20 results about "Reliability methods" patented technology

The invention discloses an offshore wind turbine supporting structure reliability evaluation method based on a reduced-order digital twin model, and the method comprises the steps: obtaining the response data of an offshore wind turbine supporting structure through multi-dimensional load analysis; and finally, setting a limit state function of the offshore wind turbine support structure in an extreme state, and calculating the failure probability of the offshore wind turbine support structure through a first-order reliability method under the condition of combining response data of the offshore wind turbine support structure so as to evaluate the reliability of the offshore wind turbine support structure. According to the method, the problems of insufficient model precision, calculation efficiency bottleneck, reliability evaluation limitation and the like of an existing reliability evaluation method for the offshore wind turbine supporting structure can be solved, and the requirements of offshore wind power engineering for high precision, high efficiency and comprehensiveness of reliability evaluation of the supporting structure can be met.

The invention discloses a decoupling design method and system for reliability optimization of an angular contact ball bearing. The method comprises the following steps: determining initial design parameters of the angular contact ball bearing; constructing a reliability optimization design model which takes maximization of the rated dynamic load as a target and comprises probability reliability constraint processed by a penalty function; constructing a design variable and failure probability mapping agent model, specifically, identifying and quantifying uncertainty parameters, constructing a quasi-statics model and a limit state function, calculating the failure probability of a sample point through a probability reliability method, and training the agent model taking the design variable as input and the failure probability as output; and based on the proxy model, solving the reliability optimization design model by using an optimization algorithm, and outputting optimal bearing design parameters. According to the method, the reliability analysis process and the optimization iteration process are decoupled, so that the optimization efficiency is greatly improved while the design robustness is ensured.

The invention discloses a robustness test method and device, which are used for improving the reliability of robustness test. The method comprises the steps that an adversarial sample is acquired, the adversarial sample is obtained by adding N disturbances to an original sample, N is a positive integer larger than 1, the original sample is sensing data or regulation control data, and the N disturbances comprise one key disturbance and N-1 non-key disturbances; the robustness of a processing model is tested using an adversarial sample, the processing model being used to identify the sample. According to the scheme, the robustness of the processing model is tested by constructing the adversarial sample with the multi-dimensional disturbance, the performance of the processing model in a real environment can be simulated, the actual use condition of the processing model is better met, and therefore the reliability of the robustness test can be improved.

The invention relates to the technical field of offshore wind power, and discloses a limit turbulence prediction method and device, electronic equipment, a medium and a product, and the method comprises the steps: obtaining a plurality of actually measured wind data subsets of an offshore wind plant; extracting a plurality of average wind speed values and a plurality of wind speed standard deviation values in the plurality of actually measured wind data subsets, and constructing a real-time two-dimensional data set; and on the basis of the real-time two-dimensional data set, through processing of a target Gaussian mixture model and an inverse first-order reliability method, a limit turbulence prediction result of the offshore wind plant is obtained, and the target Gaussian mixture model is used for fitting joint probability distribution of average wind speed and turbulence intensity. By implementing the method, accurate and reliable limit turbulence prediction is realized, and the application requirements of an offshore wind plant are met.

The application belongs to the technical field of electric power, and discloses a substation intelligent inspection rule generation and research method, which is characterized by comprising the following steps: based on ontology analysis of substation operation and maintenance regulations and fault cases, a hierarchical and graded semantic rule template library containing a device layer, an inspection layer and a defect layer is constructed; through a multi-level tabular parameter configuration interface, executable inspection rules are generated; multi-source heterogeneous monitoring data is standardized pretreated and subjected to feature engineering, and a device operation feature vector is extracted; a multi-dimensional model adopting weighted fuzzy comprehensive judgment and multi-feature fusion decision is used for abnormal research and judgment, and a defect level is output; rule effects are automatically evaluated according to defect disposal results, and rule parameters are iteratively optimized by using a self-adaptive genetic algorithm. The application has the following main beneficial technical effects: operation and maintenance efficiency is improved, cost is reduced, research and judgment accuracy and reliability are improved, the method automatically adapts to continuous evolution, standardized management and control are realized, and scale promotion is supported.

