Food additive production management and control system and method based on intelligent scheduling

Abstract

The invention discloses a food additive production management and control system and method based on intelligent scheduling, and relates to the technical field of additive production. The method comprises a printing step and an extraction step, and the printing step comprises the following steps that a scheduling unit obtains scheduling records of a production workshop and uniformly uploads the scheduling records to a processing unit, the processing unit stores the scheduling records to a database, and meanwhile, a data classification program is executed according to the data length L of the scheduling records to obtain data blocks and a compression algorithm; the method comprises the steps that a data block is stored in a database, a processing unit obtains a packaging picture from the database, the processing unit executes a picture fusion program according to the data block and a compression algorithm to obtain a fused picture, and the processing unit synchronously stores the fused picture to the database. The distributed storage of the scheduling record can be realized, the data security is improved, the scheduling record is prevented from being manually tampered, and the authenticity of the scheduling record is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of additive production, in particular to a food additive production control system and method based on intelligent scheduling. BACKGROUND

[0002] As a key component of the food industry, food additives have improved production management levels as consumers demand higher food safety and quality, and every product on the market can be traced and checked for scheduling records.

[0003] Existing intelligent scheduling information only saves scheduling records in databases or cloud servers, and scheduling records are at risk of being tampered with or lost, so new distributed storage methods are needed to ensure the data security of scheduling records, and printing scheduling records directly on product packaging poses a risk of exposing enterprise privacy, so a distributed storage system with security features to back up scheduling records is a technical problem that needs to be solved by those skilled in the art. SUMMARY

[0004] To address the deficiencies of the prior art, the present application provides a food additive production control system and method based on intelligent scheduling, which solves the problems raised in the background art.

[0005] To achieve the above purpose, the present application is implemented by the following technical solutions: a food additive production control method based on intelligent scheduling, realized based on a database, a printing module, a processing unit, a scanning terminal, a recording module, a product module, a production module and a personnel module, comprising a printing step and an extraction step, the printing step comprising the following steps:

[0006] Step 1: The scheduling unit obtains the scheduling records of the production workshop and uploads them to the processing unit;

[0007] Step 2: The processing unit saves the scheduling records to the database, and simultaneously executes a data classification program according to the data length L of the scheduling records to obtain data blocks and compression algorithms;

[0008] Step 3: The processing unit obtains the packaging pictures from the database, and executes a picture fusion program according to the data blocks and compression algorithms to obtain a fusion picture, which is saved to the database by the processing unit;

[0009] Step 4: The processing unit transmits the fusion picture to the printing module for printing;

[0010] The extraction step comprises the following steps:

[0011] Step 5: The operator uses the scanning terminal to take a first image of the fusion picture printed on the surface of the product. The scanning terminal uploads the first image to the processing unit through wireless communication. The processing unit compares the first image with the fusion pictures stored in the database to calculate the similarity. The processing unit sends the data block and compression algorithm corresponding to the fusion picture with the highest similarity to the scanning terminal through wireless communication.

[0012] Step 6: The operator uses the scanning terminal to repeatedly take several first images of the fusion picture from different angles on the surface of the product. The scanning terminal executes a picture stitching program to stitch the several first images into a second image. The first image is a partial fusion picture, and the second image is a complete fusion picture. Since the complete fusion picture needs to be continuously taken by the scanning terminal, the data acquisition amount involved is large. If all the data is uploaded to the processing unit, it will increase the computational load of the processing unit and the transmission pressure of the upload bandwidth. Therefore, the processing unit sends the data block and compression algorithm to the scanning terminal, so that the scanning terminal can execute the picture stitching program and the subsequent picture extraction program locally, saving the computational resources of the processing unit and the upload bandwidth of the scanning terminal, and improving the response speed of the program.

[0013] Step 7: The scanning terminal executes a picture extraction program based on the data block and the compression algorithm to obtain a scheduling record. The extracted scheduling record is all scheduling records recorded by the scheduling unit in the production process of the product. The complete traceability of the product can be realized according to the scheduling record.

[0014] Further, the scheduling unit obtaining the scheduling record specifically includes the following steps:

[0015] Step 101: The recording module respectively obtains the equipment information of the production module, the personnel information of the personnel module, and the product information of the product module.

[0016] Step 102: The recording module associates the equipment information, the personnel information, and the product information according to the production process of the food additive.

