Intelligent electric oven temperature control management system and method

Abstract

The present invention relates to the field of control engineering technology, and in particular to an intelligent electric oven temperature control and regulation management system and method, comprising a food analysis module, a preheating module, a temperature detection module, a temperature fluctuation detection module, a temperature analysis module, a cleaning analysis module, and a management database. The system obtains images of food and obtains the recommended temperature of the food in combination with the recommended temperature analysis of the food cooking method. The temperature evaluation coefficient of the electric oven is obtained by analyzing the temperature compliance and temperature uniformity of the electric oven, and the system is fed back. The cleaning requirement coefficient of the electric oven is obtained by analyzing the internal cleaning parameters of the electric oven, and the cleaning requirement coefficient is fed back to the system, so that the temperature performance of the electric oven is accurately understood for adjustment and optimization, thereby ensuring the reliability of the cooking temperature and providing users with a more intelligent cooking solution and electric oven management strategy.

Description

Technical Field

[0001] The present invention relates to the technical field of control engineering, and in particular to an intelligent electric oven temperature control and regulation management system and method. Background Art

[0002] With the continuous development of science and technology and the improvement of people's living standards, cooking methods are also constantly evolving and innovating. Electric ovens, as a convenient cooking device, occupy an important position in people's daily lives.

[0003] In the past, traditional electric ovens had problems such as inaccurate temperature control and inflexible adjustment, which not only affected the baking effect and taste of food, but also may lead to energy waste. In modern society, people have higher and higher requirements for cooking experience and food quality, and the limitations of traditional electric ovens are becoming increasingly prominent.

[0004] The emergence of intelligent electric oven temperature control technology is precisely to solve these pain points. Through advanced sensors, precise control systems and intelligent algorithms, it can achieve accurate monitoring and rapid adjustment of the oven temperature to ensure that all kinds of ingredients can be baked at the appropriate temperature. This intelligent temperature control brings many benefits, such as better retaining the nutrients of food, improving the uniformity of baking, and meeting the personalized pursuit of food by different consumers. It can also improve energy utilization efficiency, reduce unnecessary energy loss, and comply with the development trend of energy conservation and environmental protection.

[0005] The technical solution published in a Chinese patent entitled "Temperature Control Method for Bread-Making Equipment" (patent number 92114833.X) detects the temperature of the heating part through a sensor and reaches the target temperature by means of heater on / off control. The method can detect the lag time point when the temperature rises after the heater is powered on and then drops due to being turned off, and power on the heater again after that time point and before the sensor detects that the temperature drops to the corresponding target value setting value. The subsequent heater can be powered on again or the current can be repeatedly switched on / off intermittently, but there are still some shortcomings, which are specifically manifested in the following aspects: First, the solution reaches the target temperature by means of heater on / off control, but does not involve analysis of the target temperature. For example, temperature recommendations are provided for ingredients, and the target temperature may not be effectively set according to actual needs and specific environments. The target temperature is set too high or too low, affecting the final heating effect or user experience. At the same time, there is a lack of in-depth analysis of the target temperature, and it may be difficult to adapt to the diverse requirements of different scenarios and workpieces, thereby reducing the adaptability and flexibility of the solution.

[0006] 2. The plan does not involve an analysis of the need for cleaning. A large amount of dirt, grease, etc. may accumulate inside the oven due to long-term non-cleaning, which not only affects the hygiene of the oven, but may also breed bacteria and affect food health and safety. At the same time, the accumulation of dirt may affect the heating efficiency and performance of the oven and increase energy consumption. Summary of the invention

[0007] In order to overcome the shortcomings of the background technology, the embodiments of the present invention provide an intelligent electric oven temperature control and regulation management system and method, which can effectively solve the problems involved in the above background technology.

[0008] The purpose of the present invention can be achieved through the following technical solutions: The present invention provides an intelligent electric oven temperature control and management system, including: a food analysis module, which is used to acquire images of food, obtain the quality and thickness of the food, and obtain the recommended temperature of the food in combination with the recommended temperature analysis of the cooking method of the food.

[0009] The preheating module is used to detect the temperature of each temperature monitoring point of the electric oven, obtain the temperature increase value of the electric oven per unit time, and then analyze the preheating time of the electric oven and give a reminder.

