A fast and accurate homography matrix method for four-wheel positioning detection was presented in the paper.Fewer sensors were required with simpler operation and faster detection.Firstly,eight feature points were ex...A fast and accurate homography matrix method for four-wheel positioning detection was presented in the paper.Fewer sensors were required with simpler operation and faster detection.Firstly,eight feature points were extracted by using the target detection algorithm based on the fitting method.Secondly,six feature points were obtained by line fitting-based selection.Thirdly,from the selected six feature points,five points were randomly chosen to minimize the re-projection error.Finally,four points were randomly selected from these five feature points to find the homography matrix,and the other point was back to the homography matrix for verification.The experimental results show that the mean re-projection error is reduced by about 3.41%−4.57%compared with the modified RANSAC(Random sample consensus)algorithm.With the optimized algorithm,the error is reduced by about 12.81%−13.86%compared with the improved RANSAC algorithm.Compared with traditional targets,the average calibration time is reduced by about 26.95%−27.88%.The results indicated that the combination of target algorithm and optimization algorithm could ensure the accuracy and reliability of four-wheel positioning.展开更多
Gear assembly errors can lead to the increase of vibration and noise of the system,which affect the stability of system.The influence can be compensated by tooth modification.Firstly,an improved three-dimensional load...Gear assembly errors can lead to the increase of vibration and noise of the system,which affect the stability of system.The influence can be compensated by tooth modification.Firstly,an improved three-dimensional loaded tooth contact analysis(3D-LTCA)method which can consider tooth modification and coupling assembly errors is proposed,and mesh stiffness calculated by proposed method is verified by MASTA software.Secondly,based on neural network,the surrogate model(SM)that maps the relationship between modification parameters and mesh mechanical parameters is established,and its accuracy is verified.Finally,SM is introduced to establish an optimization model with the target of minimizing mesh stiffness variations and obtaining more even load distribution on mesh surface.The results show that even considering training time,the efficiency of gear pair optimization by surrogate model is still much higher than that by LTCA method.After optimization,the mesh stiffness fluctuation of gear pair with coupling assembly error is reduced by 34.10%,and difference in average contact stresses between left and right regions of the mesh surface is reduced by 62.84%.展开更多
Although significant progress has been made in precision machining of free-form surfaces recently, inspection of such surfaces remains a difficult problem. In order to solve the problem that no specific standards for ...Although significant progress has been made in precision machining of free-form surfaces recently, inspection of such surfaces remains a difficult problem. In order to solve the problem that no specific standards for the verification of free-form surface profile are available, the profile parameters of free-form surface are proposed by referring to ISO standards regarding form tolerances and considering its complexity and non-rotational symmetry. Non-uniform rational basis spline（NURBS） for describing free-form surface is formulated. Crucial issues in surface inspection and profile error verification are localization between the design coordinate system（DCS） and measurement coordinate system（MCS） for searching the closest points on the design model corresponding to measured points. A quasi particle swarm optimization（QPSO） is proposed to search the transformation parameters to implement localization between DCS and MCS. Surface subdivide method which does the searching in a recursively reduced range of the parameters u and v of the NURBS design model is developed to find the closest points. In order to verify the effectiveness of the proposed methods, the design model is generated by NURBS and the measurement data of simulation example are generated by transforming the design model to arbitrary position and orientation, and the parts are machined based on the design model and are measured on CMM. The profile errors of simulation example and actual parts are calculated by the proposed method. The results verify that the evaluation precision of freeform surface profile error by the proposed method is higher 10%-22% than that by CMM software. The proposed method deals with the hard problem that it has a lower precision in profile error evaluation of free-form surface.展开更多
The accurate measurement of surfaces of large aviation components is vital for the assessment of manufacturing and assembly quality of such components.To satisfy the measurement requirement of large-size components,mo...The accurate measurement of surfaces of large aviation components is vital for the assessment of manufacturing and assembly quality of such components.To satisfy the measurement requirement of large-size components,most current researches pay more attention to combined measurement methods utilizing different measuring instruments,but the related researches on error analysis and optimization methods are not taken enough attention.This paper proposes a combined laser-assisted measurement method with feature enhancement techniques,and it also develops an error propagation model of the main factors affecting the overall measurement error in detail.Firstly,the surface of a large-size component is measured by the measurement system at multiple stations.Secondly,a control point coordinate system is established as a bridge to unify all local measurement data into the global coordinate system.To improve the overall measurement accuracy,the pixel extraction error as a key factor causing the overall measurement error is analyzed in detail.Next,the error propagation model is established,and some optimization strategies of layout for minimizing measurement error and transformation error are researched.Finally,experiments are carried out to verify the effectiveness of the proposed method.The results show that the measurement error of the proposed method reaches 0.073%and 0.14%with a 1 D standard ruler and a flat plate,respectively.展开更多