[0017] Step 103: The recording module records the scheduling behavior of each personnel, equipment, and product in the production workshop in real time, intelligently synchronously modifies the scheduling record according to the scheduling behavior, and transmits the scheduling record to the processing unit.

[0018] Further, the data classification program specifically includes the following steps:

[0019] Step 201: The processing unit performs binary encoding on the scheduling record and counts the length L of the encoded data.

[0020] Step 202: The processing unit matches the appropriate data block and compression algorithm according to the data length L, the compression algorithm including the compression ratio and the reference number, the data block being the smallest cutting unit of the packaging picture, the packaging picture being cut into a plurality of data blocks of the same size, the compression ratio being the compression ratio of the packaging picture, and the reference number being the pixel at a fixed position in the data block used to replace the compressed packaging picture. The processing unit saves the binary coded scheduling record in the pixel at the fixed position in each data block of the packaging picture in sequence, and uses the gray value of the pixel with the reference number to record the binary coding of the scheduling record, thereby realizing the saving of the scheduling record. The size of the data block depends on the value of the data length L. The larger the value of the data length L, the smaller the required data block and the smaller the compression ratio. In the limited number of pixels of the packaging picture, more data can be saved as possible. Conversely, the smaller the value of the data length L, the larger the required data block and the larger the compression ratio. In the packaging picture, as much repeated data or data of adjacent products as possible can be saved. The gray value of the pixel at the fixed position with the reference number in each data block ranges from 0 to 255, and the gray value of the pixel is used to save the data of the scheduling record.

[0021] Step 203: The processing unit counts the total amount of data saved G of all data blocks, and the total amount of data saved G needs to meet the condition G≥3L, that is, each packaging picture can save at least 3 scheduling records. The 3 scheduling records can be the scheduling records of the repeated product itself or the scheduling records of the adjacent product. The processing unit selects the largest data block from the data blocks meeting the condition. After the data block is determined, the compression ratio in the compression algorithm is also determined. The compression ratio is the square of the length of the side of the data block. The processing unit randomly selects a pixel at a fixed position in the data block and records the position of the pixel as the reference number.

[0022] Step 204: The processing unit saves the data block corresponding to the packaging picture, the compression ratio and the reference number to the database.

[0023] Further, the picture fusion program specifically includes the following steps:

[0024] Step 301: The processing unit calls the data block, the compression algorithm and the corresponding packaging picture from the database. The processing unit cuts the packaging picture based on the data block;

[0025] Step 302: The processing unit calls the scheduling record corresponding to the product from the database and obtains a first data chain by binary conversion. The processing unit splits the first data chain into a single byte and inputs the packaging picture. The single byte is saved in each data block from top to bottom, and the gray value of the pixel at the specified position in the data block is used to save the split first data chain;

[0026] Step 303: The processing unit aggregates all the data blocks recording the first data chain to obtain a fusion picture.

[0027] Further, the picture splicing program specifically comprises the following steps:

[0028] Step 601: The scanning terminal obtains the gray value of each first picture edge pixel;

[0029] Step 602: The scanning terminal repeatedly compares the gray value of the first picture edge pixel with the gray value of another first picture edge pixel, and when the pixel gray values are different, the pixels are offset by one pixel in reverse and the pixel gray values are compared again. The difference in gray value between the pixels is calculated once each time until the pixels on one side edge of the first picture and the pixels on one side edge of another first picture are all compared.

[0030] Step 603: The scanning terminal selects the time with the smallest gray value difference in the comparison for splicing. The smallest gray value difference represents the highest similarity of the edge pixels between the two first pictures, and it is most likely to be adjacent pictures taken. Repeated reverse comparison can reduce the error during picture splicing. After splicing, a second picture is obtained.

[0031] Further, the picture extraction program specifically comprises the following steps:

[0032] Step 701: The scanning terminal compresses the second picture based on a compression algorithm, and obtains an extracted picture after compression. At this time, the gray value of each pixel in the extracted picture is the fixed position of the reference number of the first data chain;

[0033] Step 702: The scanning terminal converts each pixel in the extracted picture into a gray value from top to bottom, and connects the gray values two by two to obtain a second data chain. The second data chain is the first data chain after restoration. The scanning terminal performs inverse binary encoding on the second data chain to obtain a scheduling record.

