80 results about "Event tree" patented technology

A quantitative risk assessment system (QRAS) builds a risk model of a system for which risk of failure is being assessed, then analyzes the risk of the system corresponding to the risk model. The QRAS performs sensitivity analysis of the risk model by altering fundamental components and quantifications built into the risk model, then re-analyzes the risk of the system using the modifications. More particularly, the risk model is built by building a hierarchy, creating a mission timeline, quantifying failure modes, and building/editing event sequence diagrams. Multiplicities, dependencies, and redundancies of the system are included in the risk model. For analysis runs, a fixed baseline is first constructed and stored. This baseline contains the lowest level scenarios, preserved in event tree structure. The analysis runs, at any level of the hierarchy and below, access this baseline for risk quantitative computation as well as ranking of particular risks. A standalone Tool Box capability exists, allowing the user to store application programs within QRAS.

The invention relates to a multi-stage task spacecraft reliability improving method based on risks. The multi-stage task spacecraft reliability improving method based on the risks comprises the following steps of (1) determining the conversion relation of a key task stage and a task result state and between the task result states, (2) the key task stage risk characteristic is analyzed, a fault tree, a dynamic fault tree and a Bayes network method are used, a risk characteristic model is built, and relative data are collected to determine the key task failure occurring possibility and main risk factors, and (3) a spacecraft task process event tree model is built, the different task result state possibility is obtained by solving the model, the main risk factors are combined, and reliability improving measures are made. The multi-stage task spacecraft reliability improving method can realize the multi-stage task spacecraft conventional invalidity, redundancy backup invalidity and relative invalidity modeling analysis, the task result state possibility and the main risk factors are obtained, and the multi-stage task spacecraft reliability improving method based on the risks can provide technical support for the spacecraft reliability improving.

The invention discloses a reliability evaluation method of a distribution network cyber-physical system considering the whole process of fault processing. The reliability evaluation method of the distribution network cyber-physical system considering the whole process of fault processing comprises the following steps: initializing the distribution network cyber-physical system; confirming the current state of the distribution network cyber-physical system based on the sequential Monte Carlo method; obtaining the reliability of the three stages of fault location, fault isolation and power supply recovery by means of the fault tree model in view of the state of the distribution network cyber-physical system after the fault; classifying the load points according to the fault processing whole process event tree model to determine the impact degree of the fault processing on each load point; and calculating to obtain the system reliability indexes finally. The invention reflects the effect of the information failure on the state of the system after the fault from the overall point of view of fault processing, and takes full consideration of the time sequence process of the fault processing. According to the reliability evaluation method of the distribution network cyber-physical system considering the whole process of fault processing, the function of the information system in the analysis process of the fault consequences is considered, therefore, the invention helps to identify the integrated energy and the weak links of the communication infrastructure, assists the integrated operation of the distribution network cyber-physical system and the planning of the effective decision-making.

The invention discloses an assessment method of operating dynamic risk of electric transmission and transformation equipment. In combination with a fault tree and event tree analysis method, causes and effects of a fault mode are analyzed, a bow-tie model taking the fault mode as a central node is formed, the bow-tie model can be used for analyzing causes, effects and risk of accidents in combination with a fault tree and an event tree, and corresponding risk control measures are determined. According to the operating risk of the electric transmission and transformation equipment, the operating risk can be assessed dynamically. Compared with a fault diagnosis mechanism in the prior art, a dynamic fault diagnosis mechanism has the advantages that judgment of evidence information requirements is added, blindness of a diagnosis process is reduced, the fault condition of the electric transmission and transformation equipment can be judged effectively, and therefore a result, obtained through assessment, of the service life of the electric transmission and transformation equipment is more accurate and conforms to actual conditions better, and the assessment method has better guiding significance in engineering application.

The invention relates to an alarm transmission mode based alarm correlation analysis system and an analysis method thereof. The method comprises the steps of conducting normalization processing and conversion on all alarms in a uniform format; combining network configuration information to establish a directed graph containing all logic and physical nodes and relations of an event management system (EMS) for a single EMS; positioning alarms on related nodes on the directed graph and judging correlations of alarms according to accessible relations of nodes; and conducting mode matching analysis on homologous alarms by using an improved event tree model to derive the source alarm. By the aid of the system and the method, the problem that the prior art can not conduct alarm correlation analysis comprehensively is effectively solved, the accuracy, the high efficiency and the adaptability of alarm correlation analysis are enhanced, operation and maintenance costs and the operation difficulty are reduced, the system and the method are convenient to popularize and implement, and the system and the method are particularly suitable for current network conditions of the growing complexity and using habits of users.

