Automatic detection system for disinfection of infant tableware

Abstract

The invention relates to the technical field of sanitary equipment detection, and particularly discloses an automatic detection system for disinfection of infant tableware, which is used for solving the problems that the existing tableware disinfection equipment is non-uniform in disinfection, the cleanliness of tableware and the disinfection effectiveness are directly influenced, and hidden dangers are brought to infant health. According to the invention, the surface image of the tableware of the same type after cleaning is extracted, the standard surface image of the tableware of the type after cleaning is obtained, and the cleanliness of the tableware is analyzed based on the tableware surface image and the pixel value of the standard surface image, so that whether the surface of the tableware has an area which is not thoroughly disinfected or not can be identified, and the comprehensiveness of the disinfection process is ensured; based on the obtained pressure value of the tableware storage layer of the tableware disinfection equipment, whether tableware placement is reasonable or not is analyzed, and then tableware disinfection uniformity analysis is carried out by constructing a tableware disinfection uniformity analysis strategy; the tableware disinfection equipment solves the problem of non-uniform disinfection of existing tableware disinfection equipment, so that potential health hazards are prevented.

Description

Technical Field

[0001] The present invention relates to the technical field of sanitary equipment detection, and more specifically, to an automatic detection system for disinfecting children's tableware. Background Art

[0002] Disinfection of children's tableware and food safety are key links in kindergartens, childcare institutions and family life. Children's immune systems are not yet fully developed, and they have weak resistance to harmful substances such as pathogens and viruses in the external environment. Therefore, ensuring the cleanliness and disinfection of tableware is a basic work to prevent the spread of diseases and protect the health of children. The traditional process of disinfecting children's tableware mainly relies on manual cleaning, soaking in disinfectant, high-temperature steaming, etc., but these methods have many problems in actual operation, such as incomplete manual cleaning, inadequate cleaning of tableware before disinfection, and residual food residues and grease affecting the disinfection effect, resulting in incomplete disinfection or secondary contamination.

[0003] In the existing public literature, document 1 (Yang Yih Machinery Co., Ltd.; Patent Issued for Tableware Sterilizing and Drying Apparatus [J]. Journal of Engineering, 2014) studied the internal environment of the tableware disinfection cabinet and analyzed the hygiene problems that may exist during the use of the disinfection cabinet. The results showed that during the operation of the disinfection cabinet, factors such as internal temperature, humidity and microbial indicators have a significant impact on the disinfection effect; document 2 ([1] Aldo H, Jaesung L, Joel H, et al. Efficacy of electrolyzed water and anacidic formulation compared with regularly used chemical sanitizers for tableware sanitization during mechanical and manual ware-washing protocols. [J]. Journal of food protection, 2009, 72 (6): 1315-20.) studied the disinfection effect of electrolyzed water and an acidic disinfection formula on tableware during mechanical washing and manual washing processes compared with conventionally used chemical disinfectants. The above-mentioned staff often have irregular operations during the disinfection process, such as insufficient disinfection time, substandard temperature, incomplete closure of the disinfection cabinet, and tableware not being neatly placed. There is no effective monitoring method, which leads to uneven disinfection, directly affecting the cleanliness of the tableware and the effectiveness of disinfection, posing a hidden danger to the health of young children. In order to solve the above problems, a technical solution is now provided. Summary of the invention

