Food safety supervision system based on cloud platform

Abstract

The invention relates to the field of safety supervision, in particular to a food safety supervision system based on a cloud platform, and the system comprises a collection module which collects a contour diagram of a package and a morphological diagram of target food; the fitting degree analysis module is used for determining the contour coincidence degree and the edge distance according to the contour map and the form map, and determining whether the fitting degree of the target food and the package is qualified or not based on the contour coincidence degree and the edge distance; the shake risk analysis module is used for detecting the package with qualified fitting degree to obtain the deformation degree and the distribution condition of the package folds in the transportation process so as to determine whether the shake risk is qualified or not; the packaging material evaluation module is used for carrying out migration test on the package with the qualified shaking risk so as to evaluate the material safety of the package according to the migration condition of substances in the packaging material to the food; and the safety determination module determines that the target food in the package is safe food according to the fitting degree, the shaking risk and the material safety. And comprehensive guarantee is provided for food safety.

Description

Technical Field

[0001] The present invention relates to the field of safety supervision, and in particular to a food safety supervision system based on a cloud platform. Background Art

[0002] In today's society, vacuum food has the following main problems in packaging safety: fit, shaking risk and packaging material safety. These problems are directly related to the quality, shelf life and health of food. In order to ensure the quality of food and the health of consumers, it is necessary to strengthen the selection and testing of packaging materials.

[0003] Patent document with publication number CN116165209A discloses a food vacuum small package defect detection system based on deep learning, which includes: an image acquisition module, an image processing module and a motion control module; the image acquisition module is used to obtain images of food vacuum small packages on a conveyor belt through an industrial camera; the image processing module is used to receive images transmitted by the image acquisition module, detect and locate defective packages in the image using a target detection algorithm based on deep learning, and transmit the location information of the defective packages to the motion control module after the defective packages are detected; the image processing module includes an image preprocessing submodule and a vacuum small package defect detection and positioning submodule; the image preprocessing submodule is used to preprocess the food vacuum small package image, including image size scaling and base Image denoising based on wavelet transform; the vacuum small package defect detection and positioning submodule includes a model pre-training process and a real-time detection and positioning process; the food vacuum small package defect detection model adopts an improved YOLOv5s network model, and the real-time detection and positioning process is as follows: the real-time image collected by the image acquisition module is input into the trained food vacuum small package defect detection model to obtain the detection result, and the position of the defective package on the image is located at the same time as the defective package is detected. According to the mapping relationship between the position on the image and the actual position of the conveyor belt, the position information of the defective package is transmitted to the motion control module in combination with the model reasoning consumption time and the conveyor belt transportation speed; the motion control module includes an industrial robot, which is used to remove the defective package detected by the image processing module.

[0004] In the prior art, defective vacuum packages detected by an image processing module are eliminated, but the vacuum packages that are not eliminated are not analyzed, and quality assurance for food safety cannot be provided. Summary of the invention

[0005] To this end, the present invention provides a food safety supervision system based on a cloud platform, which solves the quality assurance problem of food safety by detecting the fit, shaking risk and packaging material safety of vacuum-packaged food.

[0006] To achieve the above objectives, the present invention provides a food safety supervision system based on a cloud platform, comprising:

[0007] A collection module, used to collect the outline of the package and the morphology of the target food;

[0008] a fit analysis module connected to the acquisition module, configured to determine the contour overlap according to the contour lines of the contour map and the morphology map, determine the edge distance according to the edge points of the contour map and the morphology map, and determine whether the fit between the target food and the package is qualified based on the contour overlap and the edge distance;

[0009] A shaking risk analysis module, connected to the fit analysis module, is used to detect packages with qualified fit to obtain the deformation degree and distribution of wrinkles on the package surface during transportation, and to determine deformation data and movement range based on the deformation degree and distribution, so as to determine whether the shaking risk of the target food in the package is qualified;

[0010] A packaging material assessment module, connected to the shaking risk analysis module, is used to perform a migration test on the packaging that meets the shaking risk requirements, so as to assess the material safety of the packaging according to the migration of substances in the packaging material to the food;

[0011] The safety determination module is connected to the fit analysis module, the shaking risk analysis module and the packaging material evaluation module respectively, and is used to determine whether the target food in the package is safe food based on the fit, the shaking risk and the material safety.

