470results about How to "Improve normative" patented technology

The invention provides an enhanced document generation and retrieval method based on a knowledge graph, and relates to the technical field of knowledge graphs, and the method comprises the following steps: receiving heterogeneous document input, and carrying out dynamic segmentation on the heterogeneous document; constructing a Graph-RAG model, wherein the Graph-RAG model comprises a knowledge graph-document index extraction module and a design document generation module; constructing and updating a knowledge graph based on document segmentation through a knowledge graph-document index extraction module; extracting feature vectors of the document segments by using a feature extraction model, establishing a mapping relationship between the document segments and entities in the knowledge graph through a matching strategy, and constructing a retrieval index; and receiving a query sequence of a user, retrieving the related entities and document segments through the retrieval index, and generating a target design document in combination with a preset template. According to the method, accurate retrieval and high-quality document generation based on semantic understanding are realized, and the technical problems of insufficient semantic understanding, low knowledge association degree, poor generation quality and the like in a traditional document processing method can be solved.

The invention discloses a medical record quality management system and method, and relates to the technical field of medical information processing, and the method comprises the steps: collecting medical record data, and carrying out the preprocessing of the collected medical record data; analyzing the preprocessed medical record data by adopting an NLP, and extracting a medical record core field through an NER; constructing a dynamic medical knowledge graph, and matching the dynamic medical knowledge graph with the medical record core field; after matching is completed, a graph reasoning algorithm is used for conducting logic consistency verification on the medical record, logic contradiction points are marked, and a verification result is generated; and generating a medical record quality auditing report according to the verification result. According to the method, the dynamic medical knowledge graph is constructed and matched with the core field of the medical record, and the graph reasoning algorithm is adopted to perform logic consistency verification on the medical record, so that the intelligence and precision of medical record quality management are realized.

The invention relates to the technical field of law enforcement intelligent alarm, in particular to a multi-mode intelligent analysis method and system based on law enforcement supervision. The method comprises the following steps: acquiring a law enforcement scene video file from a law enforcement supervision recorder platform, and performing audio and video segmentation and law enforcement behavior information identification analysis to obtain law enforcement scene audio behavior information data and law enforcement scene image behavior information data; performing timestamp and spatial position extraction processing on the law enforcement scene video file, performing multi-modal time-space synchronization association analysis, and performing law enforcement behavior sequence connection processing and event behavior intention recognition analysis at the same time to obtain law enforcement scene event behavior intention information data; and obtaining a preset law enforcement event behavior knowledge graph, and carrying out behavior normative score calculation and nonstandard behavior intelligent alarm optimization analysis to generate a law enforcement scene event nonstandard behavior optimization suggestion report. According to the invention, the accuracy of law enforcement nonstandard behavior supervision alarm can be improved.

The invention discloses a visual network freight platform transportation transaction management system. The system comprises an order management module, a vehicle scheduling module, a transportation monitoring module, a transaction settlement module and a visual display module. Each module has innovative functions, such as order intelligent classification, vehicle optimization scheduling algorithm to minimize comprehensive cost, real-time monitoring and accurate settlement. The corresponding management method adopts advanced technologies to ensure efficient operation of each link, including block chain recording, intelligent contract settlement and the like. The whole system realizes efficient management, real-time monitoring and convenient visualization of transportation transaction of a freight platform, and improves the efficiency and quality of logistics transportation; according to the visual network freight platform management system, efficient and accurate order management is realized, vehicle scheduling is optimized, the cost is reduced, comprehensive and real-time transportation monitoring is guaranteed to be safe, safe and accurate transaction settlement is realized, convenient and visual display is convenient to make decisions, and the logistics transportation efficiency, quality and user experience are improved.

The invention provides a semiconductor equipment data acquisition method and a semiconductor equipment data acquisition system supporting standardized communication transformation, which are used for realizing data acquisition and process control on different types of semiconductor equipment, formulating corresponding communication rules for equipment conforming to a communication standard, and converting an equipment communication protocol by a cluster system so as to match a standard interface. For equipment which does not completely meet the standard but can realize communication through programming, the trunking system directly acquires required data and converts the required data to meet the standard interface specification. For equipment without communication capability, data is acquired through an equipment interface by adopting an image recognition technology, data input and function operation are realized through simulating keyboard and mouse operation, and finally, protocol conversion from data to a standard interface is completed by a cluster equipment control system. And the equipment data is converted into a message data packet conforming to a standard semiconductor equipment communication interface, so that docking with a semiconductor equipment data analysis and process control system is realized, and the production efficiency and quality of the semiconductor equipment are improved.

