Iterative methods based on finite element simulation are effective approaches to design mold shape to compensate springback in sheet metal forming.However,convergence rate of iterative methods is difficult to improve ...Iterative methods based on finite element simulation are effective approaches to design mold shape to compensate springback in sheet metal forming.However,convergence rate of iterative methods is difficult to improve greatly.To increase the springback compensate speed of designing age forming mold,process of calculating springback for a certain mold with finite element method is analyzed.Springback compensation is abstracted as finding a solution for a set of nonlinear functions and a springback compensation algorithm is presented on the basis of quasi Newton method.The accuracy of algorithm is verified by developing an ABAQUS secondary development program with MATLAB.Three rectangular integrated panels of dimensions 710 mm′750 mm integrated panels with intersected ribs of 10 mm are selected to perform case studies.The algorithm is used to compute mold contours for the panels with cylinder,sphere and saddle contours respectively and it takes 57%,22%and 33%iterations as compared to that of displacement adjustment(DA)method.At the end of iterations,maximum deviations on the three panels are 0.618 4 mm,0.624 1 mm and 0.342 0 mm that are smaller than the deviations determined by DA method(0.740 8 mm,0.740 8 mm and 0.713 7 mm respectively).In following experimental verification,mold contour for another integrated panel with 400 mm×380 mm size is designed by the algorithm.Then the panel is age formed in an autoclave and measured by a three dimensional digital measurement devise.Deviation between measuring results and the panel’s design contour is less than 1 mm.Finally,the iterations with different mesh sizes(40 mm,35mm,30 mm,25 mm,20 mm)in finite element models are compared and found no considerable difference.Another possible compensation method,Broyden-Fletcher-Shanmo method,is also presented based on the solving nonlinear functions idea.The Broyden-Fletcher-Shanmo method is employed to compute mold contour for the second panel.It only takes 50%iterations compared to that of DA.The proposed method can serve a faster mold contour compensation method for sheet metal forming.展开更多
Quasi-Newton methods are the most widely used methods to find local maxima and minima of functions in various engineering practices. However, they involve a large amount of matrix and vector operations, which are comp...Quasi-Newton methods are the most widely used methods to find local maxima and minima of functions in various engineering practices. However, they involve a large amount of matrix and vector operations, which are computationally intensive and require a long processing time. Recently, with the increasing density and arithmetic cores, field programmable gate array(FPGA) has become an attractive alternative to the acceleration of scientific computation. This paper aims to accelerate Davidon-Fletcher-Powell quasi-Newton(DFP-QN) method by proposing a customized and pipelined hardware implementation on FPGAs. Experimental results demonstrate that compared with a software implementation, a speed-up of up to 17 times can be achieved by the proposed hardware implementation.展开更多
A balancing technique for casting or forging parts to be machined is presented in this paper.It allows an optimal part setup to make sure that no shortage of material(undercut)will occur during machining.Particularly ...A balancing technique for casting or forging parts to be machined is presented in this paper.It allows an optimal part setup to make sure that no shortage of material(undercut)will occur during machining.Particularly in the heavy part in- dustry,where the resulting casting size and shape may deviate from expectations,the balancing process discovers whether or not the design model is totally enclosed in the actual part to be machined.The alignment is an iterative process involving nonlinear con- strained optimization,which forces data points to lie outside the nominal model under a specific order of priority.Newton methods for non-linear numerical minimization are rarely applied to this problem because of the high cost of computing.In this paper, Newton methods are applied to the balancing of blank part.The aforesaid algorithm is demonstrated in term of a marine propeller blade,and result shows that The Newton methods are more efficient and accurate than those implemented in past research and have distinct advantages compared to the registration methods widely used today.展开更多
The non-quasi-Newton methods for unconstrained optimization was investigated. Non-monotone line search procedure is introduced, which is combined with the non-quasi-Newton family. Under the uniform convexity assumptio...The non-quasi-Newton methods for unconstrained optimization was investigated. Non-monotone line search procedure is introduced, which is combined with the non-quasi-Newton family. Under the uniform convexity assumption on objective function, the global convergence of the non-quasi-Newton family was proved. Numerical experiments showed that the non-monotone line search was more effective.展开更多