[0012] Furthermore, the fit analysis module includes:

[0013] A contour line extraction unit is used to perform edge recognition on the contour image and the morphological image by edge detection to extract the contour line of the target food and the contour line of the package;

[0014] The coincidence calculation unit is connected to the contour extraction subunit, aligns the target food contour line and the package contour line through image registration technology, obtains contour point positions respectively, and calculates contour coincidence according to the contour point positions.

[0015] Furthermore, the fit analysis module also includes:

[0016] An edge point extraction unit, used to respectively extract target food edge points and package edge points by using edge detection;

[0017] The matching subunit is connected to the edge point extraction unit and is used to match the target food edge point with the package edge point to calculate the shortest distance between the matching points as the edge distance.

[0018] Furthermore, if the contour overlap is higher than a first qualified threshold and the edge distance is lower than a second qualified threshold, it is determined that the fit between the target food and the package is qualified.

[0019] Furthermore, the shaking risk analysis module includes:

[0020] The wrinkle assessment unit physically simulates the vibration and impact environment of the package during transportation and obtains the deformation degree and distribution of wrinkles on the package surface through image processing;

[0021] The shaking risk determination unit is connected to the wrinkle evaluation unit, and measures the deformation data and movement range of the target food in the package according to the deformation degree and the distribution, so as to determine whether the shaking risk of the target food in the package is qualified.

[0022] Furthermore, the shaking risk determination unit includes:

[0023] A monitoring subunit, used to monitor the deformation data of the wrinkles and the movement range of the target food in the package in real time;

[0024] a data determination subunit, connected to the monitoring subunit, for determining a maximum deformation degree of the target food in the package according to the deformation data, and determining a maximum movement range of the target food in the package according to the movement range;

[0025] The shaking risk assessment subunit is connected to the data determination subunit. When the maximum deformation degree and the maximum movement range are both within the standard safety range, it is determined that the shaking risk of the target food in the package is qualified.

[0026] Furthermore, the packaging material evaluation module includes:

[0027] Environmental simulation unit, used to simulate the actual contact environment between the target food and packaging materials under test conditions;

[0028] a migration substance detection unit connected to the environment simulation unit, for periodically sampling the target food in the actual contact environment and detecting the migration substances therein by gas chromatography;

[0029] A quantitative analysis unit connected to the migration substance detection unit to perform quantitative analysis on the migration substance to determine its concentration and migration amount;

[0030] The safety assessment unit is connected to the quantitative analysis unit to determine whether the concentration and the migration amount are within the prescribed limit standard range, thereby evaluating the material safety of the packaging.

[0031] Furthermore, the quantitative analysis unit includes:

[0032] The pretreatment subunit pre-treats the target food containing the migrating substances to ensure that the target food meets the requirements of quantitative analysis;

[0033] A concentration analysis subunit, connected to the pretreatment subunit, is used to inject the pretreated target food into the quantitative analysis instrument, separate, detect and quantify according to the spectroscopic method, record the spectral absorbance output by the instrument, and convert the spectral absorbance into the concentration of the migration substance using a regression equation;

[0034] The migration amount calculation subunit is connected to the concentration analysis subunit and calculates the migration amount according to the concentration and the contact time of the target food.

[0035] Furthermore, the regression equation is established using known concentrations of migrating substances and corresponding spectral absorbance data to reflect the quantitative relationship between spectral absorbance and the concentration of migrating substances. The concentration analysis subunit measures the spectral absorbance of the target food and detects the concentration value corresponding to the migrating substance in the regression equation to achieve conversion of spectral absorbance into substance concentration.

[0036] Furthermore, the safety determination module includes:

[0037] A data evaluation unit, for generating a food safety evaluation report based on the fit, the shaking risk and the material safety;

[0038] The risk assessment unit is connected to the data assessment unit and assesses the food safety assessment report according to safety standards, thereby determining that the target food in the package is safe food.

[0039] Compared with the prior art, the beneficial effects of the present invention are that the accuracy and clarity of the package contour map and the target food morphology map are ensured through image acquisition technology, and timely data support is provided for subsequent analysis and processing. The fit analysis module analyzes the contour lines and edge points to accurately evaluate the fit between the package and the target food, ensuring the tightness and stability of the package. The shake risk analysis module simulates the transportation environment to evaluate the shake risk of the package, ensure the safety of food during transportation, and reduce losses and return costs caused by transportation. The packaging material evaluation module uses migration testing to ensure that harmful substances in the packaging material will not migrate into the food to protect the health of consumers. The safety determination module comprehensively considers the fit, shake risk and packaging material safety to provide a comprehensive assessment of food safety.

