63 results about "Dynamic reliability" patented technology

The invention discloses a cable-stayed bridge cross brace optimization system based on system reliability and an intelligent algorithm, which relates to the technical field of bridge engineering, and comprises a multi-source parameter input module used for collecting and processing data such as a main beam section, stay cable parameters, a strain sequence, a vibration sequence, a satellite cloud picture, a traffic monitoring flow, laser point cloud and the like; and outputting the structured design data, the monitoring data flow, the dynamic load spectrum, the probability distribution model and the construction error correction parameters. According to the invention, all-dimensional data such as design, monitoring, load, materials and construction errors are integrated through the multi-source parameter input module, and multi-level and dynamic reliability evaluation is carried out on the component, the subsystem and the system level by using the system reliability analysis module, so that the component failure probability, the system reliability index time sequence and the like can be output; therefore, the real reliability level of the cross brace of the cable-stayed bridge in the whole life cycle is reflected more accurately, and the one-sidedness of a traditional method is avoided.

The invention discloses a reliability index distribution method and system suitable for a ship power system. The objective of the invention is to overcome the defects of a traditional ship power system reliability evaluation method in the aspects of dynamic performance, real-time performance and adaptability. According to the method, real-time operation data, including temperature, pressure, vibration frequency, abrasion loss and other key parameters, of all subsystems in a ship power system are collected, and dynamic reliability influence factors are constructed based on the data. By introducing a deep reinforcement learning model, the system can adjust the weight coefficient of each subsystem according to the current dynamic reliability influence factor. In addition, in combination with historical fault data, a fault propagation path is modeled through a graph neural network (GNN), and a fault rate correction factor is calculated, so that the accuracy of reliability distribution is improved. And finally, verifying the rationality of a reliability distribution result through a Monte Carlo simulation method, and dynamically adjusting system parameters according to a simulation result to ensure stable operation of the ship power system.

The application discloses a dynamic reliability evaluation method for a permanent magnet planetary gear transmission system, and belongs to the technical field of reliability analysis of electromechanical coupling transmission systems. The method is characterized in that: firstly, the service process of the system is divided into stages, and a random variable model is established; based on the wear evolution relationship, parameters of each stage are obtained through parameter mapping; then, stage high-fidelity unified electromechanical dynamics solving is performed, and frequency-related characteristic indexes are extracted; a multi-failure mode limit state vector is constructed, and a stage failure event is defined; on this basis, a multi-response Gaussian process proxy model is used for fitting and iterative updating of the limit state function through stage-by-stage active learning; the U function is used for initial screening of candidate samples, EFF is calculated and sorted, and a new sample point is selected according to the Top-K criterion to update the proxy model, until the convergence criterion is met; finally, the dynamic failure probability of the system is calculated by using the updated proxy model. The application realizes efficient and accurate evaluation of the failure probability of multiple failure modes, reduces the calculation cost, and improves the engineering applicability.

The invention discloses a Bayesian reasoning method for high-voltage power supply reliability under common cause failure influence, and belongs to the technical field of high-voltage power supply reliability analysis. Constructing a dynamic fault tree of the high-voltage power supply; acquiring the proportion of common cause failure in each pair of bottom event failures, and collecting evaluation suggestions for the proportion of the bottom event to construct a fuzzy matrix; determining common cause failure factors of common cause failure of each pair of bottom events; the dynamic fault tree of common cause failure is converted into a discrete time Bayesian network, and a Bayesian network graph, a conditional probability table and a marginal probability table are obtained respectively; and performing bidirectional reasoning on the dynamic reliability of the high-voltage power supply, and calculating reliability and maintainability indexes of the high-voltage power supply in each time period. According to the method, the common cause failure factor is determined through the fuzzy theory, and the dynamic fault tree considering common cause failure is mapped into the Bayesian network for reliability analysis, so that the problems that the common cause failure factor is difficult to determine and the reliability analysis calculation amount is too large are solved, and the high-voltage power supply reliability analysis precision and calculation efficiency are effectively improved.

