717 results about "Safety management systems" patented technology

The invention relates to the technical field of unmanned aerial vehicles, in particular to a mooring unmanned aerial vehicle safety management system which comprises a multi-source data acquisition module, a data fusion and analysis module, an intelligent risk assessment module, a control instruction generation module and an execution mechanism module. The multi-source data acquisition module acquires flight and mooring cable data of the unmanned aerial vehicle by using various sensors, and transmits the flight and mooring cable data to the data fusion and analysis module through a time division multiple access protocol with low packet loss rate and low delay; the intelligent risk assessment module judges a risk level by combining a risk assessment model based on a support vector machine and a Bayesian network algorithm according to the information, and generates prompt information if the risk level exceeds a preset range; the control instruction generation module generates instructions according to a risk prompt and a preset strategy, ranks the instructions and sends the instructions to the execution mechanism module; a flight control system in the execution mechanism module cooperates with a mooring cable electric take-up and pay-off device and the like, real-time adjustment and control over the flight attitude of the unmanned aerial vehicle and the cable state are achieved, and it is ensured that tasks are safely and stably executed in the complex environment.

Methods, systems, and computer storage media for providing security posture management using an artificial intelligence security engine in a security management system. Security posture management supports security management of a computing environment based on contextual information associated with artificial-intelligence-supported applications. The security management system provides an artificial intelligence security graph associated with the artificial-intelligence-supported applications. The artificial intelligence engine uses the artificial intelligence security graph to correlate artificial intelligence attack monitoring data with operational data of the artificial-intelligence-supported applications. In operation, artificial intelligence attack monitoring data is accessed. An artificial intelligence security graph associated with a plurality of artificial-intelligence-supported applications is accessed. Based on the artificial intelligence attack monitoring data and the artificial intelligence security graph, operational data of an artificial-intelligence-supported application is accessed. The artificial intelligence attack monitoring data and the operational data are analyzed to identify an artificial intelligence security alert. The artificial intelligence security alert is communicated.

The present invention relates to the technical field of highway maintenance management, and in particular to a highway maintenance safety management system. The system includes a road condition monitoring module, a traffic load assessment module, a traffic flow redistribution module, a maintenance timing determination module, and a maintenance effect verification module, which are used to monitor multi-layer road condition data of the highway, and perform table-deep correlation detection to obtain road surface abnormal point data; quantify the road surface loss risk of the road surface abnormal point data to obtain road surface loss early warning indicators; collect vehicle images and meteorological data; analyze vehicle model loss contribution based on vehicle images; construct an environmental impact coefficient matrix based on meteorological data; construct a dynamic weight model based on vehicle model loss contribution and environmental impact coefficient matrix to obtain a road surface loss dynamic weight model. The present invention improves the efficiency, benefit and intelligence level of highway maintenance management by organically integrating highway maintenance with traffic management.

The invention relates to the technical field of data security management, and discloses a blockchain-based forestry data security management system and method, and the system comprises a data collection unit which is used for comprehensively obtaining a multi-dimensional information flow of forest ecology and resource states; the data processing unit is used for carrying out deep cleaning, standardized regulation and feature value extraction on the originally collected mass heterogeneous data; the block chain storage unit is used for constructing a permanent, tamper-proof and distributed secure storage infrastructure platform of the forestry core data; a verification unit; the safety control unit is used for constructing a covering data transmission, storage and access full-chain depth defense system structure model; a user interface unit; an auditing unit; and a network communication unit. The method is reasonable in design, and the intelligent analysis module is used for processing to form a forest interannual growth trend prediction function distribution map state visual output result set.

The invention discloses a petrochemical equipment fault prediction and safety management system and method, and belongs to petrochemical equipment management. The system comprises the following modules: a working condition sensing and classifying module for realizing real-time identification, classification and feature extraction of the equipment operation state; the health state evaluation module is used for calculating equipment health indexes and outputting an equipment performance degradation trend analysis result; the fault prediction and diagnosis module is used for predicting potential fault types and occurrence time, performing diagnosis analysis on fault mechanisms and providing credibility evaluation of diagnosis results; the risk assessment and early warning module comprehensively assesses multi-dimensional risk factors and generates graded early warning information through dynamic threshold optimization and a multi-stage early warning strategy; the maintenance decision support module is used for optimizing a maintenance strategy and providing resource scheduling and maintenance scheme suggestions based on the equipment health state, the fault prediction and the risk assessment result; and the management and optimization module ensures efficient cooperative operation of each module and continuously improves the system performance.