[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides an automated detection system for disinfecting children's tableware, which analyzes the cleanliness of the tableware based on the pixel values ​​of the tableware surface image and the standard surface image, analyzes whether the tableware is placed reasonably based on the pressure value of the tableware storage layer of the tableware disinfection equipment, and then analyzes the uniformity of tableware disinfection by constructing a tableware disinfection uniformity analysis strategy, thereby solving the problem of uneven disinfection existing in the existing tableware disinfection equipment, thereby preventing potential health hazards, and solving the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] An automated detection system for disinfecting children's tableware comprises a tableware disinfection device, a first tableware automatic detection module and a second tableware automatic detection module; the tableware disinfection device is connected to the second tableware automatic detection module; the second tableware automatic detection module comprises a third feature processing unit, a second camera, a first-level disinfection impact analysis unit and a tableware disinfection uniform optimization unit; the third feature processing unit is used to obtain a tableware placement image inside the tableware disinfection device and the real-time temperature and humidity inside the tableware disinfection device during the disinfection period through the second camera, obtain the tableware placement spacing based on the tableware placement image inside the tableware disinfection device, and obtain the tableware type, the number of tableware, the space value occupied by the tableware inside the tableware disinfection device and the space value inside the disinfection device during the disinfection period; the first-level disinfection impact analysis unit is used to obtain the real-time temperature and humidity inside the tableware disinfection device during the disinfection period, and calculate the tableware disinfection impact value by importing the real-time temperature and humidity inside the tableware disinfection device during the disinfection period into a disinfection impact value calculation model; the tableware disinfection uniform optimization unit is used to analyze the tableware disinfection uniformity by importing the disinfection impact value, the tableware placement spacing, the number of tableware in the disinfection period, the space value occupied by the tableware inside the tableware disinfection device and the space value inside the disinfection device into a tableware disinfection uniform analysis strategy, and the formula of the tableware disinfection uniform analysis strategy is:

[0007]

[0008] Where: F cx is the average value of tableware disinfection, d x is the disinfection impact value, k cj k is the space occupied by tableware inside the tableware disinfection equipment, n is the internal space value of the disinfection equipment, d j is the spacing between the jth tableware, d b is the preset tableware spacing, and m is the number of tableware within the disinfection period.

[0009] As a further solution of the present invention, the formula of the disinfection impact value calculation model is:

[0010]

[0011] Where: d x is the disinfection impact value, T is the number of moments in the disinfection period, e t+1 is the real-time temperature and humidity inside the tableware disinfection equipment at time t+1, e t is the real-time temperature and humidity inside the tableware disinfection equipment at time t, e max is the maximum real-time temperature and humidity inside the tableware disinfection equipment during the disinfection period, e min It is the minimum real-time temperature and humidity inside the tableware disinfection equipment during the disinfection period.

[0012] As a further solution of the present invention, the second tableware automatic detection module also includes a second feature processing unit, a second automatic detection unit, and a third automatic detection unit; the second feature processing unit is connected to the second automatic detection unit, the second camera is connected to the third feature processing unit, the third feature processing unit is connected to the first-level disinfection impact analysis unit, and the third feature processing unit and the disinfection impact analysis unit are respectively connected to the tableware disinfection uniformity optimization unit.

[0013] As a further solution of the present invention, the second feature processing unit is used to divide the tableware storage layer of the tableware disinfection equipment into several weight sensing areas, set several weight sensing points in each weight sensing area, and set a pressure sensor at each weight sensing point. After the tableware is placed, the pressure values ​​of all weight sensing points are obtained, the variance of the pressure values ​​of all weight sensing points is calculated to obtain the pressure distribution coefficient of each weight sensing area, and the mean of the weight sensing points in each weight sensing area is calculated to obtain the pressure concentration value; the second automatic detection unit is used to obtain the pressure distribution coefficient and pressure concentration value of each weight sensing area, and whether the tableware placement is reasonable is detected through the pressure distribution coefficient and pressure concentration value of each weight sensing area.

[0014] As a further solution of the present invention, the first tableware automatic detection module includes a first camera, a first feature extraction unit, a first feature processing unit, and a tableware cleanliness analysis unit; the first camera is connected to the first feature extraction unit, the first feature extraction unit is connected to the first feature processing unit, and the first feature extraction unit and the first feature processing unit are respectively connected to the tableware cleanliness analysis unit.

[0015] As a further solution of the present invention, the first camera is used to capture the surface image of the tableware after cleaning; the first feature extraction unit is used to extract the surface image of the same type of tableware after cleaning, and obtain the standard surface image of the type of tableware after cleaning; the tableware surface image and the standard surface image are respectively obtained, the tableware surface image is divided into a number of feature pixel blocks, the pixel values ​​of the pixel points in the feature pixel blocks are extracted, and the feature pixel values ​​of the feature pixel blocks are summarized to obtain the feature pixel values ​​of the feature pixel blocks, and then the standard surface image is divided into a number of standard feature pixel blocks, the pixel values ​​of the pixel points in the standard feature pixel blocks are extracted, and the standard feature pixel values ​​of the standard feature pixel blocks are summarized to obtain the standard feature pixel values ​​of the standard feature pixel blocks.

