26 results about "Reliability block diagram" patented technology

The invention provides a Monte Carlo reliability simulation method based on a SysML activity diagram, and relates to the technical field of system reliability modeling and reliability evaluation. The Monte Carlo reliability simulation method based on the SysML activity diagram comprises the following steps: step 1, carrying out system reliability modeling based on the SysML activity diagram; step 2, fault simulation based on discrete events; and step 3, reliability simulation based on Monte Carlo. According to the method, the SysML activity diagram is expanded, the reliability meta-model is built, then the system reliability block diagram model is built, a unified data source of system design and system reliability simulation is formed based on SysML, an information island between the system design and the system reliability simulation is broken through, the system design analysis efficiency is improved, the SysML is adopted to build the system reliability block diagram model, a tracing mechanism is easily built, and the system reliability simulation efficiency is improved. When the system design is changed, the system reliability block diagram can be correspondingly changed in time, and the consistency is ensured.

A flight control equipment reliability allocation iterative optimization and dynamic prediction method comprises the following steps: constructing a Bayesian network through a system reliability block diagram of FMEA at an offline stage, expanding the Bayesian network, updating the network by taking a failure probability as a prior probability, and performing system reliability check to obtain a Bayesian network considering weight nodes; setting a conditional probability table and prior distribution of weight nodes; in the online stage, reliability is obtained through calculation according to the service life data of the parts, then the reliability is updated to be the prior probability in the Bayesian network, upward reasoning is conducted through the Bayesian network, and a real-time reliability predicted value is obtained. The Bayesian network is used for integrating prior knowledge and sample data, the variable dependency relationship is expressed through the conditional probability table, joint probability distribution is simplified, and the method is suitable for complex causal relationship modeling in reliability analysis.

The invention discloses an unmanned transportation system operation reliability analysis method based on a cloud control platform, and the method comprises the steps: obtaining a task success definition, a judgment criterion and a reliability block diagram of an unmanned mine car system in a transportation stage, and an adjacent matrix through the analysis of an unmanned mine car transportation task process; according to mine car fault type analysis, the influence of mine car faults with different properties on the unmanned transportation system is obtained, and an unmanned mine car task success judgment model is established; and the task success rate of the unmanned mine car and the related fault type conclusion are obtained in combination with historical data of the cloud control platform, and a final unmanned transportation system operation reliability analysis result is obtained. The conclusion of the task success rate and the fault type is obtained by constructing the model, reference and basis are provided for corresponding research of risk management of the unmanned transportation system, and a foundation is laid for task success and efficiency research of the unmanned transportation system, fault maintenance spare part requirements and the like.

The application discloses a steam generator system reliability calculation method and equipment based on a digital simulation method, which can realize the failure-free time interval and task reliability evaluation of the whole steam generator system. The method first establishes a reliability block diagram of the steam generator, and then establishes a reliability mathematical analysis model of the whole steam generator system about each component subsystem. Secondly, the failure time sample of the component subsystem and a sample virtual extension evaluation method based on Bootstrap are used to fit the failure time probability density function. According to the failure time probability density function, the MCMC digital simulation method is used to extract the failure time sample, which is substituted into the system reliability analysis model to finally calculate the average failure-free interval and task reliability of the whole machine. The method can effectively evaluate the reliability simulation of the steam generator, and when the task reliability threshold value is given, the method can give a warning for the operation reliability of the steam generator.

The invention relates to the technical field of reliability engineering, in particular to a reliability evaluation method and evaluation device for an engineering production system, and the method comprises the steps: obtaining a reliability block diagram of the engineering production system, determining the metadata of each function block, generating a reliability function network, marking a typical reliability structure unit, and obtaining a reliability function network; the method comprises the following steps: determining a function subnet, configuring a time domain strategy to generate a self-adaptive time grid, solving the equivalent reliability of the function subnet at a self-adaptive time point of the self-adaptive time grid to obtain a reliability sampling sequence of the engineering production system, and generating a reliability evaluation result. Therefore, the problems that in the related technology, due to the fact that semantic information corresponding to a reliability block diagram depends on manual disassembly, and a reliability evaluation result is calculated through fixed step size discrete approximation, missed judgment and misjudged are likely to occur due to complex topology, the calculation precision is poor in a high-risk time period, the calculation efficiency is low in a stable time period, and engineering decision is difficult to support are solved.

