Food safety traceability method and platform for rice and flour product production line

Abstract

The invention discloses a food safety traceability method and platform for a rice and flour product production line, and relates to the related field of food traceability management, and the method comprises the steps: collecting raw material information, and adding a plurality of safety monitoring nodes; collecting production process parameters, environment monitoring data and quality detection data; taking the production process parameters as first index entries, and collecting first forward and reverse tracing sets; collecting a second forward tracing set and a second reverse tracing set by taking the environmental monitoring data as a second index entry; taking the quality detection data as a third index entry, and collecting a third forward and traceability set; establishing a food safety traceability structure through the traceability set in combination with the raw material information; and when a food safety event occurs, positioning production chain information of the same batch of products, and outputting a tracing report. The technical problems of low traceability efficiency and inaccurate traceability result in the existing food safety traceability are solved, and the technical effect of improving the accuracy and high efficiency of the food safety traceability is achieved.

Description

Technical Field

[0001] The present application relates to fields related to food traceability management, and in particular, to a food safety traceability method and platform for a rice and flour product production line. Background Art

[0002] The food safety traceability system can quickly locate the source of the problem and take effective measures to deal with it when a food safety incident occurs. In the current food safety traceability system, manual records and paper files are mainly used for management. Manual records cannot fully and accurately record all key information in the production process of rice and flour products. There is a problem of incomplete data records, and paper files are easily tampered with, which affects the accuracy of the traceability results. At the same time, when a food safety incident occurs, manually flipping through a large number of paper files for tracing is inefficient.

[0003] Among the current related technologies, food safety traceability used in rice and flour product production lines has technical problems such as low traceability efficiency and inaccurate traceability results. Summary of the invention

[0004] The present application provides a food safety traceability method and platform for a rice and flour product production line, collects raw material information, adds multiple safety monitoring nodes to each production link, collects production process parameters, environmental monitoring data and quality inspection data through the safety monitoring nodes, takes the production process parameters as the first index item, constructs a first forward and reverse traceability set, takes the environmental monitoring data as the second index item, constructs a second forward and reverse traceability set, takes the quality inspection data as the third index item, constructs a third forward and reverse traceability set, combines the raw material information and the above-mentioned traceability sets to establish a food safety traceability structure, and when a food safety incident occurs, uses the food safety traceability structure to locate the production chain information of the same batch of products, outputs a traceability report and other technical means, thereby achieving the technical effect of improving the accuracy and efficiency of food safety traceability.

[0005] The present application provides a food safety traceability method for a rice and flour product production line, comprising: in the rice and flour product production line, collecting raw material information and adding multiple safety monitoring nodes, wherein the multiple safety monitoring nodes are respectively located in multiple rice and flour product production links, and each rice and flour product production link is configured in a preset operation area; through the multiple safety monitoring nodes, collecting the production process parameters, environmental monitoring data, and quality inspection data of the multiple rice and flour product production links; using the production process parameters of the multiple rice and flour product production links as the first index item, collecting a first forward tracing set and a first reverse tracing set; using the multiple rice and flour product production links as the first index item, collecting the first forward tracing set and the first reverse tracing set; The environmental monitoring data of the production link is used as the second index item to collect the second forward traceability set and the second reverse traceability set; the quality inspection data of the multiple rice and flour product production links are used as the third index item to collect the third forward traceability set and the third reverse traceability set; the first forward traceability set and the first reverse traceability set, the second forward traceability set and the second reverse traceability set, the third forward traceability set and the third reverse traceability set are combined with the raw material information to establish a food safety traceability structure; when a food safety incident occurs, the food safety traceability structure is used to locate the production chain information of the same batch of products, and a traceability report is output.

[0006] In a possible implementation, the multiple safety monitoring nodes are respectively located in multiple rice and flour product production links, and each rice and flour product production link is configured in a preset operation area to perform the following processing: using the safety monitoring tasks issued by the distributed computing architecture, combined with the storage conditions of the raw material information, to set the monitoring and control targets, the monitoring and control targets including the frequency allocation threshold and the precision allocation threshold; based on the rice and flour product production line, combined with the frequency allocation threshold in the monitoring and control target, a frequency control network is established; based on the rice and flour product production line, combined with the precision allocation threshold in the monitoring and control target, a precision control network is established; based on the frequency control network and the precision control network, a resource allocation mechanism for the multiple rice and flour product production links is set.

[0007] In a possible implementation, a resource allocation mechanism for the multiple rice and flour product production links is set based on the frequency control network and the precision control network, and the following processing is performed: the frequency control network is used as the upper layer, and the precision control network is used as the lower layer to connect the nodes to construct a control optimization fully connected layer; the rice and flour product production line is connected to obtain real-time operating parameters, which include the speed of moving parts, the temperature of heating / cooling equipment, and equipment pressure parameters; based on the control optimization fully connected layer, the resources of multiple rice and flour product production links in the rice and flour product production line are balanced through the real-time operating parameters to obtain the resource allocation mechanism.