The invention belongs to the technical field of power systems, and relates to a reliability evaluation method and system for an extreme meteorological new energy high-permeability power system. The method comprises the following steps: judging extreme meteorology, and constructing a new energy output and meteorological factor coupling model under the extreme meteorology; establishing a system operation model considering extreme meteorology, and obtaining system operation state parameters and power distribution parameters; calculating a short-time index reliability score and an ultra-short-time index reliability score of the system under each extreme weather and different time length scales; and fusing the reliability scores to obtain a comprehensive reliability score. The method can accurately describe the instantaneous impact and short-term influence of the extreme weather on the operation of the new energy high-permeability power system, and realizes the quantitative analysis of the reliability of the system; the reliability indexes of the system are divided into a short-time type and an ultra-short-time type, the power shortage risks under different time scales can be captured respectively, and more refined and dynamic reliability evaluation is provided for system operation under extreme weather.

The invention relates to the technical field of data processing, in particular to a PLM-based BOM data management method and system, and the method comprises the steps: obtaining product BOM basic data, complementing missing parameters needed by MTBF calculation, and obtaining a calculation-ready BOM; splitting function fragments for the calculation-ready BOM according to a hierarchical structure, deploying MTBF calculation nodes, and calling the function fragments for calculation to obtain a dynamic reliability calculation result; a dynamic reliability calculation result is analyzed through a decision tree algorithm, BOM potential fault points are identified, risks are quantified, an optimization scheme is generated by combining PLM with a component reliability knowledge base, and an optimized reliability calculation result is obtained; and based on an optimized reliability calculation result, integrating key value-added contents through an intelligent enhancement system, normalizing a report format according to bid invitation requirements, and generating a standardized reliability prediction report. According to the scheme, a BOM full-process closed-loop mechanism with deep cooperation of the PLM and the MTBF is constructed, and the reliability and the accuracy are improved.

This invention discloses a method for calculating the dynamic reliability of electromechanical systems based on inter-component interoperability, comprising: (1) constructing a hidden Markov model for system risk transmission and an inter-component risk state transmission matrix; (2) combining load effects to calculate inter-component interoperability and resistance coefficients, quantifying relevant parameters of the state transition matrix, and calculating the probability that the risk of a component will not escalate after risk transmission; (3) applying inter-component interoperability, determining the final state sequence of the system based on the idea of ​​stochastic computation, and calculating the dynamic reliability of the system. For complex electromechanical systems, the interoperability calculation method of this invention can make the system reliability calculation closer to the actual situation, and based on this, an improved maintenance strategy is proposed. Compared with the traditional maintenance strategy, the maintenance strategy considering inter-component interoperability proposed in this invention can maintain the system at a higher reliability and have a lower maintenance cost in the long term.

This invention relates to the field of disaster prevention and mitigation technology for marine engineering structures, and discloses a method for plotting vulnerability curves of guide seawall structures based on random load combinations. The method includes: constructing a nonlinear finite element model of a deep-water guide seawall; introducing a two-dimensional phase coupling vector to generate random dynamic load samples containing temporal coupling characteristics of earthquakes and waves; inputting the samples into the model, tracking the structural frequency drift in real time and considering pore flow abrupt change damping, and calculating the multidimensional dynamic response of the structure; constructing a multidimensional dynamic limit state surface that shrinks with cumulative plastic damage, and determining the failure state based on the relative relationship between the dynamic response and the state surface; estimating the failure probability using extreme value statistics theory, and establishing a probabilistic demand model containing cross-coupling terms of earthquake and wave intensity; and plotting a vulnerability surface describing the change of the failure probability with bivariate strength indices based on this model. This invention can accurately assess the dynamic reliability of deep-water guide seawalls under the coupling effects of multiple disasters.

The invention belongs to the technical field of power system reliability evaluation, and particularly relates to an offshore wind power grid-connected system reliability evaluation method based on vector Lz transformation. The method comprises the following steps: constructing an offshore wind power grid-connected system reliability evaluation model based on vector Lz transformation; and introducing the vulnerability-based key index into the reliability evaluation model of the offshore wind power grid-connected system, and carrying out reliability evaluation calculation on the offshore wind power grid-connected system. According to the invention, the dynamic reliability evaluation of the equipment in different states is realized, and the state change and fault risk of the wind power system in a severe marine environment are accurately evaluated; the multi-state change characteristics of the equipment are comprehensively described, the accuracy of reliability analysis is improved, the mutual influence among the equipment is accurately described, the evaluation capability of the overall reliability of the system is enhanced, and the safety, the operation stability and the system evaluation efficiency of the system are improved.