The invention relates to a hydropower station safety comprehensive management system based on a digital twinborn scene, which designs a hydropower station data resource coding system, establishes a hydropower engineering digital twinborn base, integrates all related geospatial data, basic data, monitoring data and business management data of a hydropower station, and constructs the hydropower station digital twinborn scene. Predicting displacement and deformation conditions of a building structure of the hydropower station and a change trend of important facility and equipment state indexes of the hydropower station, and predicting and pre-judging safety risks therein; the reservoir flow of the hydropower station, the upstream and downstream river section water level, the flow change and the power generation output and the power generation capacity of the hydropower station are forecasted or predicted, corresponding plans are provided for flood early warning or meteorological disaster early warning or water level over-limit early warning, and key links of the plans are simulated in combination with a simulation engine; and performing simulation calculation on different power generation and reservoir scheduling strategies to obtain an optimal scheduling scheme. According to the invention, the intelligent management of hydropower station engineering safety, scheduling safety and power generation safety is realized.

The invention discloses a battery energy storage safety management system based on a BMS, and relates to the technical field of battery energy storage safety management, the system comprises a data acquisition module, a data analysis processing module, an equalization strategy generation module, an equalization execution module and a safety monitoring early warning module; operation parameters of the battery pack and the single batteries are comprehensively acquired through the data acquisition module, the actual operation state of the battery pack is accurately sensed, health factors are calculated by comprehensively considering multiple factors, weight coefficients are dynamically adjusted, the characteristics of the single batteries are comprehensively considered, and the charging and discharging states of the battery pack are calculated according to the health factors, the charging and discharging stages and the environment temperature. The equalization strategy and current are determined through a self-adaptive algorithm, dynamic response to the running state of the battery pack and environment change is achieved, equalization operation is accurately executed through the equalization execution module, accurate equalization control is achieved, and through real-time monitoring of the safety monitoring and early warning module, safe running of the battery in different environments is guaranteed, the performance of the battery is improved, and the service life of the battery is prolonged.

The invention discloses an intelligent management system for nuclear power plant personnel situation prediction and risk assessment, and relates to the field of intelligent safety management systems, and the system comprises a data collection unit, a multi-dimensional situation awareness unit, a risk prediction and assessment unit, an intelligent decision intervention unit and a visual interaction unit. And multi-source data acquisition, real-time situation construction, dynamic risk prediction and evaluation, intelligent early warning intervention and information visualization are realized. According to the invention, real-time monitoring, dynamic risk prediction and intelligent management of the safety state of the operating personnel can be realized, and the defects of real-time monitoring, dynamic prediction and intelligent management of the operating personnel in a high-risk area in the prior art are overcome, so that the safety management level is improved, the life safety is guaranteed, and the accident occurrence probability is reduced.

The invention discloses an intelligent building safety management system based on big data, and belongs to the technical field of intelligent buildings. Comprising the following modules: a multi-source data fusion and preprocessing module, which adopts intelligent data standardization and feature extraction technologies to realize efficient integration and semantic conversion of cross-source heterogeneous data and ensure data quality and consistency; the security risk dynamic knowledge graph construction module is used for constructing a semantic association network of building security elements through a graph neural network so as to continuously self-learn and dynamically update a risk feature relationship; the intelligent risk assessment and early warning module is used for carrying out comprehensive modeling, accurate positioning, layered assessment and intelligent early warning on building safety risks; the safety decision support module is used for providing an executable risk assessment report and an emergency decision suggestion; and the safety management visualization module adopts an interactive multi-dimensional visualization technology to intuitively present the dynamic evolution process of the building safety risk, so that the risk perception and management efficiency is remarkably improved.

The invention discloses a construction site intelligent safety management system and method based on a BIM technology, and relates to the technical field of constructional engineering, and the method comprises the following steps: S100, building a three-dimensional digital model of a construction site by using BIM software, and collecting construction site data by deploying a video camera, personnel positioning equipment and an environment sensor; s200, preprocessing the acquired data, and performing potential safety hazard identification and environment detection on the construction site; s300, fusing and displaying the generated BIM three-dimensional digital model and the processed data through spatial alignment, data mapping and dynamic updating; s400, calculating the probability of occurrence of potential safety hazards on the construction site and a comprehensive decision score; and S500, carrying out quantitative assessment on the potential safety hazards of the construction site by constructing a risk assessment model, sorting the calculated risk scores of the potential safety hazards, and determining the priority processing sequence of the potential safety hazards of the construction site, so that intelligent safety management of the construction site is realized.