Data on inspection, diagnosis, repair and operation histories are entered in a plant-maintenance apparatus for equipment that constitute a plant to be maintained. Failure-event tree breakdown is performed on failures to be expected for the equipment. Unreliability is predicted of at least one starting item in the failure-event tree breakdown. Unreliability of each item in the failure-event tree is calculated based on a failure unreliability function. Unreliability and a cost of recovery from each failure event in the failure-event tree are multiplied and results of the multiplication are accumulated in accordance with the tree breakdown to obtain a recovery cost. Preventive maintenance expenses are calculated for preventing failure events. Maintenance timing and technique are decided through comparison between the recovery cost and the preventive maintenance expenses.

A Unity 3D based three-dimensional virtual crowd scene generating method includes 1, establishing a database; 2, establishing a static virtual environment; 3, creating an event; 4; creating figure models; 5, creating a story control object and constructing an event tree, an event trigger generation sub object, an event selection sub object, an event confliction detection sub object and a crowd dynamic generation sub object in the story control object; 6, calling the story control object by a game engine to generate a three-dimensional virtual dangerous environment; 7, implementing the construction of the three-dimensional virtual dangerous environment. According to the invention, uniform design of crowd, environment and event is preformed, function completeness is achieved. By employing assemblies and plug-ins provided by the Unity 3D game engine, development operation is simplified. The invention synthesizes basic design elements required for virtual crowd scene development, improves efficiency of virtual crowd dangerous scene generation and similar game environment development and has advantages of function completeness and high development efficiency.

The invention discloses a risk-informed nuclear power plant LBLOCA (large break loss-of-coolant accident) analysis method. The method mainly comprises the following steps: 1) selecting an initial event as a nuclear power plant LLOCA; 2) according to a risk system evaluation method, establishing an event tree under the initial event, and indentifying all possible response sequences of a safety system for mitigation measures of a nuclear power plant after occurrence of the LLOCA; 3) for the event tree analysis results, combining with fault tree analysis and taking various failure data into overall consideration, quantizing occurrence possibility of all event sequences; 4) calculating peak cladding temperature corresponding to each event sequence; and 5) estimating peak cladding temperature margin of the LLOCA. By introducing a probability risk evaluation technique to a conventional deterministic analysis method, a purpose of taking overall consideration of cognitive uncertainty and accidental uncertainty of the nuclear power plant is achieved, and analysis result is closer to actual situations of the nuclear power plant.

The invention relates to an aircraft task reliability modeling method based on dynamic characteristics. The method includes the steps of firstly, conducting aircraft system analysis and task analysis, and establishing an aircraft task result state set; secondly, selecting an event tree (ET) method, and establishing an aircraft task process reliability reference model; thirdly, analyzing aircraft initial/middle task reliability characteristics, selecting a dynamic failure tree (DFT) method, a Bayesian network (BN) method, a Markov method and the like, and establishing an initial/middle task reliability characteristic model; fourthly, establishing an aircraft task reliability comprehensive model by compositing the initial/middle task reliability model. By means of the method, the dynamic characteristics in the aircraft complicated task process can be more accurately depicted, the influences of dynamic changes of aircraft system composition at different task stages in the aircraft task process on the aircraft task reliability are comprehensively reflected, and the established task reliability model can be more accurate.

The invention discloses a fault diagnosis system and a fault diagnosis method based on sequence and consequence analysis of an event tree. The system comprises a data input module, an event tree resolution module, a fault tree preprocessing module, a fault tree analysis module and a diagram display module, wherein the data input module is used for acquiring reliability data and structure data of a given system, and storing the data in modes of a fault tree model and an event tree model; the event tree resolution module is used for processing the given event tree model and the fault tree model, processing a successful branch of the event tree with a respective substitution method, and constructing a traditional sequence fault tree model and a consequence fault tree model; the fault tree preprocessing module is used for preprocessing the given fault tree model; the fault tree analysis module is used for performing fault mode analysis, probability computation, importance computation, sensitivity computation and uncertainty analysis on the given fault tree model; and the diagram display module is used for displaying a fault analysis result of the given system in a diagram form. The system and the method can accurately construct sequence and consequence fault trees, and perform various approximate computation and accurate computation on the successful branch of each function event of the event tree, so that the reliability is improved.

A method for dynamic human reliability analysis of a multi-unit nuclear power plant comprises that follow steps: first, modeling a human error event by using a dynamic event tree, analyzing human error of an operator of the multi-unit nuclear power plant, and determining a type of human error and a potential human error; 2, construct a causal model of human error based on that Bayesian network andthe data guide modeling technology, and calculating nominal human error probabilities of various human error by using the model; 3, establish a function of that behavior forming factor with respect to the time variable base on the numerical solution method of the inverse problem, and establishing a calculation format of the dynamic human error probability according to the obtained function relation; 4, analyze that dynamic feedback loop in the model established in the step 1 by use the system dynamics, and combining the calculation result in the step 2 and the calculation format of the dynamic human error probability established in the step 3, constructing a dynamic reliability quantitative analysis model, and calculate the quantitative calculation value of the human factor reliability.