To estimate the parameters of the mixed additive and multiplicative(MAM)random error model using the weighted least squares iterative algorithm that requires derivation of the complex weight array,we introduce a deriv...To estimate the parameters of the mixed additive and multiplicative(MAM)random error model using the weighted least squares iterative algorithm that requires derivation of the complex weight array,we introduce a derivative-free cat swarm optimization for parameter estimation.We embed the Powell method,which uses conjugate direction acceleration and does not need to derive the objective function,into the original cat swarm optimization to accelerate its convergence speed and search accuracy.We use the ordinary least squares,weighted least squares,original cat swarm optimization,particle swarm algorithm and improved cat swarm optimization to estimate the parameters of the straight-line fitting MAM model with lower nonlinearity and the DEM MAM model with higher nonlinearity,respectively.The experimental results show that the improved cat swarm optimization has faster convergence speed,higher search accuracy,and better stability than the original cat swarm optimization and the particle swarm algorithm.At the same time,the improved cat swarm optimization can obtain results consistent with the weighted least squares method based on the objective function only while avoiding multiple complex weight array derivations.The method in this paper provides a new idea for theoretical research on parameter estimation of MAM error models.展开更多
Conventional reliability-based design optimization （RBDO） requires to use the most probable point （MPP） method for a probabilistic analysis of the reliability constraints. A new approach is presented, called as th...Conventional reliability-based design optimization （RBDO） requires to use the most probable point （MPP） method for a probabilistic analysis of the reliability constraints. A new approach is presented, called as the minimum error point （MEP） method or the MEP based method, for reliability-based design optimization, whose idea is to minimize the error produced by approximating performance functions. The MEP based method uses the first order Taylor＇s expansion at MEP instead of MPP. Examples demonstrate that the MEP based design optimization can ensure product reliability at the required level, which is very imperative for many important engineering systems. The MEP based reliability design optimization method is feasible and is considered as an alternative for solving reliability design optimization problems. The MEP based method is more robust than the commonly used MPP based method for some irregular performance functions.展开更多
Taking the accelerometer installation errors into consideration, the attitude optimization algorithm of Gyro Free Inertial Meastement Unit （GFIMU） is studied in the high spinning condition in this paper. A ten-accel...Taking the accelerometer installation errors into consideration, the attitude optimization algorithm of Gyro Free Inertial Meastement Unit （GFIMU） is studied in the high spinning condition in this paper. A ten-accelerometer configuration is designed so as to establish a mathematical model to acquire the angular speeds in the case of installation errors. Precision of the algorithm is evaluated by using damping GaussNewton method. A large amotmt of sinmlation results show that ff the accelertlmter＇s angleinstallation errors main-tain small （〈5°）, the errors of attitude angles can be limited within ±1°. Hence, the algorithm has a great applicable value in engineering.展开更多
The machining precision of blades is critical to the service performance of aero engines.The Leading Edge(LE) of high-pressure compressor blades poses a challenge for precision machining due to its thin size, high deg...The machining precision of blades is critical to the service performance of aero engines.The Leading Edge(LE) of high-pressure compressor blades poses a challenge for precision machining due to its thin size, high degree of bending, and significant change of curvature. Aimed at optimizing the machining error, this paper presents a framework that integrates toolpath planning and process parameter regulation. Firstly, an Iterative Subdivision Algorithm(ISA) for clamped Bspline curve is proposed, based on which toolpath planning method towards the LE is developed.Secondly, the removal effect of Cutter Contact(CC) point on the sampling points is investigated in the calculation of grinding dwell time by traversing in u-v space. A global material removal model is constructed for the solution. Thirdly, the previous two steps are interconnected based on the Improved Whale Optimization Algorithm(IWOA), and the optimal parameter combination is searched using the Root Mean Square Error(RMSE) of the machining error as the objective function. Based on this, the off-line programming and robotic grinding experiments are carried out. The experimental results show that the proposed method with error optimization can achieve 0.0143 mm mean value and 0.0160 mm standard deviations of LE surface error, which is an improvement of32.5% and 33.9%, respectively, compared with previous method.展开更多
On-machine measurement(OMM)stands out as a pivotal technology in complex curved surface adaptive machining.However,the complex structure inherent in workpieces poses a significant challenge as the stylus orientation f...On-machine measurement(OMM)stands out as a pivotal technology in complex curved surface adaptive machining.However,the complex structure inherent in workpieces poses a significant challenge as the stylus orientation frequently shifts during the measurement process.Consequently,a substantial amount of time is allocated to calibrating pre-travel error and probe movement.Furthermore,the frequent movement of machine tools also increases the influence of machine errors.To enhance both accuracy and efficiency,an optimization strategy for the OMM process is proposed.Based on the kinematic chain of the machine tools,the relationship between the angle combination of rotary axes,the stylus orientation,and the calibration position of pre-travel error is disclosed.Additionally,an OMM efficiency optimization model for complex curved surfaces is developed.This model is solved to produce the optimal efficiency angle combinations for each to-be-measured point.Within each angle combination,the effects of positioning errors on measurement results are addressed by coordinate system offset and measurement result compensation method.Finally,the experiments on an impeller are used to demonstrate the practical utility of the proposed method.展开更多
This paper analyzes the generalization of minimax regret optimization(MRO)under distribution shift.A new learning framework is proposed by injecting the measure of con-ditional value at risk(CVaR)into MRO,and its gene...This paper analyzes the generalization of minimax regret optimization(MRO)under distribution shift.A new learning framework is proposed by injecting the measure of con-ditional value at risk(CVaR)into MRO,and its generalization error bound is established through the lens of uniform convergence analysis.The CVaR-based MRO can achieve the polynomial decay rate on the excess risk,which extends the generalization analysis associated with the expected risk to the risk-averse case.展开更多