[0034] Further, when the processing unit randomly selects a reference number of a data block, the processing unit synchronously obtains other packaging pictures adjacent to the packaging picture. The processing unit calculates the similarity F between the adjacent packaging pictures pixel by pixel. Specifically, the processing unit calculates the difference cz in gray value between the same position pixels of the two packaging pictures. The processing unit accumulates the difference in gray value to obtain the total difference CZ. The processing unit counts the total number of pixels PIX of the two packaging pictures. The processing unit calculates the similarity F between the adjacent packaging pictures according to the formula F=1-(CZ / PIX)*100%;

[0035] If the value of the similarity F between adjacent packaging pictures exceeds 98%, it represents that the two adjacent packaging pictures are the packaging pictures of the same product, and the products corresponding to the two adjacent packaging pictures can be the same production batch. If the same reference number is obtained when the first picture is acquired at the scanning terminal, it is easy to cause the distortion of the extracted scheduling record, and therefore, it needs to be avoided. The processing unit sets the value of the reference number of the two adjacent packaging pictures to be not adjacent.

[0036] If the value of the similarity F between adjacent packaging pictures is less than or equal to 98%, it represents that the two adjacent packaging pictures are the packaging pictures of different products, and the reference number of the packaging picture is not limited.

[0037] Further, when the data block completely saves the data chain, the processing unit counts the number g1 of the data blocks in which a single byte of data is input and the number g2 of the data blocks in which a single byte of data is not input.

[0038] If the number g2 is greater than or equal to three times the number g1, it represents that the packaging picture can save more data chains. The processing unit compares the size of the data block of the adjacent packaging picture with the size of the current data block. If the sizes of the data blocks of the adjacent packaging picture and the current data block are consistent, it represents that the adjacent packaging picture can be the packaging picture of the same product. The processing unit saves the data chain corresponding to the adjacent packaging picture into the data block in which a single byte of data is not input. If the product is lost, the scheduling record of the lost product can be acquired by scanning the adjacent product. If the sizes of the data blocks of the adjacent packaging picture and the current data block are inconsistent, it represents that the adjacent packaging picture can be the packaging picture of different products. The processing unit repeatedly writes the data chain into the data block in which a single byte of data is input, as a data backup. If the subsequent fused picture is damaged, the remaining part can still restore the complete scheduling record.

[0039] If the number g2 is less than three times the number g1, the processing unit stops writing the data chain into the data block in which a single byte of data is not input, so as to reduce the operation pressure of the processing unit.

[0040] A food additive production control system based on intelligent scheduling includes a database, a printing module, a processing unit, a scanning terminal and a scheduling unit. The scheduling unit includes a record module, a product module, a production module and a personnel module. The port of the processing unit and the port of the database establish bidirectional communication. The output end of the processing unit is connected with the input end of the printing module. The port of the processing unit and the port of the scanning terminal establish bidirectional communication through wireless communication. The wireless communication between the scanning terminal and the processing unit is based on LoRa or TD-LTE communication technology. The output ends of the product module, the production module and the personnel module are connected with the input end of the record module. The output end of the record module is connected with the input end of the processing unit.

[0041] The scheduling unit is used for recording the scheduling record among all production modules, product modules and personnel modules in the food additive production workshop, specifically, the recording module obtains equipment information of the production module, the recording module obtains personnel information of the personnel module, the recording module obtains product information of the product module, the recording module associates the equipment information, the personnel information and the product information according to the production process of the food additive, and then makes synchronous modification according to the intelligent scheduling behavior of the production workshop to obtain the scheduling record, and the recording module uploads the scheduling record to the processing unit;

[0042] The processing unit stores the scheduling record in the database, selects a data block and a compression algorithm according to the scheduling record, splits the scheduling record based on the data block and the compression algorithm, and integrates the scheduling record into a packaging picture to obtain a fusion picture, the packaging picture is a picture of a food additive packaging or a food packaging surface, the processing unit transmits the fusion picture to the printing module, and the printing module prints the fusion picture.

[0043] Further, the scanning terminal photographs part of the fusion picture to obtain a first image, the scanning terminal uploads the first image to the processing unit, the processing unit determines the data block and the compression algorithm according to the first image, the processing unit sends the data block and the compression algorithm to the scanning terminal, the scanning terminal photographs multiple times to obtain first pictures at different angles and splices the first pictures to obtain a second image, and the scanning terminal extracts the scheduling record from the second image based on the data block and the compression algorithm, so that the hidden scheduling record can be directly obtained by scanning the packaging picture of the product, the traceability of the product scheduling record can be realized without affecting the product packaging design, the confidentiality of the scheduling record is ensured, and the scheduling record in the production process is prevented from being leaked.