[0016] As a further solution of the present invention, the first feature processing unit is used to process the feature pixel values ​​of each feature pixel block and the standard feature pixel values ​​of each standard feature pixel block; the variance value of the feature pixel value of each feature pixel block is calculated to obtain the pixel representation value of the tableware surface image, and then the variance value of the standard feature pixel value of each standard feature pixel block is calculated to obtain the pixel standard value of the standard surface image; the tableware cleanliness analysis unit is used to construct a tableware cleanliness analysis strategy to analyze the cleanliness of the tableware through the feature pixel values ​​of each feature pixel block, the standard feature pixel values ​​of each standard feature pixel block, the pixel representation value and the pixel standard value.

[0017] As a further solution of the present invention, the tableware cleanliness analysis unit is used to construct a tableware cleanliness analysis strategy to analyze the cleanliness of the tableware through the characteristic pixel values ​​of each characteristic pixel block, the standard characteristic pixel values ​​of each standard characteristic pixel block, the pixel performance value and the pixel standard value, and obtain the cleanliness value of the tableware by importing the characteristic pixel values ​​of each characteristic pixel block, the standard characteristic pixel values ​​of each standard characteristic pixel block, the pixel performance value and the pixel standard value into the formula of the tableware cleanliness analysis strategy. The formula of the tableware cleanliness analysis strategy is:

[0018]

[0019] Where: J c is the cleanliness of the tableware, n is the number of feature pixel blocks, is the pixel representation value of the i-th feature pixel block, is the pixel standard value of the i-th feature pixel block, is the pixel representation value of the i-th standard feature pixel block, is the pixel standard value of the i-th standard feature pixel block, γ is the adjustment parameter to prevent the denominator from being zero, is the characteristic pixel value of the i-th characteristic pixel block, is the maximum characteristic pixel value of each characteristic pixel block in the tableware surface image, is the minimum characteristic pixel value of each characteristic pixel block in the tableware surface image, is the characteristic pixel value of the i-th standard characteristic pixel block, is the maximum standard feature pixel value of each standard feature pixel block in the standard surface image, It is the minimum standard feature pixel value of each standard feature pixel block in the standard surface image.

[0020] The technical effects and advantages of an automated detection system for disinfecting children's tableware of the present invention are as follows: the present invention extracts surface images of tableware of the same type after cleaning, obtains standard surface images of the tableware of the type after cleaning, and analyzes the cleanliness of the tableware based on the pixel values ​​of the tableware surface images and the standard surface images, thereby effectively preventing secondary contamination caused by incomplete disinfection, fundamentally ensuring the cleanliness of children's tableware, and ensuring the comprehensiveness of the disinfection process; based on obtaining the pressure value of the tableware storage layer of the tableware disinfection equipment, analyzing whether the tableware is placed reasonably, ensuring uniform air circulation and heat distribution during the disinfection process, and avoiding uneven disinfection caused by improper operation of staff (such as insufficient disinfection time, substandard temperature, and incomplete closure of the disinfection cabinet); and then analyzing the uniformity of tableware disinfection by constructing a tableware disinfection uniformity analysis strategy, reducing the need for manual intervention, improving operating efficiency and disinfection quality, and thus preventing potential health hazards. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a schematic diagram of the structure of an automated detection system for disinfecting children's tableware provided in Example 1 of the present invention. DETAILED DESCRIPTION

[0022] The following will be combined with the accompanying drawings in the present invention to clearly and completely describe the technical solution in the present invention. Obviously, the described technical solution is only a part of the present invention, not all of it. Based on the technical solution in the present invention, all other technical solutions obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0023] Figure 1 FIG. 1 shows a schematic diagram of the structure of an automated detection system for disinfecting tableware for infants provided in Embodiment 1 of the present invention. Figure 1 As shown, an automatic detection system for disinfecting tableware for infants in this embodiment includes a tableware disinfection device, a first tableware automatic detection module and a second tableware automatic detection module; the tableware disinfection device is connected to the second tableware automatic detection module;

[0024] Tableware disinfection equipment is used to disinfect children's tableware;

[0025] The first tableware automatic detection module is used to construct a tableware cleanliness analysis strategy to analyze the cleanliness of the tableware;

[0026] The second tableware automatic detection module is used to construct a tableware disinfection uniformity analysis strategy to analyze the uniformity of tableware disinfection.