with the merits of the easy manufacture and the long service life and the processing the inside or outside form surface, round body form tool is extensive use in large scales production. Its main demerit is the big hy...with the merits of the easy manufacture and the long service life and the processing the inside or outside form surface, round body form tool is extensive use in large scales production. Its main demerit is the big hyperbolic error which is caused in the process of processing cone, but about the discussion of hyperbolic error, there are two drawbacks in the current books and documents: (1) The error measuring plane is established on the rake face of tool, which doesn’t coincide with the actual measuring plane (axial plane) of work piece; (2) When the influential elements of error are analyzed, single parameter is only discussed. In order to overcome these demerits, the mathematical model of hyperbolic error on the axial plane of work piece is built in this paper when round body form tool processes cone. The fundamental reason which causes hyperbolic error when round body form tool processes cone is that the line profile replaces the curve profile of theory in the radial cut plane of tool in the design and manufacture of tool. In order to evaluate the mathematical formula of its error, firstly, the equation of cone of work piece must be established, secondly, the equation of cutting lip in the rake face is established, then, the profile equation of the radial plane of tool is evaluated on the condition that coordinate is changed, at last, the hyperbolic error is derived according to the equation and the substitutional line equation, and the error is converted to the axial plane of work piece which is coincided with the measuring plane. The actual calculation and the theory analysis indicated that if the cone length and the coning of the cone of work piece are fixed, the main elements which affect the hyperbolic error in the axial plane of work piece are the outside diameter R of round body form tool, the rake angle and the rear angle in "base point". If these three parameters are combined rationally, the hyperbolic error is minimum when round body form tool process cone, and the machining precision of work piece can be improved, on the condition that neither the work capacity of the tool design nor the manufacture cost of tool increases.展开更多
This paper presents an innovative and effective control strategy tailored for a deregulated,diversified energy system involving multiple interconnected area.Each area integrates a unique mix of power generation techno...This paper presents an innovative and effective control strategy tailored for a deregulated,diversified energy system involving multiple interconnected area.Each area integrates a unique mix of power generation technologies:Area 1 combines thermal,hydro,and distributed generation;Area 2 utilizes a blend of thermal units,distributed solar technologies(DST),and hydro power;andThird control area hosts geothermal power station alongside thermal power generation unit and hydropower units.The suggested control system employs a multi-layered approach,featuring a blended methodology utilizing the Tilted Integral Derivative controller(TID)and the Fractional-Order Integral method to enhance performance and stability.The parameters of this hybrid TID-FOI controller are finely tuned using an advanced optimization method known as the Walrus Optimization Algorithm(WaOA).Performance analysis reveals that the combined TID-FOI controller significantly outperforms the TID and PID controllers when comparing their dynamic response across various system configurations.The study also incorporates investigation of redox flow batteries within the broader scope of energy storage applications to assess their impact on system performance.In addition,the research explores the controller’s effectiveness under different power exchange scenarios in a deregulated market,accounting for restrictions on generation ramp rates and governor hysteresis effects in dynamic control.To ensure the reliability and resilience of the presented methodology,the system transitions and develops across a broad range of varying parameters and stochastic load fluctuation.To wrap up,the study offers a pioneering control approach-a hybrid TID-FOI controller optimized via the Walrus Optimization Algorithm(WaOA)-designed for enhanced stability and performance in a complex,three-region hybrid energy system functioning within a deregulated framework.展开更多
Based on the high-resolution Regional Ocean Modeling System(ROMS) and the conditional nonlinear optimal perturbation(CNOP) method, this study explored the effects of optimal initial errors on the prediction of the Kur...Based on the high-resolution Regional Ocean Modeling System(ROMS) and the conditional nonlinear optimal perturbation(CNOP) method, this study explored the effects of optimal initial errors on the prediction of the Kuroshio large meander(LM) path, and the growth mechanism of optimal initial errors was revealed. For each LM event, two types of initial error(denoted as CNOP1 and CNOP2) were obtained. Their large amplitudes were found located mainly in the upper 2500 m in the upstream region of the LM, i.e., southeast of Kyushu. Furthermore, we analyzed the patterns and nonlinear evolution of the two types of CNOP. We found CNOP1 tends to strengthen the LM path through southwestward extension. Conversely,CNOP2 has almost the opposite pattern to CNOP1, and it tends to weaken the LM path through northeastward contraction.The growth mechanism of optimal initial errors was clarified through eddy-energetics analysis. The results indicated that energy from the background field is transferred to the error field because of barotropic and baroclinic instabilities. Thus, it is inferred that both barotropic and baroclinic processes play important roles in the growth of CNOP-type optimal initial errors.展开更多
AIM: To evaluate the effect of different lens constant optimization methods on the accuracy of intraocular lens(IOL) power calculation formulas for highly myopic eyes.METHODS: This study comprised 108 eyes of 94 conse...AIM: To evaluate the effect of different lens constant optimization methods on the accuracy of intraocular lens(IOL) power calculation formulas for highly myopic eyes.METHODS: This study comprised 108 eyes of 94 consecutive patients with axial length(AL) over 26 mm undergoing phacoemulsification and implantation of a Rayner(Hove, UK) 920H IOL. Formulas were evaluated using the following lens constants: manufacturer’s lens constant, User Group for Laser Interference Biometry(ULIB) constant, and optimized constant for long eyes. Results were compared with Barrett Universal II formula, original Wang-Koch AL adjustment method, and modified Wang-Koch AL adjustment method. The outcomes assessed were mean absolute error(MAE) and percentage of eyes with IOL prediction errors within ±0.25, ±0.50, and ±1.0 diopter(D). The nonparametric method, Friedman test, was used to compare MAE performance among constants.RESULTS: Optimized constants could significantly reduce the MAE of SRK/T, Hoffer Q, and Holladay 1 formulas compared with manufacturer’s lens constant, whereas the percentage of eyes with IOL prediction errors within ±0.25, ±0.50, and ±1.0 D had no statistically significant differences. Optimized lens constant for long eyes alone showed non-significant refractive advantages over the ULIB constant. Barrett Universal II formula and formulas with AL adjustment showed significantly higher accuracy in highly myopic eyes(P<0.001). CONCLUSION: Lens constant optimization for the subset of long eyes reduces the refractive error only to a limited extent for highly myopic eyes.展开更多