[0044] The application has the following advantages:

[0045] 1. By integrating the scheduling record into the packaging picture of the product using the compression algorithm, distributed storage of the scheduling record can be realized, each product can be quickly traced using the scanning terminal, the scheduling record is prevented from being tampered with, and the authenticity of the scheduling record is improved.

[0046] 2. The scheduling record is hidden in the packaging picture of each product by the data block and the compression algorithm, the enterprise privacy data is prevented from being leaked, each product can be used as a backup of the database, and the data security of the scheduling record is improved.

[0047] Of course, any product implementing the present application does not necessarily need to achieve all the advantages described above. BRIEF DESCRIPTION OF DRAWINGS

[0048] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0049] Figure 1 The block diagram of the food additive production control system based on intelligent scheduling of the present application;

[0050] Figure 2 The flowchart of the data block and compression algorithm of the present application;

[0051] Figure 3 The schematic diagram of the pixel gray value comparison between the first pictures in step 602 of the present application. DETAILED DESCRIPTION

[0052] The technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without any creative effort belong to the protection scope of the present application.

[0053] Please refer to Figures 1-3 The present application provides a technical solution: a food additive production control method based on intelligent scheduling, which is realized based on a database, a printing module, a processing unit, a scanning terminal, a recording module, a product module, a production module and a personnel module, and includes a printing step and an extraction step. The printing step includes the following steps:

[0054] Step 1: The scheduling unit obtains the scheduling records of the production workshop and uploads them to the processing unit;

[0055] Step 2: The processing unit saves the scheduling records to the database, and executes a data classification program according to the data length L of the scheduling records to obtain a data block and a compression algorithm;

[0056] Step 3: The processing unit obtains the packaging pictures from the database, executes a picture fusion program according to the data block and the compression algorithm to obtain a fusion picture, and saves the fusion picture to the database synchronously;

[0057] Step 4: The processing unit transmits the fusion picture to the printing module for printing;

[0058] The extraction step includes the following steps:

[0059] Step 5: The operator uses the scanning terminal to take a first image of the fusion picture printed on the surface of the product. The scanning terminal uploads the first image to the processing unit through wireless communication. The processing unit compares the first image with the fusion pictures stored in the database to calculate the similarity. The processing unit sends the data block and compression algorithm corresponding to the fusion picture with the highest similarity to the scanning terminal through wireless communication.

[0060] Step 6: The operator uses the scanning terminal to repeatedly take several first images of the fusion picture from different angles on the surface of the product. The scanning terminal executes a picture stitching program to stitch the several first images into a second image. The first image is a partial fusion picture, and the second image is a complete fusion picture. Since the complete fusion picture needs to be continuously taken by the scanning terminal, the data collection amount involved is large. If all the data is uploaded to the processing unit, it will increase the computational load of the processing unit and the transmission pressure of the upload bandwidth. Therefore, the processing unit sends the data block and compression algorithm to the scanning terminal, so that the scanning terminal can execute the picture stitching program and the subsequent picture extraction program locally, saving the computational resources of the processing unit and the upload bandwidth of the scanning terminal, and improving the response speed of the program.

[0061] Step 7: The scanning terminal executes a picture extraction program based on the data block and the compression algorithm to obtain a scheduling record. The extracted scheduling record is all the scheduling records recorded by the scheduling unit in the production process of the product. The complete traceability of the product can be realized according to the scheduling record.

[0062] Specifically, the scheduling unit obtaining the scheduling record comprises the following steps:

[0063] Step 101: The recording module respectively obtains the equipment information of the production module, the personnel information of the personnel module, and the product information of the product module.

[0064] Step 102: The recording module associates the equipment information, the personnel information, and the product information according to the production process of the food additive.

[0065] Step 103: The recording module records the scheduling behavior of each personnel, equipment, and product in the production workshop in real time, intelligently synchronously modifies the scheduling record according to the scheduling behavior, and transmits the scheduling record to the processing unit.

[0066] Specifically, the data classification program comprises the following steps:

[0067] Step 201: The processing unit performs binary encoding on the scheduling record, and counts the length L of the encoded data. For example, a scheduling record occupies 1024 bytes after encoding, i.e. L = 1024.