[0027] The first tableware automatic detection module includes a first camera, a first feature extraction unit, a first feature processing unit, and a tableware cleanliness analysis unit; the first camera is connected to the first feature extraction unit, the first feature extraction unit is connected to the first feature processing unit, and the first feature extraction unit and the first feature processing unit are respectively connected to the tableware cleanliness analysis unit;

[0028] The first camera is used to capture the image of the surface of the tableware after cleaning;

[0029] The first feature extraction unit is used to extract the surface image of the same type of tableware after cleaning, and obtain the standard surface image of the tableware of the same type after cleaning; respectively obtain the tableware surface image and the standard surface image, divide the tableware surface image into a number of feature pixel blocks, extract the pixel values ​​of the pixel points in the feature pixel blocks, and summarize to obtain the feature pixel values ​​of the feature pixel blocks, then divide the standard surface image into a number of standard feature pixel blocks, extract the pixel values ​​of the pixel points in the standard feature pixel blocks, and summarize to obtain the standard feature pixel values ​​of the standard feature pixel blocks;

[0030] It should be noted that the same type of tableware after cleaning refers to tableware with exactly the same type, material, size, shape and surface decoration; the standard surface image after cleaning refers to an ideal surface image of tableware that has been fully cleaned and is free of any stains or residues, which is used as a comparison benchmark; the tableware surface image is segmented into several feature pixel blocks, which can be uniformly segmented or a specific segmentation strategy can be implemented according to the image content, each feature pixel block contains a number of pixels, and the segmentation of the standard surface image adopts the same segmentation method as the tableware surface image segmentation, ensuring that the segmentation methods of the actual surface image and the standard surface image are consistent, while ensuring that each actual feature pixel block and the corresponding standard feature pixel block have the same corresponding position in the image, that is, the number of feature pixel blocks and the corresponding standard feature pixel blocks are the same.

[0031] By acquiring and analyzing the surface images of cleaned tableware and standard surface images, the cleanliness of the tableware can be accurately judged. Since tableware of the same type has the same material, size, shape and surface decoration, the system can identify any subtle differences in cleaning through precise comparison of pixel values ​​to ensure that the cleanliness of each piece of tableware meets the standard. The use of automated methods for cleanliness detection avoids subjective misjudgments and operational errors in manual detection. Through automatic segmentation and pixel analysis, the consistency and accuracy of each detection is ensured, greatly reducing the possibility of missed detection or misjudgment.

[0032] The first feature processing unit is used to process the feature pixel values ​​of each feature pixel block and the standard feature pixel values ​​of each standard feature pixel block; the variance value of the feature pixel value of each feature pixel block is calculated to obtain the pixel representation value of the tableware surface image, and then the variance value of the standard feature pixel value of each standard feature pixel block is calculated to obtain the pixel standard value of the standard surface image; by comparing the feature pixel values ​​of the actual tableware surface image with the standard surface image, the cleaning effect can be quantified for optimizing the cleaning process, such as adjusting the cleaning time, temperature or detergent concentration to achieve the best cleaning effect; when it is detected that the tableware surface is unclean, real-time feedback can be given to the operator to prompt secondary cleaning or adjust the cleaning equipment settings, which helps to correct the problem in time and avoid the outflow of unclean tableware; it can not only significantly improve the quality of tableware cleaning and disinfection, but also provide convenience for operators, ensure the health and safety of users, and at the same time bring significant efficiency improvements and cost reductions in management and operations.