[0008] In a possible implementation, based on the rice and flour product production line and in combination with the frequency allocation threshold in the monitoring and control target, a frequency control network is established, and the following processing is performed: a radio frequency identification module is connected, flow tracking parameters are obtained, and multiple frequency allocation trigger intervals are determined; the multiple frequency allocation trigger intervals are combined and mapped with the frequency allocation threshold in the monitoring and control target, and a frequency control rule set is set; the frequency control rule set is used for screening to form a first candidate frequency combination set, the optimal frequency combination is selected from the first candidate frequency combination set, and a node mapping map of the frequency control network is determined.

[0009] In a possible implementation, the optimal frequency combination is selected from the first candidate frequency combination set, and the following processing is performed: the nutrition label is extracted through the nutrition test data, and the nutrition categories corresponding to the nutrition label include protein content, fat content, and carbohydrate content; based on the dynamic change characteristics of the real-time operating parameters, the nutrition label is used as a verification condition to select the optimal frequency combination from the first candidate frequency combination set.

[0010] In a possible implementation, the real-time operating parameters are used to evenly configure the resources of multiple rice and flour product production links in the rice and flour product production line to obtain the resource allocation mechanism, and perform the following processing: image acquisition of the rice and flour product production line is performed through visual inspection equipment to obtain rice and flour product image data; based on the rice and flour product image data, the production status of the rice and flour products is determined, and abnormal judgments are made, and abnormal events are recorded; a digital twin model of the rice and flour product production line is established, simulation optimization is performed according to the abnormal events, and the resource allocation of multiple rice and flour product production links in the rice and flour product production line is adaptively adjusted.

[0011] In a possible implementation, when a food safety incident occurs, the food safety traceability structure is used to locate the production chain information of the same batch of products, a traceability report is output, and the following processing is performed: the first candidate frequency combination set and the optimal frequency combination, the first candidate precision combination set and the optimal precision combination are stored on the blockchain; the production process parameters, environmental monitoring data, quality inspection data and resource allocation of each rice and flour product production link are automatically recorded and verified through the distributed ledger of the blockchain; based on the distributed ledger, the production chain information of the same batch of products located by the food safety traceability structure is trusted and authenticated, and then a traceability report is output.

[0012] The present application also provides a food safety traceability platform for a rice and flour product production line, including: a safety monitoring node adding module, used to collect raw material information and add multiple safety monitoring nodes in the rice and flour product production line, wherein the multiple safety monitoring nodes are respectively located in multiple rice and flour product production links, and each rice and flour product production link is configured in a preset operation area; a production link information collection module, used to collect the production process parameters, environmental monitoring data, and quality inspection data of the multiple rice and flour product production links through the multiple safety monitoring nodes; a first tracing set collection module, used to collect the first forward tracing set and the first reverse tracing set using the production process parameters of the multiple rice and flour product production links as the first index item; a second tracing set collection module, used to The environmental monitoring data of the multiple rice and flour product production links are used as the second index item to collect the second forward traceability set and the second reverse traceability set; the third traceability set collection module is used to collect the third forward traceability set and the third reverse traceability set by taking the quality inspection data of the multiple rice and flour product production links as the third index item; the food safety traceability structure establishment module is used to establish the food safety traceability structure by combining the first forward traceability set with the first reverse traceability set, the second forward traceability set with the second reverse traceability set, the third forward traceability set with the third reverse traceability set, and the raw material information; the traceability module is used to use the food safety traceability structure to locate the production chain information of the same batch of products when a food safety incident occurs, and output a traceability report.

[0013] The food safety traceability method and platform for rice and flour product production lines proposed in this application first collects raw material information in the rice and flour product production line and adds multiple safety monitoring nodes, wherein the multiple safety monitoring nodes are respectively located in multiple rice and flour product production links, and each rice and flour product production link is configured in a preset operation area. Then, the production process parameters, environmental monitoring data, and quality inspection data of the multiple rice and flour product production links are collected through the multiple safety monitoring nodes. Then, the production process parameters of the multiple rice and flour product production links are used as the first index item to collect the first forward tracing set and the first reverse tracing set. The environmental monitoring data of the multiple rice and flour product production links are used as the first index item to collect the first forward tracing set and the first reverse tracing set. The quality inspection data of multiple rice and flour product production links are used as the third index item to collect the third forward traceability set and the third reverse traceability set. Then, the first forward traceability set and the first reverse traceability set, the second forward traceability set and the second reverse traceability set, the third forward traceability set and the third reverse traceability set are combined with the raw material information to establish a food safety traceability structure. Finally, when a food safety incident occurs, the food safety traceability structure is used to locate the production chain information of the same batch of products, and a traceability report is output, thereby achieving the technical effect of improving the accuracy and efficiency of food safety traceability. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solution of the embodiment of the present invention, the accompanying drawings of the embodiment of the present invention will be briefly introduced below. A flow chart is used in this application to illustrate the operations performed by the platform according to the embodiment of the present application. It should be understood that the previous or following operations are not necessarily performed precisely in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0015] Figure 1 A schematic flow chart of a food safety traceability method for a rice and flour product production line provided in an embodiment of the present application.

[0016] Figure 2 A schematic diagram of the structure of a food safety traceability platform for a rice and flour product production line provided in an embodiment of the present application.

