22 results about "Central composite design" patented technology

The invention discloses an outer rotor permanent magnet synchronous motor torque optimization method, which comprises the following steps: 1) design parameter selection: selecting key characteristics of a motor stator slot as design parameters, including slot shoulder height Hs1, tooth length Hs2, chord length Bs0 and slot shoulder width Bs1; 2) finite element model construction: establishing a multi-target finite element model with cogging torque, torque pulsation and average torque as targets; 3) establishing an analytic model: establishing the analytic model of the motor torque by using an energy method and a repetitive unit method, and comparing the analytic model with the finite element model to verify the accuracy of the analytic model; 4) response surface model construction: based on the simulation data of the finite element model, performing finite element analysis by adopting a central composite design CCD, constructing a response surface model, performing sensitivity analysis on design variables, and determining the influence of each variable on an optimization target; and 5) optimization efficiency improvement: determining optimal configuration in a design space by using an adaptive genetic aggregation algorithm AGA, and achieving a multi-objective optimization effect.

The invention relates to a construction method of a superfine tailing slurry pipe transportation resistance calculation model, and belongs to the technical field of metallurgical mine mining methods. According to the technical scheme, on the basis of analysis of physicochemical properties of tailings and cement, the relation between rheological parameters and mass concentration, the cement-sand ratio and slurry temperature test factors is discussed on the basis of a center composite design response curved surface method, the parameter ratio is optimized, so that the pipe conveying resistance reaches the minimum value, and the pipe conveying performance is improved. A pipeline conveying resistance loss calculation model comprehensively considering the multi-factor effect is established, and numerical simulation verification is carried out. The method has the beneficial effects that a theoretical guidance value can be provided for superfine tailing pipeline transportation, the filling pipeline transportation energy consumption is further reduced, pipeline transportation accidents are reduced, and the filling efficiency is improved.

The invention discloses a mountainous area pier durability evaluation method and system based on water-sand composite abrasion, and belongs to the technical field of bridge structure safety evaluation. A composite abrasive particle model considering tangential cutting and normal impact effects is established, discrete solution is performed on the composite abrasive particle model through a smooth particle element solver, and the durability of a pier in a mountainous area is evaluated. Constructing an initial mountainous area pier abrasion rate calculation model; orthogonal test simulation is carried out based on a Box-Behnken design method and a center combination design method, a curve estimation theory and a multivariate nonlinear regression theory are combined, and influences of river water depth, pier pile diameter, flow velocity before water-sand mixed particle impact, sand content, silt particle roundness coefficient and concrete compressive strength on the abrasion rate are considered. Constructing a high-precision bridge pier water-sand abrasion rate calculation model; based on the high-precision bridge pier water-sand abrasion rate calculation model and the bridge site hydrological working condition data, the bridge pier annual abrasion depth is calculated, and whether the bridge pier durability meets the service requirement or not is evaluated based on the concrete protection layer thickness and the bridge pier annual abrasion depth.

The application provides a floor grinding machine gear box guide plate structure parameter optimization design method, which is used for determining the optimal values of three radial clearances between the guide plate and the gear tooth top. Firstly, a parameterized gear box model containing clearance as a variable is constructed, and a gear oil stirring loss theoretical model is established based on the boundary layer theory and the fluid resistance theory; taking the maximum lubrication efficiency as the target and the oil stirring power loss not exceeding the set threshold as the constraint condition, a central composite design method is used to select representative sample points in the design space; through computational fluid dynamics simulation, a moving particle semi-implicit method is used for splash lubrication transient analysis to obtain performance data of each point; based on the simulation data, a high-precision proxy model is constructed; finally, under the condition of meeting the oil stirring power loss constraint condition, the maximum lubrication efficiency is taken as the target for optimization solving to obtain the optimal clearance combination. The method realizes the quantitative design from parameters to performance, and effectively replaces the traditional trial and error method.

