22 results about "Event tree" patented technology

The invention provides a nuclear power plant safety system based on causal reasoning, and relates to the technical field of nuclear power plant safety monitoring and fault diagnosis. The nuclear power plant safety system comprises a multi-source sensing layer and a causal engine layer, the multi-source sensing layer is used for collecting operation parameters of a nuclear power plant, and the causal engine layer comprises a dynamic causal network construction module and an online reasoning module. The dynamic causal network construction module is used for constructing a dynamic causal network according to the operation parameters, a continuous causal edge generated based on an equipment physical equation and a discrete event edge generated based on a probabilistic safety evaluation event tree; and the online reasoning module is used for determining a key fault propagation path according to the dynamic causal network so as to locate a fault source. According to the method, the equipment physical equation is embedded into the dynamic causal network, so that the reasoning process is ensured to accord with thermal hydraulic and safety physical rules, the problem of high false alarm rate caused by correlation misjudgment in deep learning is avoided, and the safety of the nuclear power plant is improved.

The invention discloses a nuclear chemical engineering facility safety analysis method and system and electronic equipment, and belongs to the technical field of nuclear chemical plant safety analysis. The analysis method comprises the steps of obtaining an originating event list of the nuclear chemical engineering facility; according to the originating event list and the event sequence logic, respectively constructing an event tree model corresponding to each originating event; a fault tree model of a key fault branch in each event tree model is constructed, and the fault tree model comprises basic events connected with logic gates; calculating a basic event probability based on correlation analysis, human factor reliability analysis and an equipment failure database; and according to each event tree model, the fault tree model and the basic event probability, calculating a safety analysis result corresponding to each originating event. According to the method, the problems that a security analysis method based on a deterministic theory in the prior art is too conservative and low in accuracy can be solved.

This invention discloses a safety analysis method for ship SOFC systems, belonging to the field of risk prevention and control technology. It includes: identifying the causative factors of the ship SOFC system; constructing a failure fault tree and event tree model; constructing a Bow-Tie model based on the failure fault tree and event tree model; quantitatively analyzing potential causative factors to identify key factors affecting the SOFC system; combining the analyzed ship SOFC system accident causation data and collected ship fuel cell standard and specification data to form a data system and construct a ship SOFC system accident risk prevention knowledge graph; and conducting SOFC system safety analysis based on the ship SOFC system accident risk prevention knowledge graph. This invention clarifies the criticality, hierarchical relationship, and action path of each causative factor; constructs the causative factors into a complex accident causation network; and, combining the semantic information of the knowledge graph and the capabilities of complex network analysis, deeply reveals the accident causation propagation mechanism, providing a comprehensive perspective for understanding the occurrence and development of accidents.

The invention provides an oil and gas storage and transportation station safety risk dynamic evaluation method and system, and belongs to the technical field of oil and gas storage and transportation safety, and the method comprises the steps: carrying out the recognition and analysis of hazard source events of an oil and gas storage and transportation station, and preliminarily constructing a hazard source event tree; key factor events of the oil and gas storage and transportation station are identified and analyzed, and a key factor event tree is preliminarily constructed; performing safety level division, dividing the safety problem of the oil and gas storage and transportation station into three levels of equipment, operation and management, and analyzing the hazard source event tree and the key factor event tree according to the divided safety levels; identifying and analyzing security elements of the key equipment; and formulating a solution. The system comprises a data acquisition module, a database and a multi-terminal communication module. According to the method, the event tree is constructed, possible trigger factors and development paths of each dangerous source and key factor are analyzed in detail, the safety management work of the oil and gas storage and transportation station is perfected, and the long-term and stable development and progress of the oil and gas storage and transportation station are finally realized.

The invention discloses a human-computer interaction task failure evolution path identification method based on a binary decision diagram, and aims to solve the problem that a task failure path in a complex human-computer interaction system is difficult to accurately identify. The method comprises the following steps: constructing a man-machine interaction task event tree and converting the man-machine interaction task event tree into BDD; determining a top event based on the event tree, constructing a fault tree and converting the fault tree into BDD; integrating the event tree BDD and the fault tree BDD to form a unified BDD corresponding to the ET-FT model; and traversing and identifying a failure evolution path based on the integrated BDD. Unified modeling of static logic and dynamic evolution is achieved through BDD, the causal relationship is quantified by combining Shannon decomposition and the ITE method, and the method has the advantages of being accurate in modeling, efficient in analysis and high in expansibility, can be widely applied to the fields of aerospace, medical equipment and the like and provides support for system reliability optimization.