[0017] Explanation of the reference numerals: safety monitoring node adding module 10 , production link information collecting module 20 , first traceability set collecting module 30 , second traceability set collecting module 40 , third traceability set collecting module 50 , food safety traceability structure establishing module 60 , traceability module 70 . DETAILED DESCRIPTION

[0018] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0019] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0020] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, method, platform, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0021] The present application embodiment provides a food safety traceability method for a rice and flour product production line, such as Figure 1 As shown, the method includes: Step S100, in the rice and flour product production line, collect raw material information and add multiple safety monitoring nodes, wherein the multiple safety monitoring nodes are respectively located in multiple rice and flour product production links, and each rice and flour product production link is configured in a preset operation area.

[0022] Specifically, by scanning the barcode or QR code on the raw material packaging, or entering the raw material information (such as the type of raw material, supplier name, raw material batch number, production date, etc.), this information is entered into the food safety management system. Safety monitoring nodes are set up in the key production links of rice and flour product production lines (such as raw material warehousing, ingredients, mixing, molding, baking / cooking, packaging, finished product warehousing, etc.). These nodes are equipped with monitoring equipment such as sensors and cameras to monitor production status, environmental parameters, product quality, etc. in real time.

[0023] In one possible implementation, the multiple safety monitoring nodes are respectively located in multiple rice and flour product production links, and each rice and flour product production link is configured in a preset operation area. Step S100 further includes step S110, which uses the safety monitoring tasks issued by the distributed computing architecture to set monitoring and control targets in combination with the storage conditions of the raw material information. The monitoring and control targets include frequency adjustment thresholds and precision adjustment thresholds.

[0024] Specifically, the distributed computing architecture is an architecture that distributes data and processing tasks to multiple computing units for execution, which is used to improve computing efficiency and scalability. The distributed computing architecture is used to send security monitoring tasks to security monitoring nodes in each production link. These nodes are used to collect and transmit data. Combined with the storage conditions of raw material information (such as sensitive factors such as temperature, humidity, and light), specific monitoring and control targets are set for each production link, including frequency allocation thresholds and precision allocation thresholds. Among them, the frequency allocation threshold refers to the upper and lower limits of the data acquisition frequency, which is used to balance data integrity and system resource consumption. Specifically, according to the characteristics of the raw materials and the sensitivity of the production links, the data acquisition frequency of different time periods or production stages is set. For example, for the processing of perishable raw materials, a higher data acquisition frequency is required. The precision allocation threshold refers to the upper and lower limits of data acquisition accuracy, which is used to ensure data accuracy while considering cost-effectiveness. Specifically, according to the importance of the data, accuracy requirements, and the performance of the monitoring equipment, the accuracy of data acquisition is set. For example, for key quality control points, high-precision sensors and data acquisition methods are required.

[0025] Step S120, based on the rice and flour product production line, combined with the frequency allocation threshold in the monitoring and control target, a frequency control network is established. Specifically, based on the layout of the rice and flour product production line and the frequency allocation threshold in the monitoring and control target, a frequency control network is established. The frequency control network is a network architecture for managing and optimizing data acquisition frequency, and optimizes the data acquisition frequency of each monitoring node through an algorithm to ensure that system resource consumption is minimized while meeting data integrity requirements.

[0026] Step S130, based on the rice and flour product production line, combined with the precision allocation threshold in the monitoring and control target, establish a precision control network. Specifically, based on the layout of the rice and flour product production line and the precision allocation threshold in the monitoring and control target, establish a precision control network. The precision control network is a network architecture for managing and optimizing data acquisition accuracy, which optimizes the data acquisition accuracy of each monitoring node through an algorithm to ensure that the cost is controlled while meeting the data accuracy requirements.

[0027] Step S140, based on the frequency control network and the precision control network, set the resource allocation mechanism of the multiple rice and flour product production links. Specifically, based on the results of the frequency control network and the precision control network, set the resource allocation mechanism for the safety monitoring nodes of each production link, including calculating the data collection task volume of each node, the required computing resources (such as CPU, memory, storage space, etc.) and data transmission bandwidth, etc. Through the dynamic resource allocation algorithm, it is ensured that each node can efficiently utilize system resources while meeting the monitoring requirements. This implementation method balances the relationship between data integrity and accuracy requirements and system resource consumption by setting the frequency allocation threshold and the precision allocation threshold, thereby ensuring the stability and sustainability of the food safety traceability system.

[0028] In a possible implementation, based on the rice and flour product production line, combined with the frequency allocation threshold in the monitoring and control target, a frequency control network is established, and step S120 further includes step S121, connecting the radio frequency identification module, obtaining the flow tracking parameters, and determining multiple frequency allocation trigger intervals. Specifically, radio frequency identification (RFID, a wireless communication technology that automatically identifies the target object and obtains relevant data through radio frequency signals) modules are installed at key positions in the rice and flour product production process. These modules can automatically identify and track materials, semi-finished products or finished products on the production line, and obtain their flow tracking parameters, such as position, time, speed, etc. Based on these parameters, combined with the layout and process flow of the production line, the changes in the demand for data monitoring frequency at different production stages or different product flow states are analyzed, so as to determine multiple frequency allocation trigger intervals. These intervals represent specific ranges or time points where the data acquisition frequency needs to be adjusted under different production conditions.

