54results about How to "Accurate traceability" patented technology

The invention provides a robot skill knowledge characterization method based on Granger causality test. The method comprises the following steps: collecting original video stream data in a robot operation process; standard operation steps and sudden abnormal conditions of the robot are coded into a standard operation state and a random event state respectively, stage variables are formed, executable operation after the standard operation or the random event occurs is coded into an executable operation state, and action variables are formed; modeling the sequential relationship between the historical stage variable and the current action variable by using a VAR model to obtain a VAR-based stage-action model; performing Granger causality test on variables in the stage-action model based on the VAR to confirm the causality between the variables; and according to the result of the Granger causal test, constructing a causal relationship network in the robot operation process, and forming a causal rule device. According to the method, the real dependency relationship in the time series data can be deeply mined, and a skill characterization framework based on a causal mechanism is established.

The invention discloses a multi-source heterogeneous data pollution traceability and management system based on end-edge-cloud collaboration. The system comprises a multi-source heterogeneous data acquisition module, a cloud-edge collaboration data management and control module, an environment traceability graph embedded sensing module, an interpretable traceability analysis module, a closed-loop regulation and control decision module and a pollution abatement feedback module. A sensing end multi-dimensional sensor collects various types of data, edge end preprocessing and cloud deep analysis cooperation are carried out, an abnormal sensing algorithm is embedded based on an environment traceability graph, a dynamic pollution source identification mechanism is constructed by an interpretable environment pollution traceability analysis model, and a strategy is adjusted in combination with a data pollution closed-loop regulation and control decision model. And the links of early warning, patrol, traceability, disposal and feedback are covered. According to the system, the robustness and maintainability of a multi-source data system are improved, rapid response, accurate traceability and intelligent closed-loop management of pollution events are realized, the problems of insufficient monitoring data collaboration and poor traceability treatment closed-loop performance are effectively solved, and the fine management requirement of environment monitoring is met.

The intelligent twist lock for the container ship comprises a lock body master control box, an upper lock head driving box and a lower lock head driving box are arranged on the upper portion and the lower portion of the lock body master control box respectively, an upper lock head is arranged on the top of the upper lock head driving box in a sliding mode, and a lower lock head is arranged at the bottom of the lower lock head driving box in a sliding mode; an upper lock head driving assembly is arranged in the upper lock head driving box, and a lower lock head driving assembly is arranged in the lower lock head driving box. A lock body information chip convenient for a ship remote control platform to remotely operate the twist lock is arranged on the front side of the upper lock head driving box; the lock body information chip and the control module are additionally arranged on the twist lock, and the twist lock is in communication connection with the ship remote control platform, so that key data basis and equipment support are provided for intelligent stowage and yard automatic management of the container ship; the driving motor is matched with the precise spiral lifting and rotating mechanism, so that the whole process automation of locking and unlocking of the twist lock is realized, the working efficiency is greatly improved, and the labor intensity is reduced.

The application discloses a multi-source education data attribution analysis system and method based on a large model Function Call, and belongs to the technical field of computers. The system comprises: a multi-source data access module for constructing a unified education data warehouse; an intelligent semantic routing module for identity recognition and intent analysis; a function registration and execution module for triggering atomized analysis functions; and a comprehensive attribution analysis module for generating an attribution report in combination with a knowledge base. The method comprises the following steps: accessing multi-source education data and preprocessing, guiding the large model to identify the intent by using the prompt engineering, outputting a structured instruction to trigger the function call, and finally performing causal reasoning. The application realizes the deep fusion and accurate attribution of multi-source education data, reduces the interaction threshold, and provides a scientific basis for teaching decisions.

The invention belongs to the technical field of flue gas monitoring, and provides a multipoint patrolling method, system and device. The method comprises the following steps of adaptive sampling and preprocessing, distributed full-dimensional self-diagnosis and fault early warning, fault root cause mining and processing, LIBS spectral analysis and 4D pollution diffusion model construction, environment-data dual-drive dynamic calibration mechanism and data fusion and collaborative analysis. According to the method, LIBS spectral analysis and a CFD model are coupled to construct a 4D pollution diffusion model, and an environment-data dual-drive dynamic calibration mechanism is combined, so that accurate simulation and prediction of a pollution diffusion rule are realized; through space fusion and time trend prediction, a scientific basis is provided for pollution source responsibility division and emission reduction decision, adaptive sampling, multi-modal fault diagnosis and dynamic pollution modeling are integrated, closed-loop and environment-data dual-drive dynamic calibration from data acquisition to decision support is achieved, limitation of a traditional static model is broken through, multi-dimensional collaborative decision support is achieved, and the method is suitable for large-scale popularization and application. And a landing emission reduction scheme is provided.