A grating eddy current displacement sensor(GECDS) can be used in a watertight electronic transducer to realize long range displacement or position measurement with high accuracy in difficult industry conditions.The pa...A grating eddy current displacement sensor(GECDS) can be used in a watertight electronic transducer to realize long range displacement or position measurement with high accuracy in difficult industry conditions.The parameters optimization of the sensor is essential for economic and efficient production.This paper proposes a method to combine an artificial neural network(ANN) and a genetic algorithm(GA) for the sensor parameters optimization.A neural network model is developed to map the complex relationship between design parameters and the nonlinearity error of the GECDS,and then a GA is used in the optimization process to determine the design parameter values,resulting in a desired minimal nonlinearity error of about 0.11%.The calculated nonlinearity error is 0.25%.These results show that the proposed method performs well for the parameters optimization of the GECDS.展开更多
Although the two-grid finite element decoupled scheme for mixed Navier-Stokes/ Darcy model in literatures has given the numerical results of optimal convergence order, the theoretical analysis only obtain the optimal ...Although the two-grid finite element decoupled scheme for mixed Navier-Stokes/ Darcy model in literatures has given the numerical results of optimal convergence order, the theoretical analysis only obtain the optimal error order for the porous media flow and a non-optimal error order for the fluid flow. In this article, we give a more rigorous of the error analysis for the fluid flow and obtain the optimal error estimates of the velocity and the pressure.展开更多
In this paper,we investigate a streamline diffusion finite element approxi- mation scheme for the constrained optimal control problem governed by linear con- vection dominated diffusion equations.We prove the existenc...In this paper,we investigate a streamline diffusion finite element approxi- mation scheme for the constrained optimal control problem governed by linear con- vection dominated diffusion equations.We prove the existence and uniqueness of the discretized scheme.Then a priori and a posteriori error estimates are derived for the state,the co-state and the control.Three numerical examples are presented to illustrate our theoretical results.展开更多
Focused energy delivery(FED) is a technique that can precisely bring energy to the specific region,which arouses wide attention in precision electronic warfare(PREW).This paper first proposes a joint optimization mode...Focused energy delivery(FED) is a technique that can precisely bring energy to the specific region,which arouses wide attention in precision electronic warfare(PREW).This paper first proposes a joint optimization model with respect to the locations of the array and the transmitted signals to improve the performance of FED.As the problem is nonconvex and NP-hard,particle swarm optimization(PSO) is adopted to solve the locations of the array,while designing the transmitted signals under a feasible array is considered as a unimodular quadratic program(UQP) subproblem to calculate the fitness criterion of PSO.In the PSO-UQP framework established,two methods are presented for the UQP subproblem,which are more efficient and more accurate respectively than previous works.Furthermore,a threshold value is set in the framework to determine which method to adopt to take full advantages of the methods above.Meanwhile,we obtain the maximum localization error that FED can tolerate,which is significant for implementing FED in practice.Simulation results are provided to demonstrate the effectiveness of the joint optimization algorithm,and the correctness of the maximum localization error derived.展开更多
We’ll study the FEM for a model for compressible miscible displacement in porous media which includes molecular diffusion and mechanical dispersion in one-dimensional space.A class of vertices-edges-elements interpol...We’ll study the FEM for a model for compressible miscible displacement in porous media which includes molecular diffusion and mechanical dispersion in one-dimensional space.A class of vertices-edges-elements interpolation operator ink is introduced.With the help of ink(not elliptic projection),the optimal error estimate in L∞(J;L2(Ω)) norm of FEM is proved.展开更多
Highly accurate spatial discretization is essentially required to perform numerical climate and weather prediction. The difference between the differential and the finite-difference operator is however a primitive err...Highly accurate spatial discretization is essentially required to perform numerical climate and weather prediction. The difference between the differential and the finite-difference operator is however a primitive error source in the numerics. This paper presents an optimization of centered finite-difference operator based on the principle of constrained cost function, which can reduce the truncation error to minimum. In the optimization point of view, such optimal operator is in fact an attempt to minimize spatial truncation er-rors in atmospheric modeling, in a simple way and indeed a quite innovative way to implement Variational Continuous Assimilation (VCA) technique. Furthermore, the optimizing difference operator is consciously designed to be meshing-independent, so that it can be used for most Arakawa-mesh configurations, such as un-staggered (Arakawa-A) or com-monly staggered (Arakawa-B, Arakawa-C, Arakawa-D) mesh. But for the calibration purpose, the pro-posed operator is implemented on an un-staggered mesh in which the truncation oscillation is mostly ex-cited, and it thus makes a severe and indeed a benchmark test for the proposed optimal scheme. Both theo-retical investigation and practical modeling indicate that the aforementioned numerical noise can be significantly eliminated.展开更多
基金supported by Anhui Province Key Research and Development Program(No.2022107020012)Shenzhen Science and Technology Innovation Project(No.JSGG20191129102008260).