[0040] In particular, precise edge detection and calculation can accurately evaluate the fit of the target food, thus avoiding the influence of subjective judgment and realizing automatic analysis of the packaging contour map and the target food morphology map, thereby ensuring the stability and consistency of product quality.

[0041] In particular, through the collaborative work of the contour extraction subunit and the overlap calculation subunit, the contour lines of the target food and the package can be accurately extracted, and the overlap between them can be calculated, thereby improving the accuracy of fit detection. The calculation unit realizes the automatic extraction and alignment of the contour lines of the target food and the package, as well as the automatic calculation of the overlap, thereby improving the detection efficiency.

[0042] In particular, the matching subunit can match the edge points on the target food contour with the corresponding edge points on the packaging contour, which provides accuracy for the subsequent calculation of the edge distance. Through an efficient matching algorithm, it can quickly find matching points and calculate the shortest distance between them, that is, the edge distance, thereby improving the efficiency of the entire evaluation process.

[0043] In particular, by comprehensively considering the two indicators of contour overlap and edge distance, the fit between the package and the target food can be evaluated more comprehensively. The comprehensive evaluation method is more accurate than a single indicator and can more truly reflect the actual match between the package and the target food.

[0044] In particular, by precisely measuring wrinkle parameters and performing physical simulations, the performance of packaging during transportation can be more accurately evaluated, helping to reduce cargo damage or transportation caused by improper packaging design. At the same time, reducing the risk of shaking can also reduce the additional costs caused by cargo damage.

[0045] In particular, real-time monitoring and data analysis can more accurately assess the risk of food shaking during transportation, reduce potential losses caused by inaccurate assessments, and make targeted optimizations to packaging design to improve packaging stability.

[0046] In particular, through environmental simulation and migration substance detection, the actual contact environment between packaging materials and food can be simulated and detected more accurately, thereby improving the accuracy of safety assessment. The results of quantitative analysis and safety assessment can provide valuable feedback for the production of packaging materials and promote the innovation and improvement of packaging materials to meet more stringent safety requirements.

[0047] In particular, the establishment of the regression equation is based on a large amount of experimental data and therefore has a high degree of accuracy. Through this equation, the concentration of migrating substances in the target food can be accurately measured to reduce errors. Traditional detection methods may require complex chemical reactions or long experimental processes, while the use of regression equations for detection greatly simplifies the detection steps and improves detection efficiency.

[0048] In particular, by generating a food safety assessment report through the data evaluation unit, the safety of food can be comprehensively and accurately assessed, thereby protecting the health and safety of consumers. Food safety assessment helps to improve product quality and market competitiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A schematic diagram of the structure of a food safety supervision system based on a cloud platform provided in an embodiment of the present invention;

[0050] Figure 2 A schematic diagram of the structure of a fit analysis module of a food safety supervision system based on a cloud platform provided in an embodiment of the present invention;

[0051] Figure 3 A schematic diagram of the structure of a shaking risk analysis module of a food safety supervision system based on a cloud platform provided in an embodiment of the present invention;

[0052] Figure 4 A schematic diagram of the structure of a packaging material evaluation module of a food safety supervision system based on a cloud platform provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0053] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0054] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0055] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be understood as a limitation on the present invention.

[0056] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0057] See also Figure 1 As shown, the present invention provides a food safety supervision system based on a cloud platform, comprising:

[0058] A collection module 10 is used to collect the outline of the package and the morphology of the target food;

[0059] A fit analysis module 20, connected to the acquisition module, is used to determine the contour overlap according to the contour lines of the contour map and the morphology map, determine the edge distance according to the edge points of the contour map and the morphology map, and determine whether the fit between the target food and the package is qualified based on the contour overlap and the edge distance;

[0060] The shaking risk analysis module 30 is connected to the fit analysis module, and is used to detect the packages with qualified fit, so as to obtain the deformation degree and distribution of wrinkles on the package surface during transportation, and determine the deformation data and movement range based on the deformation degree and distribution, so as to determine whether the shaking risk of the target food in the package is qualified;

[0061] A packaging material evaluation module 40, connected to the shaking risk analysis module, is used to perform a migration test on the packaging that meets the shaking risk requirements, so as to evaluate the material safety of the packaging according to the migration of substances in the packaging material to the food;

[0062] The safety determination module 50 is connected to the fit analysis module, the shaking risk analysis module and the packaging material evaluation module respectively, and is used to determine whether the target food in the package is safe food based on the fit, the shaking risk and the material safety.