[0010] The temperature detection module is used to monitor the temperature of the electric oven at each time point in real time and analyze the temperature compliance of the electric oven.

[0011] The temperature fluctuation detection module is used to obtain the average temperature difference of the electric oven through the temperature of the electric oven at each time point, and then analyze and obtain the temperature uniformity of the electric oven.

[0012] The temperature analysis module is used to obtain the temperature evaluation coefficient of the electric oven through analyzing the temperature compliance degree and temperature uniformity degree of the electric oven, and provide feedback.

[0013] The cleaning analysis module is used to detect the internal cleaning parameters of the electric oven, analyze the cleaning demand coefficient of the electric oven and feed it back to the system. The internal cleaning parameters include food residue ratio and stain degree.

[0014] The management database is used to store the recommended temperature for each cooking method corresponding to the set quality ingredients and the internal factory image of the electric oven.

[0015] Preferably, the specific analysis method of the food analysis module is as follows: weigh the food put into the electric oven and record it as M, and at the same time obtain an image of the food, record it as the food image, use the edge contour detection technology to extract the edge contour of the food from the food image, read the thickness of the food therefrom, record it as d, and select the cooking method on the electric oven panel, record it as the food cooking method, read the recommended temperature of each cooking method corresponding to the set quality food from the management database, record the set quality as ΔM, compare the food cooking method with the recommended temperature of each cooking method corresponding to the set quality food, screen out the recommended temperature of the food cooking method, record it as C', and substitute it into the formula Get the recommended temperature C of the ingredients 推荐 ,κ 1 Indicates the proportional constant between the set unit weight of the food and the temperature, κ 2 Indicates the proportional constant between the set food thickness and temperature.

[0016] Preferably, the specific analysis method of the preheating module is: detecting the initial temperature of the electric oven, recorded as C 0 , turn on the electric oven and select a number of monitoring points with equal time intervals according to the set time, record them as temperature monitoring points, monitor the temperature of each temperature monitoring point of the electric oven, record them as C i , i represents the number of the i-th temperature monitoring point, i=1,2,...,n, substitute it into the formula Get the temperature increase value of the electric oven per unit time ΔC, where C (i+1) The temperature of the i+1th temperature monitoring point of the electric oven is expressed by the formula The preheating time T of the electric oven is obtained, and the preheating time of the electric oven is timed accordingly and the system is reminded when the preheating is finished.

[0017] Preferably, the specific analysis method of the temperature detection module is: after the temperature of the electric oven reaches the recommended temperature of the food, a number of detection time points are taken according to the set interval time, recorded as each time point, and the temperature of the electric oven at each time point is monitored in real time, recorded as C" m , m represents the number of the mth time point, m=1,2,...,q, substitute it into the formula Get the temperature compliance degree γ of the electric oven, q represents the number of time points, C 推荐 Indicates the recommended temperature for ingredients.

[0018] Preferably, the specific analysis method of the temperature fluctuation detection module is: reading the temperature C" of the electric oven at each time point m 、Recommended temperature of ingredients C 推荐 , substituting it into the formula ΔC″ m =C 推荐 -C" mGet the temperature difference ΔC at each time point of the electric oven" m , by averaging the temperature difference of the electric oven at each time point, we can get the average temperature difference per unit time point of the electric oven, recorded as ΔC", and substitute it into the formula The temperature uniformity of the electric oven is obtained, λ, where q represents the number of time points.

[0019] Preferably, the specific analysis method of the temperature analysis module is: read the temperature compliance degree γ of the electric oven and the temperature uniformity degree λ of the electric oven, and substitute them into the formula x=(e+1) γ *φ 1 +(e-1) λ *φ 2 Get the temperature evaluation coefficient χ of the electric oven, where φ 1 ,φ 2 The weight factor represents the degree of compliance with the set temperature and the degree of temperature uniformity, e represents a natural constant, and the temperature evaluation coefficient of the electric oven is compared with the preset temperature evaluation coefficient threshold. If the temperature evaluation coefficient of the electric oven is greater than or equal to the preset temperature evaluation coefficient threshold, it means that the temperature of the electric oven is qualified. If the temperature evaluation coefficient of the electric oven is less than the preset temperature evaluation coefficient threshold, it means that the temperature of the electric oven is unqualified, and feedback is given to the system.