文摘A fast and accurate homography matrix method for four-wheel positioning detection was presented in the paper.Fewer sensors were required with simpler operation and faster detection.Firstly,eight feature points were extracted by using the target detection algorithm based on the fitting method.Secondly,six feature points were obtained by line fitting-based selection.Thirdly,from the selected six feature points,five points were randomly chosen to minimize the re-projection error.Finally,four points were randomly selected from these five feature points to find the homography matrix,and the other point was back to the homography matrix for verification.The experimental results show that the mean re-projection error is reduced by about 3.41%−4.57%compared with the modified RANSAC(Random sample consensus)algorithm.With the optimized algorithm,the error is reduced by about 12.81%−13.86%compared with the improved RANSAC algorithm.Compared with traditional targets,the average calibration time is reduced by about 26.95%−27.88%.The results indicated that the combination of target algorithm and optimization algorithm could ensure the accuracy and reliability of four-wheel positioning.
基金Project(11972112)supported by the National Natural Science Foundation of ChinaProject(N2103024)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(J2019-IV-0018-0086)supported by the National Science and Technology Major Project,China。
文摘Gear assembly errors can lead to the increase of vibration and noise of the system,which affect the stability of system.The influence can be compensated by tooth modification.Firstly,an improved three-dimensional loaded tooth contact analysis(3D-LTCA)method which can consider tooth modification and coupling assembly errors is proposed,and mesh stiffness calculated by proposed method is verified by MASTA software.Secondly,based on neural network,the surrogate model(SM)that maps the relationship between modification parameters and mesh mechanical parameters is established,and its accuracy is verified.Finally,SM is introduced to establish an optimization model with the target of minimizing mesh stiffness variations and obtaining more even load distribution on mesh surface.The results show that even considering training time,the efficiency of gear pair optimization by surrogate model is still much higher than that by LTCA method.After optimization,the mesh stiffness fluctuation of gear pair with coupling assembly error is reduced by 34.10%,and difference in average contact stresses between left and right regions of the mesh surface is reduced by 62.84%.
基金supported by National Natural Science Foundation of China(Grant No. 51075198)Jiangsu Provincial Natural Science Foundation of China(Grant No. BK2010479)+1 种基金Jiangsu Provincial Project of 333 Talents Engineering of ChinaJiangsu Provincial Project of Six Talented Peak of China
文摘Although significant progress has been made in precision machining of free-form surfaces recently, inspection of such surfaces remains a difficult problem. In order to solve the problem that no specific standards for the verification of free-form surface profile are available, the profile parameters of free-form surface are proposed by referring to ISO standards regarding form tolerances and considering its complexity and non-rotational symmetry. Non-uniform rational basis spline（NURBS） for describing free-form surface is formulated. Crucial issues in surface inspection and profile error verification are localization between the design coordinate system（DCS） and measurement coordinate system（MCS） for searching the closest points on the design model corresponding to measured points. A quasi particle swarm optimization（QPSO） is proposed to search the transformation parameters to implement localization between DCS and MCS. Surface subdivide method which does the searching in a recursively reduced range of the parameters u and v of the NURBS design model is developed to find the closest points. In order to verify the effectiveness of the proposed methods, the design model is generated by NURBS and the measurement data of simulation example are generated by transforming the design model to arbitrary position and orientation, and the parts are machined based on the design model and are measured on CMM. The profile errors of simulation example and actual parts are calculated by the proposed method. The results verify that the evaluation precision of freeform surface profile error by the proposed method is higher 10%-22% than that by CMM software. The proposed method deals with the hard problem that it has a lower precision in profile error evaluation of free-form surface.
基金co-supported by the National Key Research and Development Project of China(No.2018YFA0703304)the High-level Personnel Innovation Support Program of Dalian(No.2017RJ04)+2 种基金Youth Program of National Natural Science Foundation of China(No.51905077)Liaoning Revitalization Talents Program(No.XLYC1807086)China Postdoctoral Science Foundation Grand(No.2019M651110)。
文摘The accurate measurement of surfaces of large aviation components is vital for the assessment of manufacturing and assembly quality of such components.To satisfy the measurement requirement of large-size components,most current researches pay more attention to combined measurement methods utilizing different measuring instruments,but the related researches on error analysis and optimization methods are not taken enough attention.This paper proposes a combined laser-assisted measurement method with feature enhancement techniques,and it also develops an error propagation model of the main factors affecting the overall measurement error in detail.Firstly,the surface of a large-size component is measured by the measurement system at multiple stations.Secondly,a control point coordinate system is established as a bridge to unify all local measurement data into the global coordinate system.To improve the overall measurement accuracy,the pixel extraction error as a key factor causing the overall measurement error is analyzed in detail.Next,the error propagation model is established,and some optimization strategies of layout for minimizing measurement error and transformation error are researched.Finally,experiments are carried out to verify the effectiveness of the proposed method.The results show that the measurement error of the proposed method reaches 0.073%and 0.14%with a 1 D standard ruler and a flat plate,respectively.
基金supported by the National Natural Science Foundation of China(No.42174011 and No.41874001).