The application relates to the technical field of electric digital data processing in intelligent manufacturing, and discloses a natural fragment finite element model equivalent calculation method and system, which can reduce the test times and ensure the reliability of simulation results. The method comprises the following steps: randomly selecting part of fragments in a mass interval, establishing a fragment model according to the average length, the average width and the average height; simulating and analyzing the estimated residual mass and the estimated residual velocity of the fragment model and the target plate model after penetration under different contact conditions; comparing the actual residual mass and the actual residual velocity of at least one fragment selected in a real test environment; obtaining correction coefficients corresponding to the estimated residual mass and the estimated residual velocity under different contact conditions; then obtaining the correction interval range corresponding to the estimated residual mass and the estimated residual velocity; and correcting the single-value simulation results corresponding to the residual mass and the residual velocity in the mass interval into interval range values according to the correction interval range.

The invention relates to the technical field of digital twinning, and discloses a data processing method and system in the virtual production switching process of a production line so as to improve the production switching efficiency and reliability. The method comprises the steps that when all equipment models on a current production line are packaged, the function relation that structural parameters of parts of a sealing part vary along with the change of geometric parameters of a machined object is increased; after a user modifies geometric parameters of processing objects corresponding to all equipment models in a task scheduler on a copy of a current production line according to an actual production switching task, an initial production switching production line is automatically generated according to modification of the task scheduler; executing automatic deformation of structural parameters of part of parts of the equipment model reserved in the production line according to the packaged function relationship along with the change of geometric parameters of a processing object; and then outputting a simulation result for a user to determine the existing resources to be reused and the new resources to be introduced.

The invention provides a shell process parameter reliability determination method and device, relates to the field of shell processes, and solves the problems of low reliability and large redundant mass caused by the fact that parameter randomness is not considered in existing traditional deterministic design and low calculation efficiency of a common probability reliability method. The method specifically comprises the following steps: acquiring process parameters of a plurality of shells, calculating an average value of the process parameters and a random parameter dispersion degree of a standard deviation, and determining a variable coefficient; based on the variable coefficient and the process parameters, determining a fiber strength exerting coefficient of the shell; determining fiber stresses of the plurality of shells based on the fiber strength exerting coefficients and the process parameters, and determining a mean value and a standard deviation of the fiber stresses; and determining the reliability of the process parameters based on the mean value and the standard deviation of the fiber stress and the fiber strength. The method is used for shell reliability analysis.

The present invention provides a rock slope reliability analysis method that takes into account non-Gaussian correlated random variables, and belongs to the field of geological engineering reliability analysis. The method includes the following steps: analyzing the components of the anti-sliding force and sliding force of the rock slope and calculating them; constructing the functional function of the rock slope; determining the probability distribution information of the random variables; and calculating the reliability index of the rock slope. The core of the present invention lies in: 1. It fully considers the stress characteristics of the rock slope itself, and conducts reliability analysis based on this; 2. It directly places the design point iterative calculation of the first-order reliability method based on Copula theory in the physical space, giving the iterative process an intuitive and easy-to-understand physical meaning, while significantly enhancing the stability of the iterative process. This breakthrough technology not only accurately meets the actual needs of geological engineering, especially slope reliability analysis, but also provides a solid and reliable technical backing for rock slope engineering design.

The invention discloses a method for calculating a complete machine acceleration factor based on component information, and relates to the field of aerospace reliability methods, and the method comprises the following steps: S1, constructing a failure influence matrix M; s2, calculating an acceleration factor AFi or a comprehensive acceleration factor of the component; S3, calculating an acceleration factor AFj of the failure mode j through a weighted average method; s4, a whole machine acceleration factor AFsystem is calculated; the working behavior of the whole machine is accurately predicted by considering the characteristics of different components and the influence of the different components on the overall performance, and continuous analysis and optimization are carried out, so that the service life of the whole machine is effectively prolonged, the reliability and stability of the whole machine are ensured, and the reliability and stability of the whole machine are ensured by comprehensively considering the influence of different stresses. Performance and potential fault points of the equipment under actual use conditions are accurately evaluated, and improvement of reliability and service life of the whole machine is facilitated.