[0020] Preferably, the specific analysis method of the internal cleaning parameters of the electric oven is as follows: the first step is to obtain an image of the interior of the electric oven after the food is cooked, which is recorded as the internal image of the electric oven, identify food residues from the internal image of the electric oven by target detection technology, and count the pixels occupied by the food residues, which is recorded as At the same time, the total number of pixels of the internal image of the electric oven is extracted and recorded as By formula The food residue ratio δ of the electric oven is obtained.

[0021] In the second step, the image of the interior of the electric oven is grayed and recorded as the gray image of the interior of the electric oven. At the same time, the internal factory image of the electric oven is read from the management database, and the gray image is grayed and recorded as the standard gray image of the interior of the electric oven. The gray image of the interior of the electric oven and the standard gray image of the interior of the electric oven are processed into the same size, and the gray value of each pixel of the gray image of the interior of the electric oven and the standard gray image of the interior of the electric oven after the size processing is detected, which is recorded as σ k ,σ' k , where k represents the number of the k-th pixel, k = 1, 2, ..., j, and substitute it into the formula Δσ k =|σ k -σ' k |Get the grayscale difference Δσ of each pixel in the grayscale image inside the electric oven k, compare the grayscale difference of each pixel of the grayscale image of the interior of the electric oven with the preset grayscale difference range of stains. If the grayscale difference of a pixel of the grayscale image of the interior of the electric oven is within the preset grayscale difference range of stains, it is recorded as a stain pixel. If the grayscale difference of a pixel of the grayscale image of the interior of the electric oven is not within the preset grayscale difference range of stains, it means that the grayscale difference of the pixel is not a stain. Statistically screen out all the stain pixels in the grayscale image of the interior of the electric oven, and record its number as N. At the same time, extract the total number of pixels of the grayscale image of the interior of the electric oven, and record it as N 总 , through the formula Get the degree of stain l of the electric oven.

[0022] Preferably, the specific analysis method of the cleaning analysis module is: respectively read the food residue ratio δ of the electric oven and the stain level l of the electric oven, and substitute them into the formula Get the cleaning requirement coefficient of the electric oven where δ 0 Indicates the maximum allowable ratio of food residue. They respectively represent the set food residue ratio and the weight factor of the stain degree, e represents a natural constant, and the cleaning requirement coefficient of the electric oven is compared with the preset cleaning requirement coefficient threshold. If the cleaning requirement coefficient of the electric oven is greater than or equal to the preset cleaning requirement coefficient threshold, it means that the cleaning degree of the electric oven is unqualified and needs to be cleaned, and feedback is given to the system; if the cleaning requirement coefficient of the electric oven is less than the preset cleaning requirement coefficient threshold, it means that the cleaning degree of the electric oven is qualified and does not need to be cleaned for the time being.

[0023] Preferably, the present invention provides a temperature control and regulation management method for an intelligent electric oven, and the specific steps of the temperature control and regulation management method are as follows: S1. Food analysis: acquiring images of the food to obtain the quality and thickness of the food, and combining the recommended temperature analysis of the cooking method of the food to obtain the recommended temperature of the food.

[0024] S2. Preheating the electric oven: Detect the temperature of each temperature monitoring point of the electric oven to obtain the temperature increase value of the electric oven per unit time, and then analyze the preheating time of the electric oven and give a reminder.

[0025] S3. Electric oven temperature detection: Monitor the temperature of the electric oven at each time point in real time and analyze the temperature compliance of the electric oven.

[0026] S4. Electric oven temperature fluctuation detection: The average temperature difference of the electric oven is obtained by the temperature of the electric oven at each time point, and then the temperature uniformity of the electric oven is analyzed.

[0027] S5. Electric oven temperature analysis: The temperature evaluation coefficient of the electric oven is obtained by analyzing the temperature compliance and temperature uniformity of the electric oven, and feedback is provided.

[0028] S6. Electric oven cleaning detection: The internal cleaning parameters of the electric oven are obtained by acquiring images of the interior of the electric oven. The internal cleaning parameters include the food residue ratio and the degree of stains.

[0029] S7. Electric oven cleaning demand analysis: The cleaning demand coefficient of the electric oven is obtained based on the internal cleaning parameter analysis of the electric oven, and feedback is provided.