[0033] The tableware cleanliness analysis unit is used to construct a tableware cleanliness analysis strategy to analyze the cleanliness of the tableware through the characteristic pixel value of each characteristic pixel block, the standard characteristic pixel value of each standard characteristic pixel block, the pixel performance value and the pixel standard value;

[0034] The tableware cleanliness analysis unit is used to construct a tableware cleanliness analysis strategy to analyze the cleanliness of the tableware through the characteristic pixel values ​​of each characteristic pixel block, the standard characteristic pixel values ​​of each standard characteristic pixel block, the pixel performance value and the pixel standard value, and obtain the cleanliness value of the tableware by importing the characteristic pixel values ​​of each characteristic pixel block, the standard characteristic pixel values ​​of each standard characteristic pixel block, the pixel performance value and the pixel standard value into the formula of the tableware cleanliness analysis strategy. The formula of the tableware cleanliness analysis strategy is:

[0035]

[0036] Where: J c is the cleanliness of the tableware, n is the number of feature pixel blocks, is the pixel representation value of the i-th feature pixel block, is the pixel standard value of the i-th feature pixel block, is the pixel representation value of the i-th standard feature pixel block, is the pixel standard value of the i-th standard feature pixel block, γ is the adjustment parameter to prevent the denominator from being zero, is the characteristic pixel value of the i-th characteristic pixel block, is the maximum characteristic pixel value of each characteristic pixel block in the tableware surface image, is the minimum characteristic pixel value of each characteristic pixel block in the tableware surface image, is the characteristic pixel value of the i-th standard characteristic pixel block, is the maximum standard feature pixel value of each standard feature pixel block in the standard surface image, is the minimum standard feature pixel value of each standard feature pixel block in the standard surface image;

[0037] Extract the cleanliness value of the tableware, and compare the cleanliness value of the tableware with the preset cleanliness threshold of the tableware. If the cleanliness value of the tableware is greater than or equal to the preset cleanliness threshold of the tableware, the cleanliness of the tableware is qualified; if the cleanliness value of the tableware is less than the preset cleanliness threshold of the tableware, the cleanliness of the tableware is unqualified.

[0038] By using a formula to calculate the cleanliness value of the tableware, the cleanliness condition of each characteristic pixel block can be quantified, and multiple key parameters of the tableware surface image and the standard surface image (such as pixel performance value, standard value) are comprehensively considered. Through the difference calculation of the formula, the system can keenly detect any subtle differences in the cleaning process, ensuring that even tiny contaminants or residues can be identified; through automated cleanliness calculation and analysis, it greatly reduces reliance on manual inspection, reduces the error of human subjective judgment, and makes the cleaning process more standardized and consistent; through preset cleanliness thresholds, the system can provide a unified cleaning standard for all tableware, helping to ensure that different batches of tableware can meet the same cleanliness standards, whether used on the same device or across devices.

[0039] The second tableware automatic detection module includes a second camera, a second feature processing unit, a second automatic detection unit, a third feature processing unit, a third automatic detection unit, a first-level disinfection impact analysis unit, and a tableware disinfection uniformity optimization unit; the second feature processing unit is connected to the second automatic detection unit, the second camera is connected to the third feature processing unit, the third feature processing unit is connected to the first-level disinfection impact analysis unit, and the third feature processing unit and the disinfection impact analysis unit are respectively connected to the tableware disinfection uniformity optimization unit;

[0040] The second feature processing unit is used to divide the tableware storage layer of the tableware disinfection equipment into a plurality of weight sensing areas, set a plurality of weight sensing points in each weight sensing area, set a pressure sensor at each weight sensing point, obtain the pressure values ​​of all weight sensing points after the tableware is placed, perform variance calculation on the pressure values ​​of all weight sensing points to obtain the pressure distribution coefficient of each weight sensing area, and calculate the mean of the weight sensing points in each weight sensing area to obtain the pressure concentration value;

[0041] The second automatic detection unit is used to obtain the pressure distribution coefficient and the pressure concentration value of each weight sensing area, and to detect whether the tableware is placed reasonably through the pressure distribution coefficient and the pressure concentration value of each weight sensing area; the specific detection of whether the tableware is placed reasonably is as follows: if the pressure distribution coefficient of the weight sensing area is less than the preset pressure distribution threshold, and the pressure concentration value is greater than the preset pressure concentration threshold, it means that the tableware is placed unreasonably in the weight sensing area; if the pressure distribution coefficient of the weight sensing area is greater than or equal to the preset pressure distribution threshold, and the pressure concentration value is less than or equal to the preset pressure concentration threshold, it means that the tableware is placed reasonably in the weight sensing area.