[0068] Step 202: The processing unit matches the appropriate data block and compression algorithm according to the data length L. The compression algorithm includes a compression ratio and a reference number. The data block is the minimum cutting unit of the packaging image, that is, the packaging image is cut into several data blocks of the same size. The compression ratio is the compression ratio of the packaging image. The reference number is the pixel at a fixed position in the data block used to replace the compressed packaging image after the packaging image is compressed. For example, Figure 2 As shown, a1 is a 3x3 data block, b1 is a 4x4 data block, when the data block a1 is compressed at a compression ratio of 9:1, a pixel a2 at a fixed position with a reference number (1, 1) is used instead of a1, and when the data block b1 is compressed at a compression ratio of 16:1, a pixel b2 at a fixed position with a reference number (3, 1) is used instead of b1. The processing unit saves the binary-coded scheduling record in the pixels at the fixed positions of the reference numbers in each data block of the packaging image, and uses the grayscale value of the reference numbered pixels to record the binary code of the scheduling record, thereby realizing the storage of the scheduling record. The size of the data block depends on the value of the data length L. The larger the value of the numerical length L, the smaller the data block required and the smaller the compression ratio. In this way, more data can be saved as much as possible in the limited number of pixels in the packaging image. Conversely, the smaller the value of the numerical length L, the larger the data block required and the greater the compression ratio. In this way, as much repeated data or data of adjacent products as possible can be saved in the packaging image. The grayscale value range of the pixel at a fixed position in each data block is 0-255. The grayscale value of the pixel is used to save the data of the scheduling record. The data length that can be saved in each data block is 8 bits of binary.

[0069] Step 203: The processing unit counts the total amount of data stored in all data blocks, G. The total amount G must meet the condition G ≥ 3L, that is, each packaging image can store at least three scheduling records. The three scheduling records can be repeated scheduling records for the product itself or scheduling records for adjacent products. The processing unit selects the largest data block from the data blocks that meet the condition. After determining the data block, the compression ratio in the compression algorithm is also determined. The compression ratio is the square of the side length of the data block. Each data block is a square. The processing unit randomly selects a pixel at a fixed position from the data block and records the position of the pixel as a reference number.

[0070] Step 204: The processing unit saves the data block, compression ratio and reference number corresponding to the packaging image into a database.

[0071] The image fusion program specifically includes the following steps:

[0072] Step 301: The processing unit retrieves data blocks, compression algorithms, and corresponding packaging images from a database, and segments the packaging images based on the data blocks.

[0073] Step 302: The processing unit calls the scheduling record corresponding to the product from the database and performs binary conversion to obtain a first data chain. The processing unit splits the first data chain into a single byte input package picture. The single byte is saved in each data block from top to bottom. The gray value of the pixel at the specified position in the data block is used to save the split first data chain.

[0074] Step 303: The processing unit aggregates all data blocks recording the first data chain to obtain a fusion picture.

[0075] The picture splicing program specifically includes the following steps:

[0076] Step 601: The scanning terminal obtains the gray value of each first picture edge pixel.

[0077] Step 602: As shown in the figure, the scanning terminal repeatedly compares the gray value of the first picture edge pixel with the gray value of another first picture edge pixel. When the pixel gray values are different, the pixels are offset by one pixel point in reverse and the pixel gray values are compared again. The difference in gray value between the pixels is calculated once each time until the pixels on one side of the first picture and the pixels on one side of another first picture are all compared. Figure 3

[0078] Step 603: The scanning terminal selects the time with the smallest gray value difference in the comparison for splicing. The smallest gray value difference represents the highest similarity between the edge pixels of the two first pictures, which are most likely to be adjacent pictures taken. Repeated reverse comparison can reduce the error during picture splicing. After splicing, a second picture is obtained.

[0079] The picture extraction program specifically includes the following steps:

[0080] Step 701: The scanning terminal compresses the second picture based on a compression algorithm. After compression, an extraction picture is obtained. At this time, the gray value of each pixel in the extraction picture is the fixed position pixel whose reference number is saved in the first data chain.

[0081] Step 702: The scanning terminal converts each pixel in the extraction picture from top to bottom into a gray value. The gray values are connected two by two to obtain a second data chain. The second data chain is the first data chain after restoration. The scanning terminal performs reverse binary encoding on the second data chain to obtain a scheduling record.