[0030] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: 1. The present invention obtains the recommended temperature of the food by acquiring images of the food and combining the recommended temperature analysis of the cooking method of the food. Different temperature recommendations can be provided for different ingredients, thereby reducing the probability of cooking failure due to improper temperature.

[0031] Second, the present invention obtains the temperature evaluation coefficient of the electric oven by analyzing the temperature compliance and temperature uniformity of the electric oven, and provides feedback, so that the user can adjust and optimize the cooking process in a targeted manner to ensure that the food is better baked.

[0032] 3. The present invention obtains the cleaning demand coefficient of the electric oven through internal cleaning parameter analysis of the electric oven, and provides feedback thereto, so as to remind the user to clean the oven in time to avoid the influence of stain accumulation on the use and baking effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0034] Figure 1 The module connection diagram of an intelligent electric oven temperature control and management system.

[0035] Figure 2 The present invention is a flow chart of a temperature control and adjustment management method for an intelligent electric oven. DETAILED DESCRIPTION

[0036] 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.

[0037] See also Figure 1As shown, an intelligent electric oven temperature control and regulation management system includes a food analysis module, a preheating module, a temperature detection module, a temperature fluctuation detection module, a temperature analysis module, a cleaning analysis module, and a management database.

[0038] The management database is connected to the food analysis module, the preheating module, the cleaning analysis module, and the temperature analysis module; the temperature analysis module is connected to the temperature detection module and the temperature fluctuation detection module; and the preheating module is connected to the food analysis module.

[0039] The food material analysis module is used to acquire images of food materials, thereby obtaining the quality and thickness of the food materials, and combining the recommended temperature analysis of the food material cooking method to obtain the recommended temperature of the food materials.

[0040] The specific analysis method of the food analysis module is as follows: weigh the food put into the electric oven and record it as M, and at the same time obtain an image of it and record it as the food image, use the edge contour detection technology to extract the edge contour of the food from the food image, read the thickness of the food from it and record it as d, and select the cooking method on the electric oven panel and record it as the food cooking method, read the recommended temperature of each cooking method corresponding to the set quality food from the management database, record the set quality as ΔM, compare the food cooking method with the recommended temperature of each cooking method corresponding to the set quality food, screen out the recommended temperature of the food cooking method and record it as C', and substitute it into the formula Get the recommended temperature C of the ingredients 推荐 ,κ 1 Indicates the proportional constant between the set unit weight of the food and the temperature, κ 2 It indicates the proportional constant between the set thickness of the food and the temperature. By weighing and detecting the thickness, it can provide accurate recommended temperature according to the specific situation of the food to ensure the perfect cooking effect. At the same time, it can adapt to the needs of different ingredients and cooking methods to meet a variety of tastes and requirements.

[0041] The preheating module is used to detect the temperature of each temperature monitoring point of the electric oven, obtain the temperature increase value of the electric oven per unit time, and then analyze the preheating time of the electric oven and give a reminder.

[0042] The specific analysis method of the preheating module is: the initial temperature of the electric oven is detected and recorded as C 0 , turn on the electric oven and select a number of monitoring points with equal time intervals according to the set time, record them as temperature monitoring points, monitor the temperature of each temperature monitoring point of the electric oven, record them as C i , i represents the number of the i-th temperature monitoring point, i=1,2,...,n, substitute it into the formula Get the temperature increase value of the electric oven per unit time ΔC, where C (i+1)The temperature of the i+1th temperature monitoring point of the electric oven is expressed by the formula The preheating time T of the electric oven is obtained, and the preheating time of the electric oven is timed and the system is reminded when the preheating is finished; a reasonable preheating time can save energy and time, and remind the user in time that the preheating is finished, which is convenient for subsequent operations and less prone to errors.

[0043] The temperature detection module is used to monitor the temperature of the electric oven at each time point in real time and analyze the temperature compliance of the electric oven.

[0044] The specific analysis method of the temperature detection module is: after the temperature of the electric oven reaches the recommended temperature of the food, a number of detection time points are taken according to the set interval time, recorded as each time point, and the temperature of the electric oven at each time point is monitored in real time, recorded as C" m , m represents the number of the mth time point, m=1,2,...,q, substitute it into the formula Get the temperature compliance degree γ of the electric oven, q represents the number of time points, C 推荐 Indicates the recommended temperature for the ingredients; if the temperature deviates from the specified level, timely measures can be taken to adjust it to ensure the cooking effect.