文摘To estimate the parameters of the mixed additive and multiplicative(MAM)random error model using the weighted least squares iterative algorithm that requires derivation of the complex weight array,we introduce a derivative-free cat swarm optimization for parameter estimation.We embed the Powell method,which uses conjugate direction acceleration and does not need to derive the objective function,into the original cat swarm optimization to accelerate its convergence speed and search accuracy.We use the ordinary least squares,weighted least squares,original cat swarm optimization,particle swarm algorithm and improved cat swarm optimization to estimate the parameters of the straight-line fitting MAM model with lower nonlinearity and the DEM MAM model with higher nonlinearity,respectively.The experimental results show that the improved cat swarm optimization has faster convergence speed,higher search accuracy,and better stability than the original cat swarm optimization and the particle swarm algorithm.At the same time,the improved cat swarm optimization can obtain results consistent with the weighted least squares method based on the objective function only while avoiding multiple complex weight array derivations.The method in this paper provides a new idea for theoretical research on parameter estimation of MAM error models.
基金This project is supported by National Natural Science Foundation of China(No.50575072)Outstanding Youth Fund of Hunan Education Department, China (No.04B007).
文摘Conventional reliability-based design optimization （RBDO） requires to use the most probable point （MPP） method for a probabilistic analysis of the reliability constraints. A new approach is presented, called as the minimum error point （MEP） method or the MEP based method, for reliability-based design optimization, whose idea is to minimize the error produced by approximating performance functions. The MEP based method uses the first order Taylor＇s expansion at MEP instead of MPP. Examples demonstrate that the MEP based design optimization can ensure product reliability at the required level, which is very imperative for many important engineering systems. The MEP based reliability design optimization method is feasible and is considered as an alternative for solving reliability design optimization problems. The MEP based method is more robust than the commonly used MPP based method for some irregular performance functions.
基金supported by National Key Laboratory for Electronic Measurement and Technology(No.9140C120401080C12)
文摘Taking the accelerometer installation errors into consideration, the attitude optimization algorithm of Gyro Free Inertial Meastement Unit （GFIMU） is studied in the high spinning condition in this paper. A ten-accelerometer configuration is designed so as to establish a mathematical model to acquire the angular speeds in the case of installation errors. Precision of the algorithm is evaluated by using damping GaussNewton method. A large amotmt of sinmlation results show that ff the accelertlmter＇s angleinstallation errors main-tain small （〈5°）, the errors of attitude angles can be limited within ±1°. Hence, the algorithm has a great applicable value in engineering.
基金supported by the National Natural Science Foundation of China (No. 52075059)Graduate Scientific Research and Innovation Foundation of Chongqing (No. CYB23021)the Innovation Fund of Aero Engine Corporation of China (No. ZZCX-2022-019)。
文摘The machining precision of blades is critical to the service performance of aero engines.The Leading Edge(LE) of high-pressure compressor blades poses a challenge for precision machining due to its thin size, high degree of bending, and significant change of curvature. Aimed at optimizing the machining error, this paper presents a framework that integrates toolpath planning and process parameter regulation. Firstly, an Iterative Subdivision Algorithm(ISA) for clamped Bspline curve is proposed, based on which toolpath planning method towards the LE is developed.Secondly, the removal effect of Cutter Contact(CC) point on the sampling points is investigated in the calculation of grinding dwell time by traversing in u-v space. A global material removal model is constructed for the solution. Thirdly, the previous two steps are interconnected based on the Improved Whale Optimization Algorithm(IWOA), and the optimal parameter combination is searched using the Root Mean Square Error(RMSE) of the machining error as the objective function. Based on this, the off-line programming and robotic grinding experiments are carried out. The experimental results show that the proposed method with error optimization can achieve 0.0143 mm mean value and 0.0160 mm standard deviations of LE surface error, which is an improvement of32.5% and 33.9%, respectively, compared with previous method.
基金Projects(51775445,52175435)supported by the National Natural Science Foundation of ChinaProject(CX2023051)supported by the Innovation Foundation for Doctor Dissertation of Northwestern Polytechnical University,China。
文摘On-machine measurement(OMM)stands out as a pivotal technology in complex curved surface adaptive machining.However,the complex structure inherent in workpieces poses a significant challenge as the stylus orientation frequently shifts during the measurement process.Consequently,a substantial amount of time is allocated to calibrating pre-travel error and probe movement.Furthermore,the frequent movement of machine tools also increases the influence of machine errors.To enhance both accuracy and efficiency,an optimization strategy for the OMM process is proposed.Based on the kinematic chain of the machine tools,the relationship between the angle combination of rotary axes,the stylus orientation,and the calibration position of pre-travel error is disclosed.Additionally,an OMM efficiency optimization model for complex curved surfaces is developed.This model is solved to produce the optimal efficiency angle combinations for each to-be-measured point.Within each angle combination,the effects of positioning errors on measurement results are addressed by coordinate system offset and measurement result compensation method.Finally,the experiments on an impeller are used to demonstrate the practical utility of the proposed method.
基金Supported by Education Science Planning Project of Hubei Province(2020GB198)Natural Science Foundation of Hubei Province(2023AFB523).
文摘This paper analyzes the generalization of minimax regret optimization(MRO)under distribution shift.A new learning framework is proposed by injecting the measure of con-ditional value at risk(CVaR)into MRO,and its generalization error bound is established through the lens of uniform convergence analysis.The CVaR-based MRO can achieve the polynomial decay rate on the excess risk,which extends the generalization analysis associated with the expected risk to the risk-averse case.
