170 results about "Reliability optimization" patented technology

The invention relates to a reliability optimization method of a distributed power supply system. In the method, the random uncertainty of a load forecasting value and the fuzzy uncertainty of the renewable energy type DG (Distributed Generation) output are mainly considered, the load forecasting value is represented by a random variable in normal distribution, the renewable energy type DG active output is represented by a trapezoidal fuzzy variable, and the minimization of an expected value of the sum of the investment and operating cost and the outage loss compensation cost of the distributed power supply system is taken as a target function, so as to establish a hybrid chance-constrained programming model based on reliability optimization. In comparison with the scheme obtained by the conventional method, the method provided by the invention has stronger adaptability to the uncertainty of future factors, and can largely reduce compensation investment after the event and reduce loss and waste.

The invention discloses a non-probabilistic reliability optimization design method for a structural system. The non-probabilistic reliability optimization design method for the structural system comprises the following steps that (1) based on a safety factor design method, a design scheme of the structural system with a given safety factor is optimized; (2) based on quantitative results of uncertain sources in the structural system, dispersity of response of the structural system under multiple failure modes is obtained by an interval uncertainty analysis; (3) a non-probabilistic reliability index is introduced to calculate the reliability of the structural system under the multiple failure modes; (4) a non-probabilistic reliability optimization design model is established under the constraint of a non-probabilistic reliability or a given reliability of a safety factor scheme; (5) based on a conventional optimization algorithm to solve an optimization problem, the design scheme of the structural system with optimal reliability allocation is obtained. According to the non-probabilistic reliability optimization design method for the structural system, on the basis of ensuring the non-probabilistic reliability of the safety factor design scheme, the quality of the structural system is further reduced and the performance of the structural system is improved.

The invention relates to a method for optimizing reliability of a harmonic gear used for a space vehicle based on fault physics. The method comprises the following steps: 1) establishing a physical model of the harmonic gear used for the space vehicle; 2) confirming bottom fault information of the harmonic gear used for the space vehicle; 3) analyzing and acquiring a key part of the harmonic gearused for the space vehicle and a main failure mode thereof; 4) confirming a response surface function of the main failure mode; 5) converting a strength restrain and a fatigue restrain in design optimization of the harmonic gear used for the space vehicle into reliable restrains; and 6) establishing a function expression of the volume of the harmonic gear used for the space vehicle and taking thefunction expression as an optimizing target function. The method provided by the invention has the beneficial effects that the method can be used for performing quantitative optimization of the reliability and ensuring the reliability while efficiently reducing the weight of a product, thereby lowering launching cost.

The invention relates to the technical field of optimization design and provides a stiffened plate shell structure reliability optimization method with the multisource uncertainty being considered. The stiffened plate shell structure reliability optimization method with the multisource uncertainty being considered comprises the following steps of performing reliability optimization on a stiffened plate shell structure by utilizing an equivalent stiffness model; performing finite element analysis validation on every elite individual in a candidate solution set, wherein the finite element analysis validation comprises performing nonlinear post-buckling analysis on the stiffened plate shell structure comprising defects by utilizing a single-point disturbing load method with defect factors being considered to screen out the elite individuals satisfying a reliability constraint condition; performing the reliability optimization on the stiffened plate shell structure by utilizing a finite element model. The stiffened plate shell structure reliability optimization method with the multisource uncertainty being considered can improve the reliability optimization efficiency of the stiffened plate shell structure and reduce calculation costs.

The invention relates to a turbine disc multi-failure-mode reliability optimization method based on EGRA, and the method comprises the steps: (1) carrying out the parametric modeling of a turbine discsector, analyzing the geometric parameter sensitivity of a turbine disc, and selecting a design variable; (2) performing LHC sampling on the design variables, calculating the service life of each sampling point under each failure mode, and establishing a reliability model of each failure mode; (3) evaluating the reliability model of each failure mode by using an efficient global reliability analysis (EGRA) method, and if the reliability model of each failure mode is greater than a convergence limit, adding sample points into the initial model until the model converges; (4) fitting the servicelife in each failure mode by using the reliability model updated in the step (3); and obtaining the system service life according to the related form and carrying out optimization solution on the system service life, if the optimization result does not meet the system reliability requirement, calculating the optimal point real service life value, adding the optimal point real service life value into the reliability model to update the model, and repeating the steps of checking convergence and updating the model until the system reliability is met to obtain the optimization result.