[0045] The temperature fluctuation detection module is used to obtain the average temperature difference of the electric oven through the temperature of the electric oven at each time point, and then analyze and obtain the temperature uniformity of the electric oven.

[0046] The specific analysis method of the temperature fluctuation detection module is: The specific analysis method of the temperature fluctuation detection module is:

[0047] Read the temperature of the electric oven at each time point C" m 、Recommended temperature of ingredients C 推荐 , substituting it into the formula ΔC' m '=C 推荐 -C" m Get the temperature difference ΔC at each time point of the electric oven" m , by averaging the temperature difference of the electric oven at each time point, we can get the average temperature difference per unit time point of the electric oven, recorded as ΔC", and substitute it into the formula The temperature uniformity of the electric oven is obtained, and q represents the number of time points; it is conducive to maintaining a stable temperature state, making the cooking results more consistent, and at the same time helps to ensure that the food is heated evenly to obtain a more ideal cooking effect.

[0048] The temperature analysis module is used to obtain the temperature evaluation coefficient of the electric oven through analyzing the temperature compliance degree and temperature uniformity degree of the electric oven, and provide feedback.

[0049] The specific analysis method of the temperature analysis module is: read the temperature compliance degree γ of the electric oven and the temperature uniformity degree λ of the electric oven, and substitute them into the formula x=(e+1) γ *φ 1 +(e-1) λ *φ 2 Get the temperature evaluation coefficient χ of the electric oven, where φ 1 ,φ 2 The weight factor represents the degree of compliance with the set temperature and the degree of temperature uniformity, e represents a natural constant, and the temperature evaluation coefficient of the electric oven is compared with the preset temperature evaluation coefficient threshold. If the temperature evaluation coefficient of the electric oven is greater than or equal to the preset temperature evaluation coefficient threshold, it means that the temperature of the electric oven is qualified. If the temperature evaluation coefficient of the electric oven is less than the preset temperature evaluation coefficient threshold, it means that the temperature of the electric oven is unqualified, and feedback is given to the system; the reliability of the temperature of the electric oven is enhanced, and the cooking temperature can be ensured to be qualified, thereby ensuring the quality and taste of the food.

[0050] It should be noted that, in a specific embodiment, φ 1 Can be set to 0.5, φ 2 It can be set to 0.5. Temperature compliance is directly related to whether the appropriate temperature can be provided for the ingredients as expected, and temperature uniformity is also critical to the consistency of cooking results. Therefore, the weights of temperature compliance and temperature uniformity are equal.

[0051] The cleaning analysis module is used to detect the internal cleaning parameters of the electric oven, analyze the cleaning demand coefficient of the electric oven and feed it back to the system. The internal cleaning parameters include food residue ratio and stain degree.

[0052] The specific analysis method of the internal cleaning parameters of the electric oven is as follows: the first step is to obtain an image of the interior of the electric oven after the food is cooked, which is recorded as the internal image of the electric oven, identify food residues from the internal image of the electric oven by target detection technology, and count the pixels occupied by the food residues, which is recorded as At the same time, the total number of pixels of the internal image of the electric oven is extracted and recorded as By formula The food residue ratio δ of the electric oven is obtained; the residue accumulation that affects the subsequent cooking effect and sanitation can be avoided, and a data basis is provided for the normal maintenance of the electric oven, which helps to extend the service life.

[0053] In the second step, the image of the interior of the electric oven is grayed and recorded as the gray image of the interior of the electric oven. At the same time, the internal factory image of the electric oven is read from the management database, and the gray image is grayed and recorded as the standard gray image of the interior of the electric oven. The gray image of the interior of the electric oven and the standard gray image of the interior of the electric oven are processed into the same size, and the gray value of each pixel of the gray image of the interior of the electric oven and the standard gray image of the interior of the electric oven after the size processing is detected, which is recorded as σ k ,σ' k , where k represents the number of the k-th pixel, k = 1, 2, ..., j, and substitute it into the formula Δσ k =σ k -σ' k Get the grayscale difference Δσ of each pixel in the grayscale image of the interior of the electric oven k , compare the grayscale difference of each pixel of the grayscale image of the interior of the electric oven with the preset grayscale difference range of stains. If the grayscale difference of a pixel of the grayscale image of the interior of the electric oven is within the preset grayscale difference range of stains, it is recorded as a stain pixel. If the grayscale difference of a pixel of the grayscale image of the interior of the electric oven is not within the preset grayscale difference range of stains, it means that the grayscale difference of the pixel is not a stain. Statistically screen out all the stain pixels in the grayscale image of the interior of the electric oven, and record its number as N. At the same time, extract the total number of pixels of the grayscale image of the interior of the electric oven, and record it as N 总 , through the formula Get the degree of stain l of the electric oven; help users accurately understand the specific degree of stains, facilitate targeted cleaning, and improve cleaning efficiency and effect.