The invention provides a fastening connection system reliability dynamic modeling method which comprises the following steps: establishing a reliability model of fracture failure and loosening failure of a single threaded connection pair to obtain the reliability of the single threaded connection pair in different failure modes; based on a multi-competitive failure mode of a single threaded connection pair, establishing a dynamic reliability model of the fastening connection system under consideration of dynamic degradation by introducing an exponential decay model; wherein the exponential decay model is used for representing the decay process of the bolt pre-tightening force and strength along with time; and constructing a general generation function of each threaded connection pair for performing dynamic reliability calculation on the dynamic reliability model of the fastening connection system, and determining an optimal maintenance interval. According to the method, the multi-competition failure problem of fracture failure and loosening failure of a single threaded connection layer is effectively solved, the method better conforms to engineering practice, calculation is convenient and easy, implementation is easy, and engineering technicians can conveniently master the method.

The application discloses a multi-factor coupling error compensation calibration method for gas cylinder external water pressure test, and relates to the technical field of special equipment.The application couples and weights each systematic error value, the corresponding error effectiveness coefficient and the preset weight coefficient to generate a high-precision compensated standard bottle calibration deformation, and uses the same as the final calibration value of the standard bottle to calibrate the water pressure test device, simultaneously updates the calibration parameter library to form a closed-loop feedback.In general, the application adopts a three-in-one technical path of multi-factor decoupling, dynamic reliability evaluation and adaptive weighted compensation, greatly improves the accuracy, stability and repeatability of the standard bottle calibration result, fundamentally enhances the overall reliability and intelligent level of the gas cylinder water pressure test system, and provides solid technical support for the safety inspection of special equipment.

This invention provides a dynamic reliability analysis method for double-laminated insulated glass under wind loads, belonging to the field of stress analysis technology for building curtain wall glass. This method proposes a dynamic reliability analysis approach for double-laminated insulated glass under wind loads. First, a finite element analysis model of the double-laminated insulated glass is established, considering the coupling problem between the interlayer structure and the flow field within the cavity. The differences between the finite element model and experimental results, as well as the differences between the sub-parts of the finite element model and the numerical algorithm, are compared. Then, the structural response under two common wind loads is calculated, and a dynamic reliability analysis process is constructed. This solves the problem that current double-laminated insulated glass design relies entirely on empirical formulas, and the finite element model is interpretable. The accuracy of the finite element model is verified from both theoretical and experimental perspectives. A comprehensive wind load damage model is established, comprehensively considering the influence of typhoons and natural winds.

The invention provides a hydraulic structure periodicity reliability evaluation method and device based on monitoring and early warning, and relates to the technical field of hydraulic structure health monitoring. The method comprises the following steps: establishing a dynamic model containing a basic random variable set, defining a concerned physical quantity vector and setting prior probability distribution; fuzzy fusion is carried out on the denoised multi-source monitoring signals to obtain real-time graded early warning; carrying out representative time period division; extracting a time sequence feature vector from a denoised signal; correcting prior probability distribution and selecting a representative point; obtaining a generalized speed according to deterministic dynamics analysis; and performing graded early warning according to the comprehensive membership degree. According to the method, physical interpretability and data assimilation capability are considered, and large-scale Monte Carlo is replaced by representative point approximation and numerical evolution, so that the calculation amount can be reduced, and the real-time performance and precision of dynamic reliability evaluation can be improved.

