563 results about "Reliability model" patented technology

The invention includes a method for determining a software reliability metric, including obtaining testing defect data, obtaining test case data, determining testing exposure time data using the test case data, and computing the software reliability metric using testing defect data and testing exposure time data. The defect data includes software defect records. The test case data includes test case execution time data. A testing results profile is determined using testing defect data and testing exposure time data. A software reliability model is selected according to the testing results profile. A testing defect rate and a number of residual defects are determined by using the software reliability model and the testing results profile. A testing software failure rate is determined using the testing defect rate and the number of residual defects. A field software availability metric is determined using the field software failure rate determined using the testing software failure rate.

A handwriting recognition method and a handwriting recognition device are provided to recognize a character sequence continuously inputted by a user for convenience. The present method comprises steps of calculating various features of the inputted character sequence which include single character recognition accuracy features and space geometry features of different stroke combinations in the inputted character sequence, calculating segmentation reliabilities of respective stroke combinations in different segmented patterns by using a probabilistic model in which coefficients of the probabilistic model are estimated by a parameter estimation method through sample trainings, recognizing characters in different writing patterns by using a multiple-template matching method when performing single character recognition of the stroke combinations, searching for the best segmentation path and conducting post-processing to optimize the recognition results. The present method and device have advantages of simple structure, low hardware requirement, fast recognition speed and high recognition accuracy and can be implemented in an embedded system.

The invention discloses a regional integrated energy system optimization control method. The method comprises the following steps: S1, optimizing a control objective function of the regional integrated energy system; The purposes of the lowest total operation cost and the highest reliability and system emission reduction rate of the regional comprehensive energy system are achieved, and the objective function is divided into an operation cost model, an environment cost model and a system reliability model; including S11, constructing an objective function based on an operation cost model; S12,constructing an objective function based on an environment cost model; S13, constructing an objective function based on the system reliability model; S2, analyzing optimization control constraint conditions of the regional comprehensive energy system; S21, energy balance constraint analysis; S22, performing energy balance constraint analysis; And S23, system operation constraint. The control method aims at achieving the purposes that the total operation cost of the system is lowest, and reliability and system emission reduction rate are highest.

The invention discloses a wind and photovoltaic complementary power generation system reliability evaluation method based on a Copula theory. The method comprises the following steps of: (1) determining the power probability distribution of a wind power station and a photovoltaic plant; (2) respectively performing integral operation on the power probability distribution fWT(P1) and fPV(P2) of thewind power station and the photovoltaic plant, and calculating the accumulative power probability distribution of the wind power station and the photovoltaic plant; (3) calculating Kendall rank correlation coefficients of the power of the wind power station and the photovoltaic plant; (4) calculating a correlation parameter theta of a Frank Copula function; (5) forming a simultaneous equation through a formula (2) and a formula (4) to obtain the joint probability density of the random variables P1 and P2; and (6) acquiring the accumulative probability distribution of the wind and photovoltaiccomplementary power station through integral operation according to a joint probability density function of the power of the wind power station and the photovoltaic plant, forming an off-the-line table of the power of the wind and photovoltaic complementary power station through the accumulative power, and establishing a reliability model of the wind and photovoltaic complementary power station. According to the method, the reliability of the wind and photovoltaic complementary power generation system can be accurately evaluated.

The invention discloses an evaluation method of reliability of an aerospace electronic product based on a failure mechanism. On the basis that an analysis method with a combination of physical simulation and a test is adopted, a physical simulation model of the electronic product is constructed, the means such as sensitivity analysis, Monte Carlo analysis, and stress analysis are adopted, and product key elements are identified and in combination with actual working conditions of the elements, a failure mechanism analysis is conducted. Currently, the failure mechanism analysis aiming at the elements is a means used for analyzing a failure reason after a failure occurs during the test or in the using process of the electronic product, thus pertinent improvement is conducted on the product, the service life of the product is prolonged, and the reliability of the product is improved; the failure mechanism analysis aims at finding key characteristic parameters which affect the service life and the reliability of weak elements as an independent variable of the reliability model.