[0054] The specific analysis method of the cleaning analysis module is: respectively read the food residue ratio δ of the electric oven and the stain level l of the electric oven, and substitute them into the formula Get the cleaning requirement coefficient of the electric oven where δ 0 Indicates the maximum allowable ratio of food residue. They respectively represent the set food residue ratio and the weight factor of the stain degree, e represents a natural constant, and the cleaning requirement coefficient of the electric oven is compared with the preset cleaning requirement coefficient threshold. If the cleaning requirement coefficient of the electric oven is greater than or equal to the preset cleaning requirement coefficient threshold, it means that the cleanliness of the electric oven is unqualified and needs to be cleaned, and feedback is given to the system; if the cleaning requirement coefficient of the electric oven is less than the preset cleaning requirement coefficient threshold, it means that the cleanliness of the electric oven is qualified and does not need to be cleaned for the time being; it can ensure that the electric oven is at an appropriate cleanliness level for a long time, which is beneficial to its performance stability and service life.

[0055] It should be noted that, in a specific embodiment, It can be set to 0.4. It can be set to 0.6. Although food residues need to be cleaned, they are usually easier to find and deal with directly. Most of them can be removed by simple sweeping or wiping. Stains may be more stubborn and difficult to clean. They have a more direct and critical impact on the user experience and hygiene of the electric oven. Therefore, the weight corresponding to the degree of stains is larger.

[0056] The management database is used to store the recommended temperature for each cooking method corresponding to the set quality ingredients and the internal factory image of the electric oven.

[0057] See also Figure 2 As shown, in addition, the present invention provides a temperature control and regulation management method for an intelligent electric oven, and the specific steps of the temperature control and regulation management method are as follows: S1. Food analysis: Acquire images of the food to obtain the quality and thickness of the food, and combine the recommended temperature analysis of the cooking method of the food to obtain the recommended temperature of the food.

[0058] S2. Preheating the electric oven: Detect the temperature of each temperature monitoring point of the electric oven to obtain the temperature increase value of the electric oven per unit time, and then analyze the preheating time of the electric oven and give a reminder.

[0059] S3. Electric oven temperature detection: Monitor the temperature of the electric oven at each time point in real time and analyze the temperature compliance of the electric oven.

[0060] S4. Electric oven temperature fluctuation detection: The average temperature difference of the electric oven is obtained by the temperature of the electric oven at each time point, and then the temperature uniformity of the electric oven is analyzed.

[0061] S5. Electric oven temperature analysis: The temperature evaluation coefficient of the electric oven is obtained by analyzing the temperature compliance and temperature uniformity of the electric oven, and feedback is provided.

[0062] S6. Electric oven cleaning detection: The internal cleaning parameters of the electric oven are obtained by acquiring images of the interior of the electric oven. The internal cleaning parameters include the food residue ratio and the degree of stains.

[0063] S7. Electric oven cleaning demand analysis: The cleaning demand coefficient of the electric oven is obtained based on the internal cleaning parameter analysis of the electric oven, and feedback is provided.

[0064] This system obtains the recommended temperature of the food by acquiring images of the food and analyzing the recommended temperature of the cooking method of the food. The temperature evaluation coefficient of the electric oven is obtained by analyzing the temperature compliance and temperature uniformity of the electric oven, and feedback is given to the system. The cleaning requirement coefficient of the electric oven is obtained by analyzing the internal cleaning parameters of the electric oven and fed back to the system, so as to accurately understand the temperature performance of the electric oven for adjustment and optimization, ensure the reliability of the cooking temperature, and provide users with more intelligent cooking plans and electric oven management strategies.

[0065] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations on the present invention. A person skilled in the art may make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention and they are still covered by the protection scope of the present invention.