The invention relates to the field of battery safety management, in particular to a battery pack safety management method and system based on an intelligent algorithm. A battery pack safety management system based on an intelligent algorithm comprises a battery pack parameter monitoring module, a weight calculation module and a fault prediction module. According to the method, key parameters such as the single voltage, the total voltage, the charging and discharging current and the cell surface temperature are acquired in real time, the dynamic threshold values of the total voltage, the charging and discharging current and the charge state are calculated respectively, judgment is performed in combination with the preset fixed threshold value, abnormal conditions in the running process of the battery pack can be found in time, and corresponding abnormal response measures are executed; comprehensive real-time monitoring and dynamic threshold judgment of the parameters of the battery pack are achieved, the safety and reliability of the battery pack are effectively improved, and safety accidents caused by abnormal parameters are prevented.

The invention relates to the field of hospital patient safety management, and particularly discloses a hospital patient safety management system and method based on data analysis, and the method comprises the steps: firstly obtaining the hospitalization record of a patient, the heart rate values, collected by an intelligent device, of the patient at a plurality of preset time points, and the blood pressure values, collected by the intelligent device, of the patient at a plurality of preset time points; and then feature extraction and correlation analysis are carried out on the three by using a deep learning technology, and finally whether a patient safety early warning is sent out is judged through a classifier, so that the patient nursing quality is improved, and the response speed to the health condition of the patient is improved.

The invention discloses an electric energy safety management system and method based on a cloud platform, and relates to the technical field of electric energy safety management, and the scheme comprises the steps: collecting the operation data of a micro-grid unit in a power grid, and transmitting the operation data to the cloud platform; judging whether the operation data at each time point is abnormal or not; constructing a topological structure of the power network according to the physical connection between the micro-grid units; dividing all nodes into different areas, calculating a comprehensive evaluation value of each node, and selecting the node with the highest comprehensive evaluation value as a local center node of each area; and when a plurality of micro-grid units in any area have an electric energy safety fault, calculating the priority of each fault node according to the local aggregation coefficient of the fault node and the connectivity between the fault node and the local center node, and performing maintenance according to the priority of the fault node. And comprehensive monitoring and management of the electric energy quality are realized.

The invention, which relates to the technical field of nursing management, discloses a patient information safety management system for liver, gall and pancreatic internal medicine nursing, comprising a nursing information management center. The nursing information management center is in communication connection with a patient information collection module, an information classification processing module, a health trend analysis module, a risk assessment analysis module, a risk early warning planning module and an information synchronous updating module. According to the patient information safety management system for nursing in the department of hepatobiliary and pancreatic, through implementation of the patient information safety management system, medical staff can access latest and most accurate patient data in real time, and a risk assessment analysis module comprehensively analyzes the medical history, the current illness state and the treatment progress of a patient and calculates a risk assessment coefficient; in addition, by updating the medical information of the patient in real time, making and executing a personalized nursing plan, the change of the illness state of the patient is quickly responded, and the nursing and treatment scheme is adjusted in time.

The invention discloses a new energy automobile driving motor safety management system and method based on intelligent control, particularly relates to the technical field of driving motors, and provides an important basis for evaluating mechanical interaction between motors by obtaining mechanical transmission coupling information to calculate a mechanical transmission coupling coefficient; electrical coupling coefficients are calculated by acquiring electrical coupling information among the motors in the multi-motor driving system, transmission and influence of electrical signals among the motors are further revealed, and abnormity in an electrical system is recognized; control coupling information among motors in a multi-motor driving system is obtained to calculate a control coupling coefficient to quantify the coupling degree of motor control signals, cooperative control behaviors among the motors are determined, each motor provides independent fault information, and a mechanical transmission coupling coefficient, an electrical coupling coefficient and the control coupling coefficient are synthesized to realize cooperative control of the motors. A single-point cooperative fault discrimination model is constructed, and a single-point motor fault and a system cooperative fault can be effectively distinguished.