The invention discloses a safety assessment method and device for a nuclear power system, and the method comprises the steps: obtaining the first information of a to-be-analyzed nuclear power system, and the first information comprises the identifications of a plurality of parts in the nuclear power system, the state type, and the equipment parameters of the parts identified by the plurality of part identifications; constructing a fault tree according to the first information; according to the equipment parameters of the parts corresponding to the multiple basic events in the fault tree, a first corresponding relation is determined, and the first corresponding relation comprises multiple first operation durations of the parts corresponding to all the basic events and first failure probabilities corresponding to all the first operation durations; simulating the accident evolution process of the nuclear power system according to the first corresponding relation to obtain simulation information; according to the simulation information, the safety of the nuclear power system is evaluated to obtain the evaluation result, and the event tree and the fault tree are associated, so that the problem that the static probability and the dynamic evolution are disjointed is solved, the path probability is more practical, the accuracy of the safety evaluation result is improved, and the deviation is effectively reduced.

The application discloses a method and device for changing component states by visual data driving engine, wherein the method comprises the following steps: a data driving engine abstracts data objects into a dragable layer object, and presents the data objects in a user component layer tree in groups, and defines component layer tree model attributes for the data objects; when the data objects participate in binding between component objects, a json data object structure is defined; the data driving engine generates a corresponding event tree through a component object binding relationship recorded in the json data object structure, and completes interaction through a method defined in the component object for interacting with external component objects; and the data driving engine combines an event tree with an abstract syntax tree, and dynamically generates business codes. The method and device realize centralized management subscription, avoid single event binding, and can dynamically generate project source codes through engine compilation.

The invention discloses an earthquake emergency scheduling method and system for a diversion type hydropower station, and relates to the technical field of hydropower station scheduling control, and the method comprises the steps: obtaining multi-source safety data in real time through a data collection unit, and generating an alarm; constructing a fault tree based on the alarm, calculating an event occurrence probability, expanding an event tree path, and evaluating a risk degree in combination with an accident consequence; dividing each event path into a risk area and a risk level according to the assessment risk degree, and executing an emergency scheduling strategy for different risk levels; and after each scheduling is implemented, the security alarm is collected again, and the fault tree model is updated, so that continuous dynamic response is realized. According to the method, multi-source data of earthquakes, units, dams, communication and the like are collected in real time, potential risks can be comprehensively identified, probability calculation and accident consequence analysis are combined, and quantitative assessment and grading of the risks are achieved. The scientificity and the accuracy of emergency decision making are improved, and the adaptability and the robustness of emergency scheduling are improved through continuous feedback and dynamic optimization.

The invention relates to the technical field of nuclear power plant safety and operation, in particular to a nuclear power plant risk monitoring model processing method suitable for equipment performance degradation. A nuclear power plant risk monitoring model processing method suitable for equipment performance degradation comprises the steps that whether an original model is updated or not is judged according to the appearance form of performance degradation equipment in an original PSA model; if so, updating the original PSA model into a probabilistic security analysis model M1 suitable for equipment performance degradation; acquiring an event sequence to be subjected to analogue simulation analysis, and performing analogue simulation analysis on the event sequence; updating the M1 into a new probabilistic safety analysis model M2 according to an analogue simulation analysis result; and calculating to obtain the damage frequency of the reactor core after the performance degradation of the equipment. According to the method, the probability theory safety analysis technology and the deterministic theory safety analysis technology are combined, the method which can reflect the equipment performance degradation change and has the capacity of updating the event tree model and the fault tree model is provided, and risk monitoring related to equipment performance degradation is achieved.

The application provides a CBTC automatic self-test method and device, the method comprising: obtaining a first test sequence based on an event graph, wherein the first test sequence comprises a correct complete event sequence and a fault complete event sequence; optimizing the first test sequence based on an event tree optimized test sequence optimization algorithm to obtain a second test sequence with lower redundancy; and testing the second test sequence based on a CBTC automatic test platform of an event-driven model to obtain a test result.

This application provides a no-code programming method, system, and medium for robots based on event-driven and asset graphs. The method includes: importing physical asset models into a 3D simulation environment; assigning predefined functional labels to each physical asset model; generating basic motion events for non-robot assets based on functional labels and configuration parameters; generating composite events for robot assets based on process types and key work points defined in an interactive interface; constructing an asset graph based on asset functional labels, assembly relationships in 3D space, and defined work space points; traversing the asset graph and automatically generating logical control events in an event tree; compiling the final constructed event tree and logical relationships to generate underlying control code; and automatically deriving and establishing logical dependencies between events by analyzing the graph relationships composed of asset types, spatial position relationships, and work point identifiers, thereby achieving efficient and intuitive no-code programming.