The recognition of electroencephalogram (EEG) signals is the key of brain computer interface (BCI). Aimed at the problem that the recognition rate of EEG by using support vector machine (SVM) is low in BCI, based on t...The recognition of electroencephalogram (EEG) signals is the key of brain computer interface (BCI). Aimed at the problem that the recognition rate of EEG by using support vector machine (SVM) is low in BCI, based on the assumption that a well-defined physiological signal which also has a smooth form "hides" inside the noisy EEG signal, a Quasi-Newton-SVM recognition method based on Quasi-Newton method and SVM algorithm was presented. Firstly, the EEG signals were preprocessed by Quasi-Newton method and got the signals which were fit for SVM. Secondly, the preprocessed signals were classified by SVM method. The present simulation results indicated the Quasi-Newton-SVM approach improved the recognition rate compared with using SVM method; we also discussed the relationship between the artificial smooth signals and the classification errors.展开更多
With the emergence of location-based applications in various fields,the higher accuracy of positioning is demanded.By utilizing the time differences of arrival(TDOAs) and gain ratios of arrival(GROAs),an efficient alg...With the emergence of location-based applications in various fields,the higher accuracy of positioning is demanded.By utilizing the time differences of arrival(TDOAs) and gain ratios of arrival(GROAs),an efficient algorithm for estimating the position is proposed,which exploits the Broyden-Fletcher-Goldfarb-Shanno(BFGS) quasi-Newton method to solve nonlinear equations at the source location under the additive measurement error.Although the accuracy of two-step weighted-least-square(WLS) method based on TDOAs and GROAs is very high,this method has a high computational complexity.While the proposed approach can achieve the same accuracy and bias with the lower computational complexity when the signal-to-noise ratio(SNR) is high,especially it can achieve better accuracy and smaller bias at a lower SNR.The proposed algorithm can be applied to the actual environment due to its real-time property and good robust performance.Simulation results show that with a good initial guess to begin with,the proposed estimator converges to the true solution and achieves the Cramer-Rao lower bound(CRLB) accuracy for both near-field and far-field sources.展开更多
In this paper, a switching method for unconstrained minimization is proposed. The method is based on the modified BFGS method and the modified SR1 method. The eigenvalues and condition numbers of both the modified upd...In this paper, a switching method for unconstrained minimization is proposed. The method is based on the modified BFGS method and the modified SR1 method. The eigenvalues and condition numbers of both the modified updates are evaluated and used in the switching rule. When the condition number of the modified SR1 update is superior to the modified BFGS update, the step in the proposed quasi-Newton method is the modified SR1 step. Otherwise the step is the modified BFGS step. The efficiency of the proposed method is tested by numerical experiments on small, medium and large scale optimization. The numerical results are reported and analyzed to show the superiority of the proposed method.展开更多
文摘Iterative methods based on finite element simulation are effective approaches to design mold shape to compensate springback in sheet metal forming.However,convergence rate of iterative methods is difficult to improve greatly.To increase the springback compensate speed of designing age forming mold,process of calculating springback for a certain mold with finite element method is analyzed.Springback compensation is abstracted as finding a solution for a set of nonlinear functions and a springback compensation algorithm is presented on the basis of quasi Newton method.The accuracy of algorithm is verified by developing an ABAQUS secondary development program with MATLAB.Three rectangular integrated panels of dimensions 710 mm′750 mm integrated panels with intersected ribs of 10 mm are selected to perform case studies.The algorithm is used to compute mold contours for the panels with cylinder,sphere and saddle contours respectively and it takes 57%,22%and 33%iterations as compared to that of displacement adjustment(DA)method.At the end of iterations,maximum deviations on the three panels are 0.618 4 mm,0.624 1 mm and 0.342 0 mm that are smaller than the deviations determined by DA method(0.740 8 mm,0.740 8 mm and 0.713 7 mm respectively).In following experimental verification,mold contour for another integrated panel with 400 mm×380 mm size is designed by the algorithm.Then the panel is age formed in an autoclave and measured by a three dimensional digital measurement devise.Deviation between measuring results and the panel’s design contour is less than 1 mm.Finally,the iterations with different mesh sizes(40 mm,35mm,30 mm,25 mm,20 mm)in finite element models are compared and found no considerable difference.Another possible compensation method,Broyden-Fletcher-Shanmo method,is also presented based on the solving nonlinear functions idea.The Broyden-Fletcher-Shanmo method is employed to compute mold contour for the second panel.It only takes 50%iterations compared to that of DA.The proposed method can serve a faster mold contour compensation method for sheet metal forming.