The invention provides an engineering structure optimization design method used in an uncertain environment, and relates to the technical field of engineering structure reliability optimization. According to the method, an uncertain engineering structure optimization design problem is defined first, an engineering structure and uncertain information in the use environment are described as random variables, interval variables or combinations of the random variables and the interval variables according to existing samples, corresponding optimization models are established according to different types of uncertain variables, reliability indexes in the optimization models are calculated on the basis of the point collocation random/interval propagation analysis method, and finally different optimization solvers are selected according to actual problems for outer layer optimization. Reliability indexes of an inner layer failure function are obtained through efficient uncertain propagation analysis, and formation of the nested optimization problem is avoided; hybrid uncertainty models including random parameters and interval parameters in the same problem are considered, and the method has a practical engineering significance in interval parameter optimization problem under random process stimulation.

The invention provides a quantitative method for conducting reliability analysis evaluation and reliability optimization in a process design stage. Through reliability analysis evaluation, advantages and disadvantages of different process schemes can be compared, the manufacturing risks are evaluated, and important parameters influencing a manufacturing result can be found out; more reliable parameter optimal values can be obtained through reliability design optimization. The method mainly comprises the 5 steps that manufacturing process defects are analyzed and the influencing parameters are screened; the indeterminacy of the manufacturing process is identified; process reliability analysis and manufacturing risk evaluation are conducted on the basis of an approximate model; process optimization modeling is conducted on the basis of the reliability; a solution to a process reliability optimization model is obtained.

The invention discloses a mechanical structure fuzzy fatigue reliability optimization method based on a self-constructed membership function, and belongs to the field of fatigue reliability optimization. The objective of the invention is to solve the problem of fuzzy fatigue reliability optimization design under a small amount of sample data. The principle includes: representing fatigue damage fuzziness of a mechanical structure by a self-constructed membership function, verifying the accuracy of the mechanical structure through test data, and deriving a failure probability and reliability analysis expression; defining a random variable, a fuzzy variable and a fuzzy fatigue reliability function, verifying the accuracy of the function, and establishing an optimized objective function; and determining a design variable constraint condition, determining an optimization target interval based on a blind number theory, performing global optimization through a genetic algorithm, and obtainingan optimal result. The uncertainty factors of the size, material parameters and load of the mechanical structure are fully considered, the fatigue damage fuzziness of the mechanical structure is represented through the self-constructed membership function, the optimization target interval is defined based on the blind number theory, calculation is accurate and reliable, and the efficiency is high.

The invention belongs to the field of structure optimization design for components of compressors, and particularly relates to a reciprocating compressor crankshaft reliability optimization design method. The reciprocating compressor crankshaft reliability optimization design method includes steps of performing three-dimensional modeling, meshing to generate finite element modules, obtaining crankshaft stress values on discrete working conditions, calculating stress strain distribution of a crankshaft on the discrete working conditions by the aid of finite element modules, determining dangerous working conditions and dangerous nodes of the crankshaft, obtaining the stress values of the dangerous nodes on different discrete working conditions, checking fatigue strength of the different dangerous nodes, analyzing the finite element modal of the crankshaft to obtain natural vibration mode and natural frequency of the crankshaft, and finally judging whether resonance exists between frequency of exciting force and the natural frequency or not. The reciprocating compressor crankshaft reliability optimization design method is easy to operate and implement, has effects of improving working reliability of the crankshaft practically, improving operation reliability of high-parameter compressors while having a high reference value to realize miniaturization and light weight on the premise of reliability guarantee.

The invention discloses a discrete variable truss non-probability reliability optimization design method. The method includes the steps that firstly, a design variable and related design parameters of a truss needing optimization design are determined; secondly, the to-be-optimized truss is subjected to optimization processing by means of a pre-built discrete variable truss non-probability reliability optimization model. The method is simple in step, reasonable in design and good in use effect, an uncertain parameter vector influencing the reliability of the truss is taken into consideration, a displacement non-probability reliability indicator function and a stress non-probability reliability indicator function are built, structural optimization of truss discrete variable non-probability reliability is achieved, the weight of the truss is reduced, and it is guaranteed that the optimal design scheme of the truss is obtained.

The invention relates to a nonprobability reliability optimization based design method of a vibration optimal control system. According to the method, a finite element equation of structural vibration is converted into a state space form via variable substitution, and a state space control equation of structural vibration is established; a nonprobability reliability analysis theory of an active control system of structural vibration is provided; and based on the provided nonprobability reliability analysis theory, reliability optimization is carried out on a controller obtained via an optimal control theory, and a closed-loop controller satisfying the reliability index is obtained. The uncertainly of a closed-loop control system is overcome in the aspect of reliability, and the problems that optimal control cannot satisfy the reliability requirement and robust control is too conservative can be effectively solved.