The invention discloses an electric power engineering defect diagnosis method based on AI image recognition and a block chain technology, and relates to the technical field of electric power engineering defect diagnosis, and the method comprises the following steps: setting the initial flight rate of an unmanned plane according to the monitoring demands and field conditions of an electric power line, it is ensured that the unmanned aerial vehicle can cover all key areas of the power line in the inspection process, and meanwhile the inspection efficiency is kept. According to the invention, by intelligently adjusting the flight rate of the unmanned aerial vehicle, the unmanned aerial vehicle can stay in a potential abnormal area for a longer time, and detailed acquisition of temperature data is ensured, so that tiny temperature changes, especially tiny temperature anomalies caused by electric arcs and electrical overload, can be captured more accurately. According to the intelligent adjusting mechanism, in the inspection process, the inspection efficiency of the whole process can be guaranteed, accurate monitoring of the key area can be guaranteed, and the risk of detail loss or temperature anomaly missing detection caused by the too high flight speed is reduced.

The invention, which relates to the technical field of nursing quality monitoring, discloses a nursing quality monitoring and feedback system comprising a data acquisition monitoring module, a nursing index extraction module, a nursing quality evaluation module, an intelligent analysis early warning module, a nursing quality feedback module and a nursing process optimization module. Wherein the modules are connected through electric signals. According to the nursing quality monitoring and feedback system, through real-time collection and analysis of physiological data of a patient, operation records of nursing personnel and feedback suggestions of the patient and family members, potential problems and risks in the nursing process are found, improvement suggestions are generated, the nursing personnel are guided to adjust a nursing plan, the operation process is optimized, and therefore the nursing quality is remarkably improved; and operation of nursing personnel can be monitored and fed back in real time, improper behaviors can be found and corrected, and standardization and accuracy of nursing operation are improved.

The invention discloses an encrypted traffic detection method based on LLM enhanced semi-supervised learning. The method comprises the following steps: firstly, training a traffic detection model for detecting encrypted traffic under an LESS framework; and detecting the encrypted traffic by using the trained traffic detection model. Components of the LESS framework include a Prompt orchestrator, an NSSN, and an LLM optimizer. The components work cooperatively, a detection model is trained by using a labeled training set and a label-free training set, and each piece of data in a data set is formed by arranging length values of data packets in a network flow in sequence; the Prompt composer guides the LLM to generate label-free enhanced data in different scenes; the NSSN automatically sets a pseudo label for the enhanced label-free traffic data, and learns traffic detection knowledge accordingly; under the guidance of the SSL loss, the LLM optimizer adjusts the enhancement strategy of the LLM to align the semi-supervised training requirements of the detection model. The training steps of the detection model include LLM pre-fine tuning; marking the LLM enhanced data; and continuous demand alignment can be realized.

The invention relates to the technical field of circuit board assembly, and discloses an automatic circuit board feeding device and method.The automatic circuit board feeding device comprises a machining platform, a feeding mechanism is installed at the bottom of the machining platform and used for controlling a plurality of supporting plates to vertically move, a material suction arm is slidably connected to the rear side of the top of the machining platform, and a mounting mold is arranged on the left side of the machining platform; a deviation rectifying mechanism is arranged in the material suction arm, a material suction plate is installed at the bottom of the material suction arm, a detection lamp is installed in the middle of the machining platform and used for visually detecting a circuit board, and a recycling mechanism is arranged on the side, close to the material suction arm, of the rear end of the machining platform. Related gears, threaded rods and other parts are driven by the motor, accurate positioning and efficient conveying of the tray are achieved, the material suction arm can automatically suck circuit boards, all the parts are in close cooperation, the automation degree is high, manual operation links are greatly reduced, and the feeding time is effectively shortened.