[0082] ​When the processing unit randomly selects a reference number of a data block, the processing unit synchronously acquires other packaging pictures adjacent to the packaging picture, the processing unit calculates the similarity F between the adjacent packaging pictures pixel by pixel, specifically, the processing unit calculates the difference cz of the gray values between the pixels at the same position of the two packaging pictures, the processing unit accumulates the difference of the gray values to obtain the total difference CZ, the processing unit counts the total number of pixels PIX of the two packaging pictures, and the processing unit calculates the similarity F between the adjacent packaging pictures according to the formula F = 1 - (CZ / PIX) * 100%.

[0083] If the value of the similarity F between the adjacent packaging pictures exceeds 98%, it means that the two adjacent packaging pictures are packaging pictures of the same product, and the products corresponding to the two adjacent packaging pictures may be of the same production batch. If the reference numbers are the same when the first picture is acquired at the scanning terminal, it is easy to cause distortion of the extracted scheduling record, so it is necessary to avoid it. The processing unit sets the reference number values of the two adjacent packaging pictures to be non-adjacent, for example, the similarity F of the packaging picture P1 and the packaging picture P2 is 99%, and the reference number of the packaging picture P1 is (1, 1). Then, the reference number of the packaging picture P2 cannot be (1, 2), (2, 1) and (2, 2). The processing unit removes these reference numbers and randomly selects from the remaining reference numbers.

[0084] If the value of the similarity F between the adjacent packaging pictures is less than or equal to 98%, it means that the two adjacent packaging pictures are packaging pictures of different products, and the reference number of the packaging picture is not limited.

[0085] When the data block completely saves the data chain, the processing unit counts the number g1 of data blocks in which a single byte of data is input and the number g2 of data blocks in which a single byte of data is not input.

[0086] If the number g2 is greater than or equal to three times the number g1, it means that the packaging picture can save more data chains. The processing unit compares the data block of the adjacent packaging picture with the current data block. If the sizes of the data blocks of the adjacent packaging pictures are consistent with the size of the current data block, it means that the adjacent packaging pictures may be packaging pictures of the same product. The processing unit saves the data chain corresponding to the adjacent packaging picture into the current data block in which a single byte of data is not input. If the product is lost, the scheduling record of the lost product can be obtained by scanning the adjacent product. If the sizes of the data blocks of the adjacent packaging pictures are inconsistent with the size of the current data block, it means that the adjacent packaging pictures may be packaging pictures of different products. The processing unit repeatedly writes the data chain into the data block in which a single byte of data is input, which serves as a data backup. If the subsequent fused picture is damaged, the remaining part can still restore the complete scheduling record.

[0087] If the number of g2 is less than three times the number of g1, the processing unit stops writing the data chain to the data block without inputting a single byte, reducing the operation pressure of the processing unit.

[0088] A food additive production management and control system based on intelligent scheduling, as shown in Figure 1 The scheduling unit includes a recording module, a product module, a production module, and a personnel module. The port of the processing unit establishes bidirectional communication with the port of the database. The output end of the processing unit is connected with the input end of the printing module. The port of the processing unit establishes bidirectional communication with the port of the scanning terminal through wireless communication. The wireless communication between the scanning terminal and the processing unit is based on LoRa or TD-LTE communication technology. The output ends of the product module, the production module, and the personnel module are all connected with the input end of the recording module. The output end of the recording module is connected with the input end of the processing unit.

[0089] The scheduling unit is used to record the scheduling records between all production modules, product modules, and personnel modules in the food additive production workshop. Specifically, the recording module obtains device information of the production module, personnel information of the personnel module, and product information of the product module. The recording module associates the device information, the personnel information, and the product information according to the production process of the food additive, and makes synchronous modification according to the intelligent scheduling behavior of the production workshop to obtain the scheduling records. For example, A employee in the personnel information uses B device in the device information to produce C product in the product information. The recording module uploads the scheduling records to the processing unit.

[0090] The processing unit saves the scheduling records to the database. The processing unit selects a data block and a compression algorithm according to the scheduling records. The processing unit splits and integrates the scheduling records into a packaging picture based on the data block and the compression algorithm to obtain a fusion picture. The packaging picture is a picture of the surface of a food additive packaging or a food packaging. The processing unit transmits the fusion picture to the printing module. The printing module prints the fusion picture.