The present invention relates to the technical field of aircraft health management, and discloses an electronic equipment health assessment device, including a component-level health assessment module and a system-level health assessment module. The component-level health assessment module includes a fuzzy severity level calculation module and a component health calculation module, and the system-level health assessment module includes a component weight adaptive construction module and a system health calculation module. The present invention realizes the health assessment of electronic equipment in the absence of status monitoring parameters, dynamically assesses the health status of components based on component failure risks and in-machine self-test information, and dynamically assesses the health status of the system based on the system reliability block diagram and the adaptive weights of the components, thereby improving the health management capability of the aircraft and contributing to the realization of autonomous health management of the aircraft.

The invention belongs to the technical field of unmanned aerial vehicles, and particularly discloses an unmanned aerial vehicle flight control system reliability prediction method based on component secondary screening data, which comprises the following steps: establishing a component secondary screening data matrix of an unmanned aerial vehicle flight control system, and performing component reliability model parameter estimation; obtaining reliability model parameters of various types of components in the unmanned aerial vehicle flight control system; dividing key function modules of the unmanned aerial vehicle flight control system and constructing a reliability block diagram of the unmanned aerial vehicle flight control system; and performing reliability prediction of the unmanned aerial vehicle flight control system by using a Monte Carlo sampling method based on reliability model parameters of various types of components in the unmanned aerial vehicle flight control system, key function modules of the unmanned aerial vehicle flight control system and a reliability block diagram structure of the unmanned aerial vehicle flight control system. According to the method, the problems of low data utilization rate, poor model relevance, high modeling complexity and insufficient random processing capability of an existing method are solved, and comprehensive, scientific and efficient reliability prediction of the flight control system of the unmanned aerial vehicle is realized.

The application discloses a kind of based on reliability block diagram numerical control system evaluation method, it is related to numerical control system reliability evaluation technical field, including: selecting the key component in numerical control system carries out temperature-humidity double stress accelerated degradation test, obtains degradation data, and establishes performance degradation model and generalized Eyring temperature-humidity double stress coupling acceleration model based on degradation data, obtains reliability function and temperature humidity stress-degradation parameter mapping relationship;The application is accurately calibrated by temperature-humidity double stress accelerated degradation test and generalized Eyring model, again in combination with real-time field environment data, realizes the state monitoring and optimization guidance of the continuous, self-adapting, precision of numerical control system reliability.

The application discloses a kind of based on deep reinforcement learning and important sampling electromechanical system reliability evaluation method, first establish complex electromechanical system reliability block diagram, then analyze the sensor data of each level operating state of system, build electromechanical system sensor data and multi-physics field performance simulation analysis fusion dataset, then establish the reliability evaluation model based on deep reinforcement learning, based on the important sampling strategy of adaptive MCMC, the reliability of electromechanical system is evaluated, finally, the reliability sensitivity of electromechanical system operating parameters is analyzed, the operating parameters are optimized based on particle swarm intelligence algorithm, and the effectiveness of the optimization strategy is verified through environmental information.The method of the application combines the intelligent decision-making capability of deep reinforcement learning and the adaptive sampling strategy of important sampling, reduces the computing resources and time required for evaluation, while improving the accuracy and reliability of the evaluation results, to better support the design, maintenance and optimization decisions of electromechanical systems.

The present invention belongs to the technical field of unmanned aerial vehicles, and specifically discloses a method for predicting the reliability of an unmanned aerial vehicle flight control system based on the data of secondary screening of components, including: establishing a data matrix of secondary screening of components for the unmanned aerial vehicle flight control system, and estimating the parameters of the component reliability model to obtain the reliability model parameters of each type of component in the unmanned aerial vehicle flight control system; dividing the key functional modules of the unmanned aerial vehicle flight control system and constructing a reliability block diagram of the unmanned aerial vehicle flight control system; based on the reliability model parameters of each type of component in the unmanned aerial vehicle flight control system, the key functional modules of the unmanned aerial vehicle flight control system, and the structure of the reliability block diagram of the unmanned aerial vehicle flight control system, using the Monte Carlo sampling method to predict the reliability of the unmanned aerial vehicle flight control system. The present invention solves the problems of low data utilization rate, poor model correlation, high modeling complexity, and insufficient randomness processing ability of the existing methods, and realizes the comprehensiveness, scientificity, and efficiency of the reliability prediction of the unmanned aerial vehicle flight control system.