文摘with the merits of the easy manufacture and the long service life and the processing the inside or outside form surface, round body form tool is extensive use in large scales production. Its main demerit is the big hyperbolic error which is caused in the process of processing cone, but about the discussion of hyperbolic error, there are two drawbacks in the current books and documents: (1) The error measuring plane is established on the rake face of tool, which doesn’t coincide with the actual measuring plane (axial plane) of work piece; (2) When the influential elements of error are analyzed, single parameter is only discussed. In order to overcome these demerits, the mathematical model of hyperbolic error on the axial plane of work piece is built in this paper when round body form tool processes cone. The fundamental reason which causes hyperbolic error when round body form tool processes cone is that the line profile replaces the curve profile of theory in the radial cut plane of tool in the design and manufacture of tool. In order to evaluate the mathematical formula of its error, firstly, the equation of cone of work piece must be established, secondly, the equation of cutting lip in the rake face is established, then, the profile equation of the radial plane of tool is evaluated on the condition that coordinate is changed, at last, the hyperbolic error is derived according to the equation and the substitutional line equation, and the error is converted to the axial plane of work piece which is coincided with the measuring plane. The actual calculation and the theory analysis indicated that if the cone length and the coning of the cone of work piece are fixed, the main elements which affect the hyperbolic error in the axial plane of work piece are the outside diameter R of round body form tool, the rake angle and the rear angle in "base point". If these three parameters are combined rationally, the hyperbolic error is minimum when round body form tool process cone, and the machining precision of work piece can be improved, on the condition that neither the work capacity of the tool design nor the manufacture cost of tool increases.
文摘This paper presents an innovative and effective control strategy tailored for a deregulated,diversified energy system involving multiple interconnected area.Each area integrates a unique mix of power generation technologies:Area 1 combines thermal,hydro,and distributed generation;Area 2 utilizes a blend of thermal units,distributed solar technologies(DST),and hydro power;andThird control area hosts geothermal power station alongside thermal power generation unit and hydropower units.The suggested control system employs a multi-layered approach,featuring a blended methodology utilizing the Tilted Integral Derivative controller(TID)and the Fractional-Order Integral method to enhance performance and stability.The parameters of this hybrid TID-FOI controller are finely tuned using an advanced optimization method known as the Walrus Optimization Algorithm(WaOA).Performance analysis reveals that the combined TID-FOI controller significantly outperforms the TID and PID controllers when comparing their dynamic response across various system configurations.The study also incorporates investigation of redox flow batteries within the broader scope of energy storage applications to assess their impact on system performance.In addition,the research explores the controller’s effectiveness under different power exchange scenarios in a deregulated market,accounting for restrictions on generation ramp rates and governor hysteresis effects in dynamic control.To ensure the reliability and resilience of the presented methodology,the system transitions and develops across a broad range of varying parameters and stochastic load fluctuation.To wrap up,the study offers a pioneering control approach-a hybrid TID-FOI controller optimized via the Walrus Optimization Algorithm(WaOA)-designed for enhanced stability and performance in a complex,three-region hybrid energy system functioning within a deregulated framework.
基金supported by the National Natural Scientific Foundation of China (Grant Nos. 41230420 and 41576015)the Qingdao National Laboratory for Marine Science and Technology (Grant No. QNLM2016ORP0107)+2 种基金the NSFC Innovative Group (Grant No. 41421005)the NSFC–Shandong Joint Fund for Marine Science Research Centers (Grant No. U1606402)the National Programme on Global Change and Air–Sea Interaction (Grant No. GASI-IPOVAI-06)
文摘Based on the high-resolution Regional Ocean Modeling System(ROMS) and the conditional nonlinear optimal perturbation(CNOP) method, this study explored the effects of optimal initial errors on the prediction of the Kuroshio large meander(LM) path, and the growth mechanism of optimal initial errors was revealed. For each LM event, two types of initial error(denoted as CNOP1 and CNOP2) were obtained. Their large amplitudes were found located mainly in the upper 2500 m in the upstream region of the LM, i.e., southeast of Kyushu. Furthermore, we analyzed the patterns and nonlinear evolution of the two types of CNOP. We found CNOP1 tends to strengthen the LM path through southwestward extension. Conversely,CNOP2 has almost the opposite pattern to CNOP1, and it tends to weaken the LM path through northeastward contraction.The growth mechanism of optimal initial errors was clarified through eddy-energetics analysis. The results indicated that energy from the background field is transferred to the error field because of barotropic and baroclinic instabilities. Thus, it is inferred that both barotropic and baroclinic processes play important roles in the growth of CNOP-type optimal initial errors.