The invention discloses a time-dependent fatigue reliability analysis method based on bilinear cumulative damage. The method includes the steps that 1, the probability distribution type and statistical characteristic parameter of fatigue life data are determined; 2, the appropriate reference life is selected, and a bilinear cumulative damage physical model is built; 3, according to the bilinear cumulative damage physical model, a probability cumulative damage model is built; 4, according to the stress-strength interference theory, a time-dependent fatigue reliability model is built; 5, a reliability curve is drawn and compared with an experimental result; the characteristics of a crack initiation stage and a crack propagation stage in the fatigue failure process and the randomness in the damage accumulation process are comprehensively considered, the bilinear damage theory serves as a modeling base, the probability cumulative damage model is built, through the combination with the stress-strength interference theory, the time-dependent fatigue reliability model based on cumulative damage and critical damage is built, the time-varying characteristics of fatigue loading and the dynamic behavior of the damage accumulation process are reflected, and the reliability prediction in the whole fatigue life cycle is achieved.

Predictive maintenance systems and methods are described. A method includes measuring environmental conditions using a plurality of sensors within the IED, processing the environmental measurements to determine long-term exposure factors representing historical operating conditions of the IED, applying a reliability model to the long-term exposure factors, determining a numerical measure of IED life based on the long-term exposure factors and the reliability model, comparing the numerical measure of IED life to preselected boundary values, and signaling if the numerical measure of IED life is outside of the preselected boundary values.

A performance or reliability model representing the behaviour of an application under different system resource conditions is provided. This model may take the form of one or more sparse matrix providing a reliability or performance values for different combinations of conditions. This model is distributed to a user of the application, and is consulted during execution of the application with reference to system resource information provided by the operating system or other monitoring software so as to provide an indication of the expected performance of the application under present operating conditions. This indication may be notified to a user, for example in a case where the indication falls outside predetermined bounds of satisfactory operation. The system may also attempt to renegotiate attributed system resources to as to improve performance.

The invention relates to an embedded system reliability analysis and evaluation method. The method is technically characterized by comprising the following steps of: based on an AADL architecture model file and an AADL error model file, forming an AADL reliability model file; converting an AADL reliability model into a general stochastic Petri net (GSPN) reliability model; and performing quantitative analysis on the AADL reliability model by using a conventional GSPN reliability evaluation method. The method brings convenience to automation of software architecture reliability analysis, and brings the convenience to a user to analyze and evaluate the reliability of embedded software at an early stage of software design and evaluate the reliability of software at an architecture level; and if the model architecture cannot meet a requirement, then the software architecture can be modified in advance. Therefore, not only development cost can be saved, but also a development period can be shortened.

The invention belongs to the technical field of numerical control machine tool and relates to a motorized spindle accelerated life testing time design method. The method includes the steps that firstly, product load data and fault information are collected; secondly, a load distribution model is established; thirdly, a program load spectrum is designed; fourthly, a product service life estimated formula is determined on the basis of the Miner fatigue accumulation damage theory, and an accelerated life testing accelerating factor model is built on the basis of the formula; fifthly, based on the fault information, a first fault time reliability mode is built through model hypothesis, parameter estimation and hypothesis testing; sixthly, testing time design is conducted on the basis of the first fault time, the first fault time corresponding to an acceptable reliability degree serves as a standard, and a relational model of motorized spindle testing time and the sample capacity is established; seventhly, an accelerating factor is considered for testing time design, and the creditability of the testing time design is verified. The relational model of the testing time and the sample capacity is considered, the accelerating factor model is established on the basis of the modification Miner theory, the modeling accuracy is improved, and the method better conforms to actual conditions.