The invention relates to the technical field of storage tank safety monitoring, in particular to a visual real-time monitoring method and system for a digital floating disc of a storage tank. The method comprises the following steps: carrying out real-time floating disc signal acquisition on a full liquid receiving floating disc to obtain real-time floating disc sensing signal data, and carrying out data filtering preprocessing on the real-time floating disc sensing signal data to obtain floating disc sensing signal data; performing Kalman filtering data fusion on the floating disc sensing signal data to obtain real-time floating disc sensing fusion data; performing floating disc abnormal state detection on the real-time floating disc sensing fusion data to obtain floating disc abnormal detection data; floating disc early warning information integration is carried out according to the floating disc anomaly detection data, so that an abnormal floating disc alarm strategy is obtained; data of the full-liquid-receiving floating disc auxiliary mechanism is obtained, prevention and control strategy analysis is carried out, an abnormal floating disc prevention and control strategy is obtained, and the abnormal floating disc prevention and control strategy is uploaded to a controller to execute a floating disc prevention and control task. The safety of the storage tank can be improved.

The embodiment of the invention discloses a dangerous chemical identification method, and the method comprises the steps: obtaining chemical information data, and constructing a dangerous chemical semantic database according to the chemical information data through employing a deep learning multi-modal data fusion algorithm; according to naming rules and attributes of chemicals, defining text variables and numerical variables, extracting hazardous chemical judgment conditions from the chemical information data, and establishing a hazardous chemical rule base according to the text variables, the numerical variables and the hazardous chemical judgment conditions; according to the chemical information data, establishing a hazardous chemical data model based on a graph neural network technology; constructing a hazardous chemical substance identification system by using the hazardous chemical substance semantic library, the hazardous chemical substance rule library and the hazardous chemical substance data model; and obtaining to-be-classified chemical information, and classifying to-be-classified chemicals in the to-be-classified chemical information by using a hazardous chemical identification system to obtain a hazardous chemical judgment result. According to the invention, more intelligent and accurate dangerous chemical identification is realized.

The invention relates to a multi-service system interface integration and dynamic host automatic management method and system, and belongs to the technical field of informatization integration, and the method comprises the steps: obtaining the interface feature information of a plurality of service systems, and carrying out the feature extraction, and obtaining a preliminary interface feature set; performing logic tagging on the same type of fields, generating a unified interface semantic model, defining a data processing logic rule, and storing the data processing logic rule in a logic strategy rule base in combination with a business strategy logic rule; acquiring host node information in the enterprise infrastructure resources; obtaining a host resource mapping table based on the logic strategy rule base; generating a dynamic routing strategy and constructing a dynamic routing table; receiving an external service request in real time, obtaining an interface name, searching a dynamic routing strategy in the dynamic routing table, and selecting a target host node; and performing data processing on the data stream of the external service request and routing the data stream to the target host node. The resource utilization rate of the multi-service system can be improved, and high availability can be guaranteed.

The invention discloses an automatic auditing system and method for road engineering completion settlement. The system comprises a data acquisition and integration module; a data preprocessing module; a settlement index construction module; an intelligent auditing engine; an abnormity early warning and tracing module; a settlement result management module; and a data analysis and optimization module. The auditing method comprises the following steps: S1, collecting and integrating multi-source settlement data; s2, big data preprocessing; s3, constructing a settlement auditing index system; s4, performing intelligent automatic auditing; s5, performing abnormal early warning and tracing; s6, managing settlement results; and S7, performing big data driving optimization. According to the invention, multi-source data intelligent integration, full-process automatic auditing, abnormal accurate tracing and dynamically optimized big data driven settlement auditing can be realized; the method is applied to whole-process management of road engineering completion settlement, and data-driven intelligent auditing and continuous optimization control are realized in the process.

The invention discloses a method for rapidly detecting the content of a residual flocculating agent in washing machine-made sand, which comprises the following steps of: screening out particles with the particle size of more than 4.75 mm from machine-made sand to be detected, respectively testing the critical water contents of degraded and untreated machine-made sand samples, and determining the mass concentration range of the flocculating agent on the basis of the difference value of the critical water contents of the two kinds of machine-made sand. Compared with tests through neat paste, mortar and concrete systems, deviation possibly caused by introduction of other materials is avoided, and the method is more convenient, faster and more accurate. A'critical water absorption 'test method is provided according to the stability of the stacking state of sand, a transparent circular truncated cone test mold with scales is designed, the filling height and the tamping method of each layer of sample are accurately stipulated, and the test normalization and the test result repeatability of different time, different places and different operators are improved.