The application discloses a kind of tunnel pavement with flame-retardant asphalt and preparation method thereof.Flame-retardant asphalt is based on matrix asphalt, carbon nanotube, fly ash and lignin are added as flame-retardant component.The best flame-retardant proportion of flame-retardant asphalt can be further obtained by central composite design model and comprehensive evaluation method.The preparation method includes matrix asphalt heating, flame-retardant component preheating, matrix asphalt and flame-retardant component step-by-step mixing, high-speed shearing and degassing processes, which can adapt to indoor test preparation process and industrial scale preparation process, with good adaptability and practicality.The application introduces carbon nanotube, fly ash and lignin to form a composite flame-retardant system, and the three components synergistically build a stable multi-scale flame-retardant structure, which significantly improves the flame-retardant performance of asphalt material, while considering environmental protection, economy and engineering adaptability, with significant engineering application value and promotion prospect.

The application provides a kind of anti-rotation plate design parameter sensitivity analysis method and system, method includes: selecting the geometric parameter of k anti-rotation plate as test factor, and based on central composite design test method generates the code table containing multiple anti-rotation plate geometric parameter combination;Based on the code table, generate multiple anti-rotation plate sealing structure, and carry out numerical simulation of steady-state rotor static eccentricity to each anti-rotation plate sealing structure under the same working condition, to obtain the index value of each anti-rotation plate sealing structure stability evaluation index;Based on stability evaluation index analysis anti-rotation plate parameter sensitivity to anti-rotation plate design, and determine the preferred anti-rotation plate design parameter combination according to the analysis result.The application is mainly based on test design DOE method to analyze the sensitivity of key geometric parameters and then obtain the preferred anti-rotation plate design parameter combination, which helps turbine designers to quickly and efficiently meet the anti-rotation plate design requirements in the engineering design process.

The present invention provides a method and system for designing an improved solidification solution for subgrade soil, relating to the field of soil solidification, including: obtaining soil solidification data, expanding the soil solidification data through deep learning to obtain a curing agent information database; screening in the curing agent information database according to soil parameters to obtain a basic formula and corresponding strength data; constructing an initial relationship equation based on the basic formula; designing the coded levels of influencing factors through central composite design to obtain corresponding true values, and fitting the initial relationship equation to obtain an early strength equation and a late strength equation; finding the optimal intersection of the solutions of the early strength equation and the late strength equation to obtain a target formula, and obtaining an improved solidification solution according to the target formula. The present invention automatically calculates and outputs the optimal ratio of raw materials through deep learning and central composite design, thereby realizing intelligent design of the soil curing agent formula.

The present application relates to the technical field of laser cladding, and discloses a laser cladding layer forming quality regulation method and system based on a molten pool powder island, which comprises the following steps: constructing a plurality of different process parameter value combinations based on central composite design according to the value range of each process parameter in the laser cladding process; obtaining the molten pool image in the laser cladding process under each process parameter value combination, extracting the molten pool area and the powder island area to obtain the powder island area proportion, and constructing a relationship model between the powder island area proportion and each process parameter value; determining the optimal value range of the powder island area proportion according to the relationship between the laser cladding layer forming quality and the powder island area proportion; and in the laser cladding process, controlling the value of each process parameter in real time according to the relationship model so that the real-time powder island area proportion is within the optimal value range. The present application can optimize the process parameters in real time, improve the efficiency and the laser cladding layer forming quality in the laser cladding process.

The application discloses a kind of geopolymer repair mortar mix ratio multi-objective optimization design methods, comprising: selecting geopolymer repair mortar mix ratio key parameters, using central composite design to determine mix ratio test scheme, based on the response surface equation of each repair index of mechanical property test result is established;Set mix ratio factor reasonable range to construct constraint function, according to different repair scene demand to establish multi-objective optimization mathematical model, and using non-dominated sorting genetic algorithm NSGA-II to solve;To the Pareto solution set obtained Application of ideal solution sorting method TOPSIS carries out decision analysis, and finally filters out the optimal mix ratio of geopolymer repair mortar under target scene.The present application can provide a more reasonable method for the mix ratio design of geopolymer repair mortar, reduce the cost of trial and error repeatedly, and can meet the multi-performance collaborative optimization demand under complex repair scene.