The application provides a release film surface defect detection method and system, relates to the technical field of defect detection, and the method comprises the following steps: through the non-contact multi-physical field information collection on the same detection area of the continuously running functional film to be detected on a film production line, holographic quality field original data are acquired, space-time correlation fusion is performed on corresponding real-time process parameters, the quality field data cube is input into a pre-trained defect diagnosis model, double-channel defect traceability diagnosis and performance attenuation prediction are executed in parallel, and a release film surface defect diagnosis result is generated. The technical problem that the prior art only performs simple detection on the surface defects of the release film, cannot distinguish whether the performance has defects, and leads to the reduction of release film defect detection precision is solved. Through multi-physical field synchronous detection and space-time fusion analysis, accurate defect traceability and performance attenuation prediction are realized, and the technical effects of improving the release film detection precision and performance reliability are achieved.

The invention relates to the technical field of motor vehicle exhaust pollutant analysis and monitoring, and particularly discloses a motor vehicle emission supervision method and system based on remote measurement and OBD fusion, and more accurate motor vehicle emission supervision is realized by combining a road remote measurement technology and OBD data. The method comprises the following steps: firstly, acquiring vehicle passing characteristics, actually measured emission concentration and OBD real-time parameters, and generating a group reference interval to perform credibility evaluation; generating a dynamic self-inspection instruction packet for the suspicious vehicle, triggering the vehicle-mounted terminal to execute a diagnosis excitation script at the target remote measurement point, and collecting excitation response data; generating a deep diagnosis conclusion by analyzing the dynamic response consistency of the tail gas concentration in the excitation period and the excitation response data, updating the credibility score of the vehicle data according to the deep diagnosis conclusion, and generating an emission supervision instruction; according to the invention, data authenticity and law enforcement credibility are improved, and optimal configuration of supervision resources is realized.

The application discloses a kind of time difference risk hedging method and device of insurance fund custody, it is related to financial risk control technical field, the method includes: creating virtual sub-account for each user and being bound with corresponding policy account one by one to realize fund physical isolation;When consumption incentive enters the custody special account, it is frozen to corresponding virtual sub-account by calling bank freezing interface and generates directional payment instruction;When daily business ends, generate custody fund flow sheet snapshot, before batch deduction of insurance company next day, pre-reconciliation is carried out to custody fund flow sheet snapshot and to-be-deducted list, and according to result, unfreezing transfer or difference processing is executed;Risk reserve pool is established simultaneously, when unilateral account is abnormal, first pay, complete account adjustment to realize error recovery after finding out reason and clearing up.The application realizes fund physical isolation by virtual sub-account binding and fund freezing directional transfer, effectively hedges the supervision and operation risk caused by fund circulation time difference, and improves the stability of fund custody.

The invention discloses a railway precast beam full-period digital delivery and disease tracing method and system, and the method comprises the following steps: S1, collecting and sorting precast beam data, and building an IFC entity model based on the data; s2, pre-burying a two-dimensional code plate and an RFID tag on the precast beam, and recording the digital identity of the precast beam; s3, obtaining the completion coordinate of the precast beam, and binding the digital identity of the precast beam with the completion coordinate at one time; s4, performing block chain evidence storage on the application data of the precast beam; s5, developing a front-end APP, and judging whether the precast beam meets a traceability condition or not; s6, all data of the precast beam meeting the traceability condition are called, and root cause judgment is conducted based on the IFC entity model. According to the method, by establishing the IFC standard data link which runs through design-production-operation and maintenance, data barriers of links of design, production and operation and maintenance can be broken through, data run-through is achieved, data islands are avoided, and comparison time consumption is greatly shortened.

The invention discloses an equipment maintenance cost management and control system and method, and relates to the technical field of industrial equipment management. The system comprises an Internet of Things data sensing layer, a maintenance digital twinborn construction module, a multi-dimensional dynamic preventive maintenance cost prediction engine, a cost control and execution layer based on an intelligent contract and a self-adaptive cost allocation and optimization feedback loop. The method comprises the following steps: collecting data in real time and constructing an equipment maintenance digital twinborn body; the prediction engine generates a virtual maintenance unit containing predicted cost based on the twinborn body data; when the risk exceeds a threshold value, a block chain intelligent contract is automatically triggered, and automatic and traceable management and control are carried out on budget, process and payment; after maintenance is completed, cost is automatically shared, and data is fed back to optimize the model. According to the method, the change of the maintenance cost from passive response to active prediction and from post-event recording to whole-process automatic management and control is realized, transparency is ensured through an intelligent contract, a self-optimization closed loop is formed, and the refinement level and cost effectiveness of cost management and control are improved.