The invention discloses an electronic nursing medical record safety management system based on a block chain, and relates to the technical field of medical informatization. The system comprises a user management module, a block chain encryption module, a data consistency verification module, a data integrity verification module, a data analysis and evaluation module, a data transmission module and a data management module which are connected through electric signals. And the user management module adopts an identity authentication technology of a block chain to realize registration, login, authority distribution and logout functions of user information. According to the electronic nursing medical record safety management system based on the block chain, through the data consistency verification module and the data integrity verification module, the consistency and integrity of the electronic nursing medical record data are ensured, so that the system can discover the inconsistency and inintegrity of the data in time, corresponding correction measures are taken, data errors are reduced, and the safety of the electronic nursing medical record safety management system is improved. And data quality is improved.

The invention discloses a smart city public safety management system based on video monitoring, and relates to the technical field of public safety management, original video data streams and a real-time road data set D are collected in real time through an API interface, a time sequence feature matrix TSM and a road congestion coefficient Ck are generated, and the data integration efficiency is improved. The behavior feature extraction module identifies group behavior features through target detection and an optical flow algorithm, and encryption transmission guarantees privacy. The risk prediction module calculates a cross-regional risk index RRI based on federated learning, triggers a response mechanism and accurately early warns risks, and the dynamic decision module combines real-time data to generate a resource scheduling scheme and selects a proper path and callable resources. Through the combination of the execution feedback module and the driving iterative optimization module, the algorithm is dynamically adjusted, closed-loop management is formed, the problems of data splitting, response lag and model stiffness of a traditional system are solved, and the real-time performance, the accuracy and the scene adaptability of public safety management are remarkably improved.

The invention discloses an energy storage power station safety management system capable of realizing thermal runaway grading early warning based on flame-retardant foaming, which is characterized in that a battery module is quickly wrapped and isolated from oxygen by controlling refrigerant spraying and triggering a foaming device to start, a large amount of high-temperature-resistant flame-retardant foaming agent is quickly released, and the thermal runaway grading early warning is realized by combining the refrigerant spraying with a foaming material. The further spreading risk of thermal runaway of the battery module is avoided, and safety management of the energy storage power station is achieved. By controlling the valves, switching of different operation modes can be achieved, and safety management of graded early warning of thermal runaway of the energy storage power station is achieved. According to the system, two stages of grading early warning stages are set for the battery of the energy storage power station, a battery cooling operation mode of the second-stage early warning stage and a battery thermal runaway blocking mode in the first-stage early warning mode are achieved, the battery operation temperature can be reasonably regulated and controlled, the battery operation efficiency is improved, and the energy storage power station is protected. And the risk propagation of thermal runaway of the battery is effectively blocked.

The invention provides a user travel data safety management system and method based on cloud computing, and the system comprises a multi-source data collection and adaption module which is used for collecting user travel data from various types of travel equipment; the hybrid encryption transmission channel module is used for establishing a safe transmission link between the data acquisition terminal and the cloud computing platform; the privacy screening and desensitization module is used for identifying and processing privacy sensitive contents in the data received by the cloud computing platform; the distributed storage architecture module is used for reliably storing user travel data on the cloud computing platform; the authority control and auditing module is used for controlling the calling authority of the external main body to the user travel data and auditing the data access condition; the data backup and recovery scheduling module recovers data when data risks exist; and the data visualization and analysis auxiliary module is used for presenting the data in a visualization mode. According to the invention, confidentiality, integrity and availability of travel data transmission and transparency and traceability of data access are ensured.

The invention relates to the technical field of safety management, in particular to an intelligent safety management system based on municipal engineering, which comprises a construction area risk dynamic assessment module, a hierarchical dynamic inspection frequency optimization module, an inspection path optimization module, an abnormal behavior monitoring module and a high-risk area early warning module. According to the method, quantitative safety assessment basis is provided for different types of operation by utilizing the environmental data of the construction area, combining with historical accident records and calculating the construction risk level, the inspection frequency is dynamically adjusted according to the risk level of the construction area, the self construction progress and abnormal records, so that the inspection resources are inclined to a high-risk area, and the inspection efficiency is improved. The polling efficiency is improved, meanwhile, the pertinence of safety management is enhanced, in combination with positioning information of constructors and boundary data of a high-risk area, the moving track of the constructors is analyzed, early warning is triggered when the constructors enter the high-risk area, safety risks are intervened in time, the safety supervision capacity of municipal engineering construction is improved, and the probability of construction safety accidents is reduced.