The invention provides a performance optimization method and system for electromechanical equipment, and relates to the technical field of intelligent control, and the method comprises the steps: obtaining a process index set and a quality index set through the interaction of a target electromechanical equipment scene; establishing a simulation analysis model of a production target of the equipment, and determining an adjustable range of a process index; obtaining a parameter optimization space and carrying out central composite design; calling the simulation model to perform analogue simulation to obtain a sample scheme matrix, and constructing and training a target agent model based on the matrix; the target agent model is used as an optimization target, and a multi-target optimization algorithm is used for optimizing the process index set of the electromechanical equipment, so that the technical problems of poor adaptability to complex scenes, low optimization accuracy and efficiency and difficulty in guaranteeing the intelligence and stability of equipment operation in the performance optimization process of the electromechanical equipment are solved; the accuracy and efficiency of performance optimization of the electromechanical equipment are improved, and then the production efficiency and the product quality are improved.

The invention discloses an intelligent optimization method and system for an equipment model. The intelligent optimization method comprises the steps of obtaining multiple pieces of model test data of equipment; carrying out sparse sampling on the multiple pieces of test data by adopting a central composite design algorithm or a Benkine box design algorithm to obtain a data sample; inputting the data sample into a pre-constructed intelligent optimization model to obtain a prediction equipment model; wherein the intelligent optimization model is obtained by training a polynomial response surface model by adopting historical sample data. According to the system and the method, the artificial intelligence technology is utilized, historical test data and simulation data are combined, forward and reverse fusion is carried out, an intelligent optimization model is constructed, a designer does not need to carry out simulation calculation, optimal model parameters are rapidly obtained through the intelligent optimization model, and therefore manpower and time are saved.

The invention provides an optimization design method for structural parameters of a flow guide plate of a gear box of a floor grinding machine. The optimization design method is used for determining optimal values of three radial internal clearances between the flow guide plate and a gear tooth crest. The method comprises the following steps: firstly, constructing a parameterized gearbox model containing a clearance as a variable, and establishing a gear oil stirring loss theoretical model based on a boundary layer theory and a fluid resistance theory; selecting representative sample points in a design space by adopting a central composite design method by taking lubrication efficiency maximization as a target and taking the condition that the oil stirring power loss does not exceed a set threshold value as a constraint condition; carrying out splash lubrication transient analysis by adopting a moving particle semi-implicit method through computational fluid dynamics simulation to obtain performance data of each point; constructing a high-precision proxy model based on the simulation data; and finally, under the condition that the oil stirring power loss constraint condition is met, optimization solution is carried out by taking lubrication efficiency maximization as a target, and an optimal clearance combination is obtained. According to the method, quantitative design from parameters to performance is achieved, and a traditional trial and error method is effectively replaced.

The motor driver comprises a PCB substrate, an MOS tube, a capacitor and a resistor, and the method comprises the following steps: S1, simplifying a physical model of the motor driver, establishing a FLOTHERM thermal model of the motor driver on the basis of simplifying the physical model, determining an input parameter set, and setting a parameter set; comprise power device loss parameters, material thermophysical parameters and boundary condition parameters; s2, actual measurement temperature data of key temperature measurement points of the motor driver are obtained through a steady-state temperature measurement experiment; s3, performing sensitivity analysis on the input parameters by adopting Latin hypercube sampling in combination with a Pearson correlation coefficient, and screening out high-sensitivity parameters; s4, constructing a response surface model based on central composite design, and optimizing and correcting high-sensitivity parameters in combination with a genetic algorithm; s5, the corrected parameters are substituted into the FLOTHERM thermal model, and the error between the simulation temperature and the actual measurement temperature is verified. The accuracy of the thermal model is remarkably improved.

This invention discloses a multi-objective optimization method for motors that integrates neural networks and NSGA-III, relating to the fields of motor body design optimization and neural learning technology. The method first clarifies the optimization objectives and design variable constraints of maximizing average torque, efficiency, and minimizing torque ripple. Samples are collected and preprocessed through central composite design and finite element simulation. An FNN-CNN hybrid mapping model is constructed, simultaneously extracting local and global features, and establishing a high-precision mapping relationship with a MAE less than 3% as the training termination condition. Based on NSGA-III, θ dominance relations, density indices, and FC functions are introduced to optimize Nadir point estimation and genetic operations, achieving multi-objective collaborative optimization. Finally, the optimization effect is verified through finite element simulation. This invention improves mapping accuracy and the uniformity of the optimized solution distribution, has a faster convergence speed, and strong robustness, making it applicable to various permanent magnet motors and effectively solving the problems of inaccurate modeling and inefficient convergence in traditional methods.