An automation system for accident analysis of a nuclear power plant and an automation method thereof are provided. The automation method of accident analysis in a nuclear power plant includes loading primary input information including user input information and event tree information on accident scenario information for accident analysis in a primary input information generation module, generating accident scenario information of the nuclear power plant based on the primary input information in an accident scenario information generation module, generating secondary input information for accident analysis based on the accident scenario information in a secondary input information generation module, and generating accident analysis information by performing accident analysis for the nuclear power plant based on the secondary input information in an accident analysis execution module.

Examinations are used to determine the ability of a candidate such as a student or prospective practitioner as it pertains to proficiency in a particular subject or skill set. Many standardized tests are now administered online, and online examinations are difficult to proctor. One solution to overcome the above challenge is to predict the behaviour of the candidate using Machine Learning (ML). However, conventional ML based methods fail to consider sequence of incidents pertaining to a candidate during online proctoring for assessing the behavior of the candidate. To overcome the above challenges, embodiments herein provide a method and system for regression based prediction of aberrant behavior in online proctoring. The present disclosure generally concerns with exam proctoring and more specifically focus on detecting of aberrant behaviors in advance during examination by analyzing a plurality of incidents pertaining to a candidate using incident tree based regression analysis.

The application discloses a kind of discrete dynamic event tree and nuclear simulation program efficient parallel dynamic coupling analysis method, this method includes: constructing discrete dynamic event tree DET simulation model, determine nuclear simulation program simulation time and run, according to nuclear simulation program simulation result analysis obtains the time information of all DET simulation object state transition control TRIP variable change, and according to DET simulation model branch rule obtains the restart time and restart number of nuclear simulation program backtracking restart of all DET simulation objects of current accident sequence, judge whether restart time and parent sequence restart time are identical, update the failure restart file as input, copy necessary restart input file in parent sequence to current folder, according to branch number backtracking executes multi-thread parallel simulation to complete the simulation of all DET failure branches.This method makes up the deficiency of traditional safety analysis method in handling the time sequence dynamic response of nuclear power plant accident process, and multi-thread parallel computing mode also improves the calculation efficiency.

The application discloses a kind of equipment dynamic risk assessment methods based on neural differential equation and dynamic event tree, comprising the following: neural event differential equation is used to generate system simulation path and node, then according to node merging simulation path generates DDET and carries out post-pruning to it;Black box event function is learned, and new DDET is generated using the black box event function;The simulation result of system dynamics is realized using the generated DDET;Above-mentioned link in the whole process, further acceleration is carried out using GPU parallel computing technology to it.In many PSA methods, the significant advantage of using DDET is that it can break the limitations of static analysis method in describing the dynamic behavior of complex equipment system, effectively describe the dynamic characteristics and accident evolution scene of the system, especially in the processing of the mutual influence between process variables and component state.

The invention discloses a GIS equipment installation operation risk management and control method and system, and belongs to the technical field of power equipment installation operation risk assessment. Through constructing a GIS installation operation risk event tree, the relationship between each risk point and the overall risk is quantified; according to the method, various risk types are selected, the influence degrees among the risk types are set in an objective judgment mode, multiple risk points and influence factors in installation work are comprehensively considered, quantitative evaluation of different risk points and the overall risk of equipment is achieved, the problems that an evaluation result is too single and depends on expert experience in a traditional method are solved, and the evaluation efficiency is improved. The efficiency and accuracy of risk management and control are effectively improved, and the safety and reliability of GIS installation operation are ensured.

The invention discloses a dynamic event tree automatic coupling analysis method and system for nuclear power plant accidents and a storage medium, and relates to the technical field of nuclear power plant safety analysis. Inputting a basic input file of the deterministic theory program; identifying the TRIP card and classifying the TRIP card into an effective TRIP card (direct control system / equipment action) and an intermediate TRIP card (auxiliary signal transmission); identifying the controlled system / equipment according to the effective TRIP card; failure events are divided into demand-type failures (functions are not started) and operation-type failures (actions are not completed on time); establishing a dynamic event tree (DET) branch for demand type failure by adopting a universal auxiliary variable method, and coupling with a deterministic theory program for calculation; identifying an operation type failure sequence meeting an acceptance criterion; discretizing time parameters to calculate an operation type failure boundary; and clustering and analyzing the accident scene. According to the method, the problems that DET modeling depends too much on experience of analysts and the analysis efficiency is low in the safety analysis process of existing nuclear power facilities are solved, and therefore efficient modeling and operation are achieved.