[0063] Specifically, after the production of vacuum food is completed, several target foods are randomly selected for safety testing. The packaging is used to wrap the target food, and the fit of the vacuum packaging, the risk of shaking and the safety of the packaging materials are analyzed to determine whether the vacuum food in this production batch meets the industry's food vacuum packaging standards, thereby ensuring the safety of food from packaging to consumption in the food packaging industry chain.

[0064] Specifically, the packaging contour map and food morphology map of the target food are collected according to the image sensor to capture the appearance characteristics of the packaging and food, image processing is performed on the packaging contour map and the food morphology map to obtain contour lines and edge points, analysis is performed based on the contour lines and edge points to obtain contour overlap and edge distance, so as to determine the fit of the target food, based on the package with qualified fit, the packaging wrinkle parameters are further detected, the deformation and movement of the package are observed by simulating vibration and impact during transportation, the deformation degree and distribution of wrinkles are obtained, so as to determine the deformation data and movement range, so as to evaluate the shaking risk, based on the package with qualified shaking risk, a migration test is performed, and gas chromatography is used to detect the migration of substances in the packaging material to the food under the test conditions of the target food and packaging, so as to evaluate the safety of the packaging material, and finally the safety of the food is determined by comprehensively considering the fit, shaking risk and safety of the packaging material.

[0065] Specifically, gas chromatography is a highly sensitive analytical method that can be used to detect harmful substances in packaging materials that may migrate into food.

[0066] Specifically, image acquisition technology is used to ensure the accuracy and clarity of the packaging contour map and the target food morphology map, and timely data support is provided for subsequent analysis and processing. The fit analysis module analyzes the contour lines and edge points to accurately evaluate the fit between the package and the target food, ensuring the tightness and stability of the package. The shake risk analysis module simulates the transportation environment to evaluate the shake risk of the package, ensure the safety of food during transportation, and reduce losses and return costs caused by transportation. The packaging material evaluation module uses migration testing to ensure that harmful substances in the packaging materials will not migrate into the food to protect the health of consumers. The safety determination module comprehensively considers the fit, shake risk and packaging material safety to provide a comprehensive assessment of food safety.

[0067] See also Figure 2 As shown, the fit analysis module 20 includes:

[0068] A contour extraction unit 21 is used to perform edge recognition on the contour image and the morphological image by edge detection to extract the contour of the target food and the contour of the package;

[0069] The coincidence calculation unit 22 is connected to the contour extraction subunit, aligns the target food contour line and the package contour line through image registration technology, obtains contour point positions respectively, and calculates contour coincidence according to the contour point positions.

[0070] Specifically, the coincidence calculation subunit aligns the extracted target food with the packaging contour line. The coincidence calculation subunit can obtain the position of the corresponding point on the contour line and calculate the contour coincidence based on the position. The higher the coincidence, the better the fit between the target food and the packaging; conversely, the lower the coincidence, the worse the fit.

[0071] Specifically, the formula for measuring contour overlap is: J(A,B) = |A∩B| / |A∪B|, where A and B represent the contour point sets of food and packaging respectively, |A∩B| represents the number of elements in the intersection of the two sets (i.e., the number of overlapping contour points), and |A∪B| represents the number of elements in the union of the two sets (i.e., the total number of contour points). The value range is between 0 and 1. The closer the value is to 1, the higher the overlap is, and the closer the value is to 0, the lower the overlap is. For example: Assume that the food contour point set A has 5 points and the packaging contour point set B has 7 points, and there are 3 overlapping points between them. Then the overlap is: J(A,B) = 3 / (5+7-3) = 3 / 9≈0.333, which means that the overlap between food and packaging is about 33.3%.

[0072] Specifically, through the collaborative work of the contour extraction subunit and the overlap calculation subunit, the contour lines of the target food and the package can be accurately extracted, and the overlap between them can be calculated, thereby improving the accuracy of fit detection. The calculation unit realizes the automatic extraction and alignment of the contour lines of the target food and the package, as well as the automatic calculation of the overlap, thereby improving the detection efficiency.