The invention relates to the technical field of risk control, and provides a high-speed rail risk analysis and control method and a high-speed rail risk analysis and control system. The method includes the steps: performing cause analysis and effect analysis for hazardous events of a high-speed rail system by the aid of a fault tree and an event tree respectively, enabling m types of causes and n types of effects to form mXn accident sequences, and obtaining risk values of all the accident sequences; and sequencing all the accident sequences according to the risk values to obtain high-risk accident sequences, setting cause and effect control measures aiming at the high-risk accident sequences, and setting further failure control measures for preventing the cause and effect control measures from failing. The method and the system have the advantages that risk of the hazardous events is comprehensively predicated by means of risk analysis of the accident sequences, and the control measures are set by expanding the causes and the effects of the high-risk accident sequences, so that two elements forming the risk of the hazardous events are controlled respectively, and further the risk of the hazardous events is effectively controlled.

The invention relates to a data network risk evaluation method based on semi-physical simulation. The method comprises the following steps that the communication reliability is selected as an evaluation index of power telecommunication network failure; firstly, a fault tree and an event tree of the power telecommunication network failure are built, and the power telecommunication network failure reason is analyzed; then, a Bayesian network conversion algorithm is provided by respectively aiming at the fault tree and the event tree, and the power telecommunication network failure degree is judged by adopting a Bayesian network. The data network risk evaluation method has the advantages that the power telecommunication network failure is analyzed from the point of graph theory, the power telecommunication network failure reason is analyzed, and the communication reliability is selected as the evaluation index of the power telecommunication network failure.

The invention relates to a reservoir group outlet structure failure assessment method based on the Bayesian network. The reservoir group outlet structure failure assessment method includes the steps of establishing a Bayesian network topological structure, determining respective probability, calculating spillway system failure probability, and calculating the integral failure probability. The Bayesian network for failure probability determination is combined with a conventional event tree for determining stepped reservoir group spillway facility failure, and calculating the probability of downstream control step failure caused by upstream dam bursting flood is added as needed to form a complete Bayesian spillway facility failure assessment network. A reservoir group outlet structure failure is a complex multivariable system, and the assessment system can be used to analyze common cause failure and conduct backward inference. The assessment system can scientifically determine the value of information and determine whether new information needs to be acquired, so that the outlet structure failure analysis is gradually improved and becomes more scientific.

The invention discloses a log event extraction method and system based on a log tree and a parse tree. The method is divided into two steps of preprocessing and log content parsing, and the method specifically comprises the steps of providing and maintaining a rule base composed of regular expressions and heuristic rules, and extracting a small part of logs to automatically generate a log format; recognizing the log as a log head and log content on line based on the log format; searching the analytic tree, and respectively calculating the similarity between the static field and the dynamic parameter in the log tree and the event tree by adopting the longest common substring and the longest common subvector; and matching the log tree and the event tree by adopting a clustering technology, and extracting events and corresponding parameters. In order to cope with the complexity of the log content, the preprocessing and log content analysis steps in the online event extraction method are improved. The workload of manually recognizing log formats is reduced, the problem that an existing method is difficult to identify events containing uncertain number of parameters is solved, and log events are extracted more accurately.

The invention relates to a feature-based space multi-phase mission system reliability modeling method. The method comprises the steps of (1) analyzing a mission profile of a space multi-phase mission system, determining a system reliability feature, and defining a phase mission state and a system mission state; (2) proposing a space multi-phase mission system reliability modeling method, building a system mission reliability model by adopting a multi-state event tree (MSET) method, and building a phase mission reliability model by adopting a Markov chain (MC) method; (3) calculating a state occupation probability (SOP) matrix in a terminal stage of phase mission, and determining a phase mission state probability; (4) building a phase state transfer model, and determining a phase transfer probability; and (5) calculating a system mission state probability. According to the method, the mission reliability feature of the space multi-phase mission system can be accurately described, so that the built mission reliability model is more accurate.

A managing unit included in a distributed storage network (DSN) receives an event representation request, and identifies event record entries based on that request. The event record entries include information associating reporting entities with the event record entries. The management unit obtains the event record entries from the reporting entities; at least one event record entry is obtained from a first reporting entity, and at least another event record entry is obtained from a second reporting entity. In response to receiving the event representation request, the management unit generates a representation of the event record entries, and outputs the representation to a requesting entity.