[0042] By calculating the pressure distribution coefficient and pressure concentration value of the weight sensing area, it is possible to accurately determine whether the tableware is placed evenly. Even placement is an important prerequisite for ensuring even air flow and heat distribution inside the disinfection equipment, thereby improving the overall disinfection effect and avoiding incomplete disinfection caused by stacking or concentrated placement of tableware. Automatic detection of the placement of tableware reduces the need for manual inspection and the risk of human operational errors. Especially in the large-scale tableware disinfection process, automatic detection helps to ensure consistent quality of each disinfection and reduces negligence and misjudgment in manual inspection. Through the analysis of the pressure distribution coefficient and pressure concentration value, it can help operators reasonably allocate the placement of tableware inside the equipment to avoid local overload or vacancy, thereby maximizing the utilization efficiency of the equipment. Evenly distributed tableware can make more effective use of the space and resources of the disinfection equipment. Warnings can be issued in advance by detecting unreasonable placement to prevent equipment loss or failure due to uneven loads. Long-term eccentric loading or uneven placement may accelerate the wear of equipment components and increase maintenance costs, and the system can effectively prevent such problems.

[0043] The second camera is used to obtain an image of the tableware placement inside the tableware disinfection device;

[0044] The third feature processing unit is used to obtain the tableware placement image inside the tableware disinfection device and the real-time temperature and humidity inside the tableware disinfection device during the disinfection period, obtain the tableware placement spacing based on the tableware placement image inside the tableware disinfection device, and obtain the tableware type, tableware quantity, space value occupied by the tableware inside the tableware disinfection device and space value inside the disinfection device during the disinfection period;

[0045] The first-level disinfection impact analysis unit is used to obtain the real-time temperature and humidity inside the tableware disinfection equipment during the disinfection period, and calculate the tableware disinfection impact value by importing the real-time temperature and humidity inside the tableware disinfection equipment during the disinfection period into the disinfection impact value calculation model. The formula of the disinfection impact value calculation model is:

[0046]

[0047] Where: d x is the disinfection impact value, T is the number of moments in the disinfection period, e t+1 is the real-time temperature and humidity inside the tableware disinfection equipment at time t+1, e t is the real-time temperature and humidity inside the tableware disinfection equipment at time t, e max is the maximum real-time temperature and humidity inside the tableware disinfection equipment during the disinfection period, e min The minimum real-time temperature and humidity inside the tableware disinfection equipment during the disinfection period;

[0048] The tableware disinfection uniformity optimization unit is used to analyze the tableware disinfection uniformity by importing the disinfection impact value, the tableware placement spacing, the number of tableware in the disinfection period, the space value occupied by the tableware inside the tableware disinfection equipment, and the space value inside the disinfection equipment into the tableware disinfection uniformity analysis strategy. The formula of the tableware disinfection uniformity analysis strategy is:

[0049]

[0050] Where: F cx is the average value of tableware disinfection, d x is the disinfection impact value, k cj k is the space occupied by tableware inside the tableware disinfection equipment, n is the internal space value of the disinfection equipment, d j is the spacing between the jth tableware, d b is the preset tableware spacing, and m is the number of tableware within the disinfection period;

[0051] Extract the tableware disinfection average value, and compare the tableware disinfection average value with the preset tableware disinfection average threshold value. If the tableware disinfection average value is greater than or equal to the preset tableware disinfection average threshold value, the tableware disinfection uniformity within the period is qualified; if the tableware disinfection average value is less than the preset tableware disinfection average threshold value, the tableware disinfection uniformity within the period is unqualified;

[0052] Combining multiple parameters such as real-time temperature and humidity, tableware placement spacing, tableware quantity, and space utilization within the equipment, the disinfection uniformity is analyzed through an accurate calculation model, which can comprehensively evaluate the disinfection effect and ensure that all tableware can be evenly and fully disinfected to avoid blind spots in disinfection. Through the disinfection impact value model, the impact of temperature and humidity changes at different time points on the disinfection effect can be quantified, and the disinfection process can be optimized based on these values, such as adjusting the disinfection time, temperature settings, or improving air flow, thereby improving disinfection efficiency. By calculating the disinfection uniformity value and comparing it with the preset threshold, it is possible to clearly determine whether there is unevenness in the disinfection process. Uneven disinfection may result in incomplete disinfection of some tableware, and the system can promptly detect and correct this situation to ensure that each disinfection meets the standards.