[0029] Step S122, combine and map the multiple frequency allocation trigger intervals with the frequency allocation thresholds in the monitoring and control target, and set a frequency control rule set. Specifically, combine and map the multiple frequency allocation trigger intervals determined in step S121 with the frequency allocation thresholds in the monitoring and control target set in step S110. That is, when the state of the production line enters a certain trigger interval, the corresponding frequency allocation threshold is automatically applied. Based on this mapping relationship, a series of frequency control rules are set, which define how to adjust the data collection frequency under different trigger conditions. These rules are combined to form a frequency control rule set.

[0030] Step S123, use the frequency control rule set to screen, form a first candidate frequency combination set, select the optimal frequency combination from the first candidate frequency combination set, and determine the node mapping spectrum of the frequency control network. Specifically, use the frequency control rule set set in step S122 to screen possible data acquisition frequency combinations. Based on algorithms (such as heuristic search, etc.), find frequency combinations that meet all frequency control rule constraints, and these combinations constitute the first candidate frequency combination set. Then, select the optimal frequency combination from this set, that is, the combination that can minimize system resource consumption while ensuring data integrity and accuracy. Finally, according to this optimal frequency combination, determine the mapping spectrum of each node in the frequency control network, that is, the data collection frequency of each node under different production conditions. This implementation method realizes real-time monitoring of the material flow status of the production line and intelligent adjustment of the data collection frequency by introducing a radio frequency identification module and a frequency control network, ensuring that the data of key production links are collected in a timely and accurate manner, while avoiding unnecessary high-frequency data collection in non-critical links or low-demand periods, thereby saving system resources.

[0031] In a possible implementation, the optimal frequency combination is selected from the first candidate frequency combination set, and step S123 further includes step S1231, extracting the nutrition label through the nutrition test data, and the nutrition categories corresponding to the nutrition label include protein content, fat content, and carbohydrate content. Specifically, the rice and flour products are tested for nutrition, including the steps of sampling, laboratory analysis, and data processing. The nutrition test is used to reveal the content of key nutrients in the product, including protein content, fat content, and carbohydrate content. After obtaining the nutrition test data, the nutrition label is extracted. The nutrition label is a way to standardize the content of nutrients in food, including information such as the name and content of the nutrients.

[0032] Step S1232, based on the dynamic change characteristics of the real-time operating parameters, the nutrition label is used as a verification condition to select the optimal frequency combination from the first candidate frequency combination set. Specifically, the real-time operating parameters reflect the current state of the production line, and their changes will affect the nutritional content of the product. The nutrition label is used as a verification condition, that is, in the screening process, whether the nutritional content of the product under different frequency combinations is consistent with the information on the nutrition label is analyzed. Specifically, a mathematical model or algorithm is established, which can predict the nutritional content of the product based on the real-time operating parameters and the frequency combination, and the advantages and disadvantages of different frequency combinations are evaluated by comparing the predicted results with the information on the nutrition label. Finally, the frequency combination that best matches the nutrition label (that is, the predicted result is closest to the actual result) is selected from the first candidate frequency combination set as the optimal frequency combination. This optimal frequency combination is used in the subsequent production process to ensure that the nutritional content of the product meets expectations. This implementation method ensures that the data collection frequency of the rice and flour product production line is highly consistent with the nutritional content of the product by introducing the nutrition label as a verification condition and screening in combination with the dynamic change characteristics of the real-time operating parameters.

[0033] In a possible implementation, based on the frequency control network and the precision control network, a resource allocation mechanism for the multiple rice and flour product production links is set, and step S140 further includes step S141, taking the frequency control network as the upper layer and the precision control network as the lower layer to connect the nodes and construct a control optimization full connection layer. Specifically, the frequency control network is regarded as the upper layer, which is used to adjust the frequency of data collection according to the overall operation of the production line and the storage conditions of the raw materials. The precision control network is used as the lower layer to adjust the accuracy of data collection according to the needs of the specific production link and the importance of data collection. By establishing a connection between the two networks, dynamic control of data collection frequency and accuracy is achieved to adapt to real-time changes in the production line. When constructing the fully connected layer, a neural network or a deep learning model is used as the basis for the connection. These models can learn and understand the relationship between frequency control and precision control, thereby automatically adjusting the parameters of the two networks to achieve the optimal data collection strategy.

[0034] Step S142, connecting the rice and flour product production line to obtain real-time operating parameters, which include moving part speed, heating / cooling equipment temperature, and equipment pressure parameters. Specifically, by connecting sensors and other monitoring equipment on the rice and flour product production line, the operating parameters of the production line are obtained in real time. These parameters include the speed of moving parts (such as mixer speed, conveyor belt speed), the temperature of heating / cooling equipment (such as steamer, oven, cooling tower, cooling fan, etc.), equipment pressure (such as noodle press pressure, filling pressure), etc., which reflect the current state and performance of the production line.

[0035] Step S143, based on the control optimization fully connected layer, through the real-time operating parameters, the resources of multiple rice and flour product production links in the rice and flour product production line are balanced and configured to obtain the resource allocation mechanism. Specifically, the frequency and precision control strategies learned by the control optimization fully connected layer are used to dynamically adjust the data collection frequency and precision of each production link in combination with the changes in real-time operating parameters. Finally, a set of resource allocation mechanisms is obtained, which can automatically adapt to changes in the production line and ensure that each production link reaches the optimal state in data collection and resource use. This implementation method realizes real-time monitoring and dynamic control of the production line status by constructing a control optimization fully connected layer and obtaining real-time operating parameters, which helps to promptly discover and solve problems in the production process, and can also optimize data collection and resource allocation strategies according to the real-time needs of the production line.