The application discloses a first-order reliability method based on a Copula theory in geotechnical engineering, and comprises the following steps: analyzing a geotechnical structure to determine a function function Z of the geotechnical structure and related random variables and independent random variables of the function function Z; determining an edge probability distribution function of the related random variables and a Copula function under a calculation working condition according to engineering experience and measured data; determining an edge probability distribution function of the independent random variables under the calculation working condition according to the engineering experience and the measured data; and calculating a reliability index, a design value and a failure probability of the geotechnical structure according to the edge probability distribution function of the related random variables, the Copula function and the edge probability distribution function of the independent random variables. The application can directly implement the first-order reliability method based on the Copula theory in the original space of the random variables familiar to geotechnical practitioners, and does not involve conversion of additional random variables, so that the complexity of reliability calculation is greatly reduced.

The application relates to the technical field of digital twinning, and discloses a data processing method and system in a virtual change production process of a production line, so as to improve change production efficiency and reliability. The method comprises the following steps: when encapsulating each device model on the current production line, a function relationship that a structure parameter of a part in an increase encapsulation part is changed with a geometric parameter of a machining object is encapsulated; after a user modifies the geometric parameters of machining objects corresponding to each device model in a task scheduler according to an actual change production task on a copy of the current production line, an initial change production line is automatically generated according to the modification of the task scheduler, and the structure parameter of the part of the device model retained in the change production line is automatically changed with the geometric parameter of the machining object according to the encapsulated function relationship; and then simulation results are output for the user to determine existing resources to be reused and new resources to be introduced.

The invention discloses a high-reliability method and system for on-orbit dynamic frequency point change uploading, belongs to the technical field of spaceflight measurement and control, and solves the problems of lack of static distribution and failure frequency point recovery mechanisms and the like in the traditional satellite frequency point management technology. According to the method, a frequency point uploading mechanism, a frequency point switching mechanism, a frequency point storage mechanism, a frequency point recovery mechanism, a rail ascending and descending process, frequency point telemetering storage information and the like are constructed respectively, the frequency point uploading mechanism is a dual-mode frequency point uploading mechanism, and in the uploading changing process, a dynamic frequency point allocation module is established, so that the frequency point uploading mechanism can be used for uploading the rail to the rail. And a high-reliability frequency point uploading mechanism is realized by an encryption transmission and verification mechanism, so that dynamic frequency point distribution is realized. And a failure frequency point recovery mechanism is established in the dynamic frequency point distribution module to realize recovery and utilization of failure frequency points. Meanwhile, an anti-interference and emergency switching mechanism is also designed. The method is especially suitable for frequency point resource dynamic allocation, recovery and cross-satellite multiplexing of large-scale satellite constellations, and solves the problem of resource shortage caused by traditional fixed frequency points.

The present invention relates to a method and system for calculating the safety factor of the main cable of a suspension bridge based on the secondary stress effect. The method comprises the following steps: establishing a finite element model of the bridge; determining, based on the finite element model of the bridge, the most unfavorable stress of the main cable under the most unfavorable live load based on cable structure theory, as the cable unit stress response of the main cable; calculating and evaluating the magnitude of the secondary stress of the main cable based on the cable unit stress response of the main cable according to the secondary stress effect; evaluating the magnitude of the most unfavorable stress response of the main cable by integrating the cable unit stress response and the secondary stress effect, establishing a limit state judgment model using the ultimate strength of the main cable as the failure judgment condition; establishing a probability distribution model of the structure; setting an initial design safety factor for the main cable, calculating the failure probability and reliability index of the main cable; and iterating through an inverse reliability method to change the design number of main cable strands and solve for the reliability index. Compared with the existing technology, the present invention has the advantages of more accurate calculation and strong engineering practicality.

The invention provides a reliability assessment method based on a regularization flow generative model, and belongs to the field of artificial intelligence and the technical field of reliability assessment, and the method comprises the steps: S1, determining a performance function; s2, on the basis of the regularization flow generation type model and observation data, probability modeling is carried out on multi-dimensional parameter joint distribution, and a multi-dimensional parameter joint distribution probability space conversion model is obtained; s3, combining the regularization flow generation type model with a traditional reliability degree method to form a reliability degree evaluation method based on the regularization flow generation type model; and S4, based on the multi-dimensional parameter joint distribution probability space conversion model and the performance function, performing iterative reliability calculation through a reliability evaluation method based on a regularization flow generation type model, and obtaining a failure probability. According to the method, the non-linear correlation between random variables can be more reasonably considered, the method is more accurate and efficient in the reliability problem of multi-dimensional parameter joint distribution with a non-linear correlation structure, and the method has a good application prospect.