The invention provides a reliability assessment method for a secondary system of an intelligent substation, and belongs to the field of power information automation. The assessment method divides the intelligent substation system into a communication subsystem, a control subsystem, a protection subsystem and a station control layer subsystem, obtains reliable parameters of each subsystem with the aid of the mean time to fail and the mean time to repair parameters of devices by an availability block diagram, finds out weak links of the secondary system, and improves the reliability of the secondary system of the intelligent substation, thereby achieving the purpose of increasing the quality of power supply at last, and providing an easily accepted and implemented reliability assessment method of the secondary system for the reliability assessment of the secondary system of the intelligent substation. By introducing a notion of reliability model, carrying out quantitative calculation and evaluation, and conducting sequence according to the reliability indexes and the degrees of risk, the reliability and availability of the whole intelligent substation system are improved. The assessment method of the invention can be widely applied in the system design, operation scheduling or device management fields of intelligent substation.

The present invention provides a novel system and method for designing a network. The system is preferably a computer operable to allow a user to input the nodes and links of a network, and to input product information associated with the nodes and links. The computer also stores product-reliability models corresponding to the hardware information. The computer is operable to perform operations that consider the nodes, links, product models to determine a set of reliability performance parameters. The computer can be further operable to vary certain reliability parameters to determine the impact from the perspective of an end-user or other type of network client. One method can include the collection of desired client requirements from the end-user and designing various network configurations to conform with the desired client requirements. Thus, the present invention can be used, and to optimize network designs. Another application is to incorporate the tool in network management product to be used to build or enhance existing networks. This function could be both static as well as dynamic. Thus, the present invention can also be used for other purposes such as modifying, monitoring or optimising existing networks.

The invention discloses a complex mechanism dynamic cascading reliability modeling method based on a colored stochastic Petri network. The method comprises the following five steps that firstly, a system is layered from top to bottom according to the structure, functions and operational profile of the system, the upper layer of the system is obtained by means of functional layer division, and the lower layer of the system is obtained by means of structural layer division; secondly, the fault modes and the influences of all the layers of the system are analyzed through an FMEA method, a logic relation between correlated faults is given, fault criteria influencing the functions are determined, and the hierarchy and transmissibility of the faults of the system are clarified; thirdly, a CSPN reliability submodel of each layer is established according to the logic relation between the faults and the functions; fourthly, the CSPN submodels of all the layers are connected organically by means of transition substitution to establish an overall reliability model of the system; fifthly, a color function, a node function, an arc expression function and a defense function of each layer are determined, and the reliability of the system is analyzed and evaluated by means of Monte Carlo simulation.

The invention belongs to application of a reliability analysis technology to the technical field of fire engineering, and ensures that the using reliability of a fire fighting system is accurately analyzed and calculated. A fire fighting system reliability analysis and calculation method comprises the following steps of: establishing a fire fighting system reliability model and determining reliability units according to the working principle of the fire fighting system, forming a GO chart for establishing the fire fighting system according to the boundary of the fire fighting system and success criteria, and determining a fault judgment method for the reliability units of the fire fighting system according to task analysis of the system and fire code requirements; and substituting fault statistical data of the reliability units of the fire fighting system into a GO model of the fire fighting system to calculate corresponding reliability indexes of the fire fighting system, such as a fault rate, average maintenance time, availability and the like. By the method, the reliability of the fire fighting system can be objectively qualitatively evaluated or accurately quantitatively evaluated, and the method can be widely applied to reliability design, reliability manufacture, fault analysis and system evaluation of the fire fighting system.

The invention discloses a method for evaluating reliability of a large power grid comprising a wind power station, which belongs to the technical field of evaluation on reliability of a power system. The method comprises the following steps of: firstly, establishing a wind power station time sequence power output model; then combining the wind power station time sequence power output model and a large power grid system to establish a wind power station large power grid reliability model; establishing an index system for evaluating the reliability of the large power grid comprising the wind power station; finally, evaluating the reliability of the large power grid comprising the wind power station by applying a sequential Monte Carlo simulation method. According to the invention, the related reliability model and index system are respectively established from the power grid side and the wind power station side for balancing influence of switching-in of the wind power station on reliability of the large power grid; the integral reliability condition of the system and contribution of the wind power station to the adequacy of the large power grid can be more sufficiently reflected.