The invention discloses a multi-fault diagnosis method based on an improved SDG, and belongs to the field of fault problem diagnosis. The multi-fault diagnosis method based on the improved SDG mainly comprises the step of establishing an engine entraining model, the step of establishing an SSDG model, the step of diagnosing a multi-fault problem, and the step of analyzing a fault node measuring sequence. According to the multi-fault diagnosis method, the multi-source fault source searching detection can be carried out, and the fault diagnosis can be more accurate. The fault of a large system is analyzed on the background of manufacturing a large airplane, and the fault source is found out. According to the multi-fault diagnosis method based on the improved SDG, the fault diagnosis is carried out with the SDG method, the method can carry out the analysis more thoroughly compared with an event tree method and an accident tree method, the defect that according to a traditional SDG method, only the single-fault source can be found out is overcome, the multi-fault source searching can be carried out with the multi-fault diagnosis method, and the fault diagnosis is more accurate.

A method is disclosed for generating event trees. The method includes receiving one or more events occurring within a networked computing environment. The method includes generating an event tree including the received one or more events. The method includes comparing the generated event tree with a plurality of event trees stored in a database. The method then includes assigning, based, at least in part, on the comparing, a probability to the generated event tree.

A method of providing an event tree enabling institutive understanding of the creation of electronic patient information including or any changes in electronic patient information, a server for performing the same, and a recording medium for storing the same are provided. A method for providing electronic patient information includes receiving electronic patient information of a patient from at least one terminal, identifying one or more events from the received electronic patient information, and generating an event tree of the patient based on the identified events, wherein the event tree graphically represents the electronic patient information of the patient.

The invention discloses a semantic network-based literature novelty evaluation system and method. The system includes a database, a data input device, an entity building module, an entity network similarity calculation module, an event construction module, an event network similarity calculation module and a novelty calculation module; the entity network structure similarity between the new literature and the works in the existing literature library is calculated to obtain the entity network similarity; the novelty of character characters and relations among works can be deeply mined and analyzed; The event tree similarity between new works and existing literature works is calculated; the novelty of the works is quantified from the perspective of story plot description; and finally, the novelty of the literature is evaluated by fusing the two indexes, namely the role character novelty and the story plot novelty, so that the defect of content semantic logic discrimination which cannot be realized by the existing article duplicate checking technology based on content matching is overcome, and meanwhile, more objective reference indexes are provided for literature reviewing personnel.

The invention provides a judicial case discrimination system based on event tree analysis. The judicial case discrimination system comprises a legal text collection module, an event tree constructionmodule, an automatic criminal name discrimination module and an automatic penalty discrimination module. The legal text collection module is used for converting legal statement text information submitted by a litigation user into noiseless text data; the event tree construction module is used for converting the legal text data into triple information related to the two entities through a natural language processing technology, and forming time sequence legal event tree information through a treebank; the automatic criminal name discrimination module is used for giving an automatic criminal name discrimination result through an event tree similarity matching algorithm; and the automatic penalty discrimination module is used for providing an automatic penalty discrimination result through anevent tree similarity matching algorithm on the premise of criminal name discrimination. The method has the advantages that the litigation user can be helped to quickly know the preliminary result ofcase judgment, and the system and method can help a judge to perform a final case discrimination.

The invention discloses a DET and RELAP5 coupled dynamic characteristic analysis method based on a universal auxiliary variable method, which comprises the following steps of: constructing a DET simulation model of a discrete dynamic event tree, and modifying an input file TRIP card in a manner of increasing universal auxiliary TRIP variables according to a DET simulation object state transition type; the universal auxiliary TRIP variable is a variable type or a logic type; the simulation time step length is controlled by setting the simulation time of the RELAP5 program, and an output result file of each simulation step length of the RELAP5 program is analyzed; According to the DET simulation object state transition type, backtracking and executing the RELAP5 program. The method has the advantages that the setting process and method of the DET state transition object TRIP in the RELAP5 program input file needed by DET and RELAP5 program coupling are simplified, the modeling complexity is reduced, and the modeling efficiency is improved.

The invention discloses a false information identification system and identification method based on event theme analysis. The system comprises a real event text collection module, an event tree construction module, a branch theme adhesion degree calculation module, a to-be-tested text reading module, a relevancy detection module and a branch adhesion degree comparison module. The method comprisesa real event text collection step, an event tree construction step, a branch theme adhesion degree calculation step, a to-be-tested text reading step, a relevancy detection step and a branch adhesiondegree comparison step. The system can provide help for users to distinguish false information in a network environment, so that the users can more quickly and effectively obtain real and reliable information. The false information identification efficiency is effectively improved, the time of a user is saved, the standardization of the information identification process is fully ensured, and theaccuracy of the identification result is improved.