基金Supported by the National Natural Science Foundation of China(No.61574099)
文摘Quasi-Newton methods are the most widely used methods to find local maxima and minima of functions in various engineering practices. However, they involve a large amount of matrix and vector operations, which are computationally intensive and require a long processing time. Recently, with the increasing density and arithmetic cores, field programmable gate array(FPGA) has become an attractive alternative to the acceleration of scientific computation. This paper aims to accelerate Davidon-Fletcher-Powell quasi-Newton(DFP-QN) method by proposing a customized and pipelined hardware implementation on FPGAs. Experimental results demonstrate that compared with a software implementation, a speed-up of up to 17 times can be achieved by the proposed hardware implementation.
文摘A balancing technique for casting or forging parts to be machined is presented in this paper.It allows an optimal part setup to make sure that no shortage of material(undercut)will occur during machining.Particularly in the heavy part in- dustry,where the resulting casting size and shape may deviate from expectations,the balancing process discovers whether or not the design model is totally enclosed in the actual part to be machined.The alignment is an iterative process involving nonlinear con- strained optimization,which forces data points to lie outside the nominal model under a specific order of priority.Newton methods for non-linear numerical minimization are rarely applied to this problem because of the high cost of computing.In this paper, Newton methods are applied to the balancing of blank part.The aforesaid algorithm is demonstrated in term of a marine propeller blade,and result shows that The Newton methods are more efficient and accurate than those implemented in past research and have distinct advantages compared to the registration methods widely used today.
基金Sponsored by Natural Science Foundation of Beijing Municipal Commission of Education(Grant No.KM200510028019).
文摘The non-quasi-Newton methods for unconstrained optimization was investigated. Non-monotone line search procedure is introduced, which is combined with the non-quasi-Newton family. Under the uniform convexity assumption on objective function, the global convergence of the non-quasi-Newton family was proved. Numerical experiments showed that the non-monotone line search was more effective.
基金The paper was supported by Jiangsu Education Nature Foundation(06KJD310050,06KJB520022)
文摘The recognition of electroencephalogram (EEG) signals is the key of brain computer interface (BCI). Aimed at the problem that the recognition rate of EEG by using support vector machine (SVM) is low in BCI, based on the assumption that a well-defined physiological signal which also has a smooth form "hides" inside the noisy EEG signal, a Quasi-Newton-SVM recognition method based on Quasi-Newton method and SVM algorithm was presented. Firstly, the EEG signals were preprocessed by Quasi-Newton method and got the signals which were fit for SVM. Secondly, the preprocessed signals were classified by SVM method. The present simulation results indicated the Quasi-Newton-SVM approach improved the recognition rate compared with using SVM method; we also discussed the relationship between the artificial smooth signals and the classification errors.
基金supported by the Major National Science&Technology Projects(2010ZX03006-002-04)the National Natural Science Foundation of China(61072070)+4 种基金the Doctorial Programs Foundation of the Ministry of Education(20110203110011)the"111 Project"(B08038)the Fundamental Research Funds of the Ministry of Education(72124338)the Key Programs for Natural Science Foundation of Shanxi Province(2012JZ8002)the Foundation of State Key Laboratory of Integrated Services Networks(ISN1101002)
文摘With the emergence of location-based applications in various fields,the higher accuracy of positioning is demanded.By utilizing the time differences of arrival(TDOAs) and gain ratios of arrival(GROAs),an efficient algorithm for estimating the position is proposed,which exploits the Broyden-Fletcher-Goldfarb-Shanno(BFGS) quasi-Newton method to solve nonlinear equations at the source location under the additive measurement error.Although the accuracy of two-step weighted-least-square(WLS) method based on TDOAs and GROAs is very high,this method has a high computational complexity.While the proposed approach can achieve the same accuracy and bias with the lower computational complexity when the signal-to-noise ratio(SNR) is high,especially it can achieve better accuracy and smaller bias at a lower SNR.The proposed algorithm can be applied to the actual environment due to its real-time property and good robust performance.Simulation results show that with a good initial guess to begin with,the proposed estimator converges to the true solution and achieves the Cramer-Rao lower bound(CRLB) accuracy for both near-field and far-field sources.
基金This work is supported by National Natural Key product Foundations of China 10231060.
文摘In this paper, a switching method for unconstrained minimization is proposed. The method is based on the modified BFGS method and the modified SR1 method. The eigenvalues and condition numbers of both the modified updates are evaluated and used in the switching rule. When the condition number of the modified SR1 update is superior to the modified BFGS update, the step in the proposed quasi-Newton method is the modified SR1 step. Otherwise the step is the modified BFGS step. The efficiency of the proposed method is tested by numerical experiments on small, medium and large scale optimization. The numerical results are reported and analyzed to show the superiority of the proposed method.