This invention discloses a dimension-reduction reliability assessment method for switched reluctance motors (SRMs) that considers repairability. This method analyzes the faults of the SRM at structural levels, comprehensively converting the failure probabilities of each underlying component into overall system state transition parameters. Based on this, the repairability rate is calculated according to the actual periodic maintenance cycle of the equipment, and a Markov state transition equation system containing maintenance recovery paths is established. To avoid complex calculus operations involving high-order matrices, this invention utilizes Laplace transform to convert the dynamic process into algebraic calculations in the complex frequency domain, achieving analytical order reduction of the model. By performing algebraic analysis on the complex frequency domain function, the dynamic reliability function and mean time between failures (MTBF) of the system are directly obtained. This invention overcomes the shortcomings of traditional models, such as cumbersome computation and unrealistic lifespan predictions. While effectively reducing the computational complexity of microcontrollers, it significantly improves the accuracy of lifespan prediction for motor drive systems and enhances their engineering application value.

The application discloses a nonlinear random structure dynamic reliability calculation method, and belongs to the field of structure health monitoring, comprising the following steps: collecting structure dynamic response data, and extracting high-order component signals of the structure dynamic response; correcting a random structure nonlinear model of an actual structure, and determining the probability distribution of the random structure nonlinear model parameters; applying external excitation load to the random structure nonlinear model, establishing a nonlinear random structure dynamic response state equation, and obtaining a probability density evolution equation; applying an absorbing boundary condition to the structure dynamic response according to a first exceeding failure criterion, combining a finite difference method and a nonlinear time-history integration method, obtaining the structure dynamic reliability changing with time under the dynamic load, and realizing the quantification of the reliability evolution process of the actual structure under the external load, avoiding the response assumption in the traditional reliability calculation process, and improving the calculation precision of the structure reliability.

The invention discloses a distributed intelligent power distribution network reliability influence factor analysis method and system, and relates to the technical field of influence factor analysis, and the method comprises the following steps: obtaining the operation state of a power distribution network in a target region, and constructing a topology-control mode table; performing uncertainty labeling on the key equipment to form a structural uncertainty matrix; coupling the structural uncertainty matrix with node operation data, establishing a reliability model, calculating the sensitivity of each uncertain structural unit to the reliability index of the whole system, and generating a structural sensitivity vector; and combining the structural sensitivity vector with real-time operation data to form a dynamic reliability influence factor table, and constructing a topology-control mode table. According to the method, the dynamic reliability influence factor table is generated by establishing the structure-state coupling reliability model, so that the problem that key influence factors are inaccurately identified due to the fact that the influence of topological change and control mode switching on the system reliability is not comprehensively considered in the prior art is solved.

Methods, systems, and devices for wireless communication are described. A vehicle user equipment (VUE) may generate a multicast message for transmission in an Internet of Vehicles (V2X) system. The VUE may transmit the multicast message using a transmit power based on a reliability distance corresponding to an area for providing feedback for the multicast message, wherein the reliability distance is based on one or more positioning parameters of the VUE and one or more environmental parameters associated with the V2X system. The VUE may then monitor feedback for the multicast message.

The present application belongs to the field of marine engineering equipment design and detection technology, and particularly relates to a kind of marine oil and gas development well control equipment control system toughness design method.The design method takes marine oil and gas development well control equipment control system as engineering background, takes full life cycle as design optimization time scale, comprehensively considers the coupling of system natural degradation and external impact, combines dynamic reliability, redundancy configuration and maintenance strategy, realizes the optimal control of system reliability and total cost in full life cycle.The design method includes: evaluating the dynamic reliability of marine oil and gas development well control equipment control system in full life cycle;evaluating the total cost of marine oil and gas development well control equipment control system in full life cycle;determining the integrated optimization target of reliability and redundancy;obtaining the Pareto optimal frontier solution of reliability and redundancy;using TOPSIS decision method, obtaining the optimal solution of toughness design.