The invention relates to the field of electric power engineering construction safety management, and particularly discloses an electric power engineering construction safety management system based on multiple sensors. By monitoring the relative deviation distance and direction of the gravity center point, the transfer speed and direction of the gravity center point, the inclination angle and direction of the body and the number and the supporting area of supporting framework joint points corresponding to various postures of the overhead working personnel in the electric power engineering construction process, the falling risk of the overhead working personnel is recognized; monitoring the distance between each easily-impacted part of the body of the aerial working personnel and an object adjacent to the part and the activity coefficient of the object adjacent to each easily-impacted part in the electric power engineering construction process, and identifying the collision risk of the aerial working personnel; the distance between high-altitude operation personnel and all surrounding electrified bodies in the electric power engineering construction process is monitored, the electric shock risk of the high-altitude operation personnel is recognized, recognition and evaluation of various safety risks of the high-altitude operation personnel in the electric power engineering construction process are achieved, and personnel safety is guaranteed.

The invention, which relates to the technical field of intelligent security management, discloses a smart park security management system comprising a data sensing module, an edge calculation module, an intelligent analysis module and a command execution module. According to the system, related safety data of the park are collected in real time in a multi-source mode through the data sensing module, the data collected in real time are locally preprocessed through the edge calculation module, the global safety situation in the park is sensed, then the data collected in real time are analyzed and processed through the intelligent analysis module, graded early warning signals are generated, and the safety of the park is improved. And finally, corresponding early warning emergency operation is executed through a command execution module, so that real-time monitoring, intelligent early warning and automatic emergency response of the safety of the smart park are realized, the safety management efficiency and accuracy are improved, the problems of response lag, data island and the like in the safety management of the traditional park are solved, and the safety of the park is improved. And full-process management from data acquisition, intelligent analysis to automatic disposal can be realized, and the safety protection capability of the park is remarkably improved.

The invention discloses an RSIC-V CPU security chip based on authority management, and belongs to the technical field of security startup. Comprising an embedded RSIC-V CPU core, and the embedded RSIC-V CPU core is connected with an ROM authority management module, a safety management system register and a safety authority management module. The ROM authority management module is connected with the secure ROM firmware; the security authority management module is connected with a plurality of security modules; when users with different identities access the secure ROM firmware, identity recognition is carried out, and security services with different levels are provided according to the permission of the recognized user identities. According to the method, only the request passing signature verification and security authority management authentication is allowed to access the security module, the service uniqueness of the security module is ensured, the chip security module can be pertinently accessed only through authorized upper software, the access is non-direct access, security service is carried out through ROM firmware, and a service result is fed back to the upper software, so that the security module can be accessed in a targeted manner. The security of the security module is ensured from the circuit, and the attack difficulty of the chip is greatly increased.

Disclosed is a BMS-based battery energy storage safety management system. The system comprises a BMS module, a control center module, an evaluation analysis module, a coupling analysis module, a prediction module, and a data storage module. The BMS module collects monitoring data of a battery under different operation states and then, according to the monitoring data, performs initial monitoring of a real-time health state of the battery. The evaluation analysis module, according to a change in data indicators in the monitoring data, evaluates and analyzes all fault analysis models in the BMS module to obtain an evaluation analysis result. Then the coupling analysis module combines the evaluation analysis result with the data indicators of the monitoring data to retrieve multidimensional spatio-temporal data, and constructs a coupling field model to perform coupling analysis on battery operation state. The prediction module then constructs a fault prediction model by using a coupling data set as training data, accurately locates coupling faults of different coupling surfaces, and implements comprehensive analysis and location of coupling faults.

The invention provides a railway construction safety management system based on a global linkage system, and belongs to the technical field of railway construction management, and the system comprises a material resource management module which carries out the management of material resources; the environment risk early warning module monitors the surrounding environment condition of the construction area in real time and performs assessment and early warning on the environment risk; the personnel safety management module is used for acquiring position and state information of operating personnel in real time, and evaluating and early warning operation behaviors of the operating personnel; the equipment safety management module is used for collecting equipment operation data in real time, analyzing equipment operation states and operation behaviors and predicting operation risks, equipment faults and maintenance requirements; the to-do list management module is used for uniformly managing and tracking various tasks and sending task information to related personnel; and the station yard global early warning module is used for integrating data of other modules and carrying out centralized data processing and analysis. According to the scheme, information intellectualization is realized, the management efficiency is effectively improved, and the construction collaboration is enhanced.