[0036] In a possible implementation, the resource allocation mechanism is obtained by balancing the resource allocation of multiple rice and flour product production links in the rice and flour product production line through the real-time operation parameters, and step S143 further includes step S1431, performing image acquisition on the rice and flour product production line through visual inspection equipment to obtain rice and flour product image data. Specifically, visual inspection equipment such as high-definition cameras or industrial cameras are installed at key positions of the production line, such as raw material input ports, processing areas, packaging lines, etc., to ensure full coverage of the production process. The device acquires images at a preset frame rate and transmits the captured image data to a central processing unit for further analysis.

[0037] Step S1432, based on the rice and flour product image data, determine the production status of the rice and flour product, make an abnormal judgment, and record the abnormal event. Specifically, pre-process the collected rice and flour product image data, such as denoising, contrast enhancement, etc., to improve the image quality. Use the trained machine learning model to classify and identify the image, determine whether there are abnormal conditions on the production line, such as product deformation, contamination, missing, etc., and record the identified abnormal events.

[0038] Step S1433, establish a digital twin model of the rice and flour product production line, simulate and optimize according to the abnormal event, and adaptively adjust the resource allocation of multiple rice and flour product production links in the rice and flour product production line. Specifically, according to the actual layout and process flow of the rice and flour product production line, a digital twin model is established using three-dimensional modeling software. This model can reflect the actual operating status of the production line in real time, including the operating status of the equipment, the production progress of the product, etc. The real-time operating parameters and abnormal event data are imported into the model for simulation and analysis. By adjusting the resource allocation plan, the performance changes of the production line in the model are analyzed to find the optimal resource allocation strategy. The optimized resource allocation plan is applied to the actual production line to improve production efficiency and product quality. This implementation method collects image data through visual inspection equipment, can timely discover abnormal situations on the production line, and uses digital twin technology for simulation and optimization, can predict and evaluate the impact of different resource allocation plans on the performance of the production line, so as to find the optimal resource allocation strategy and improve production efficiency and product quality.

[0039] Step S200, collecting the production process parameters, environmental monitoring data, and quality inspection data of the multiple rice and flour product production links through the multiple safety monitoring nodes.

[0040] Specifically, sensors (such as temperature sensors, humidity sensors, pressure sensors, etc.) are used to collect key parameters in the production process in real time, such as temperature, humidity, pressure, time, etc. Environmental monitoring equipment (such as air quality monitors, microbial detectors, etc.) is used to monitor the cleanliness and microbial content of the production environment (such as workshops and warehouses). After the key production links, product quality data is obtained through sampling tests (such as sensory tests, physical and chemical tests, microbial tests, etc.).

[0041] Step S300, using the production process parameters of the multiple rice and flour product production links as the first index item, collecting the first forward traceability set and the first reverse traceability set; Step S400, using the environmental monitoring data of the multiple rice and flour product production links as the second index item, collecting the second forward traceability set and the second reverse traceability set; Step S500, using the quality inspection data of the multiple rice and flour product production links as the third index item, collecting the third forward traceability set and the third reverse traceability set.

[0042] Specifically, based on production process parameters, environmental monitoring data, and quality inspection data, a forward traceability chain from raw materials to finished products is established to record relevant data for each production link. Also based on the above data, a reverse traceability chain from finished products to raw materials is established to quickly locate the source of the problem when it is discovered. Specific operations include data entry, classification, and organization to form a structured data set. Among them, the forward traceability set is used to track the product production process, and the reverse traceability set is used to reversely find the source of the problem.

[0043] Step S600: Establishing a food safety traceability structure by combining the first forward traceability set and the first reverse traceability set, the second forward traceability set and the second reverse traceability set, the third forward traceability set and the third reverse traceability set with the raw material information.

[0044] Specifically, raw material information, production process parameters, environmental monitoring data, quality inspection data and corresponding forward and reverse traceability sets are integrated into a unified food safety traceability system to form a complete traceability structure. Database technology, data association algorithms, etc. are used to accurately associate the various data items.

[0045] Step S700: When a food safety incident occurs, the food safety traceability structure is used to locate the production chain information of the same batch of products and output a traceability report.

[0046] Specifically, when a food safety incident occurs (any incident that affects food safety, such as product contamination, substandard quality, etc.), the food safety traceability structure is used to quickly locate the problem product and its production chain, including the source of raw materials, production links, quality inspection records, etc. According to the positioning results, a detailed traceability report is generated, including the batch of problem products, production time, production links, possible causes and recommended corrective measures, etc. The embodiment of the present application adopts the collection of raw material information, adds multiple safety monitoring nodes to each production link, collects production process parameters, environmental monitoring data and quality inspection data through the safety monitoring nodes, takes the production process parameters as the first index item, constructs the first forward and reverse tracing set, takes the environmental monitoring data as the second index item, constructs the second forward and reverse tracing set, takes the quality inspection data as the third index item, constructs the third forward and reverse tracing set, combines the raw material information and the above-mentioned tracing set, establishes a food safety traceability structure, and when a food safety incident occurs, uses the food safety traceability structure to locate the production chain information of the same batch of products, outputs the tracing report and other technical means, and achieves the technical effect of improving the accuracy and efficiency of food safety traceability.