基金Supported by National Natural Science Foundation of China(No.81770905)
文摘AIM: To evaluate the effect of different lens constant optimization methods on the accuracy of intraocular lens(IOL) power calculation formulas for highly myopic eyes.METHODS: This study comprised 108 eyes of 94 consecutive patients with axial length(AL) over 26 mm undergoing phacoemulsification and implantation of a Rayner(Hove, UK) 920H IOL. Formulas were evaluated using the following lens constants: manufacturer’s lens constant, User Group for Laser Interference Biometry(ULIB) constant, and optimized constant for long eyes. Results were compared with Barrett Universal II formula, original Wang-Koch AL adjustment method, and modified Wang-Koch AL adjustment method. The outcomes assessed were mean absolute error(MAE) and percentage of eyes with IOL prediction errors within ±0.25, ±0.50, and ±1.0 diopter(D). The nonparametric method, Friedman test, was used to compare MAE performance among constants.RESULTS: Optimized constants could significantly reduce the MAE of SRK/T, Hoffer Q, and Holladay 1 formulas compared with manufacturer’s lens constant, whereas the percentage of eyes with IOL prediction errors within ±0.25, ±0.50, and ±1.0 D had no statistically significant differences. Optimized lens constant for long eyes alone showed non-significant refractive advantages over the ULIB constant. Barrett Universal II formula and formulas with AL adjustment showed significantly higher accuracy in highly myopic eyes(P<0.001). CONCLUSION: Lens constant optimization for the subset of long eyes reduces the refractive error only to a limited extent for highly myopic eyes.
文摘A grating eddy current displacement sensor(GECDS) can be used in a watertight electronic transducer to realize long range displacement or position measurement with high accuracy in difficult industry conditions.The parameters optimization of the sensor is essential for economic and efficient production.This paper proposes a method to combine an artificial neural network(ANN) and a genetic algorithm(GA) for the sensor parameters optimization.A neural network model is developed to map the complex relationship between design parameters and the nonlinearity error of the GECDS,and then a GA is used in the optimization process to determine the design parameter values,resulting in a desired minimal nonlinearity error of about 0.11%.The calculated nonlinearity error is 0.25%.These results show that the proposed method performs well for the parameters optimization of the GECDS.
基金Subsidized by NSFC(11571274 and 11171269)the Ph.D.Programs Foundation of Ministry of Education of China(20110201110027)
文摘Although the two-grid finite element decoupled scheme for mixed Navier-Stokes/ Darcy model in literatures has given the numerical results of optimal convergence order, the theoretical analysis only obtain the optimal error order for the porous media flow and a non-optimal error order for the fluid flow. In this article, we give a more rigorous of the error analysis for the fluid flow and obtain the optimal error estimates of the velocity and the pressure.
基金supported by the National Basic Research Program under the Grant 2005CB321701the National Natural Science Foundation of China under the Grants 60474027 and 10771211.
文摘In this paper,we investigate a streamline diffusion finite element approxi- mation scheme for the constrained optimal control problem governed by linear con- vection dominated diffusion equations.We prove the existence and uniqueness of the discretized scheme.Then a priori and a posteriori error estimates are derived for the state,the co-state and the control.Three numerical examples are presented to illustrate our theoretical results.
基金Anhui Provincial Natural Science Foundation(Project for Youth:1908085QF252)Research Program of National University of Defense Technology(ZK19-10)。
文摘Focused energy delivery(FED) is a technique that can precisely bring energy to the specific region,which arouses wide attention in precision electronic warfare(PREW).This paper first proposes a joint optimization model with respect to the locations of the array and the transmitted signals to improve the performance of FED.As the problem is nonconvex and NP-hard,particle swarm optimization(PSO) is adopted to solve the locations of the array,while designing the transmitted signals under a feasible array is considered as a unimodular quadratic program(UQP) subproblem to calculate the fitness criterion of PSO.In the PSO-UQP framework established,two methods are presented for the UQP subproblem,which are more efficient and more accurate respectively than previous works.Furthermore,a threshold value is set in the framework to determine which method to adopt to take full advantages of the methods above.Meanwhile,we obtain the maximum localization error that FED can tolerate,which is significant for implementing FED in practice.Simulation results are provided to demonstrate the effectiveness of the joint optimization algorithm,and the correctness of the maximum localization error derived.
基金This research is supported by the Foundation for Talents for Next Century of Shandong University
文摘We’ll study the FEM for a model for compressible miscible displacement in porous media which includes molecular diffusion and mechanical dispersion in one-dimensional space.A class of vertices-edges-elements interpolation operator ink is introduced.With the help of ink(not elliptic projection),the optimal error estimate in L∞(J;L2(Ω)) norm of FEM is proved.
基金We acknowledge the anonymous reviewers for their helpful comments and criticism on an earlier manuscript.The authors are indebted to the supports from the National Natural Science Foundation of China under Grant Nos.40175025and 40028504the State key Bas
文摘Highly accurate spatial discretization is essentially required to perform numerical climate and weather prediction. The difference between the differential and the finite-difference operator is however a primitive error source in the numerics. This paper presents an optimization of centered finite-difference operator based on the principle of constrained cost function, which can reduce the truncation error to minimum. In the optimization point of view, such optimal operator is in fact an attempt to minimize spatial truncation er-rors in atmospheric modeling, in a simple way and indeed a quite innovative way to implement Variational Continuous Assimilation (VCA) technique. Furthermore, the optimizing difference operator is consciously designed to be meshing-independent, so that it can be used for most Arakawa-mesh configurations, such as un-staggered (Arakawa-A) or com-monly staggered (Arakawa-B, Arakawa-C, Arakawa-D) mesh. But for the calibration purpose, the pro-posed operator is implemented on an un-staggered mesh in which the truncation oscillation is mostly ex-cited, and it thus makes a severe and indeed a benchmark test for the proposed optimal scheme. Both theo-retical investigation and practical modeling indicate that the aforementioned numerical noise can be significantly eliminated.