[0053] The third automatic detection unit is used to integrate an accurate timer in the tableware disinfection equipment to record the start and end time of each disinfection process, and automatically control the length of the disinfection process according to the preset disinfection time standard. If the disinfection time is insufficient, the disinfection process is terminated prematurely, and an audible and visual alarm is immediately issued to alert the staff.

[0054] The embodiment of the present invention extracts the surface image of the same type of tableware after cleaning, obtains the standard surface image of the tableware of this type after cleaning, and analyzes the cleanliness of the tableware based on the pixel values ​​of the tableware surface image and the standard surface image, so as to effectively prevent secondary contamination caused by incomplete disinfection, fundamentally guarantee the cleanliness of children's tableware, and ensure the comprehensiveness of the disinfection process; based on the pressure value of the tableware storage layer of the tableware disinfection equipment, analyze whether the tableware is placed reasonably, ensure the uniformity of air circulation and heat distribution during the disinfection process, and avoid uneven disinfection caused by improper operation of the staff (such as insufficient disinfection time, substandard temperature, and incomplete closure of the disinfection cabinet); and then analyze the uniformity of tableware disinfection by constructing a tableware disinfection uniformity analysis strategy to reduce the need for manual intervention, improve operating efficiency and disinfection quality, and thus prevent potential health hazards.

[0055] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0056] 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. An automatic detection system for disinfecting tableware for infants, comprising a tableware disinfection device, a first tableware automatic detection module and a second tableware automatic detection module; the tableware disinfection device is connected to the second tableware automatic detection module; characterized in that: The second tableware automatic detection module includes a third feature processing unit, a second camera, a first-level disinfection impact analysis unit, and a tableware disinfection uniformity optimization unit; The third feature processing unit is used to obtain the tableware placement image inside the tableware disinfection device and the real-time temperature and humidity inside the tableware disinfection device during the disinfection period through the second camera, obtain the tableware placement spacing based on the tableware placement image inside the tableware disinfection device, and obtain the tableware type, tableware quantity, space value occupied by the tableware inside the tableware disinfection device and internal space value of the disinfection device during the disinfection period; The first-level disinfection impact analysis unit is used to obtain the real-time temperature and humidity inside the tableware disinfection equipment during the disinfection period, and calculate the tableware disinfection impact value by importing the real-time temperature and humidity inside the tableware disinfection equipment during the disinfection period into the disinfection impact value calculation model; the tableware disinfection uniformity optimization unit is used to analyze the tableware disinfection uniformity by importing the disinfection impact value, the tableware placement spacing, the number of tableware in the disinfection period, the space value occupied by the tableware in the tableware disinfection equipment, and the space value inside the disinfection equipment into the tableware disinfection uniformity analysis strategy. The formula of the tableware disinfection uniformity analysis strategy is: Where: F cx is the average value of tableware disinfection, d x is the disinfection impact value, k cj k is the space occupied by tableware inside the tableware disinfection equipment, n is the internal space value of the disinfection equipment, d j is the spacing between the jth tableware, d b is the preset tableware spacing, and m is the number of tableware within the disinfection period.

2. The automatic detection system for disinfecting tableware for infants according to claim 1, characterized in that: The formula for calculating the disinfection impact value model is: Where: d x is the disinfection impact value, T is the number of moments in the disinfection period, e t+1 is the real-time temperature and humidity inside the tableware disinfection equipment at time t+1, e t is the real-time temperature and humidity inside the tableware disinfection equipment at time t, e max is the maximum real-time temperature and humidity inside the tableware disinfection equipment during the disinfection period, e min It is the minimum real-time temperature and humidity inside the tableware disinfection equipment during the disinfection period.

3. The automatic detection system for disinfecting tableware for infants according to claim 1, characterized in that: The second tableware automatic detection module also includes a second feature processing unit, a second automatic detection unit, and a third automatic detection unit; the second feature processing unit is connected to the second automatic detection unit, the second camera is connected to the third feature processing unit, the third feature processing unit is connected to the first-level disinfection impact analysis unit, and the third feature processing unit and the disinfection impact analysis unit are respectively connected to the tableware disinfection uniformity optimization unit.