[0073] Specifically, the fit analysis module also includes:

[0074] An edge point extraction unit, used to respectively extract target food edge points and package edge points by using edge detection;

[0075] The matching subunit is connected to the edge point extraction unit and is used to match the target food edge point with the package edge point to calculate the shortest distance between the matching points as the edge distance.

[0076] Specifically, matching the edge points on the target food contour with the corresponding edge points on the packaging contour is the basis for edge distance calculation. The shortest distance, i.e., edge distance, is calculated through the nearest corresponding point of each food edge point on the packaging contour. For any edge point P (x1, y1) on the target food contour, its corresponding point Q (x2, y2) is found on the packaging contour through the algorithm. The edge distance d between P and Q can be expressed as: The distance d is the edge distance between two points and is used to quantify the gap or misalignment between the package and the target food.

[0077] Specifically, both the food contour and the package contour consist of a series of discrete points;

[0078] An edge point P(3,4) on the food contour;

[0079] The corresponding point Q(5,6) on the packaging contour that matches point P;

[0080] Then the edge distance d between P and Q can be calculated as:

[0081] If the preset edge distance qualified threshold is 3 mm, then in this example, the edge distance d (about 2.83 mm) is less than the qualified threshold, so it can be considered that the edge distance at this point meets the requirements. At the same time, if the contour overlap is also higher than the qualified threshold (such as 80%), it can be comprehensively judged that the fit of the target food is qualified.

[0082] Specifically, the matching subunit can match the edge points on the target food contour with the corresponding edge points on the packaging contour, providing accuracy for the subsequent edge distance calculation. Through an efficient matching algorithm, it can quickly find matching points and calculate the shortest distance between them, i.e., the edge distance, thereby improving the efficiency of the entire evaluation process.

[0083] Specifically, if the contour overlap is higher than a first qualified threshold and the edge distance is lower than a second qualified threshold, it is determined that the fit between the target food and the package is qualified.

[0084] Specifically, by comparing the contour overlap with the first qualified threshold, and the edge distance with the second qualified threshold, it can be determined whether the fit of the target food meets the requirements. For example, if the overlap is higher than the first qualified threshold (80%) and the edge distance is less than the second qualified threshold (2.5mm), it is determined that the fit between the target food and the package is qualified; otherwise, it is unqualified.

[0085] Specifically, by comprehensively considering the two indicators of contour overlap and edge distance, the fit between the package and the target food can be evaluated more comprehensively. The comprehensive evaluation method is more accurate than a single indicator and can more truly reflect the actual match between the package and the target food.

[0086] See also Figure 3 As shown, the shaking risk analysis module 30 includes:

[0087] The wrinkle evaluation unit 31 physically simulates the vibration and impact environment of the package during transportation and obtains the deformation degree and distribution of wrinkles on the package surface through image processing;

[0088] The shaking risk determination unit 32 is connected to the wrinkle evaluation unit, and measures the deformation data and movement range of the target food in the package according to the deformation degree and the distribution, so as to determine whether the shaking risk of the target food in the package is qualified.

[0089] Specifically, the degree of deformation refers to the amount of deformation of the folds under vibration and impact, including the expansion, compression or twisting of the folds.

[0090] Specifically, the distribution means that if the deformation is concentrated in a certain area of ​​the package, it may cause the food in that area to be subjected to greater impact force, thereby increasing the risk of shaking. On the contrary, if the deformation is evenly distributed, the movement of the food in the package may be relatively smooth, and the risk of shaking is relatively low.

[0091] Specifically, physical simulation is used to reproduce the vibration and impact environment that the package may encounter during transportation. During the simulation, the deformation degree and distribution of the folds are monitored, because the folds are usually the more fragile part of the package. Based on the monitoring results, the deformation data and movement range of the target food in the package are further measured. The deformation data and movement range can reflect whether the package can effectively fix the food during transportation to prevent it from shaking or shifting.

[0092] Specifically, by accurately measuring wrinkle parameters and performing physical simulations, the performance of packaging during transportation can be more accurately evaluated, which helps reduce cargo damage or transportation caused by improper packaging design. At the same time, reducing the risk of shaking can also reduce the additional costs caused by cargo damage.