The invention provides an integral box bottom mirror image milling program generation method and system. The integral box bottom mirror image milling program generation method comprises the steps of 1, compiling a profile scanning path according to pattern / model input; step 2, compiling a profile scanning path; 3, generating a profile scanning numerical control program; 4, obtaining an actual programming entity; step 5, extracting processing features; step 6, dividing a rough machining area; 7, planning an initial rough machining path; 8, a finish machining area is divided; step 9, planning an initial finish machining path; step 10, generating a milling processing path; and step 11, generating a machining numerical control program. According to the integral box bottom mirror image milling program generation method, the integral box bottom mirror image milling tool path generation steps and method are stipulated, the normalization of integral box bottom mirror image milling program generation is improved, and the machining efficiency and quality of an integral box bottom are further improved; and the bearing capacity and reliability of the carrier rocket are met.

The invention belongs to the technical field of knowledge graph construction, and particularly relates to a multi-source heterogeneous data fusion and knowledge graph automatic construction system, which comprises a semantic extraction module for extracting minimum semantic fragments from multi-source data and performing cross-source alignment to generate a symbolized semantic framework; the data purification module converts multi-source data into symbolic predicates according to the framework, filters low-evidence data and outputs a purification set; the ternary generation module inputs the initial triad candidate set into a minimum rule grammar, and extracts entities, relationships and attributes to generate an initial triad candidate set; the disambiguation calibration module generates entity two-hop topological fingerprints based on the candidate set, completes disambiguation alignment and corrects conflicts, and outputs unambiguous structured knowledge; the mapping fusion module fuses the mapping information with the minimum connected ontology, and constructs and verifies an initial mapping knowledge domain; and the incremental updating module processes newly added data, performs incremental merging and maintains consistency, and forms a complete knowledge graph. According to the method, through full-link automatic construction, efficient fusion and high-quality atlas are realized.

The invention relates to the technical field of data processing, and discloses a BIM model storage system and method based on lightweight data, and the system comprises a tree segment management module which is used for constructing a tree segment structure, and taking each segment as a storage unit; the segment multiplexing creating module is used for creating multiplexing segments in the tree-shaped segment structure, realizing data multiplexing in a reference mode, and creating style segments for centralized management of drawing attribute information; the parallel rendering module is used for rendering the model primitives by adopting a parallel computing method based on the geometric information and the attribute information in the multiplexing segments; the lightweight data generation module is used for organizing the BIM model data according to a tree-shaped segmentation structure and generating a binary data file; and the data compression module is used for compressing the binary data file to generate a compressed format storage file. The technical problem that efficient storage, transmission and application requirements of the BIM model are difficult to meet in the prior art is solved.

The invention discloses an adrenal vein blood sampling auxiliary system based on three-dimensional reconstruction. The system comprises an image acquisition module used for acquiring medical image data of an adrenal gland and a surrounding human organ tissue structure; the image preprocessing module carries out preprocessing operation on the acquired image data; the contour recognition module recognizes contours of adrenal gland, blood vessels and peripheral human organ tissue structures from the preprocessed image; the three-dimensional reconstruction module constructs a three-dimensional model of the adrenal vein and the peripheral human organ tissue structure according to the contour information; the model correction module is used for correcting and perfecting the three-dimensional model; the rendering module carries out rendering processing on the corrected three-dimensional model so as to enhance the visualization effect; and the positioning auxiliary module provides positioning auxiliary information for adrenal vein blood sampling operation. The system can effectively cope with the complex condition of a blood vessel loop, improves the three-dimensional reconstruction precision, provides accurate guidance for adrenal vein blood sampling, and assists in clinical decision making.

The invention provides an address data management method based on deep learning, and belongs to the technical field of address data management. The method comprises address identification based on deep learning and address intelligent reasoning based on an address tree model, and the address identification based on deep learning comprises the following steps: step 1, constructing an address hierarchical system; step 2, constructing an address semantic resource library; 3, constructing an address word segmentation training sample; 4, training an address identification model; step 5, identifying an address by using the model; the intelligent address reasoning based on the address tree model comprises the following steps: step A, constructing an address transfer matrix; step B, constructing a standard address tree; and step C, complementing the address name, associating the address level and complementing the missing address. According to the address data management method based on deep learning, the accuracy and the normalization of address management are improved, the data quality of client addresses is improved, and the working efficiency is improved.