Claims

1. An intelligent electric oven temperature control and management system, characterized in that: The system specifically includes the following modules: The food analysis module is used to obtain images of food, obtain the quality and thickness of the food, and analyze the recommended temperature of the food in combination with the recommended temperature of the cooking method of the food; The preheating module is used to detect the temperature of each temperature monitoring point of the electric oven, obtain the temperature increase value of the electric oven per unit time, and then analyze the preheating time of the electric oven and give a reminder; The temperature detection module is used to monitor the temperature of the electric oven at each time point in real time and analyze the temperature compliance of the electric oven; The temperature fluctuation detection module is used to obtain the average temperature difference of the electric oven through the temperature of the electric oven at each time point, and then analyze and obtain the temperature uniformity of the electric oven; The temperature analysis module is used to obtain the temperature evaluation coefficient of the electric oven through the temperature compliance and temperature uniformity of the electric oven, and provide feedback; The cleaning analysis module is used to detect the internal cleaning parameters of the electric oven, analyze and obtain the cleaning demand coefficient of the electric oven and feed it back to the system. The internal cleaning parameters include the food residue ratio and the degree of stains. Management database for storing recommended temperatures for each cooking method and internal factory images of electric ovens for ingredients of set quality; The specific analysis method of the internal cleaning parameters of the electric oven is: The first step is to obtain an image of the interior of the electric oven after the ingredients are cooked, which is recorded as the interior image of the electric oven. The food residue is identified from the interior image of the electric oven through the target detection technology, and the pixels occupied by the food residue are counted, which is recorded as , and extract the total number of pixels of the internal image of the electric oven, recorded as , through the formula Get the food residue ratio of the electric oven ; In the second step, the image of the interior of the electric oven is grayed and recorded as the gray image of the interior of the electric oven. At the same time, the internal factory image of the electric oven is read from the management database, and the gray image is grayed and recorded as the standard gray image of the interior of the electric oven. The gray image of the interior of the electric oven and the standard gray image of the interior of the electric oven are processed into the same size, and the gray value of each pixel of the gray image of the interior of the electric oven and the standard gray image of the interior of the electric oven after the size processing is detected, which is recorded as ,in Indicates The number of pixels, , substituting it into the formula Get the grayscale difference of each pixel in the grayscale image of the interior of the electric oven , compare the grayscale difference of each pixel of the grayscale image of the interior of the electric oven with the preset grayscale difference range of stains. If the grayscale difference of a pixel of the grayscale image of the interior of the electric oven is within the preset grayscale difference range of stains, it is recorded as a stain pixel. If the grayscale difference of a pixel of the grayscale image of the interior of the electric oven is not within the preset grayscale difference range of stains, it means that the grayscale difference of the pixel is not a stain. Statistically screen out all the stain pixels in the grayscale image of the interior of the electric oven, and record their number as , and extract the total pixel points of the grayscale image inside the electric oven, recorded as , through the formula Get the degree of stain of the electric oven ; The specific analysis method of the cleaning analysis module is: Read the food residue ratio of the electric oven separately , the degree of stains on the electric oven , substituting it into the formula Get the cleaning requirement coefficient of the electric oven ,in Indicates the maximum allowable ratio of food residue. They represent the set food residue ratio and the weight factor of the stain degree respectively. It represents a natural constant. The cleaning requirement coefficient of the electric oven is compared with the preset cleaning requirement coefficient threshold. If the cleaning requirement coefficient of the electric oven is greater than or equal to the preset cleaning requirement coefficient threshold, it means that the cleanliness of the electric oven is unqualified and needs to be cleaned. Feedback is given to the system. If the cleaning requirement coefficient of the electric oven is less than the preset cleaning requirement coefficient threshold, it means that the cleanliness of the electric oven is qualified and does not need to be cleaned for the time being.

2. The intelligent temperature control and management system for electric ovens according to claim 1, characterized in that: The specific analysis method of the food analysis module is: Weigh the ingredients put into the electric oven and record them as At the same time, an image is acquired, recorded as the food image, and the edge contour of the food is extracted from the food image using edge contour detection technology, from which the thickness of the food is read, recorded as , and select the cooking method on the electric oven panel, record it as the cooking method of the ingredients, read the recommended temperature for each cooking method corresponding to the set quality ingredients from the management database, and record the set quality as , compare the cooking method of the ingredients with the recommended temperature of each cooking method for the set quality ingredients, and filter out the recommended temperature of the cooking method of the ingredients, recorded as , substituting it into the formula Get the recommended temperature of ingredients , Indicates the proportional constant between the set unit weight of the ingredients and the temperature. Indicates the proportional constant between the set food thickness and temperature.