The invention relates to the field of session semantic merging, in particular to a session semantic extraction intelligent merging method for audio semantic recognition, which comprises the following steps of: obtaining an audio-metadata binding set with a unique fragment identifier and candidate semantic fragments, obtaining a semantic unit set with a multi-dimensional attribute index, constructing a high-dimensional feature vector space by taking a semantic unit set with a multi-dimensional attribute index and a cross-queue candidate association index as input, obtaining a clustering cluster set, extracting a core semantic topic of each clustering cluster in the clustering cluster set, constructing an intra-cluster semantic unit association graph, and obtaining a core dominant unit; and obtaining a preliminary combined semantic text of the clusters, and obtaining a complete semantic text after the clusters are combined. According to the method, the standardized high-dimensional feature vector space is constructed based on the multi-dimensional features, the core attributes of the semantic units are comprehensively represented, the reasonability and accuracy of cluster division are improved, and meanwhile, accurate tracing of the features and the semantic units is achieved through the feature vector-semantic unit mapping table.

This invention relates to a method and system for accessing the trusted space of inland waterway shipping data under zero-trust conditions. It includes defining the shipping trust status and transformation rules of participating entities, constructing a risk scoring model to calculate the risk score of shipping behavior, introducing federated learning to improve the accuracy of the shipping behavior risk score, constructing a trust calculation function to calculate dynamic trust values ​​in real time, designing hierarchical access decision rules for hierarchical authorization to achieve access control, and submitting the hash value of logs to the blockchain to drive the update of shipping trust status, forming a closed loop of credit update and access control. This invention provides a systematic solution for the Jianghuai inland waterway shipping industry that balances strict security, business efficiency, and compliance requirements, achieving the coordinated evolution and proactive improvement of the security defense capabilities of the entire Jianghuai inland waterway shipping ecosystem.

This utility model relates to the field of casting technology and discloses a device for quickly identifying the flow sequence of a cast billet. The device includes a billet exit section vision system, a flow sequence binding module, and a fixed numbering unit. The billet exit section vision system is installed above the post-cutting conveyor roller (1) and the steel transfer machine (2) to capture the number and position of the cast billet (3) in real time. The flow sequence binding module is configured to associate the number of the cast billet (3) with the flow sequence information through an image processing server and transmit it to the display screen (4) for real-time display. The fixed numbering unit is configured to communicate with the flow sequence binding module and spray numbers onto the cast billet (3) after it has been collected and unloaded according to the binding information. This device for quickly identifying the flow sequence of a cast billet simplifies roller operation, improves work efficiency, realizes the identification of flow sequence information, and makes product traceability more convenient and accurate.

The application relates to the technical field of testing, and discloses a test method for an application system, which comprises the following steps: acquiring a system configuration file, a local application program package and a corresponding local Java bytecode file of a local application system, and determining a target full-amount corresponding relationship of the local application system; acquiring different Java bytecode files of different versions of application program packages, and determining a program difference list; acquiring an outbound configuration file, and combining the target full-amount corresponding relationship and the program difference list to determine a first full-amount test range of the local application system and a plurality of second full-amount test ranges of a plurality of other application systems, and then testing the application system to obtain a target test result of the application system, which realizes bidirectional accurate analysis of a test range of a local program change on itself and other systems and of other system changes on the local system, comprehensively covers transaction interface and business function test requirements among multiple systems in an enterprise, and guarantees the overall operation stability of the application system.