The invention relates to the technical field of flood prediction, in particular to a non-consistent regional flood frequency analysis method based on the Bayesian theory. The method comprises the following steps: acquiring flood sequence data, meteorological data and drainage basin characteristic data of hydrological stations in a drainage basin; performing regional flood dynamic change analysis on the flood sequence data and the meteorological data to generate regional flood time sequence dynamic change data; on the basis of the regional flood time sequence dynamic change data, hydrological station flood characteristic parameters in the drainage basin are extracted from the drainage basin characteristic data, and hydrological station flood characteristic parameters in the region are obtained; and performing flood distribution parameter regression coefficient prior information derivation on the flood characteristic parameters of the hydrological stations in the region to obtain a maximum likelihood estimation value of a single hydrological station distribution parameter. According to the method, the Bayesian theory, the spatial correlation analysis and the spectral analysis are introduced, so that the accuracy and the applicability of flood frequency analysis based on the Bayesian theory are improved.

The invention discloses a digital twin model evolution method and system based on constructional engineering. The invention relates to the technical field of constructional engineering. Related data of the long-distance water conveyance project are collected, wherein the related data comprise BIM model data, oblique photography three-dimensional model data and GIS data; meanwhile, the data are preprocessed, including format conversion, coordinate unification and denoising, so that the quality and consistency of the data are ensured. A three-dimensional BIM model of the engineering facility is constructed based on Autodesk Revit according to a design drawing and collected data, the facility and equipment in the BIM model are coded according to a KKS coding rule, and a coding database is updated; according to the method, the BIM model data, the oblique photography three-dimensional model data, the GIS data and other multi-source data are fused, a refined three-dimensional scene model is constructed, and comprehensive integration of engineering facility information is achieved. Therefore, data sharing and collaboration among different departments and professions are facilitated, and the overall working efficiency is improved.

The invention relates to the technical field of data processing, and discloses a big data-based intelligent configuration method and system for an electricity consumption information acquisition terminal. The method comprises the steps that an acquisition task management scheme and a parameter configuration template are analyzed and matched through an acquisition mode recognition algorithm, and a terminal configuration strategy and a terminal acquisition task file are obtained; performing block coding and encryption processing on the terminal configuration strategy and the terminal acquisition task file according to an acquisition task structure to obtain a configuration operation sequence and an acquisition operation state; and performing multi-dimensional analysis on the configuration operation sequence and the acquisition operation state according to a scoring standard of the electric energy acquisition feature library to obtain a terminal configuration health degree index and an acquisition execution record. According to the method, the terminal function parameters are flexibly adjusted in a file configuration mode without modifying terminal program codes, and meanwhile, the safety and reliability of the configuration process are ensured, so that the influence of frequent software upgrading on the system stability is avoided.

The embodiment of the invention provides an LLM-based security report generation method, electronic equipment and a storage medium, and relates to the technical field of large language models. The method comprises the steps that a task library and a tool library are constructed, and after a generation request of a safety report is received, a corresponding task template is matched from the task library according to the generation request; executing the steps in the task template to obtain a corresponding execution result, and if a certain step includes calling the tool in the tool library, constructing a prompt to submit an operation result returned by calling the tool to the big data model to obtain a corresponding description as the execution result of the step; and after all the steps in the task template are executed, constructing a prompt to provide all the obtained execution results to the large language model, and generating a safety report. According to the embodiment provided by the invention, the safety report generation efficiency and standardization are improved.

The invention relates to the technical field of visual health management, in particular to a ciliary muscle adjustment training system and method based on eye movement tracking, and the method comprises the steps: collecting eye movement data of a fixation point track, an adjustment amplitude change rate and pupil response time in real time, and combining personalized parameters such as the age of a user, diopter and a training target; inputting a ciliary muscle training dynamic planning algorithm module, dynamically generating a stage scheme containing a training action type, a single-group duration, a stimulation interval and a focal length adjustment strategy, and adaptively adjusting the strategy according to real-time adjustment stability and a historical ability curve; through multi-dimensional matching analysis of a pre-stored standard eye movement template, a training specification score is calculated from the track goodness of fit, speed uniformity, amplitude standard-reaching rate and binocular coordination, visual fatigue parameters are obtained based on continuous training duration, pupil fluctuation and retina reflex change, a scoring result is dynamically corrected, and a visual fatigue evaluation result is obtained. Personalized, self-adaptive and quantitative safety control of the training process is realized.