4. The automatic detection system for disinfecting tableware for infants according to claim 3, characterized in that: The second feature processing unit is used to divide the tableware storage layer of the tableware disinfection equipment into a plurality of weight sensing areas, set a plurality of weight sensing points in each weight sensing area, set a pressure sensor at each weight sensing point, obtain the pressure values ​​of all weight sensing points after the tableware is placed, perform variance calculation on the pressure values ​​of all weight sensing points to obtain the pressure distribution coefficient of each weight sensing area, and calculate the mean of the weight sensing points in each weight sensing area to obtain the pressure concentration value; The second automatic detection unit is used to obtain the pressure distribution coefficient and the pressure concentration value of each weight sensing area, and detect whether the tableware is placed reasonably through the pressure distribution coefficient and the pressure concentration value of each weight sensing area.

5. The automatic detection system for disinfecting tableware for infants according to claim 1, characterized in that: The first tableware automatic detection module includes a first camera, a first feature extraction unit, a first feature processing unit, and a tableware cleanliness analysis unit; the first camera is connected to the first feature extraction unit, the first feature extraction unit is connected to the first feature processing unit, and the first feature extraction unit and the first feature processing unit are respectively connected to the tableware cleanliness analysis unit.

6. The automatic detection system for disinfecting tableware for infants according to claim 5, characterized in that: The first camera is used to capture the image of the surface of the tableware after cleaning; The first feature extraction unit is used to extract the surface image of the same type of tableware after cleaning, and obtain the standard surface image of the type of tableware after cleaning; respectively obtain the tableware surface image and the standard surface image, divide the tableware surface image into a number of feature pixel blocks, extract the pixel values ​​of the pixel points in the feature pixel blocks, and summarize the feature pixel values ​​of the feature pixel blocks, then divide the standard surface image into a number of standard feature pixel blocks, extract the pixel values ​​of the pixel points in the standard feature pixel blocks, and summarize the standard feature pixel values ​​of the standard feature pixel blocks.

7. An automated detection system for disinfecting children's tableware according to claim 6, characterized in that: The first feature processing unit is used to process the feature pixel values ​​of each feature pixel block and the standard feature pixel values ​​of each standard feature pixel block; the variance value of the feature pixel value of each feature pixel block is calculated to obtain the pixel representation value of the tableware surface image, and then the variance value of the standard feature pixel value of each standard feature pixel block is calculated to obtain the pixel standard value of the standard surface image; the tableware cleanliness analysis unit is used to construct a tableware cleanliness analysis strategy to analyze the cleanliness of the tableware through the feature pixel values ​​of each feature pixel block, the standard feature pixel values ​​of each standard feature pixel block, the pixel representation value and the pixel standard value.

8. The automatic detection system for disinfecting tableware for infants according to claim 7, characterized in that: The tableware cleanliness analysis unit is used to construct a tableware cleanliness analysis strategy to analyze the cleanliness of the tableware through the characteristic pixel values ​​of each characteristic pixel block, the standard characteristic pixel values ​​of each standard characteristic pixel block, the pixel performance value and the pixel standard value, and obtain the cleanliness value of the tableware by importing the characteristic pixel values ​​of each characteristic pixel block, the standard characteristic pixel values ​​of each standard characteristic pixel block, the pixel performance value and the pixel standard value into the formula of the tableware cleanliness analysis strategy. The formula of the tableware cleanliness analysis strategy is: Where: J c is the cleanliness of the tableware, n is the number of feature pixel blocks, is the pixel representation value of the i-th feature pixel block, is the pixel standard value of the i-th feature pixel block, is the pixel representation value of the i-th standard feature pixel block, is the pixel standard value of the i-th standard feature pixel block, γ is the adjustment parameter to prevent the denominator from being zero, is the characteristic pixel value of the i-th characteristic pixel block, is the maximum characteristic pixel value of each characteristic pixel block in the tableware surface image, is the minimum characteristic pixel value of each characteristic pixel block in the tableware surface image, is the characteristic pixel value of the i-th standard characteristic pixel block, is the maximum standard feature pixel value of each standard feature pixel block in the standard surface image, It is the minimum standard feature pixel value of each standard feature pixel block in the standard surface image.

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