The present invention belongs to the technical field related to reliability assessment, and discloses a reliability block diagram and calculation method of a series-parallel system based on discrete event simulation. The reliability block diagram includes multiple reliability components and multiple synchronization components. The reliability components correspond one-to-one to the components in the series-parallel system to be processed, and the connection relationship between the reliability components is connected according to the connection relationship between the components; the starting point and the end point of the model are provided with a starting node and an end point node, and the reliability components are directly connected through connecting lines to form a series relationship, and the front and rear ends of the modules formed by the parallel reliability components are respectively inserted with a node and the reliability components are connected to the nodes through connecting lines, and one node corresponds to one synchronization component. The present invention also discloses a calculation method for the reliability of the above reliability block diagram. Through the present invention, the problem that the reliability model and reliability value calculation of the series-parallel system cannot be established through discrete event simulation is solved.

The invention discloses a reliability analysis integrated application method of a carrier rocket control system, and the method combines the technologies of state simulation modeling, path traversal searching, reliability block diagram modeling and the like, and builds a reliability analysis system facing a complex system. The method can effectively solve the problems of a traditional method in the aspects of component state modeling, sequential logic processing, system-level netlist data analysis and the like, and powerful technical support is provided for development of a high-reliability system.

The invention discloses a mine car system reliability redundancy optimization method based on a maintenance process, and the method comprises the steps: collecting various data based on sensing equipment and a mine car system, and carrying out the data analysis; evaluating the reliability of the mine car system based on an addition risk model; generating a mine car system reliability block diagram based on redundancy design; calculating mine car system reliability based on the evaluation result and the reliability block diagram; judging whether the total maintenance cost of the mine car system is greater than a cost constraint, if so, re-evaluating, otherwise, outputting a maintenance scheme; and quantifying the maintenance effect, calculating various maintenance indexes, and outputting an optimal maintenance scheme according to a maintenance strategy. According to the method, the reliability design optimization of the series-parallel mine car system can be effectively solved by considering the influence of the cooperative change of the redundant units on the reliability, the cost, the volume, the quality, the power consumption and other performance parameters of the complex system.

The application belongs to the technical field of reliability evaluation, and discloses a ship system reliability calculation method and system based on discrete events and Monte Carlo simulation. The method comprises the following steps: (a) constructing a simulation model according to a reliability block diagram of a ship system to be processed; (b) setting a simulation test number N according to a total task of the ship system to be processed; (c) for the i-th simulation test, setting a simulation time, a time interval of token generation, generating a plurality of tokens with a label of 0 at a reliability entrance, transmitting each token along a corresponding directed connection line, updating the label in the transmission process, and obtaining a final label when the token reaches a reliability exit; (d) i = i + 1, repeating step (c) until i > N, obtaining the final labels of all tokens in all simulation tests, and calculating the reliability of the simulation model by using the final labels of all tokens. Through the application, the problem that the reliability of a complex system is difficult to calculate is solved.

The invention discloses a reliability evaluation method for a high-voltage direct-current power transmission system containing high-proportion new energy, and relates to the technical field of high-voltage direct-current power transmission systems.The reliability evaluation method comprises the steps that firstly, a reliability block diagram of a multi-terminal high-voltage direct-current power transmission system is constructed, and a subsystem division method is used for decomposing a complex system into smaller manageable subsystems; then, the reliability of the subsystems is analyzed through a state enumeration technology and a cascade network method, and reliability equivalent parameters, including the failure rate, the failure frequency and the repair time, of each subsystem are calculated; then, based on the internal connection relation of the subsystems, generating a system reliability block diagram, and calculating the reliability index of the whole system; in addition, the output fluctuation of the new energy base at the sending end and all possible system states are considered, the forced energy unavailability index of the receiving end is comprehensively calculated, and the overall reliability index of the system is synthesized.

The application discloses a kind of atmospheric and vacuum distillation unit system reliability calculation method, it includes the following steps: establishing the equipment set involved in all process flows;The equipment set involved in all process flows established is divided into a module unit according to certain connection mode according to the same function of the equipment in the same process flow node;According to the determination coefficient, determine the connection mode of each module unit in the system reliability block diagram;Obtain the reliability of each module unit;And according to the reliability of each module unit and the connection mode of each module unit in the system reliability block diagram, calculate system reliability.The application further discloses an atmospheric and vacuum distillation unit system reliability calculation system, electronic equipment and storage medium.The application divides module unit, determines the connection relationship of module unit in the system reliability block diagram according to the determination coefficient, on the one hand, ensures the accuracy and comprehensiveness of calculation, on the other hand, improves the calculation efficiency.