The present application discloses a robustness testing method and apparatus, used for improving the reliability of robustness testing. The method comprises: acquiring an adversarial sample, wherein the adversarial sample is obtained by adding N types of disturbance to an original sample, N is a positive integer greater than 1, the original sample is perception data or planning and control data, and the N types of disturbance comprise one type of key disturbance and N-1 types of non-key disturbance; and using the adversarial sample to test the robustness of a processing model, wherein the processing model is used for identifying the sample. According to the solution, the robustness of the processing model is tested by constructing the adversarial sample having multi-dimensional disturbance, so that the performance of the processing model in a real environment can be simulated, being more in line with the actual use situation of the processing model, thus improving the reliability of robustness testing.

The application provides a reliability evaluation method based on a regularization flow generative model, belongs to the fields of artificial intelligence and reliability evaluation technology, and comprises the following steps: S1, determining a performance function; S2, based on the regularization flow generative model and observation data, performing probability modeling on a multi-dimensional parameter joint distribution to obtain a multi-dimensional parameter joint distribution probability space conversion model; S3, combining the regularization flow generative model with a traditional reliability method to form the reliability evaluation method based on the regularization flow generative model; and S4, based on the multi-dimensional parameter joint distribution probability space conversion model and the performance function, performing iterative reliability calculation through the reliability evaluation method based on the regularization flow generative model to obtain a failure probability. The application can more reasonably consider the nonlinear correlation between random variables, is more accurate and efficient in the reliability problem of a multi-dimensional parameter joint distribution with a nonlinear correlation structure, and has a good application prospect.

The present application relates to the technical field of ocean engineering, and discloses a mining vehicle laying and recovering method and system based on umbilical slack prediction mechanism, which can predict the slack risk in advance and ensure the reliability of intelligent response. The method comprises the following steps: inputting the preprocessed real-time heave data into a heave data prediction model to obtain a heave motion prediction result of the ship stern in the future target time, so as to predict the umbilical slack length D at the next moment in advance; judging whether D is still in a slack state after considering the passive compensation range corresponding to the current sea state; if yes, starting the active compensation system to collect the cable in advance, and the cable length is equal to the length D; otherwise, acquiring real-time umbilical tension data and comparing it with a preset tension threshold value, if the real-time tension exceeds the tension threshold value, starting the active compensation system to execute the winch cable laying adjustment action, and when the umbilical tension data decreases to the tension threshold value range, switching the active compensation system to a dormant state.

The present application relates to computer system monitoring and operation and maintenance automation, and discloses a health management method and system based on multi-element heterogeneous monitoring data to improve the intelligence and reliability of operation and maintenance. The method comprises the following steps: based on the current value of the to-be-optimized parameter vector, the dynamic weight vector of each index in the current evaluation period is calculated according to the current state of each index in the index state matrix, combined with the basic weight, the abnormal timeliness, the running context and the index coupling relationship, and then the health prediction result of the current running state of the system is output according to the index state matrix and the dynamic weight vector; a "prediction result-real state" paired sample set is constructed combined with the subsequent actual operation and maintenance events, fault handling results and business impact records; a residual error vector is formed according to each paired sample, and then the to-be-optimized parameter vector is updated according to the parameter sensitivity matrix, the weight of each sample pair and the residual error vector, with the minimum loss function as the target.

The invention provides a liquid hydrogen storage tank structure system two-process reliability evaluation method based on a hybrid model, and relates to the technical field of reliability engineering and evaluation.The method comprises the steps that a thermal-mechanical coupling analysis model is used for analyzing the specific structure and the operation working condition of a large liquid hydrogen storage tank, and a simulation result is obtained; identifying key factors influencing the reliability of the storage tank by utilizing a simulation result in combination with expert knowledge, historical data and failure physical analysis to obtain key failure risk factors; constructing the key failure risk factors into a polymorphic fault tree structure, and mapping the polymorphic fault tree structure to obtain a dynamic Bayesian network model; and performing double-process quantitative reliability evaluation on the simulation result by using a dynamic Bayesian network model and a mixed agent model to obtain a hierarchical reliability evaluation result. According to the method, the problem that the reliability of the large liquid hydrogen storage tank is difficult to comprehensively and accurately assess by the existing single system reliability method or structure reliability method is solved.