The invention discloses an electromechanical system multilayer reliability prediction method based on fuzzy evaluation, wherein the electromechanical system multilayer reliability prediction method belongs to the field of electromechanical system reliability engineering technology. The method comprises the steps of performing layered structural processing on the electromechanical system by means of an analytic hierarchy process, layering the electromechanical system from top to bottom, wherein the electromechanical system comprises a system layer, a sub-system layer, a functional module layer and a basic functional layer; then, determining the weight coefficient of a sub unit relative to a father unit according to a risk priority number method and a fuzzy judgment matrix; and finally, establishing a multilayer reliability model which comprises a weighting coefficient, and successively performing reliability prediction on the electromechanical system. The electromechanical system multilayer reliability prediction method can be widely used in the field of electromechanical equipment reliability engineering and is particularly suitable for complicated system reliability optimization and fine design analysis.

The invention discloses a reliability optimization allocation method based on an improved Pareto artificial bee colony algorithm. The method comprises the following steps of: constructing a development cost-reliability function model, a maintenance cost-reliability function model and a total cost-reliability function model of an offshore wind turbine generator set; establishing a reliability optimal distribution model of the offshore wind turbine generator set by taking the reliability of the offshore wind turbine generator set as the target and the development cost, the maintenance cost and the total cost of the offshore wind turbine generator set as the target on the basis of analyzing the reliability constraint relationship of each subsystem through the maintenance cost-reliability function model and the total cost-reliability function model. Based on the idea of Pareto multi-objective optimization, an improved artificial bee colony algorithm is proposed to be applied to solving ofa reliability optimization allocation model; the improved artificial bee colony algorithm can effectively improve the solving efficiency and solving quality of the model. For the solved Pareto non-dominated solution set of the reliability allocation scheme, a PROMETHEE-II method is adopted to perform secondary optimization on the reliability allocation scheme, and the optimal reliability allocation index of each subsystem is determined.

The invention relates to a design method of a spiral bevel gear, which is technically characterized in that a coordinate system is established by using the tooth number z of small spiral bevel gears as an abscissa and using the end surface module mi of larger ends as an ordinate, a tooth number-module curve satisfying critical condition thereof is respectively drawn according to contact strength constraint conditions and bending strength constraint conditions, and a public area above the two curves is a feasible region satisfying strength reliability requirements. On the basis, the overlap ratio of the gear under the specific tooth number is marked, so that the optimal solution of gear driving is obtained in the feasible region simultaneously satisfying an overlap ratio constraint condition. Then a tooth number-module curve corresponding to a preset volume is drawn, and a discrete optimal solution with the smallest volume is found by continuously changing a preset volume value. A gearreliability optimization method disclosed by the invention breaks through a traditional reliability optimization method, overcomes the defects of an existing optimization method and is the design method which can be applied to the reliability optimization of all gears.

The invention discloses a body-in-white structure optimization design method and a body-in-white structure optimization design device. The body-in-white structure optimization design method comprisesthe following steps: establishing a finite element model of a body-in-white; calculating modality and rigidity of each working condition in the finite element model, carrying out test verification onthe body in white, and obtaining an error between a calculation value and a test value of the modality and the rigidity; adjusting the finite element model until the error is less than the preset percentage; according to the modality and the rigidity, a plurality of design variables for optimization design are screened out; and selecting a part of parameters in the body-in-white structure as a plurality of design variables according to the weighted relative sensitivity w of the body-in-white and the optimization cost of the body-in-white. A weighted relative sensitivity analysis method is adopted to select the design variable of the optimization design, the reliability optimization design is carried out on the white vehicle body determinacy optimization result, the white vehicle body structure meets the performance requirement, meanwhile, the vehicle body mass is reduced, and the system reliability is improved.

The invention provides a power communication network reliability prediction and guarantee method and a system based on deep learning. According to the method and the system, a deep belief network anda bidirectional LSTM neural network are adopted to carry out feature extraction and prediction on state data in the network and calculated reliability index data respectively, and a network state anda corresponding reliability index in a next effective time period are predicted. Then, the predicted reliability index is evaluated; and if the standard threshold value is not met, network optimization needs to be carried out to improve the reliability of the network, and during optimization, corresponding optical cable optimization, node optimization and service level optimization are selected incombination with the predicted network basic data in the next effective time period, so that the overall reliability of the network is improved. According to the method and the system, the power communication network is optimized by combining the predicted network service state of the next time period, so that the network reliability is improved from the perspective of providing communication service stably for a long time.

The invention discloses a fuzzy intelligent multiple response surface method for a blade reliability optimization design. The method specifically comprises the processes of comprehensively considering joint action of non-linear material attribute and mechanical load of a blade material and finding out the maximum output response point of the blade by statics analysis; selecting the input random variable, extracting an input random variable sample by applying a Latin hypercube sampling (LHS) technology and solving finite element basic equation for each sample to obtain corresponding output response; constructing a fuzzy intelligent multiple response surface function (FIMRSF) to finish reliability sensitivity analysis of the blade structure; establishing a fuzzy reliability optimization design model (FRBDO) by taking a high sensitivity parameter as a design variable; and performing fuzzy reliability optimization design by replacing the limit state function of the blade structure with FIMRSF and solving the FRBDO model by means of a multi-target genetic algorithm. The method disclosed by the invention is a quick and efficient multi-failure mode structural reliability optimization design method.