The application provides a steel structure calculation method and system based on physical logic anchoring and heterogeneous decoupling, and relates to the technical field of intelligent steel structure calculation. The method comprises the following steps: extracting user's unstructured engineering requirements into a structured feature vector, constructing a directed acyclic computation graph along a knowledge graph; starting knowledge graph reasoning and retrieval enhancement in parallel to generate a two-way evidence, calculating a logic anchoring coefficient Lambda, which includes a number version consistency judgment, a specification timeliness dynamic weight and a strong item penalty, comparing Lambda with a dynamic reliability threshold and executing a three-branch decision to eliminate index illusion; routing the calculation instruction to a physically isolated sandbox after triple audit to determine the solution and eliminate calculation illusion; based on the logic dependence hypergraph, the dissenting node is traced back and locally recalculated, and a compliant calculation report is output. From the architecture level, the calculation illusion and index illusion in the steel structure calculation are eliminated, and the industrial numerical precision and reliable specification compliance traceability are realized.

The invention discloses a bridge structure system dynamic reliability assessment method, and belongs to the technical field of bridge structure reliability assessment. The method comprises the following steps: 1, determining a reliability calculation typical section according to bridge structure characteristics and monitoring system arrangement; 2, calculating the failure probability of each section of the bridge based on the deflection dynamic monitoring data; 3, calculating the failure probability of each section of the bridge based on the strain dynamic monitoring data; and 4, evaluating the dynamic reliability of the bridge structure system. According to system reliability analysis, a multi-component collaborative failure path of a bridge serving as a redundant system is considered, the overall failure probability is analyzed, the failure probability calculation problem of a bridge structure system can be attributed to the failure probability calculation problem of a series mode, and the failure probability of the system is calculated by adopting a narrow-bound theory; and the dynamic reliability of the bridge structure system is inversely calculated, the contradiction between the fitting precision and the generalization ability is reconciled, and the high-precision and dynamic reliability evaluation requirements are met.

The invention belongs to the field of bridge structure aseismic design and safety evaluation, and relates to a mechanism enhanced physical information neural network-based bridge random vibration analysis method, which comprises the following steps of: establishing a bridge structure motion equation configured with a nonlinear tuning inerter damper; a mechanism enhanced physical information neural network model comprising a three-head prediction module and a three-state gating mechanism is constructed, and the three-head prediction module predicts and decouples nonlinear restoring force into three independent subtasks of acceleration, speed and symbol. The three-state gating mechanism divides time steps into a security domain, a crossing domain and a singular point zero point domain according to the speed and adopts a differential supervision strategy; generating a sample based on a random near-fault seismic motion model to train the network; the trained mechanism enhanced physical information neural network is deeply fused with a direct probability integral method, and the random vibration response and the dynamic reliability of the bridge structure are efficiently and accurately calculated. The invention provides an efficient and reliable analysis tool for anti-seismic safety assessment of a bridge structure.

The embodiment of the application discloses a kind of based on FG-DBN's multi-electric aircraft airborne system reliability analysis method, it is related to reliability design field, can be in fuzzy uncertain condition, to the complex polymorphic system in multi-electric aircraft airborne equipment is carried out dynamic reliability analysis.This application includes: the DBN model of complex polymorphic system in airborne equipment is established, the node in DBN model corresponds the failure state of component in complex polymorphic system;Fuzzy gradient function model containing fuzzy support radius is established, fuzzy gradient function model includes: fuzzy membership model of node in corresponding time slice and state transition matrix corresponding to failure mode;The conditional probability table is established for the failure relationship between nodes in DBN model;The output result of fuzzy gradient function model containing fuzzy support radius and the conditional probability table established are used, the node of weak link in complex polymorphic system is identified and reliability is analyzed.

The application discloses a distributed intelligent power distribution network reliability influence factor analysis method and system, relates to the technical field of influence factor analysis, and comprises the following steps: obtaining the operation state of a target area power distribution network, and constructing a topology-control mode table; marking uncertainty of key equipment to form a structure uncertainty matrix; coupling the structure uncertainty matrix with node operation data, establishing a reliability model, calculating the sensitivity of each uncertain structure unit to the overall system reliability index, and generating a structure sensitivity vector; and combining the structure sensitivity vector with real-time operation data to form a dynamic reliability influence factor table. The topology-control mode table is constructed. By establishing a structure-state coupled reliability model and generating a dynamic reliability influence factor table, the application solves the problem that the influence of topology changes and control mode switching on system reliability is not comprehensively considered in the prior art, and the problem of inaccurate identification of key influence factors is solved.