The invention provides a method for detecting a distributed denial of service attack, which comprises the following steps: receiving a network data packet, and extracting detection features which are related to the detection of the distributed denial of the service attack and used for proving the existence of the distributed denial of the service attack from the network data packet; using the detection features as an evidence in a simple reliability model, and calculating the reliability of the evidence; creating knowledge in the simple reliability model according to the detection features and calculating the reliability of the knowledge, wherein in the knowledge of the simple reliability model, an independent feature among the detection features corresponds to independent knowledge, and related detection features among the detection features are in the same knowledge; and calculating the reliability of conclusion events related to the distributed denial of the service attack by introducing the reliability of the evidence and the reliability of the knowledge into a reliability calculation formula of the simple reliability model. The method and the system have high detection capacity, high detection accuracy and excellent processing capacity.

The invention relates to a multidisciplinary integrated design method utilizing reliability as an independent discipline, comprising the followings steps: firstly, establishing a reliability simulation model by adopting a reliability model automatic generating method, and carrying out simulation for multiple times by adopting a Monte-Carlo method so as to calculate the reliability; secondly, constructing a reliability pseudo model by adopting a pseudo modelling method on the basis of the reliability simulation model; thirdly, constructing a reliability discipline model by utilizing the multi-complexity technology on the basis of the reliability simulation model and the pseudo model; fourthly, establishing pseudo models of other disciplines to serve as other discipline models; fifthly, establishing a whole optimization model containing the reliability discipline model; sixthly, decomposing the model to obtain a hierarchical multidisciplinary design optimization model; and seventhly, optimizing by adopting an improved collaborative optimization algorithm until an optimal design scheme is obtained. According to the invention, autonomy of the reliability discipline is maintained while integrated optimization is carried out on the reliability and performances, thus being beneficial to multianalysis and quantitative control on the reliability.

The invention provides a method for conducting multi-state system task reliability modeling on the basis of a performance model. The method includes the following steps of S1, collecting design information of a target multi-state system; S2, building the performance model of the target multi-state system; S3, determining failure criteria of the target multi-state system; S4, conducting analysis and modeling on an failure pattern of the target multi-state system; S5, obtaining information of failures of the target multi-state system; S6, conducting failure injection and simulation on the targetmulti-state system; S7, conducting reliability analysis and evaluation on tasks of the target multi-state system, wherein a task reliability simulation evaluation method of the failure injection based on a time sequence is utilized for calculation to obtain a mean time between critical failures (MTBCF) and mission reliability (MR) of the target multi-state system. By constructing a failure transfer relation among failure mechanisms, key parameters, component performance and the system failure criteria from bottom to top to conduct task reliability analysis and evaluation of the multi-state system, better integrity and accuracy are achieved.

The invention discloses a comprehensive reliability evaluation method based on multi-test information. The method comprises the following specific steps of: 1, establishing a reliability model of a product; 2, estimating the failure rates of the product under different environments; 3, determining environment reduced factors; 4, performing time reducing and 5, evaluating the service life and reliability of the product. According to the method disclosed by the invention, multi-test information can be integrated, so that the service life and reliability of the product can be evaluated; under the condition that product samples and data are rare, the environment reduced factors under different conditions can be determined, and the evaluation on the service life and reliability of the product can be finished; and the invention provides a method for determining environment reduced factors by utilizing a product reliability estimation result, so that the process of determining the environment reduced factors is simplified, and the method disclosed by the invention can be applied more simply and conveniently.

The invention discloses a wind power plant reliability modeling method considering a correlation between an air speed and a fault of a wind turbine generator. The method comprises the following steps: initializing parameters; calculating each correlation coefficient of the Weibull distribution parameter of the wind power plant air speed and the wind power plant air speed; calculating the correlation coefficient between the wind power plant air speed and the quantity of fault wind turbine generators; forming a matrix containing the correlation coefficients between the wind power plant air speeds and between the same wind power plant air speed and the quantity of the fault wind turbine generators; selecting an optimal Copula function; simulating and generating a related multi-dimensional random number sequence; adopting an inverse transformation method for simulating and generating the air speed sequence and the fault wind turbine generator quantity sequence of each wind power plant; calculating an hour output power sequence of the single wind turbine generator of each wind power plant during a normal running process; calculating the hour output power sequence of each wind power plant; using a linear dividing or clustering method for establishing an equivalent multi-mode output power model. A wind power plant reliability model established according to the method provided by the invention can overcome the defects of the traditional wind power plant reliability modeling method.