[0047] In a possible implementation, when a food safety incident occurs, the food safety traceability structure is used to locate the production chain information of the same batch of products, and a traceability report is output. Step S700 further includes step S710, storing the first candidate frequency combination set and the optimal frequency combination, the first candidate precision combination set and the optimal precision combination on the blockchain. Specifically, after determining the optimal frequency combination and the optimal precision combination, these data and their candidate sets are encrypted to ensure data security. Use a blockchain client or API to upload these encrypted data to the blockchain network. The nodes in the blockchain network verify the validity of these data and add them to the distributed ledger of the blockchain. Among them, the blockchain is a distributed database that is composed of a series of data blocks that are chained in chronological order into a specific data structure, and cryptographic methods are used to ensure that the distributed ledger cannot be tampered with or forged. All nodes in the blockchain network jointly maintain an account book, and each node has a complete copy of the account book to ensure data consistency and security.

[0048] Step S720, automatically record and verify the production process parameters, environmental monitoring data, quality inspection data and resource allocation of each rice and flour product production link through the distributed ledger of the blockchain. Specifically, deploy smart devices or sensors that can read and upload data at each safety monitoring node of the rice and flour product production line. These devices or sensors upload the real-time collected data to the blockchain network through the blockchain client or API. The smart contract in the blockchain network automatically verifies the validity of this data, such as checking whether the format and range of the data meet the preset rules. The verified data is added to the distributed ledger of the blockchain for subsequent query and traceability.

[0049] Step S730, based on the distributed ledger, after trust authentication is performed on the production chain information of the same batch of products located by the food safety traceability structure, a traceability report is output. Specifically, when a food safety incident occurs, the production chain information of the same batch of products is located using the food safety traceability structure. Through the distributed ledger of the blockchain, the authenticity and integrity of this information are queried and verified. Due to the immutability of the blockchain, once the information is recorded on the blockchain, it cannot be modified or deleted, thereby ensuring the authenticity and credibility of the information. Based on the verified information, a traceability report is generated and output to record the production chain information, quality inspection data, resource allocation, etc. of the product. This implementation method can view and verify the production data of each rice and flour product production link in real time through the distributed ledger of the blockchain, improve the transparency and traceability of the data, and provide strong support for the tracing and investigation of food safety incidents.

[0050] In the above, refer to Figure 1The food safety traceability method for a rice and flour product production line according to an embodiment of the present invention is described in detail. Figure 2 A food safety traceability platform for a rice and flour product production line according to an embodiment of the present invention is described.

[0051] The food safety traceability platform for a rice and flour product production line according to an embodiment of the present invention is used to solve the technical problems of low traceability efficiency and inaccurate traceability results in the prior art, and achieve the technical effect of improving the accuracy and efficiency of food safety traceability. The food safety traceability platform for a rice and flour product production line includes: a safety monitoring node adding module 10, a production link information collection module 20, a first traceability collection module 30, a second traceability collection module 40, a third traceability collection module 50, a food safety traceability structure establishment module 60, and a traceability module 70.

[0052] The safety monitoring node adding module 10 is used to collect raw material information and add multiple safety monitoring nodes in the rice and flour product production line, wherein the multiple safety monitoring nodes are respectively located in multiple rice and flour product production links, and each rice and flour product production link is configured in a preset operation area; the production link information collection module 20 is used to collect the production process parameters, environmental monitoring data, and quality inspection data of the multiple rice and flour product production links through the multiple safety monitoring nodes; the first traceability collection collection module 30 is used to collect the first forward traceability collection and the first reverse traceability collection with the production process parameters of the multiple rice and flour product production links as the first index item; the second traceability collection collection module 40 is used to collect the production process parameters of the multiple rice and flour product production links as the first index item. The environmental monitoring data of the rice and flour products is used as the second index item to collect the second forward traceability set and the second reverse traceability set; the third traceability set collection module 50 is used to collect the third forward traceability set and the third reverse traceability set by taking the quality inspection data of the multiple rice and flour product production links as the third index item; the food safety traceability structure establishment module 60 is used to establish a food safety traceability structure by combining the first forward traceability set with the first reverse traceability set, the second forward traceability set with the second reverse traceability set, the third forward traceability set with the third reverse traceability set, and the third forward traceability set with the third reverse traceability set, in combination with the raw material information; the traceability module 70 is used to use the food safety traceability structure to locate the production chain information of the same batch of products when a food safety incident occurs, and output a traceability report.

[0053] The specific configuration of the safety monitoring node adding module 10 will be described in detail below. As described above, multiple safety monitoring nodes are respectively located in multiple rice and flour product production links, and each rice and flour product production link is configured in a preset operation area. The safety monitoring node adding module 10 can further include: a monitoring and control target setting unit is used to adopt the safety monitoring task issued by the distributed computing architecture, combined with the storage conditions of the raw material information, to set the monitoring and control target, and the monitoring and control target includes a frequency allocation threshold and a precision allocation threshold; a frequency control network establishment unit is used to establish a frequency control network based on the rice and flour product production line, combined with the frequency allocation threshold in the monitoring and control target; a precision control network establishment unit is used to establish a precision control network based on the rice and flour product production line, combined with the precision allocation threshold in the monitoring and control target; a resource allocation mechanism setting unit is used to set the resource allocation mechanism of the multiple rice and flour product production links based on the frequency control network and the precision control network.