The invention discloses a multi-level electromechanical system reliability prediction method based on fuzzy judgment. The method is used for performing layered structured processing on an electromechanical system, establishing a multi-level reliability model containing weighting coefficients and performing multilevel unit weighting coefficient calculation and reliability prediction on the electromechanical system sequentially. The multi-level electromechanical system reliability prediction method comprises steps as follows: layered structured processing on the electromechanical system; calculation of a risk priority number of a bottom unit and establishment of a binary comparison matrix; establishment of a fuzzy judgment matrix of the bottom unit and calculation of unit weighting coefficients; establishment of a father unit reliability model; reliability prediction of a function module; reliability prediction of a subsystem; reliability prediction of a system. By means of the method, the defect that the importance of each system unit cannot be treated differently with an existing electromechanical system reliability prediction method can be overcome. The electromechanical system reliability prediction method can be widely used for the field of reliability engineering of mechanical and electrical equipment and is particularly suitable for reliability optimization and refined design and analysis occasions of a complicated system.

The invention discloses a non-probabilistic reliability pneumatic structure coupling optimization design method for a hypersonic velocity three-dimensional wing. The method comprises the following steps: expressing beam and rib thickness size, elasticity modulus and density into interval variables, and acquiring a sample space of input parameters by utilizing an interval vertex method; finishing finite element parametric modeling of the hypersonic velocity three-dimensional wing according to sample points in the sample space; finishing pneumatic structure coupling analysis of all sample points in the sample space by utilizing an iterative algorithm; screening to obtain internal upper and lower limits of the maximum displacement and maximum stress, and finishing propagation analysis of uncertain parameters in a coupling system; introducing a volume method thought, and defining non-probabilistic reliability indexes of a pneumatic structure coupling system; taking wing structure weight as an optimization object and taking the reliability of the structural maximum displacement and maximum stress smaller than allowable values as a constraint condition, realizing the non-probabilistic reliability optimization design of the wing structure. According to the method disclosed by the invention, the wing structure mass is reduced under the condition that the hypersonic velocity wing is high in reliability, and the wing performance is improved.

The method discloses a method for non-probability reliability optimization of a composite laminated plate. The method comprises the steps that firstly, according to force bearing characteristics of the composite laminated plate and with consideration of uncertainty effects of material fiber strength under limited samples, a non-probability reliability assessment model of the composite laminated plate is established based on non-probability reliability theories; and a gradient optimization method is further adopted, a light weight is taken as a goal, reliability is taken as a constraint, a paving layer thickness is taken as an optimization variable, and a composite paving layer scheme which can satisfy certain reliability requirements can be obtained through iterations. The method has the advantages that the composite laminated plate can have the high reliability and the light weight under uncertainty conditions; and safety and economic efficiency are also ensured.

The invention discloses an NAND Flash storage reliability optimization method based on a self-recovery effect, which not only considers the P/E times of data blocks, but also preferentially selects the data block with the earliest writing time when the P/E times of the data blocks are equal, so that the residence time of data can be prolonged. The purpose of the invention is to study the change rule of data residence errors of blocks with different wear degrees under different degrees of self-recovery effects by storing P/E times experienced by the data block and storing the last data writingtime of the block, thereby improving the reliability of the NAND Flash.

The invention relates to optimization design of a centrifuging pump, and discloses a multidisciplinary optimization design method for a centrifuging pump impeller operated in high-temperature and high-pressure limiting working conditions. The design method is a high-temperature and high-pressure pump impeller multidisciplinary optimization hydraulic design method based on four disciplines of fluid mechanics, mechanics of materials, structural mechanics and thermodynamics; and by performing multidisciplinary evaluation on a design scheme, the optimal safety performance of the pump is achieved while a condition that the hydraulic performance of the pump is better than design index is ensured. The optimization design process provided by the invention comprises system-level optimization and sub system-level optimization; the task of the system-level optimization comprises a multi-working-condition, low-gas-etching and high-efficiency hydraulic power design method of the centrifuging pump under the high-temperature and high-pressure working conditions to enable performances of multiple system objectives to be optimal; the sub system-level optimization comprises optimization of hydraulics based on a CFD technology, reliability optimization based on the structural mechanics, and multi-field coupling design based on thermodynamics; and the overall optimal solution of the system is obtained by analyzing a synergetic effect generated by interaction of the disciplines.