The invention belongs to the technical field of veterinary instruments, and particularly relates to a clinical vaccination auxiliary device and method for veterinarians, the clinical vaccination auxiliary device comprises a vaccination gun and a needle tube mounted at the end of the vaccination gun, the vaccination gun is provided with a bottle seat for placing a vaccine bottle, and the bottle seat is provided with a puncture needle for puncturing the vaccine bottle; the adjusting mechanism comprises a sleeve disc which is fixedly arranged on the vaccination gun in a sleeving manner, and a connecting frame with a sliding plate is fixedly mounted on the sleeve disc; through the design of a connecting frame, a sliding plate, an adjusting plate and an adjusting groove, the length of the needle tube entering the poultry body is controllable, and the length of the needle tube penetrating into the poultry body is rapidly adjusted according to the actual requirements of different poultry. Therefore, the device adapts to the body types, day ages, fat and thin degrees and injection site differences of different poultry, and avoids the situations that vaccines cannot be effectively absorbed and immune fails due to too shallow needle insertion, or internal organs, blood vessels and nerves are damaged due to too deep needle insertion, and stress and tissue damage of the poultry is aggravated.

The invention relates to a pressure system micro-leakage online monitoring method and device, equipment and a storage medium, and the method comprises the steps: obtaining the identity information of a to-be-monitored pressure system, associating the identity information with the monitoring process, and generating a bound monitoring task; performing pressure initialization; acquiring reference state data (reference pressure and reference temperature) of the to-be-measured pressure system and starting monitoring; in the micro-leakage monitoring process, actual state data of the to-be-measured pressure system at the current moment are circularly obtained and recorded at a preset time interval, and the actual state data comprise an actual pressure value and an actual temperature; according to the reference pressure, the reference temperature and the actual temperature, calculating a theoretical pressure value in a leakage-free state at the current moment; comparing the actual pressure value with the theoretical pressure value to obtain a pressure difference, and judging whether the pressure system leaks or not according to the pressure difference to obtain a monitoring result. The method has the effect of improving the accuracy of the micro-leakage monitoring result of the pressure system.

The invention provides a spacecraft general assembly data fusion processing system and method, and the system comprises a dual-core architecture which comprises a general assembly cooperation model module and a knowledge-driven engine module; the hierarchical classification database is connected with the dual-core architecture; the version penetration management module is used for establishing a product version penetration management mechanism based on a preset code; and a rule verification engine for automatically verifying the data based on a preset rule. The method comprises the following steps: carrying out collaborative sharing and intelligent decision making through a dual-core architecture, storing spacecraft general assembly data into a hierarchical classification database for standardized storage, establishing a product version penetration management mechanism, and automatically checking the data based on a preset rule obtained from a knowledge-driven engine module. According to the method, the data normalization and accuracy can be remarkably improved, the full-life-cycle accurate tracing of the data is realized, and the cross-professional collaboration efficiency is improved.

The application discloses a SKU-level delivery decision path mapping method and system based on Shapley value and deep learning, and relates to the technical field of data processing. The method collects multi-channel SKU-level user behavior data and pre-processes the same, quantizes contact contribution values based on an improved Shapley value algorithm and an LSTM modeling, stores the same to an optimization database to support tracing, constructs a visual engine to output a key path, and integrates data to establish quality monitoring, thereby solving the problems that SKU-level data deep analysis, contact contribution accurate attribution and decision path efficient visualization are difficult to realize in the prior art, and having the advantages that SKU-level data deep analysis, contact contribution accurate attribution and decision path efficient tracing and dynamic visualization can be realized, and marketing efficiency and effect are improved.

This invention discloses a method for attributing the spatial heterogeneity of antibiotics in regional water environments based on a GWR-GeoDetector coupled model. The method first acquires antibiotic concentration data from surface water sampling points and constructs a database containing multiple environmental driving factors. Then, it uses a geographically weighted regression model to diagnose spatial nonstationarity, dividing the study area into multiple characteristic zones based on regression coefficients. Next, within each zone, a geodetector is used to quantitatively calculate the explanatory power of each driving factor, identifying the dominant driving factor. Finally, the interaction effects between factors are evaluated, the interaction type is determined, and the core synergistic factors across the entire region are identified. This invention solves the problem that traditional models cannot accurately explain the causes of antibiotic distribution in the water environment, achieving precise spatial zoning and quantitative assessment of pollution source contributions, and providing accurate technical support for refined management of regional water environments.

The present application relates to the technical field of agricultural product origin identification and traceability, and particularly discloses an agricultural product origin identification and traceability system and method based on characteristic fingerprints, which comprises the following steps: collecting agricultural product samples to obtain a target sample set; marking the target sample set with dominant characteristic fingerprints according to the dominant characteristics of the agricultural products, and performing one-class partitioning on the target sample set according to the dominant marking result to obtain a plurality of one-class sample clusters; marking the target sample set with recessive characteristic fingerprints according to the recessive characteristics of the agricultural products, and performing two-class partitioning on the target sample set according to the recessive marking result to obtain a plurality of two-class sample clusters; comparing the one-class partitioning result and the two-class partitioning result to determine whether to start a successive verification mode or a separate verification mode; based on the successive verification mode, obtaining each verification result, and determining whether to output an actual origin traceability result according to the verification results.