[0054] Among them, based on the frequency control network and the precision control network, a resource allocation mechanism for the multiple rice and flour product production links is set, and the resource allocation mechanism setting unit may further include: a control optimization fully connected layer construction subunit is used to connect the frequency control network as the upper layer and the precision control network as the lower layer to construct a control optimization fully connected layer; a real-time operation parameter acquisition subunit is used to connect the rice and flour product production line to obtain real-time operation parameters, and the real-time operation parameters include the speed of moving parts, the temperature of heating / cooling equipment, and the equipment pressure parameters; a resource balancing configuration subunit is used to balance the resources of multiple rice and flour product production links in the rice and flour product production line based on the control optimization fully connected layer and through the real-time operation parameters to obtain the resource allocation mechanism.

[0055] Among them, based on the rice and flour product production line, combined with the frequency allocation threshold in the monitoring and control target, a frequency control network is established, and the frequency control network establishment unit may further include: a flow tracking parameter acquisition subunit is used to connect to the radio frequency identification module, obtain flow tracking parameters, and determine multiple frequency allocation trigger intervals; a frequency control rule set setting subunit is used to combine and map the multiple frequency allocation trigger intervals with the frequency allocation threshold in the monitoring and control target, and set the frequency control rule set; the optimal frequency combination selection subunit is used to use the frequency control rule set for screening to form a first candidate frequency combination set, select the optimal frequency combination from the first candidate frequency combination set, and determine the node mapping map of the frequency control network.

[0056] Among them, the optimal frequency combination is selected from the first candidate frequency combination set, and the optimal frequency combination selection subunit may further include: a nutrition label extraction component is used to extract the nutrition label through nutrition test data, and the nutrition categories corresponding to the nutrition label include protein content, fat content, and carbohydrate content; a selection component is used to select the optimal frequency combination from the first candidate frequency combination set based on the dynamic change characteristics of the real-time operating parameters and taking the nutrition label as a verification condition.

[0057] Among them, through the real-time operation parameters, the resources of multiple rice and flour product production links in the rice and flour product production line are balancedly configured to obtain the resource allocation mechanism, and the resource balancing configuration subunit may further include: an image acquisition component is used to perform image acquisition on the rice and flour product production line through visual detection equipment to obtain rice and flour product image data; an abnormality judgment component is used to determine the production status of rice and flour products based on the rice and flour product image data, and perform abnormal judgment, and record abnormal events; a resource allocation adjustment component is used to establish a digital twin model of the rice and flour product production line, perform simulation optimization according to the abnormal events, and adaptively adjust the resource allocation of multiple rice and flour product production links in the rice and flour product production line.

[0058] The specific configuration of the traceability module 70 will be described in detail below. As described above, when a food safety incident occurs, the food safety traceability structure is used to locate the production chain information of the same batch of products, and a traceability report is output. The traceability module 70 may further include: a storage unit for storing the first candidate frequency combination set and the optimal frequency combination, the first candidate precision combination set and the optimal precision combination on the blockchain; a record verification unit for automatically recording and verifying the production process parameters, environmental monitoring data, quality inspection data and resource allocation of each rice and flour product production link through the distributed ledger of the blockchain; a traceability report output unit for outputting a traceability report after trust authentication of the production chain information of the same batch of products located by the food safety traceability structure based on the distributed ledger.

[0059] The food safety traceability platform for a rice and flour product production line provided by an embodiment of the present invention can execute the food safety traceability method for a rice and flour product production line provided by any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0060] Although the present application makes various references to certain modules in the platform according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be implemented; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0061] The above specific implementation manner does not constitute a limitation to the protection scope of the present application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the protection scope of the present application. In some cases, the actions or steps recorded in the present application can be performed in an order different from that in the embodiment and can still achieve the desired results. In addition, the process depicted in the accompanying drawings does not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A food safety traceability method for a rice and flour product production line, characterized in that: The method comprises: In a rice and flour product production line, raw material information is collected and multiple safety monitoring nodes are added, wherein the multiple safety monitoring nodes are respectively located in multiple rice and flour product production links, and each rice and flour product production link is configured in a preset operation area; Through the multiple safety monitoring nodes, the production process parameters, environmental monitoring data, and quality inspection data of the multiple rice and flour product production links are collected; Using the production process parameters of the plurality of rice and flour product production links as the first index item, collecting a first forward traceability set and a first reverse traceability set; Using the environmental monitoring data of the multiple rice and flour product production links as the second index item, collecting a second forward traceability set and a second reverse traceability set; Using the quality inspection data of the plurality of rice and flour product production links as the third index item, collecting a third forward traceability set and a third reverse traceability set; By combining the first forward traceability set and the first reverse traceability set, the second forward traceability set and the second reverse traceability set, the third forward traceability set and the third reverse traceability set, and the raw material information, a food safety traceability structure is established; When a food safety incident occurs, the food safety traceability structure is used to locate the production chain information of the same batch of products and output a traceability report.