The invention discloses a high-temperature rotating part dynamic reliability prediction method and device based on digital-analog driving, and relates to the technical field of structural reliability analysis, and the method comprises the steps: obtaining a random variable and a target cycle number of a to-be-predicted high-temperature rotating part; constructing a damage-threshold interference model based on an interference theory that damage accumulation and a damage threshold obey normal distribution; inputting the variables and the circulation cycles into the trained data agent model to obtain a damage parameter predicted value and a standard deviation thereof; a prediction reliability is calculated through a damage-threshold interference model based on the predicted value. And the data agent model guides iterative training through a feedback function constructed based on a predicted value and a standard deviation, so that intelligent expansion of a sample is realized. According to the method, the physical interference mechanism and the active learning driven agent model are fused, so that efficient prediction can be realized with few physical simulation samples while the prediction precision is ensured, and the problem that the calculation efficiency and the precision are difficult to consider in the reliability evaluation of the high-temperature rotating part is solved.

Methods, systems, and devices for wireless communications are described. A vehicle user equipment (VUE) may generate a groupcast message for transmission in a vehicle to everything (V2X) system. The VUE may transmit the groupcast message using a transmit power that is based on a reliability distance that corresponds to a region for providing feedback for the groupcast message, where the reliability distance is based on one or more positioning parameters of the VUE and one or more environmental parameters associated with the V2X system. The VUE may then monitor for feedback for the groupcast message.

The invention discloses a reliability evaluation method and system for a collaborative robot PMSM servo system. Comprising the following steps: dividing a servo system into a permanent magnet, a winding and other key parts, and establishing a series reliability model; carrying out a high-temperature accelerated degradation test on the permanent magnet and the winding, and constructing a stochastic differential equation degradation model of a superimposed temperature-dependent diffusion term; a temperature condition neural generation model is introduced to generate and synthesize degradation track data; collecting a temperature sequence under a task spectrum and extracting a fusion temperature feature tensor; constructing a time sequence proxy model in which the one-dimensional dilated convolutional network and the long-short-term memory network are connected in series, and training the time sequence proxy model; recursion is carried out according to the agent model to obtain degradation variable statistics and condition failure probability, and instantaneous failure rate is determined; and substituting the instantaneous failure rate and the constant failure rate into the series model to obtain a system reliability curve. According to the method, the dynamic reliability of the collaborative robot PMSM servo system under the complex task spectrum can be accurately evaluated.

The application relates to the technical field of electronic device testing devices, and discloses a microelectronic device dynamic reliability testing device, which comprises a test plate, a limiting base connected to the test plate, and test groove positions arranged on the limiting base; two fixing buckles for pressing two rows of pins of a device to be tested on the test plate; two fixing assemblies arranged on the limiting base; an ejection assembly arranged on the limiting base; and a clamping assembly arranged in the test groove position of the limiting base. The limiting base, the fixing buckles and the fixing assemblies are matched, the limiting base preliminarily positions the device to be tested, the fixing buckles press the two rows of pins of the device to be tested on the test plate, the effective contact of the pins and the test plate is guaranteed, and the fixing assemblies fix the two fixing buckles in a magnetic attraction mode.

The invention discloses a vacuum breaking type GIS multi-field coupling method, system, equipment and medium for introducing a material degradation function into pressure-strength interference, and the method comprises the steps: achieving the quantitative description of the dynamic attenuation of the strength of a part along with the time through the building of the material degradation function, and enabling a reliability model to better fit the actual service condition; a multi-field coupling finite element model is constructed, potential distribution is accurately simulated by solving a Poisson equation, and dynamic load characteristics of a key area are analyzed and identified through stress response. Meanwhile, an improved particle swarm algorithm with an adaptive inertia weight and a variation mechanism is introduced in a model parameter identification link, so that the convergence speed and the global optimization capability of parameter optimization are effectively improved, and the accuracy and the efficiency of model calibration are ensured. Interference integration is carried out on time-varying intensity and pressure distribution, large-scale random sampling verification is carried out by adopting a Monte Carlo method, and accurate prediction of the dynamic reliability of the part in the whole life cycle is realized.