The invention discloses a clinical test data evidence storage and tracing method based on a block chain, relates to the technical field of block chain application, and aims to solve the technical problems that traditional clinical test data is easy to tamper, evidence storage is difficult, tracing efficiency is low, and data security and integrity cannot be effectively guaranteed. Comprising the following steps that S1, multi-source data in a clinical test are obtained, and the multi-source data contain remote collection equipment data, subject self-report data and third-party mechanism detection data; s2, carrying out authenticity verification and consistency verification on the multi-source data through an AI model, and generating a verification result; s3, if the verification result is abnormal, triggering early warning and freezing corresponding data; and S4, generating a block chain transaction by using the multi-source data passing the verification and the associated information thereof, and uploading the block chain transaction to a block chain for evidence storage. According to the method, the core problems that the authenticity of the multi-source data in the DCT is difficult to verify and the tracing chain is incomplete are effectively solved, and a credible foundation is laid for clinical test data.

This application provides a vehicle fault diagnosis method and related equipment, belonging to the field of vehicle intelligent diagnosis technology. The method includes: collecting multi-source heterogeneous data from the target vehicle across the entire domain; preprocessing the collected preset multi-source vehicle data to obtain vehicle feature vector data; mapping vehicle risk based on the vehicle feature vector data using a preset multi-dimensional evaluation unit to obtain vehicle risk severity data; predicting fault state classification based on the vehicle risk severity data and the vehicle feature vector data using a preset random weighted neural network diagnostic model to obtain vehicle operating state energy level data; and performing causal logic encoding based on the vehicle operating state energy level data using a preset large language model to obtain abnormal state causal tracing results. This application embodiment can realize real-time fault diagnosis and root cause tracing of vehicles under multi-physics coupling.

This invention provides a management system for WSI pathology reports based on OFD-H. It includes a presentation layer, a business layer, a data storage layer, and a standard interface for interoperability with third-party medical systems. The presentation layer includes an editor for editing OFD reports and a WSI image reader capable of coordinate backtracking of WSI images. The business layer includes: module one for automatically generating pathology image heatmaps and textual diagnostic suggestions; module two for OFD format container encapsulation; module three for three-level streaming image backtracking; and module four for adding digital signatures and watermarks. The data storage layer is used for hierarchical storage of WSI files, ROI images, and OFD documents to meet the retrieval needs of massive multimodal data. This invention can achieve "intelligent assisted generation" of reports, "two-way interoperability" between text and images, "lightweight encapsulation" of data, and "compliant traceability" of documents.

This invention relates to the field of comprehensive utilization technology of lithium battery test data, and discloses a method, system, equipment, and medium for comprehensive calculation of lithium battery test data. In the finished product testing stage, a unique identifier is generated for each battery cell and bound to the test task; raw test data is collected in real time and stored in a strong association with the identifier, forming a record with the individual battery as the primary key; a hierarchical association model is constructed to represent the relationship between finished product packages or modules and individual battery cells; in response to traceability query requests, the set of identifiers of all associated individual batteries is determined according to the model, and the corresponding test data is extracted and comprehensively calculated using these identifiers as keys; the traceability analysis results are visualized and downloaded. This invention solves the problems of lacking an individual-level data association model and being unable to efficiently trace individual battery test data, improving data utilization efficiency and the ability to locate quality problems.

The application discloses a multi-source heterogeneous data correlation retrieval method and system based on a unified identifier, a terminal and a medium, and relates to the technical field of information retrieval.The technical solution points are as follows: the application uses a unique identifier to perform strong correlation mapping between all scattered and heterogeneous physical storage and logical indexes at a logical level, and constructs a unified data view centered on an entity, so that data originally stored in object files, metadata tables, structured records, relationship graphs and retrieval indexes can be stably and accurately correlated and traced.Especially, the two-stage retrieval mode of keyword preliminary screening and graph expansion first efficiently locates a target through a retrieval engine, and then uses graph mining to find the correlation network.The application effectively solves the disadvantage that the existing retrieval scheme cannot perform correlation resource expansion, upgrades data query from single finding to network discovery, and improves the data correlation discovery rate and query completeness in a complex business scenario.