2. The food safety traceability method for a rice and flour product production line according to claim 1, characterized in that: The plurality of safety monitoring nodes are respectively located in a plurality of rice and flour product production links, each of which is configured in a preset operation area, and the method comprises: Using the safety monitoring tasks issued by the distributed computing architecture, combined with the storage conditions of the raw material information, to set monitoring and control targets, the monitoring and control targets including the frequency allocation threshold and the accuracy allocation threshold; Based on the rice and flour product production line, combined with the frequency allocation threshold in the monitoring and control target, a frequency control network is established; Based on the rice and flour product production line, combined with the precision adjustment threshold in the monitoring and control target, a precision control network is established; Based on the frequency control network and the precision control network, a resource allocation mechanism for the multiple rice and flour product production links is set up.

3. The food safety traceability method for a rice and flour product production line according to claim 2, characterized in that: Based on the frequency control network and the precision control network, a resource allocation mechanism for the multiple rice and flour product production links is set, and the method includes: The frequency control network is used as the upper layer, and the precision control network is used as the lower layer to connect the nodes to construct a control optimization fully connected layer; Connecting to the rice and flour product production line to obtain real-time operating parameters, the real-time operating parameters include moving part speed, heating / cooling device temperature, and device pressure parameters; Based on the regulation and optimization of the fully connected layer, the resources of multiple rice and flour product production links in the rice and flour product production line are balanced and configured through the real-time operation parameters to obtain the resource allocation mechanism.

4. The food safety traceability method for a rice and flour product production line according to claim 3, characterized in that: Based on the rice and flour product production line, combined with the frequency allocation threshold in the monitoring and control target, a frequency control network is established, and the method includes: Connect to the RFID module, obtain flow tracking parameters, and determine multiple frequency allocation trigger intervals; Combine and map the multiple frequency allocation trigger intervals with the frequency allocation thresholds in the monitoring and control target to set a frequency regulation rule set; The frequency control rule set is used for screening to form a first candidate frequency combination set, an optimal frequency combination is selected from the first candidate frequency combination set, and a node mapping graph of the frequency control network is determined.

5. The food safety traceability method for a rice and flour product production line according to claim 4, characterized in that: Selecting an optimal frequency combination from the first candidate frequency combination set, the method comprising: Extracting a nutrition label from the nutrition test data, wherein the nutrition labels correspond to nutrition categories including protein content, fat content, and carbohydrate content; Based on the dynamic change characteristics of the real-time operating parameters and taking the nutritional label as a verification condition, an optimal frequency combination is selected from the first candidate frequency combination set.

6. The food safety traceability method for a rice and flour product production line according to claim 5, characterized in that: By using the real-time operation parameters, the resource allocation mechanism is obtained by balancing the resource allocation of multiple rice and flour product production links in the rice and flour product production line. The method comprises: Using visual inspection equipment, image acquisition is performed on the rice and flour product production line to obtain image data of the rice and flour products; Based on the rice and flour product image data, determine the production status of the rice and flour product, make an abnormality judgment, and record the abnormal event; A digital twin model of the rice and flour product production line is established, simulation optimization is performed according to the abnormal event, and resource allocation of multiple rice and flour product production links in the rice and flour product production line is adaptively adjusted.

7. The food safety traceability method for a rice and flour product production line according to claim 6, characterized in that: When a food safety incident occurs, the food safety traceability structure is used to locate the production chain information of the same batch of products and output a traceability report. The method includes: The first candidate frequency combination set and the optimal frequency combination, the first candidate precision combination set and the optimal precision combination are stored on the blockchain; Through the distributed ledger of blockchain, the production process parameters, environmental monitoring data, quality inspection data and resource allocation of each rice and flour product production link are automatically recorded and verified; Based on the distributed ledger, after trust authentication is performed on the production chain information of the same batch of products located by the food safety traceability structure, a traceability report is output.

8. A food safety traceability platform for rice and flour product production lines, characterized in that: The platform is used to implement the food safety traceability method for a rice and flour product production line according to any one of claims 1 to 7, and the platform comprises: A safety monitoring node adding module is used to collect raw material information and add multiple safety monitoring nodes in a rice and flour product production line, wherein the multiple safety monitoring nodes are respectively located in multiple rice and flour product production links, and each rice and flour product production link is configured in a preset operation area; A production link information collection module, used to collect production process parameters, environmental monitoring data, and quality inspection data of the multiple rice and flour product production links through the multiple safety monitoring nodes; A first traceability set collection module is used to collect a first forward traceability set and a first reverse traceability set by taking the production process parameters of the plurality of rice and flour product production links as the first index item; A second traceability set collection module is used to collect a second forward traceability set and a second reverse traceability set by using the environmental monitoring data of the plurality of rice and flour product production links as a second index item; A third traceability set collection module, configured to collect a third forward traceability set and a third reverse traceability set by using the quality inspection data of the plurality of rice and flour product production links as a third index item; A food safety traceability structure establishment module, used to establish a food safety traceability structure by combining the first forward traceability set and the first reverse traceability set, the second forward traceability set and the second reverse traceability set, the third forward traceability set and the third reverse traceability set, with the raw material information; The traceability module is used to locate the production chain information of the same batch of products using the food safety traceability structure when a food safety incident occurs, and output a traceability report.

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