The invention provides a method for predicting and continuously monitoring electric power marketing risks. The method comprises the following steps: acquiring a business process with the maximum risk event occurrence probability; in the prior risk early warning stage, risk early warning evaluation is carried out on the acquired business process; in the in-event risk control stage, modeling is carried out on the obtained business process to obtain a directed graph model used for representing a circulation relationship among a plurality of process nodes, and further according to a risk checking algorithm, the process nodes with risk scores greater than a preset threshold value are determined and strategy optimization is carried out; and in the post risk processing stage, continuously monitoring the risk scores of all the process nodes after strategy optimization, and automatically triggering the emergency strategy for correction after monitoring that at least one risk score of a certain process node is still greater than a preset threshold value. By implementing the method and the system, various risk events of the power marketing business network can be covered in an all-around manner in three stages, i.e., before, during and after, so that the risk response capability and the business robustness of an enterprise are improved.

The embodiment of the invention provides a modeling method and device for an airborne system function architecture model, computer equipment and a medium, and relates to the technical field of aviation architecture design, the method comprises the following steps: inputting a design requirement document into an airborne large language model, and in the large language model, under the structural constraint of an airborne system knowledge graph, establishing a design requirement document; the method comprises the following steps: extracting a logical relationship between entities required by airborne system modeling from a design demand document, screening a corresponding airborne meta-model according to the extracted logical relationship between the entities, and constructing a demand graph; constructing and outputting a text model of a concept scene, a text model of a task scene, a text model of a system function, a text model of a logic architecture and a text model of a physical architecture of the airborne system based on the demand graph; and inputting each text model into a system modeling language modeling terminal for visualization to obtain a multi-level functional architecture model of the airborne system. According to the scheme, the modeling efficiency, consistency and normalization are improved.

The present application proposes a standard-based data asset governance method, including extracting link descriptions and link IDs of a data governance process; accessing a standard library that the data asset process depends on to obtain standard file descriptions and standard file IDs that constrain the data governance process; performing attention analysis on link descriptions and standard file representations to obtain a standard compliance matching graph; constructing a standard metadata model based on the standard compliance matching graph, and encoding the standard metadata model to obtain a standard mapping table to construct a standard data governance rule engine; assigning roles to a data-based governance organizational structure, and establishing a workflow control model between the assigned roles and link descriptions; establishing an object collaborative mapping framework between the workflow control model and the standard data governance rule engine to perform standard data asset governance tasks based on the object collaborative mapping framework.

The invention belongs to the technical field of plant monitoring, and particularly relates to a nondestructive monitoring method and system for judging the healing state of a muskmelon grafted seedling by using a wearable sensor, and the method comprises the steps: preparing a pumpkin rootstock and a muskmelon scion for grafting; grafting when the first true leaf of the pumpkin rootstock is completely flattened and the first true leaf of the scion is half-expanded; a sensor is attached to the cotyledon of the scion to continuously detect the growth state of the grafted seedling; impedance signals of the sensor are measured through an instrument, and an impedance change curve 10 days after grafting is drawn to evaluate the grafting healing state. According to the method, the physiological activity state of the grafted seedling can be directly monitored, so that whether the healing state is good or not can be judged in advance.

The invention provides a digital evaluation method and device for shadowboxing training actions, and belongs to the field of image recognition, and the method comprises the steps: extracting time sequence-based 2D skeleton node data of a plurality of preset skeleton nodes in a to-be-evaluated shadowboxing image; performing depth expansion on the 2D skeleton node data to obtain a 3D skeleton node matrix; according to the 3D skeleton node matrix, determining space geometric features and time motion features of preset skeleton nodes; classifying the spatial geometric features and the time motion features through RF to obtain a classification result of each action; and based on the action classification result, determining a deviation degree between each action and a preset standard action, and determining an evaluation result of the to-be-evaluated shadowboxing image according to the deviation degree. In this way, the Tai Chi actions are evaluated by extracting the action data of the key skeleton nodes, the evaluation result of the Tai Chi actions can be quantified, the accuracy and reliability of evaluation are improved, and a scientific basis is provided for teaching and training of Tai Chi.

The invention discloses an equipment maintenance management system based on RFID. The system comprises an RFID tag, an RFID reader-writer, a tool management terminal, a maintenance personnel management terminal, an equipment management terminal and a central database. According to the system, identification and tracking of equipment, tools and maintenance personnel are achieved through the RFID technology, management and control of the equipment maintenance process are achieved through the tool management terminal, the maintenance personnel management terminal and the equipment management terminal, and storage and analysis of equipment maintenance data are achieved through the central database. The system can improve the efficiency and quality of equipment maintenance, reduce the cost and risk of equipment maintenance, and guarantee the safety and reliability of equipment.