[0093] Specifically, the shaking risk determination unit includes:

[0094] A monitoring subunit, used to monitor the deformation data of the wrinkles and the movement range of the target food in the package in real time;

[0095] a data determination subunit, connected to the monitoring subunit, for determining a maximum deformation degree of the target food in the package according to the deformation data, and determining a maximum movement range of the target food in the package according to the movement range;

[0096] The shaking risk assessment subunit is connected to the data determination subunit. When the maximum deformation degree and the maximum movement range are both within the standard safety range, it is determined that the shaking risk of the target food in the package is qualified.

[0097] Specifically, by real-time monitoring of wrinkle deformation data and the movement range of the target food in the package, it is possible to capture the wrinkle deformation and target food movement caused by various external forces (such as vibration, impact, etc.) exerted on the package during transportation, so as to obtain the maximum deformation degree and maximum movement range of the target food in the package. Combined with industry standards, the shaking risk of the target food during transportation can be evaluated.

[0098] Specifically, for example, the fold height of the vacuum package of cooked meat products is 5 mm, the fold spacing is 4 cm, and the fold distribution is uniform. The vibration and impact environment of the package with the said fold parameters during transportation is physically simulated. The simulation conditions are set as follows: the vibration frequency is 5 Hz, the amplitude is 2 cm, the impact acceleration is 50g, and the duration is 10 milliseconds. During the simulation, it was monitored that the maximum deformation of the target food in the package reached 2 cm, and the maximum movement range exceeded 15% of the package size (relative to the original size). According to industry experience, for vacuum-packaged cooked meat products, the maximum deformation allowed is usually no more than 1 cm, and the maximum movement range is no more than 10% of the package size. Obviously, the results of this measurement exceeded these two safety ranges.

[0099] Specifically, real-time monitoring and data analysis can more accurately assess the risk of food shaking during transportation, reduce potential losses caused by inaccurate assessments, and make targeted optimizations to packaging design to improve packaging stability.

[0100] See also Figure 4 As shown, the packaging material evaluation module 40 also includes:

[0101] An environmental simulation unit 41, used to simulate the actual contact environment between the target food and the packaging material under the test conditions;

[0102] a migration substance detection unit 42, connected to the environment simulation unit, for periodically sampling the target food in the actual contact environment and detecting the migration substances therein by gas chromatography;

[0103] A quantitative analysis unit 43, connected to the migration substance detection unit, performs quantitative analysis on the migration substance to determine its concentration and migration amount;

[0104] The safety assessment unit 44 is connected to the quantitative analysis unit to determine whether the concentration and the migration amount are within the prescribed limit standard range, thereby evaluating the material safety of the packaging.

[0105] Specifically, the test conditions are the test conditions of temperature, humidity, and light during the transportation of vacuum food, which aim to restore the actual usage scenario to the greatest extent possible.

[0106] Specifically, based on the actual contact environment created by the environmental simulation unit, food is sampled regularly (24 hours), and the sampled food is tested by gas chromatography (GC). This method has the characteristics of high sensitivity, high resolution and rapid analysis, and is suitable for the detection of a variety of volatile and non-volatile organic compounds. The detection data provided by the migration substance detection unit is quantitatively analyzed to determine the concentration and migration amount of the migration substance. By comparing the data at different time points or under different test conditions, we can gain an in-depth understanding of how the migration behavior changes with time, temperature and other factors, and compare the actual concentration of the migration amount with the prescribed limit standard, which is usually formulated by government regulatory agencies or industry associations to ensure the safety of food packaging materials.

[0107] Specifically, through environmental simulation and migration substance detection, the actual contact environment between packaging materials and food can be simulated and detected more accurately, thereby improving the accuracy of safety assessment. The results of quantitative analysis and safety assessment can provide valuable feedback for the production of packaging materials and promote the innovation and improvement of packaging materials to meet more stringent safety requirements.

[0108] Specifically, the quantitative analysis unit includes:

[0109] The pretreatment subunit pre-treats the target food containing the migrating substances to ensure that the target food meets the requirements of quantitative analysis;

[0110] A concentration analysis subunit, connected to the pretreatment subunit, is used to inject the pretreated target food into the quantitative analysis instrument, separate, detect and quantify according to the spectroscopic method, record the spectral absorbance output by the instrument, and convert the spectral absorbance into the concentration of the migration substance using a regression equation;

[0111] The migration amount calculation subunit is connected to the concentration analysis subunit and calculates the migration amount according to the concentration and the contact time of the target food.