The invention provides a water diversion pipeline risk assessment method and system and a storage medium. The method comprises the steps of obtaining time sequence monitoring data of a preset monitoring node of a water diversion pipeline; for the time sequence monitoring data of any two monitoring nodes, calculating normalized mutual information in a preset time delay search domain, and generating a time delay mutual information spectrum; establishing an event tree analysis model, and determining an initial event occurrence probability through a probability mapping function when the event association feature vector and the GIS vulnerability level of the grid unit where the monitoring node is located meet a preset triggering condition together; for non-initial event nodes, the conditional transition probability is calculated based on the event association feature vector and the upstream path cumulative probability; for any scene path, the risk consequence value is calculated according to the GIS vulnerability grade, the real-time hydraulic working condition parameter and the failure mode of the corresponding grid unit; and traversing all scene paths of the event tree, multiplying the occurrence probability of each path by the risk consequence value, and summing to obtain a comprehensive risk index of the water diversion pipeline.

This invention relates to a method, system, medium, and device for quantifying successful branches in an event tree, comprising: calculating the minimum cut set of failed branches of a function header and the probability value of the failed branch; calculating the probability of a successful branch based on the probability value of the failed branch; calculating the minimum cut set of a sequence; reducing the minimum cut set of the sequence according to the minimum cut set of the failed branch to obtain a new minimum cut set; calculating the frequency of the sequence according to the new minimum cut set; and correcting the frequency of the sequence using the probability of the successful branch to obtain the target frequency of the sequence. This invention addresses the correlation between the minimum cut set of the sequence and the minimum cut set of the failed function header corresponding to the successful branch by removing the minimum cut set of the failed function header corresponding to the successful branch from the minimum cut set of the sequence, thus ensuring the accuracy of the minimum cut set of the sequence. Simultaneously, it corrects the frequency of the sequence by using the frequency of the sequence, ensuring the accuracy and reliability of the frequency and avoiding frequency overestimation.

The application relates to an AI model-based refrigeration system fault early warning method, which comprises the following steps: S1, collecting state data, equipment design parameters and maintenance work order records; S2, removing the influence of environmental temperature factors and load factors to obtain compensated state data; S3, cross-fusing the compensated state data, the equipment design parameters and the maintenance work order records to generate comprehensive health state features; S4, establishing an FMEA failure mode identification model, an FTA fault tree construction model and an ETA event tree evolution model of the refrigeration system according to the comprehensive health state features; S5, training an AI model to obtain a refrigeration system health prediction AI model; S6, performing health state evaluation on the state data, the equipment design parameters and the maintenance work order records of the refrigeration system according to the refrigeration system health prediction AI model to generate an equipment health index; and S7, determining the corresponding fault risk priority number according to the equipment health index to generate the priority of a maintenance task and a maintenance decision.

The invention discloses a nuclear power plant post-earthquake safety management method based on earthquake PSA, and belongs to the field of nuclear power. The method comprises the following steps: based on an earthquake PSA model, identifying an SSC related to an earthquake accident; obtaining an earthquake risk important SSC list based on the contribution to the core damage frequency; obtaining a normal shutdown equipment list according to a success path in the transient originating event tree and the related fault tree, and further obtaining a safe shutdown equipment list; after an earthquake occurs, when an automatic shutdown signal is not triggered and equipment functions in a single-point failure equipment list and / or an earthquake risk important SSC list are damaged, normal shutdown equipment and safe shutdown equipment are checked, and shutdown is executed when at least one group of equipment functions are normal. Otherwise, the reactor is kept running until normal reactor shutdown equipment or safe reactor shutdown equipment is repaired, and then reactor shutdown is executed. The method can effectively improve the safety management effect after the earthquake of the nuclear power plant and improve the safety after the earthquake of the nuclear power plant.

The invention particularly relates to a method and system for intelligently monitoring abnormity in a nuclear power station master control room, and belongs to the field of nuclear power station master control room monitoring. The method comprises the following steps: step 1, analyzing an intelligent monitoring anomaly model based on experience and knowledge of an operator, including knowledge collection and carding; performing anomaly analysis and event tree construction; generating an intelligent monitoring anomaly model graph; step 2, graphical configuration and debugging of the intelligent monitoring abnormal model, including variable definition and componentization; performing graphical configuration; and debugging and deploying the model. The system is used for implementing the steps of the method. According to the invention, the operation experience knowledge of the operator in the master control room is digitalized and modeled, and an intelligent abnormity monitoring model based on the experience knowledge of the operator is constructed, so that timely, reliable and automatic intelligent monitoring of the abnormal state of the nuclear power station is realized.