The invention provides an optimization method for the periodic preventive maintenance strategy of a repairable degraded system. The reliability model of the repairable degraded system under the cumulative Poisson shock is classified, a suitable reliability model is selected according to the situation and simplified, and the It is applied to the preventive maintenance strategy optimization model as a constraint condition, and a more practical preventive maintenance strategy optimization model is obtained. The invention comprehensively considers the system maintenance cost and the probability that the system is in a normal state at any time, and determines the optimal preventive maintenance period and the system update period under the premise of satisfying the reliability index. It avoids the loss of human and material resources caused by excessive maintenance, and also avoids inconvenience and economic losses caused by untimely maintenance, and obtains maximum benefits for the company in system maintenance. It can also guide enterprises to formulate reasonable equipment maintenance strategies and reduce production costs.

A method for assessing and analyzing software reliability comprises the steps of: collecting failure data from a software system during a testing period; providing a reliability model having a testing compression factor, wherein the reliability model is used to fit the failure data; providing an estimation function derived from the reliability model; obtaining the value of the testing compression factor in accordance with the estimation function; and using the testing compression factor to determine the efficiency of test cases.

The invention provides an accelerated degradation test statistical analysis method under a multi-stress multi-failure mode dependent competition condition. The method comprises the following steps: acquiring multi-stress accelerated degradation test data of a product; selecting a proper distribution model and estimating distribution parameters; establishing a model between the degradation amount distribution parameter and time and estimating a model parameter; constructing a multi-stress acceleration model; modelling multi-failure-mode dependent competitive reliability; and solving unknown parameters of the model to obtain product reliability distribution. The coupling influence of multiple stresses on life characteristics and the dependency of a degradation process and a random impact process are considered, a reliability function under the N stress M failure mode dependency competition condition is established, and the gap in the related research field is filled; based on product degradation amount distribution and a multi-stress multi-failure-mode dependent competition reliability model, an analysis method of an N-stress M-failure-mode dependent competition accelerated degradation test is established systematically for the first time, engineering practice is better met, the service life of a product is prolonged, and the accuracy of reliability evaluation is improved.

The invention belongs to the field of machine tool accuracy designing, and relates to a method for designing geometric accuracy of a multi-axis numerical control machine tool to improve processing accuracy reliability, in particular to a modeling method of space errors of the multi-axis numerical control machine tool and an analyzing method of processing accuracy reliability and reliability sensitivity of the machine tool. A space error model of the multi-axis numerical control machine tool and a processing accuracy reliability model as well as a processing accuracy sensitivity model of the multi-axis numerical control machine tool under a multi-failure mode are built, geometric error items high in processing accuracy reliability sensitivity are optimized, processing accuracy reliability of the machine tool is improved, a basis is provided for acquiring interrelation among geometric errors of the multi-axis numerical control machine tool and setting accuracy grade of main transmission components of the machine tool, and the problem of accuracy distribution of the machine tool is solved fundamentally.

Disclosed is a software application reliability and availability tracking and reporting mechanism that collects event data from target computers, analyzes the data, and produces reliability and availability reports. A network administrator specifies target computers for which event data are collected. The collected event data along with a reliability model are provided to a reliability and availability analysis engine. Output from the engine includes reliability and availability data expressed as durations of time spent in each state and as associations with the events. The reliability and availability data are fed to a report generator which computes reliability and availability metrics. The metrics are used to generate reports that can be interpreted by the network administrator without the need for specialized data analysis skills. The metrics are also aggregated to provide historical and relative ranking reliability and availability data useful for planning and tracking against reliability and availability objectives.