The invention provides an SLCC converter fault detection method based on multi-module cooperation, and belongs to the technical field of power systems, and the method comprises the steps: collecting the electrical parameter data of each module of an SLCC, calculating a coupling parameter, and constructing an incidence matrix; dynamically updating the incidence matrix to obtain an updated incidence matrix; an SLCC topological graph is constructed; on the basis of the incidence relation of the topological graph, node features are updated through an iterative formula, and final target features are obtained; inputting the final target features into a trained linear classifier, and judging the fault type at the node i and at the (t + 1) th moment by the linear classifier; and continuing to obtain the updated incidence matrix along with the time, and judging the fault type at the node i at the next time through the linear classifier. According to the invention, accurate tracing of fault causes of multi-module cooperation is realized, and the problem that only a single fault module can be positioned and cross-module cascading fault causes cannot be identified in the prior art is solved.

This invention relates to the fields of industrial monitoring and VR technology, specifically a method for managing the production of flame-retardant nonwoven fabrics based on VR technology. The method includes: collecting temperature, rotation speed, and tension data streams from the production line and performing multi-scale decomposition; identifying data offset events for each component using adaptive thresholds; and then fusing these data to generate a composite abnormal event descriptor. Based on this descriptor, fault cause chains and equipment relationship networks are retrieved from a production process knowledge graph; a virtual sensing data stream is constructed and compared with processed real data for verification; and a structured report containing fault location and maintenance suggestions is generated accordingly. The report and event descriptor are mapped to a 3D equipment model in the VR monitoring scene. This method achieves accurate tracing and early warning of complex coupled faults in the production process, and significantly improves the intuitiveness of monitoring and decision-making efficiency through immersive 3D visualization.

The invention belongs to the technical field of medical instruments, and discloses a pathological tissue sampling bottle for integral limiting of an embedding box, the pathological tissue sampling bottle comprises a lower cover and an upper cover, the central vertical section of the lower cover is cross-shaped, four side surface limiting ribs are arranged in the lower cover in a rectangular shape, two bottom supporting ribs are symmetrically arranged at the bottom in the lower cover, and the upper cover is provided with a lower cover. The two bottom supporting ribs are located in a surrounding range of the four side surface limiting ribs, and the bottom supporting ribs are matched with the side surface limiting ribs to place an embedding box together; after the lower cover and the upper cover are matched, the top of the embedding box is in contact with the inner top surface of the upper cover; the device is reliable in limiting, capable of tracing information, capable of guaranteeing sample quality and accurate management, optimizing operation and reagent efficiency, reducing medical care burden and sample loss, capable of strengthening sealing and pollution prevention, durable, economical and capable of meeting the long-term requirement of a laboratory.

This invention discloses an automatic counting method and system for the number of furnaces using ladle agitators. The method includes collecting ladle agitator usage signals, desulfurization station operation signals, and molten iron furnace number signals to determine and generate a valid agitator usage event; dynamically binding the valid agitator usage event with the current desulfurization station agitator configuration information; receiving the molten iron furnace number signal and identifying whether the current molten iron is ladle-fired; if it is ladle-fired, assigning it a unique ladle furnace number; automatically generating and storing a detailed agitator usage record based on the binding of agitator configuration information and the furnace number identification and processing; automatically counting, summarizing, and generating a statistical report of key indicators regarding the agitator usage of each desulfurization station; and designing a system to implement the above method. This invention can replace manual summarization, saving labor costs; calculates refractory material costs based on the actual number of furnaces used, achieving accurate cost accounting; and fully records special production situations, supporting process optimization.

The application provides a product identification tracking management method and system based on a two-dimensional code, and a storage medium. The method comprises the following steps: generating a two-dimensional code based on product information of a product to be processed; conveying a carrier to a processing equipment according to a production process node for product processing; updating initial information of the two-dimensional code based on a first processing result of the production process node and a second processing result of the processing equipment to obtain first target information; updating the first target information based on a first processing user preset by the production process node and a second processing user operating the processing equipment for product processing to obtain second target information; after the processing is completed, generating a product tracking management tree of the carrier based on the second target information, encrypting the product tracking management tree, and uploading the product tracking management tree to a block chain platform; and if the product to be processed is abnormal, scanning the two-dimensional code based on a two-dimensional code device, and tracking a corresponding processing user based on the product tracking management tree of the two-dimensional code. The application improves the efficiency and accuracy of responsibility tracing.