3. The intelligent temperature control and management system for electric ovens according to claim 2 is characterized in that: The specific analysis method of the preheating module is: The initial temperature of the electric oven is detected and recorded as , turn on the electric oven and select a number of monitoring points with equal time intervals according to the set time, record them as temperature monitoring points, monitor the temperature of each temperature monitoring point of the electric oven, record them as , Indicates The number of the temperature monitoring point, , substituting it into the formula Get the temperature increase value of the electric oven per unit time ,in Indicates the electric oven The temperature of the temperature monitoring point is calculated by the formula Get the preheating time of the electric oven , so as to time the preheating time of the electric oven and remind the system when the preheating is finished.

4. The intelligent temperature control and management system for electric ovens according to claim 1, characterized in that: The specific analysis method of the temperature detection module is: After the temperature of the electric oven reaches the recommended temperature of the food, several detection time points are taken according to the set interval time, recorded as each time point, and the temperature of the electric oven at each time point is monitored in real time, recorded as , Indicates The number of the time point, , substitute it into the formula Get the temperature compliance of the electric oven , represents the number of time points, Indicates the recommended temperature for ingredients.

5. The intelligent temperature control and management system for electric ovens according to claim 4, characterized in that: The specific analysis method of the temperature fluctuation detection module is: Read the temperature of the electric oven at each time point , Recommended temperature of ingredients , substituting it into the formula Get the temperature difference of the electric oven at each time point By taking the average value of the temperature difference of the electric oven at each time point, the average temperature difference of the electric oven per unit time point is obtained, which is recorded as , substituting it into the formula Get the temperature uniformity of the electric oven , Indicates the number of time points.

6. The intelligent temperature control and management system for electric ovens according to claim 5, characterized in that: The specific analysis method of the temperature analysis module is: Read the temperature compliance of the electric oven , Temperature uniformity of electric oven , substituting it into the formula Get the temperature evaluation coefficient of the electric oven ,in The weight factor that indicates the set temperature compliance and temperature uniformity. Represents a natural constant, and compares the temperature evaluation coefficient of the electric oven with the preset temperature evaluation coefficient threshold. If the temperature evaluation coefficient of the electric oven is greater than or equal to the preset temperature evaluation coefficient threshold, it means that the temperature of the electric oven is qualified. If the temperature evaluation coefficient of the electric oven is less than the preset temperature evaluation coefficient threshold, it means that the temperature of the electric oven is unqualified, and feedback is given to the system and the temperature fine adjustment module is executed.

7. An intelligent electric oven temperature control and adjustment management method, executed by the system according to any one of claims 1 to 6, characterized in that: The steps include: S1. Food analysis: Get an image of the food to get the quality and thickness of the food, and combine it with the recommended temperature analysis of the cooking method to get the recommended temperature of the food; S2. Electric oven preheating: The temperature of each temperature monitoring point of the electric oven is detected to obtain the temperature increase value of the electric oven per unit time, and then the preheating time of the electric oven is analyzed and reminded; S3. Electric oven temperature detection: Real-time monitoring of the temperature of the electric oven at each time point, and analysis of the temperature compliance of the electric oven; S4. Electric oven temperature fluctuation detection: The average temperature difference of the electric oven is obtained by the temperature of the electric oven at each time point, and then the temperature uniformity of the electric oven is analyzed; S5. Electric oven temperature analysis: The temperature evaluation coefficient of the electric oven is obtained by analyzing the temperature compliance of the electric oven and the temperature uniformity of the electric oven, and feedback is provided; S6. Electric oven cleaning detection: internal cleaning parameters of the electric oven are obtained by acquiring images of the interior of the electric oven, the internal cleaning parameters including the food residue ratio and the degree of stains; S7. Electric oven cleaning demand analysis: The cleaning demand coefficient of the electric oven is obtained based on the internal cleaning parameter analysis of the electric oven, and feedback is provided.

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