The invention discloses a ship electronic information system task reliability qualitative analysis method and device, a medium and a product, and relates to the field of task reliability analysis. The method comprises the steps that after an SFT model is constructed based on external influence factors, features and a probability function equation are solved; constructing a reliability block diagram of each stage based on a solving result and the internal influence factors, converting the reliability block diagram into an SFT model, and performing equivalence on the SFT model based on an infinitesimal substitution principle and performing integration to obtain an ISFT model of the whole stage; representing a structure function as a Boolean function based on an overall stage ISFT model, and obtaining system reliability through non-intersection; a basic event is determined based on system reliability, an AHP model is established, after an AHP judgment matrix is obtained, the weight of each layer in the AHP model is determined, hierarchical sorting and consistency verification are carried out, and qualitative analysis of task reliability is achieved. The problems that an existing reliability analysis method is poor in qualitative effect, incomplete in analysis and the like can be solved.

According to the method and the equipment for calculating the reliability of the steam generator system based on the digital simulation method, the fault-free time interval and task reliability evaluation of the whole steam generator system can be realized. The method comprises the following steps: firstly, establishing a reliability block diagram of the steam generator, and then establishing a reliability mathematical analysis model of a steam generator complete machine system about each component subsystem; secondly, fitting a failure time probability density function by utilizing a failure time sample of a component subsystem and a Bootstrap-based sample virtual augmentation evaluation method; and according to the failure time probability density function, an MCMC digital simulation method is adopted to extract a failure time sample, the failure time sample is substituted into the system reliability analysis model, and finally the average fault-free interval and the task reliability of the whole machine are obtained through calculation. According to the method, reliability simulation evaluation can be effectively carried out on the steam generator, and when a task reliability threshold value is given, early warning can be effectively carried out on the operation reliability of the steam generator through the method.

The invention relates to a mine car hardware reliability assessment method, which comprises the following steps of: acquiring failure data of key parts of a mine car, calculating to obtain an empirical function value, sequencing failure time according to a time sequence to obtain a part service life sequence number, namely a failure rank, and calculating an empirical distribution function by an approximate median rank formula; evaluating the reliability of the subsystems, and determining the reliability of the subsystems; constructing a system reliability block diagram, and establishing a mine car system structure tree according to three working logics of series connection, parallel connection and redundancy between mine car systems; and maintenance importance determination: finding out a key subsystem influencing the reliability of the system, and then finding out key parts according to the importance as the direction and path for determining the maintenance importance. According to the method, the influence of high redundancy, maintainability, nonlinearity and other structural characteristics of the mine car on the reliability state is described by using a maintenance importance index. From the part level to the system level, weighted integration is carried out based on the system structure tree model of the maintenance importance degree, and mine car multi-level reliability state evaluation is achieved.

The invention discloses a large-scale complex system reliability test and evaluation method based on multiple distributions and related equipment. The method comprises the following steps: determining a to-be-tested system based on a task unit of a large-scale system, and obtaining a reliability block diagram and type data of each product; determining the tightening system test duration of the tested sample machine in each product based on the tightening ratio; performing a laboratory reliability test on the large-scale system based on the test duration of the tightening system to obtain first test data; independently taking out the electronic and electrical part to carry out a laboratory reliability test, and carrying out a system-level bench test on a product of the electromechanical part or collecting live operation data to obtain second test data; and performing corresponding reliability evaluation on the products of different distribution types to obtain the reliability of the products of each distribution type, and finally converting according to the system reliability block diagram to obtain the system reliability. The reliability verification implementation problem of a large-scale system can be solved, and the method can be widely applied to the technical field of data processing.

The invention discloses a thermal power plant system earthquake vulnerability evaluation method based on a reliability block diagram and Monte Carlo simulation. The method comprises the following steps: establishing a reliability block diagram model; defining a residual function state function of the thermal power plant system; determining parameters in the earthquake vulnerability curve of each component in the thermal power plant system; based on the earthquake vulnerability curve, the reliability block diagram model and the residual function state function of each component in the thermal power plant system, calculating failure probability sample points of different residual function states of the thermal power plant system under different earthquake oscillation intensity parameters through a Monte Carlo simulation method; and performing curve nonlinear fitting on the failure probability sample points to obtain earthquake vulnerability curves of different residual function states of the thermal power plant system. According to the thermal power plant system earthquake vulnerability evaluation method, the earthquake vulnerability analysis of the thermal power plant system level can be realized based on the earthquake vulnerability curve of the thermal power plant component level.