[0091] The scanning terminal shoots part of the fusion picture to obtain a first image. The scanning terminal uploads the first image to the processing unit. The processing unit determines a data block and a compression algorithm according to the first image. The processing unit sends the data block and the compression algorithm to the scanning terminal. The scanning terminal shoots the first picture from different angles multiple times and splices them into a complete packaging picture to obtain a second image. The scanning terminal extracts the scheduling records from the second image based on the data block and the compression algorithm. The hidden scheduling records can be directly obtained by scanning the packaging picture of the product. The traceability of the product scheduling records can be realized without affecting the design of the product packaging. At the same time, the confidentiality of the scheduling records is ensured, and the scheduling records in the production process are prevented from being leaked.

[0092] The above merely describes preferred specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art, according to the technical solution and inventive concept of the present application, makes equivalent replacement or change within the technical range disclosed by the present application, which should be covered within the protection scope of the present application.

Claims

1. A food additive production control method based on intelligent scheduling, characterized by: The method comprises a printing step and an extracting step, wherein the printing step comprises the following steps: Step 1: The scheduling unit obtains the scheduling records of the production workshop and uploads them to the processing unit; Step 2: The processing unit saves the scheduling record to the database and executes a data classification program according to the data length L of the scheduling record to obtain data blocks and compression algorithms; Step 3: The processing unit obtains the packaging image from the database, executes the image fusion program according to the data block and compression algorithm to obtain the fused image, and synchronously saves the fused image to the database; Step 4: Transfer the fused image to the printing module for printing; The extraction step comprises the following steps: Step 5: The operator uses a scanning terminal to capture the fused image printed on the product surface to obtain a first image. The scanning terminal uploads the first image to the processing unit via wireless communication. The processing unit compares the first image with the fused image stored in the database and calculates the similarity. The data block and compression algorithm corresponding to the fused image with the highest similarity are then sent to the scanning terminal via wireless communication. Step 6: The operator uses a scanning terminal to repeatedly capture fused images of the product surface from different angles to obtain several first images. The scanning terminal then executes an image stitching program to stitch the several first images into a second image. The first image is a partial fused image, and the second image is a complete fused image. Step 7: The scanning terminal executes an image extraction program based on the data block and compression algorithm to obtain the scheduling record.

2. A food additive production control method based on intelligent scheduling according to claim 1, characterized in that: The scheduling unit obtains the scheduling record specifically including the following steps: Step 101: The recording module obtains the equipment information of the production module and the personnel information of the personnel module, and obtains the product information of the product module; Step 102: The recording module associates the equipment information, personnel information, and product information according to the production process of the food additive; Step 103: The recording module records the scheduling behavior of each person, equipment and product in the production workshop in real time, intelligently and synchronously modifies the scheduling record according to the scheduling behavior and transmits it to the processing unit.

3. A food additive production control method based on intelligent scheduling according to claim 1, characterized in that: The data classification procedure specifically includes the following steps: Step 201: The processing unit performs binary encoding on the scheduling record and calculates the length L of the encoded data; Step 202: Matching a suitable data block and compression algorithm based on the data length L. The compression algorithm includes a compression ratio and a reference number. The packaging image is divided into a number of data blocks of equal size. The compression ratio is the compression ratio of the packaging image. The reference number is the pixel at a fixed position in the data block after the packaging image is compressed to replace the compressed packaging image. The grayscale value range of the pixel at the fixed position of the reference number in each data block is 0-255. Step 203: Count the total amount of data stored in all data blocks G. If the condition G ≥ 3L is met, select the largest data block from the data blocks that meet the condition. After the data block is determined, the compression ratio in the compression algorithm is also determined. The compression ratio is equal to the square of the side length of the data block. Each data block is a square. Randomly select a pixel at a fixed position from the data block and record the position of the pixel as a reference number. Step 204: Save the data block, compression ratio and reference number corresponding to the packaging image into the database.

4. A food additive production control method based on intelligent scheduling according to claim 1, characterized in that: The image fusion program specifically includes the following steps: Step 301: The processing unit retrieves data blocks, compression algorithms, and corresponding packaging images from a database, and segments the packaging images based on the data blocks. Step 302: Retrieve the scheduling record from the database and perform binary conversion to obtain a first data chain. Split the first data chain into individual bytes and input them into the packaging image. Save the individual bytes in each data block from top to bottom. Use the grayscale value of the pixel at a specified position in the data block to save the split first data chain. Step 303: Aggregate all data blocks recording the first data link to obtain a fused image.

