterized in that, Includes the following steps: S1. Obtain the original information of the poultry ingredients to be cooked and perform preprocessing; S2. Place the pre-treated poultry ingredients into the intelligent cooking equipment, start the cooking program, and monitor the moisture, fat, protein content, and impurities of the ingredients in real time during the cooking process. S3. Analyze monitoring data using intelligent algorithms to identify impurity components and their content; S4. Automatically adjust cooking parameters or switch cooking methods based on impurity identification results; S5. Perform impurity removal operation, continuously optimize cooking parameters until cooking is completed, and output poultry dishes that meet nutritional and taste requirements.

2. The intelligent poultry cooking method based on cooking equipment according to claim 1, characterized in that, The steps for obtaining the raw information of the poultry ingredients to be cooked and preprocessing them include: Obtain at least one of the following data regarding poultry feed: type, weight, initial moisture content, initial fat content, and initial protein content; Poultry ingredients are processed by at least one of the following methods: washing, cutting into pieces, and draining. The pre-treated poultry ingredients are placed into the cooking cavity of the smart cooking equipment to ensure that the ingredients match the detection range of the monitoring components inside the equipment.

3. The intelligent poultry cooking method based on cooking equipment according to claim 1, characterized in that, The steps to start a cooking program and monitor relevant data in real time include: Preset initial cooking parameters, which include at least one of initial temperature, initial time, and initial cooking method; The smart cooking equipment uses built-in multi-dimensional sensors to collect at least one of the following data in real time: moisture content, fat content, protein content, and impurity characteristics of the ingredients. The collected monitoring data is transmitted in real time to the equipment control module for storage and processing.

4. The intelligent poultry cooking method based on cooking equipment according to claim 1, characterized in that, The steps of analyzing monitoring data and identifying impurity components and content through intelligent algorithms include: A smart algorithm model for impurity identification is constructed, and the model is trained using impurity characteristics and component content data in historical cooking data as training samples. The real-time monitoring data is input into the trained intelligent algorithm model, and through feature matching and data analysis, the impurity type is identified and the specific impurity content is determined. Set an impurity content threshold. When the detected impurity content exceeds the preset threshold, a parameter adjustment command is triggered.

5. The intelligent poultry cooking method based on cooking equipment according to claim 1, characterized in that, The steps for automatically adjusting cooking parameters or switching cooking methods based on impurity identification results include: If excessive levels of oily impurities are detected, adjust at least one of the following: cooking temperature or cooking time, or switch cooking methods. If detergent residue is found to be excessive, maintain the cooking temperature and extend the cooking time, or use a circulating cleaning method to remove the residue.

6. The intelligent poultry cooking method based on cooking equipment according to claim 1, characterized in that, The steps for performing impurity removal and continuously optimizing cooking parameters include: According to the parameter adjustment command, the corresponding impurity removal module is activated to remove impurities using at least one of the following methods: physical separation, cyclic cleaning, and high-temperature decomposition. During the impurity removal process, the composition data of the ingredients and the impurity content are continuously monitored, and the monitoring results are updated regularly. Cooking parameters are dynamically optimized based on the updated monitoring results until the impurity content stabilizes below the preset threshold.

7. The intelligent poultry cooking method based on cooking equipment according to claim 3, characterized in that, The multi-dimensional sensor includes: Moisture detection module, fat detection module, protein detection module and impurity detection module; The detection error of the sensor meets the preset accuracy requirements.

8. The intelligent poultry cooking method based on cooking equipment according to claim 4, characterized in that, The impurity content threshold includes: Thresholds for grease impurities and detergent residues; The threshold for oil impurity content is a preset ratio of the initial fat content of the food. The threshold value for detergent residue content is a preset fixed value.

9. The intelligent poultry cooking method based on cooking equipment according to claim 1, characterized in that, The criteria for determining whether cooking is complete are: the impurity content is consistently below the preset threshold, and the moisture, fat, and protein content of the ingredients reach the preset optimal ratio.

10. An intelligent poultry system based on cooking equipment, characterized in that, An intelligent cooking method for implementing the intelligent poultry cooking method according to any one of claims 1-9, the system comprising: The information acquisition and preprocessing module is used to acquire raw information about poultry ingredients and perform preprocessing operations. The cooking execution module is used to hold the ingredients and execute the cooking program; A multi-dimensional monitoring module is used to collect data on the composition of ingredients and impurities in real time during the cooking process; The intelligent analysis and control module is used to analyze monitoring data and identify impurity information through intelligent algorithms, and adjust cooking parameters, switch cooking methods and control impurity removal operations based on the analysis results. The impurity removal module is used to remove impurities generated during the cooking process using corresponding technical means.

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