[0112] Specifically, a target food containing migrating substances is obtained and subjected to necessary pretreatment operations, including filtration, dilution, concentration, etc. The pretreated target food is injected into a quantitative analysis instrument, which is usually separated, detected and quantified according to the light absorption characteristics of different substances in the target food using spectroscopy. During the concentration analysis process, the instrument will output spectral absorbance data, which is a direct reflection of the concentration of the substance in the target food.

[0113] Specifically, migration amount refers to the amount of substances that migrate from packaging materials to food per unit time.

[0114] Specifically, the migration amount (M) can be calculated by the formula: M=C×V / T, for example: the concentration of the migrating substance X is C=10 mg / L; the volume of the food is V=1 L; the contact time is T=24 h, and the calculated migration amount is: M=10 mg / L×1L / 24 h=0.42 mg / h (the result is rounded to two decimal places). Therefore, the migration amount of the migrating substance X is 0.42 mg / h, indicating that within the contact time of 24 hours, the amount of the migrating substance X that migrates from the packaging material to the food is 0.42 mg.

[0115] Specifically, the target food after pretreatment is more in line with the requirements of quantitative analysis instruments, can reduce instrument failures and errors, and extend the service life of the instrument. The concentration analysis subunit uses spectral methods for separation, detection and quantification, and can accurately determine the concentration of migrating substances in the target food. The migration amount calculation subunit calculates the migration amount based on the concentration of the migrating substance and the contact time with the target food, and can accurately assess the potential risks of migrating substances to food, and can understand the migration laws and trends of migrating substances under different conditions.

[0116] Specifically, the regression equation is established using known concentrations of migrating substances and corresponding spectral absorbance data to reflect the quantitative relationship between spectral absorbance and the concentration of migrating substances. The concentration analysis subunit measures the spectral absorbance of the target food and detects the concentration value corresponding to the migrating substance in the regression equation to achieve conversion of spectral absorbance into substance concentration.

[0117] Specifically, in actual operation, a series of migration substance samples with known concentrations are first selected, and the spectral absorbance is measured using a spectrometer. A statistical regression model (such as multiple linear regression, nonlinear regression, etc.) is used to establish a mathematical relationship between the spectral absorbance and the concentration of the migration substance, namely, a regression equation, based on these data.

[0118] Specifically, the establishment of the regression equation is based on a large amount of experimental data, so it has high accuracy. Through this equation, the concentration of migrating substances in the target food can be accurately measured to reduce errors. Traditional detection methods may require complex chemical reactions or long experimental processes, while the use of regression equations for detection greatly simplifies the detection steps and improves detection efficiency.

[0119] Specifically, the security determination module includes:

[0120] A data evaluation unit, for generating a food safety evaluation report based on the fit, the shaking risk and the material safety;

[0121] The risk assessment unit is connected to the data assessment unit and assesses the food safety assessment report according to safety standards, thereby determining that the target food in the package is safe food.

[0122] Specifically, the safety standard has a first qualified threshold value (80%) for contour overlap in fit, a second qualified threshold value (2.5 mm) for edge distance, and the safety standard for shaking risk usually allows a maximum deformation of no more than 1 cm, and a maximum movement range of no more than 10% of the packaging size. The safety standard for packaging materials is based on the limit values ​​specified in the national food safety standards. Different types of food may have different sensitivities and acceptance of migrating substances. For example, high-risk foods such as infant food and food for special medical purposes usually have stricter migration limits.

[0123] Specifically, by generating a food safety assessment report through the data evaluation unit, the safety of food can be comprehensively and accurately assessed, thereby protecting the health and safety of consumers. Food safety assessment helps to improve product quality and market competitiveness.

[0124] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0125] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A food safety supervision system based on a cloud platform, characterized in that: include: A collection module, used to collect the outline of the package and the morphology of the target food; a fit analysis module connected to the acquisition module, configured to determine the contour overlap according to the contour lines of the contour map and the morphology map, determine the edge distance according to the edge points of the contour map and the morphology map, and determine whether the fit between the target food and the package is qualified based on the contour overlap and the edge distance; A shaking risk analysis module, connected to the fit analysis module, is used to detect packages with qualified fit to obtain the deformation degree and distribution of wrinkles on the package surface during transportation, and to determine deformation data and movement range based on the deformation degree and distribution, so as to determine whether the shaking risk of the target food in the package is qualified; A packaging material assessment module, connected to the shaking risk analysis module, is used to perform a migration test on the packaging that meets the shaking risk requirements, so as to assess the material safety of the packaging according to the migration of substances in the packaging material to the food; The safety determination module is connected to the fit analysis module, the shaking risk analysis module and the packaging material evaluation module respectively, and is used to determine whether the target food in the package is safe food based on the fit, the shaking risk and the material safety.