5. A food additive production control method based on intelligent scheduling according to claim 1, characterized in that: The image stitching program specifically includes the following steps: Step 601: The scanning terminal obtains the grayscale value of each edge pixel of the first image; Step 602: Repeatedly compare the grayscale values ​​of edge pixels of the first image with the grayscale values ​​of edge pixels of the other first image in reverse order. If the pixel grayscale values ​​differ, the grayscale values ​​of the pixels are compared one pixel in reverse order. The grayscale value difference between the pixels is calculated each time until all the pixels on one edge of the first image are compared with the other first image. Step 603: Select the one with the smallest grayscale value difference in the comparison for stitching, and obtain the second image after the stitching is completed.

6. A food additive production control method based on intelligent scheduling according to claim 1, characterized in that: The image extraction procedure specifically includes the following steps: Step 701: The scanning terminal compresses the second image based on a compression algorithm to obtain an extracted image. Step 702: Convert each pixel in the extracted image into grayscale values ​​from top to bottom, connect the grayscale values ​​in pairs to obtain a second data chain, and perform reverse binary encoding on the second data chain to obtain a scheduling record.

7. A food additive production control method based on intelligent scheduling according to claim 3, characterized in that: When the processing unit randomly selects the reference number of a data block, it simultaneously obtains other adjacent packaging images, calculates the similarity F between the adjacent packaging images pixel by pixel, calculates the grayscale value difference cz between the pixels at the same position in the two packaging images, accumulates the grayscale value differences to obtain a total difference CZ, counts the total number of pixels PIX in the two packaging images, and calculates the similarity F between the adjacent packaging images according to the formula F=1-(CZ / PIX)*100%; If the similarity F between adjacent packaging images exceeds 98%, the reference numbers of the two adjacent packaging images are set to be non-adjacent. If the value of the similarity F between adjacent packaging images is less than or equal to 98%, no restriction is imposed on the reference numbers of the packaging images.

8. A food additive production control method based on intelligent scheduling according to claim 4, characterized in that: After the data block has completely saved the data chain, the processing unit counts the number of data blocks g1 that have completed inputting a single byte and the number g2 of data blocks that have not inputted a single byte; If the number of g2 is greater than or equal to three times the number of g1, obtain the data blocks of the adjacent package images and compare the sizes with the current data block. If the sizes of the data blocks of the adjacent images are consistent with the current data block size, save the data chain corresponding to the adjacent package images into the data block where a single byte has not been input. If the sizes of the data blocks of the adjacent images are inconsistent with the current data block size, repeatedly write the data chain into the data block where a single byte has been input. If the number of g2 is less than three times the number of g1, stop writing the data chain to the data block where a single byte has not been input.

9. A food additive production control system based on intelligent scheduling, characterized by Implementing a food additive production control method based on intelligent scheduling as described in any one of claims 1 to 8, comprising a database, a printing module, a processing unit, a scanning terminal and a scheduling unit, wherein the scheduling unit includes a recording module, a product module, a production module and a personnel module, a port of the processing unit establishes two-way communication with a port of the database, an output end of the processing unit is connected to an input end of the printing module, a port of the processing unit establishes two-way communication with a port of the scanning terminal via wireless communication, the output ends of the product module, the production module and the personnel module are all connected to the input end of the recording module, and the output end of the recording module is connected to the input end of the processing unit; The scheduling unit is used to record the scheduling records between all production modules, product modules and personnel modules in the food additive production workshop. The recording module obtains the equipment information of the production module, obtains the personnel information of the personnel module, obtains the product information of the product module, associates the equipment information, personnel information and product information according to the production process of the food additive, and then makes synchronous modifications according to the intelligent scheduling behavior of the production workshop to obtain the scheduling record. The recording module uploads the scheduling record to the processing unit; The processing unit transfers the scheduling record to a database for storage, selects a data block and a compression algorithm according to the scheduling record, splits the scheduling record based on the data block and the compression algorithm, and integrates the scheduling record into the packaging picture to obtain a fused picture, transmits the fused picture to a printing module, and the printing module prints the fused picture.

10. A food additive production control system based on intelligent scheduling according to claim 9, characterized in that: The scanning terminal captures a partially fused image to obtain a first image, and uploads the first image to a processing unit. The processing unit determines a data block and a compression algorithm based on the first image, and sends the data block and the compression algorithm to the scanning terminal. The scanning terminal captures the first image multiple times to obtain different angles and stitches them together into a complete packaging image to obtain a second image. The scanning terminal extracts the scheduling record from the second image based on the data block and the compression algorithm.

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