The present invention relates to the technical field of finite element simulation calculation, and proposes a finite element model optimization calculation method for high-speed dynamic loading of gradient composite materials, comprising the following steps: establishing a two-dimensional axisymmetric structural model of a layered gradient configuration; describing the material properties of the two-dimensional axisymmetric structural model to obtain material parameters, and segmentally describing the shock adiabat to obtain a segmented mathematical relationship; correcting the shock wave velocity and particle velocity based on the shear modulus and yield strength to obtain a corrected shock wave velocity and a corrected particle velocity; fitting through the segmented mathematical relationship, the corrected shock wave velocity and the corrected particle velocity to obtain a corrected segmented mathematical relationship between the corrected shock wave velocity and the corrected particle velocity, and based on the material parameters and the corrected segmented mathematical relationship, generating a large number of sample data by using the Latin hypercube sampling method and the central composite design sampling method, evaluating the data points of the sample data through a multi-objective genetic algorithm to obtain optimized sample data; modeling based on the optimized sample data to obtain an initial optimal finite element model, and repeatedly verifying the initial optimal finite element model to obtain an optimal finite element model. The present invention realizes the automation of the modeling process, increases the final particle velocity, reduces the computational time cost at the same time, and improves the accuracy and computational efficiency of the model.

The application discloses a torque optimization method for an outer rotor permanent magnet synchronous motor, and comprises the following steps: 1) design parameter selection: selecting key characteristics of a motor stator slot as design parameters, including slot shoulder height H s1 , tooth length H s2 , chord length B s0 and slot shoulder width B s1 ; 2) finite element model construction: establishing a multi-objective finite element model with tooth slot torque, torque ripple and average torque as targets; 3) analytical model establishment: establishing an analytical model of motor torque by using an energy method and a repeating unit method, and comparing with the finite element model to verify the accuracy of the analytical model; 4) response surface model construction: based on simulation data of the finite element model, performing finite element analysis by using a central composite design (CCD), constructing a response surface model, and performing sensitivity analysis on design variables to determine the influence of each variable on optimization targets; and 5) optimization efficiency improvement: determining an optimal configuration in a design space by using an adaptive genetic aggregation algorithm (AGA), so as to achieve a multi-objective optimization effect.

The present invention provides a method and system for designing an anti-rotation plate. The method includes: constructing a shaft seal model and determining the length and installation position of the anti-rotation plate based on the shaft seal model and axial displacement; obtaining the swirl ratio and rotor tangential gas flow excitation force of the shaft seal with the anti-rotation plate through numerical simulation of steady-state rotor static eccentricity; adjusting the number of rows and installation position of the anti-rotation plate, and controlling the swirl ratio within a certain range in the shaft seal section through limited iteration; generating a coding table based on the central composite design experimental method; analyzing the rotor tangential gas flow excitation force corresponding to each anti-rotation plate structure for various anti-rotation plate structures generated based on the coding table, and obtaining the anti-rotation plate structure with the best stability. The present invention can effectively improve the dynamic characteristics of the shaft seal rotor and meet the design of the anti-rotation plate structure for rapidly and efficiently improving the multi-stage shaft seal stability enhancement and vibration suppression performance during the engineering design process.

The invention discloses a quality evaluation method for determining optimal processing technological parameters of bran-stewed ginger, and belongs to the technical field of traditional Chinese medicine processing and quality control. According to the Box-Behnken central combination design principle, the simmering temperature, the simmering time and the dosage ratio of wheat bran to medicinal materials are selected as three influence factors. Putting ginger slices and wheat bran into a pot according to a certain proportion, heating with slow fire, burying and properly turning until the whole wheat bran is brown, screening out the wheat bran, and cooling to obtain stewed ginger; respectively measuring the contents of 6, 7, 8-gingerol and total gingerol as evaluation indexes, and carrying out a response surface test on the bran-stewed ginger. And carrying out model fitting and variance analysis on the comprehensive scoring result to obtain the optimal processing technological parameters of the wheat bran stewed ginger. According to the invention, the limitations of difficulty in controlling the processing degree, tedious operation and the like of the traditional processing of paper simmering, flour simmering and the like are improved, the simmered products with uniform appearance and color are prepared, and the processing purposes of slow cooking and dryness reduction are realized.