The invention relates to an aircraft LRU system-level life prediction method and device based on a network diagram, and the method comprises the steps: converting a reliability block diagram of a system into a network diagram; obtaining the residual life of each component in the system based on the degradation model of the component and the Monte Carlo simulation technology; arranging the residual lives of all the components in the system according to an ascending order, and simulating system running time according to the residual life with the arrangement result being the first bit; comparing the system operation time with the residual life, and determining a failure component; the directed edges in the network diagram corresponding to the failed components are deleted, reconstruction of the network diagram is completed, the reconstructed network diagram is analyzed, and connectivity from the source node to the target node is judged; if so, selecting the next residual life simulation system operation time of the current arrangement result, and repeating the above steps; and if not, determining the system operation time record as the system residual life. According to the method, the capability of predictive maintenance of the aircraft LRU is improved.

The invention discloses a ship equipment task reliability quantitative prediction method, equipment, a medium and a product, and relates to the field of ship equipment design and evaluation. The method comprises the following steps: constructing an equipment state matrix based on an equipment state model, constructing an equipment state and reliability combined matrix, and setting a corresponding equipment reliability block diagram for tasks in the combined matrix. Based on the block diagram, fault criteria are formulated for each task stage; determining a system state value based on the constructed joint matrix, constructing a Monte Carlo simulation framework, and obtaining a task reliability index based on a fault criterion and the system state value by adopting the framework; and constructing a task reliability optimal index intelligent selection model, and inputting the task reliability index into the model to obtain a task reliability prediction result. According to the method, the accuracy of quantitative analysis of the reliability of the ship equipment task can be remarkably improved, and solid data support is provided for maintenance and management of the ship equipment, so that the overall operation efficiency and safety of the ship are improved.

The invention discloses an automobile system reliability test specification establishment method and system, and belongs to the technical field of automobile system tests.The method comprises the steps that the object and range of an automobile system reliability test are determined through a reliability block diagram analysis method, and automobile system composition and structure analysis is conducted; performing automobile system function and performance analysis on the object and range of the automobile system reliability test based on the result of the automobile system composition and structure analysis; on the basis of automobile system function and performance analysis, environment stress, a user use environment and a user scene borne by an automobile system in the storage and transportation processes and during service are simulated; and identifying a comprehensive stress influence result generated by the stress on the reliability of the automobile system by adopting an accelerated test method, and establishing an automobile system reliability test specification based on the comprehensive stress influence result. According to the method, through combination of automobile system analysis, acceleration test and data driving, efficiency and precision of reliability verification are improved.

This application proposes a method and system for reliability assessment of telemetry devices based on MBSE. The method constructs a unified multi-view model using MBSE and SysML, integrating reliability requirements, structure, behavior, and parameters into a single data base, thus completely resolving the problems of disconnect between traditional reliability analysis and system design, data inconsistency, and difficulty in traceability. It should be noted that traditional methods often involve reliability analysis in the later stages of design, while this application allows for reliability modeling during the conceptual design phase. Furthermore, this application automates the generation of reliability analysis models, improving efficiency and accuracy. This application can automatically parse component connection relationships and redundant logic from the SysML structural model, generating reliability block diagrams or fault trees with a single click, replacing traditional manual drawing methods. In the embodiments of this application, this automated process significantly shortens modeling time, eliminates human error, and ensures real-time synchronization between the reliability model and the system design.

The invention provides a reliability block diagram model design method and device for graphical dragging, a storage medium and a program product, and relates to the technical field of reliability modeling, the method comprises the following steps: in response to dragging operation of a user on blocks, connecting lines and connecting point elements on a graphical modeling interface, constructing a reliability block diagram initial model, the connection point element supports configuration of at least one redundancy attribute type; receiving failure data configured by a user for each model unit, and establishing a data link between the failure data and the reliability-related data to generate a target reliability block diagram model, the failure data including at least one failure distribution type; performing automatic verification on the target reliability block diagram model according to the data link to generate an automatic verification result; and when the verification is passed, reliability calculation is carried out according to the redundancy attribute type and the failure distribution type, and a reliability calculation result is obtained. The technical problem that the accuracy of reliability block diagram model design is low in the prior art is solved.