2. The food safety supervision system based on the cloud platform according to claim 1 is characterized in that: The fit analysis module includes: A contour line extraction unit is used to perform edge recognition on the contour image and the morphological image by edge detection to extract the contour line of the target food and the contour line of the package; The coincidence calculation unit is connected to the contour extraction subunit, aligns the target food contour line and the package contour line through image registration technology, obtains contour point positions respectively, and calculates contour coincidence according to the contour point positions.

3. The food safety supervision system based on the cloud platform according to claim 2 is characterized in that: The fit analysis module also includes: An edge point extraction unit, used to respectively extract target food edge points and package edge points by using edge detection; The matching subunit is connected to the edge point extraction unit and is used to match the target food edge point with the package edge point to calculate the shortest distance between the matching points as the edge distance.

4. The food safety supervision system based on the cloud platform according to claim 3 is characterized in that: If the contour overlap is higher than a first qualified threshold and the edge distance is lower than a second qualified threshold, it is determined that the fit between the target food and the package is qualified.

5. The food safety supervision system based on the cloud platform according to claim 4 is characterized in that: The sloshing risk analysis module includes: The wrinkle assessment unit physically simulates the vibration and impact environment of the package during transportation and obtains the deformation degree and distribution of wrinkles on the package surface through image processing; The shaking risk determination unit is connected to the wrinkle evaluation unit, and measures the deformation data and movement range of the target food in the package according to the deformation degree and the distribution, so as to determine whether the shaking risk of the target food in the package is qualified.

6. The food safety supervision system based on the cloud platform according to claim 5 is characterized in that: The sway risk determination unit comprises: A monitoring subunit, used to monitor the deformation data of the wrinkles and the movement range of the target food in the package in real time; a data determination subunit, connected to the monitoring subunit, for determining a maximum deformation degree of the target food in the package according to the deformation data, and determining a maximum movement range of the target food in the package according to the movement range; The shaking risk assessment subunit is connected to the data determination subunit. When the maximum deformation degree and the maximum movement range are both within the standard safety range, it is determined that the shaking risk of the target food in the package is qualified.

7. The food safety supervision system based on the cloud platform according to claim 6 is characterized in that: The packaging material evaluation module includes: Environmental simulation unit, used to simulate the actual contact environment between the target food and packaging materials under test conditions; a migration substance detection unit connected to the environment simulation unit, for periodically sampling the target food in the actual contact environment and detecting the migration substances therein by gas chromatography; A quantitative analysis unit, connected to the migration substance detection unit, performs quantitative analysis on the migration substance to determine its concentration and migration amount; The safety assessment unit is connected to the quantitative analysis unit to determine whether the concentration and the migration amount are within the prescribed limit standard range, thereby evaluating the material safety of the packaging.

8. The food safety supervision system based on the cloud platform according to claim 7 is characterized in that: The quantitative analysis unit comprises: The pretreatment subunit pre-treats the target food containing the migrating substances to ensure that the target food meets the requirements of quantitative analysis; A concentration analysis subunit, connected to the pretreatment subunit, is used to inject the pretreated target food into the quantitative analysis instrument, separate, detect and quantify according to the spectroscopic method, record the spectral absorbance output by the instrument, and convert the spectral absorbance into the concentration of the migration substance using a regression equation; The migration amount calculation subunit is connected to the concentration analysis subunit and calculates the migration amount according to the concentration and the contact time of the target food.

9. The food safety supervision system based on the cloud platform according to claim 8, characterized in that: The regression equation is established using known concentrations of migrating substances and corresponding spectral absorbance data to reflect the quantitative relationship between spectral absorbance and the concentration of migrating substances. The concentration analysis subunit measures the spectral absorbance of the target food and detects the concentration value corresponding to the migrating substance in the regression equation to achieve conversion of spectral absorbance into substance concentration.

10. The food safety supervision system based on the cloud platform according to claim 9, characterized in that: The security determination module comprises: A data evaluation unit, for generating a food safety evaluation report based on the fit, the shaking risk and the material safety; The risk assessment unit is connected to the data assessment unit and assesses the food safety assessment report according to safety standards, thereby determining that the target food in the package is safe food.

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