The invention relates to a method for extracting starch from wild acorn. A response surface method and a genetic algorithm are adopted to collaboratively optimize an acorn starch extraction process. The method comprises the following steps: firstly, carrying out an experiment through central composite design, establishing a secondary prediction model of soaking temperature, pH value, time, H2O2 concentration and solid-to-liquid ratio with starch whiteness, tannin residual quantity and purity, then taking an RSM model as a fitness function of GA, and carrying out a sensitivity-guided variation strategy and a dynamic weight adjustment mechanism so as to obtain a sensitivity-guided GA (Genetic Algorithm) model. And efficient optimization is carried out in the RSM-guided contraction search space. According to the scheme, double termination conditions are adopted, the optimal process parameters are finally obtained through experimental verification, other optimization algorithms do not need to be introduced, deep collaboration of RSM and GA is achieved, a suboptimal solution caused by premature termination is avoided, resource waste caused by excessive iteration is prevented, and the optimal balance of optimization efficiency and precision is achieved.

The invention relates to the technical field of laser cladding, and discloses a molten pool powder island-based laser cladding layer forming quality regulation and control method and system, and the method comprises the following steps: constructing a plurality of different technological parameter value combinations based on central composite design according to the value range of each technological parameter in the laser cladding process; a molten pool image in the laser cladding process under each set of technological parameter value combination is obtained, a molten pool area and a powder island area are extracted to obtain a powder island area proportion, and a relation model between the powder island area proportion and all the technological parameter values is constructed; according to the relation between the forming quality of the laser cladding layer and the area proportion of the powder island, the optimal value range of the area proportion of the powder island is determined; and in the laser cladding process, the value of each process parameter is controlled in real time according to the relation model, so that the real-time powder island area proportion is within the optimal value range. According to the method, the process parameters can be optimized in real time in the cladding process, and the efficiency and the cladding layer forming quality are improved.

The invention discloses an asphalt mixture mix proportion design method based on a response surface method, and aims to solve the problems of high subjectivity, insufficient optimization and low efficiency and precision of traditional asphalt mixture mix proportion design. The method comprises the following steps: determining key design variables and response indexes, arranging an experimental scheme by adopting a central composite design in a response surface method, and combining a three-control-point hyperbolic theory to generate complete mineral aggregate gradation; a test piece is prepared, performance indexes are tested, a quadratic polynomial prediction model is established, an optimal design variable combination is solved through multi-objective optimization, and finally the optimal mix proportion is determined through verification. According to the method, on the basis of a mathematical statistical method, human experience interference is reduced, multi-factor interaction can be accurately quantified, the global optimal mix proportion is obtained with fewer test times, the performance potential of the material is maximized, and scientific and efficient technical support is provided for asphalt mixture design.

The application discloses a mountain bridge pier durability evaluation method and system based on water-sand composite abrasion, and belongs to the technical field of bridge structure safety evaluation. A composite abrasive model considering tangential cutting and normal impact is established, the composite abrasive model is discretely solved by a smoothed particle hydrodynamics solver, and an initial mountain bridge pier abrasion rate calculation model is constructed. Orthogonal test simulation is carried out based on Box-Behnken design method and central composite design method, curve estimation theory and multivariate nonlinear regression theory are combined, the influences of river depth, pier diameter, water-sand mixed particle flow velocity before impact, sand content, silt particle roundness coefficient and concrete compressive strength on the abrasion rate are considered, and a high-precision bridge pier water-sand abrasion rate calculation model is constructed. Based on the high-precision bridge pier water-sand abrasion rate calculation model and hydrological working condition data at the bridge site, the annual abrasion depth of the bridge pier is calculated, and whether the durability performance of the bridge pier can meet the service requirements is evaluated based on the concrete protective layer thickness and the annual abrasion depth of the bridge pier.