The invention relates to the technical field of safety engineering, in particular to an intelligent high-altitude and fire operation safety management system based on risk assessment, which comprises a safety helmet module, a data acquisition and transmission module, an edge calculation and processing module, a risk assessment and decision module, an emergency response module and a data analysis and optimization module. The intelligent safety helmet worn by each operator is integrated with a flame sensor and a height sensor, and flame information in an operation environment and height changes of the operators can be collected in real time. Through the low-power-consumption wireless communication technology, the collected data is transmitted to the edge computing device in real time, and the edge computing device calculates the comprehensive risk index through multi-sensor data fusion. And when the risk index exceeds a preset threshold value, the system automatically triggers alarm, sends early warning information to operators and a management platform, and takes emergency measures, so that the accident rate in high-altitude operation and fire operation can be effectively reduced, and the safety management level of the operation environment is improved.

The invention provides a railway digital intelligent logistics station platform and a storage medium. The platform comprises a digital intelligent sub-platform and a business application sub-platform. The data intelligent sub-platform comprises a data service system which is used for generating an operation service which can be applied to the business application sub-platform based on station data, a freight operation plan and a business service engine which are obtained by the Internet of Things sensing system; the artificial intelligence model system is used for storing and managing an artificial intelligence model, and the digital twin system is used for constructing a three-dimensional station model; the business application sub-platform comprises an automatic production operation system used for executing production operation and feeding back an operation state, an intelligent logistics service system used for vehicle passage reservation, information guidance and cargo storage, a safety management system used for realizing operation safety protection including crossing safety identification and field safety management, and a control system used for controlling the operation safety protection and the field safety management. And the green park management system is used for counting energy consumption. According to the invention, human, cargo, vehicle and yard total factor perception and intelligent management can be realized.

According to the house leasing information management system and method provided by the invention, comprehensive, efficient and safe management of house leasing information is realized in combination with a special hardware system and terminal equipment. The system integrates a plurality of cooperative work modules such as block chain data storage, intelligent housing resource recommendation, dynamic credit evaluation, automatic contract management and privacy protection, and adopts advanced technologies such as a distributed account book, a deep neural network, a graph neural network and an intelligent contract. And data cannot be tampered, recommendation is personalized, credit evaluation is accurate, contract management is automatic, and user privacy is strictly protected. Meanwhile, the system is provided with hardware supports such as a high-performance computing and storage cluster, security encryption and privacy protection equipment and the like, and special terminal equipment provides convenient user interaction experience. According to the invention, transparency, efficiency and user experience of the house renting market can be significantly improved, renting risks are reduced, rights and interests of both renting parties are guaranteed, and healthy development of the house renting industry is promoted.

The invention discloses a safety production management method and a production safety management system based on safety helmet detection, and relates to the technical field of production safety management. Multi-modal data acquisition is realized by constructing an explosion-proof intelligent camera cluster and a wearable positioning terminal, an improved YOLOv7-Tiny model and an HRNet key point detection technology are adopted, illumination compensation, atomization elimination and data enhancement technologies are combined, and precise recognition of the wearing state, the angle deviation and the compliance of the safety helmet is completed; triggering hierarchical response in real time based on a five-level dynamic early warning rule, predicting a future risk probability of an operator through an optimized MLP prediction network in combination with historical violation data, and formulating a personalized scheme; according to the invention, a closed-loop management system of real-time monitoring, intelligent early warning, behavior prediction and active intervention is formed, the occurrence rate of safety accidents is significantly reduced, and the safety standardization of operators and the safety management efficiency of enterprises are improved.

The invention discloses a circumferential weld safety management system and method based on a knowledge graph, and the system comprises a data collection and processing module which is used for collecting data related to a circumferential weld in an oil and gas transmission pipeline from various data sources, and carrying out the preprocessing and cleaning of the collected data, and obtaining the preprocessed data; the knowledge extraction and graph construction module is used for extracting key information from the preprocessed data and constructing a knowledge graph based on the key information; the risk sorting and hidden danger positioning module is used for carrying out correlation analysis based on the knowledge graph, determining risk key factors and carrying out risk sorting based on the risk key factors so as to determine target positioning information of risk circumferential welds in the oil and gas transmission pipeline; and the defect automatic analysis module is used for acquiring a magnetic flux leakage internal detection signal of the risk circumferential weld according to the target positioning information, and performing defect analysis based on the magnetic flux leakage internal detection signal to obtain a defect type and a defect grade of the risk circumferential weld. And the efficiency of positioning the hidden danger of the circumferential weld of the oil-gas transmission pipeline is greatly improved.