Introducing frequency agility into a distributed multipleinput multiple-output(MIMO)radar can significantly enhance its anti-jamming ability.However,it would cause the sidelobe pedestal problem in multi-target paramet...Introducing frequency agility into a distributed multipleinput multiple-output(MIMO)radar can significantly enhance its anti-jamming ability.However,it would cause the sidelobe pedestal problem in multi-target parameter estimation.Sparse recovery is an effective way to address this problem,but it cannot be directly utilized for multi-target parameter estimation in frequency-agile distributed MIMO radars due to spatial diversity.In this paper,we propose an algorithm for multi-target parameter estimation according to the signal model of frequency-agile distributed MIMO radars,by modifying the orthogonal matching pursuit(OMP)algorithm.The effectiveness of the proposed method is then verified by simulation results.展开更多
A new numerical technique named interval finite difference method is proposed for the steady-state temperature field prediction with uncertainties in both physical parameters and boundary conditions. Interval variable...A new numerical technique named interval finite difference method is proposed for the steady-state temperature field prediction with uncertainties in both physical parameters and boundary conditions. Interval variables are used to quantitatively describe the uncertain parameters with limited information. Based on different Taylor and Neumann series, two kinds of parameter perturbation methods are presented to approximately yield the ranges of the uncertain temperature field. By comparing the results with traditional Monte Carlo simulation, a numerical example is given to demonstrate the feasibility and effectiveness of the proposed method for solving steady-state heat conduction problem with uncertain-but-bounded parameters.展开更多
The estimation of model parameters is an important subject in engineering.In this area of work,the prevailing approach is to estimate or calculate these as deterministic parameters.In this study,we consider the model ...The estimation of model parameters is an important subject in engineering.In this area of work,the prevailing approach is to estimate or calculate these as deterministic parameters.In this study,we consider the model parameters from the perspective of random variables and describe the general form of the parameter distribution inference problem.Under this framework,we propose an ensemble Bayesian method by introducing Bayesian inference and the Markov chain Monte Carlo(MCMC)method.Experiments on a finite cylindrical reactor and a 2D IAEA benchmark problem show that the proposed method converges quickly and can estimate parameters effectively,even for several correlated parameters simultaneously.Our experiments include cases of engineering software calls,demonstrating that the method can be applied to engineering,such as nuclear reactor engineering.展开更多
The dynamic performance of a nozzle-flapper servo valve can be affected by several factors such as the disturbance of the input signal,the motion of the armature assembly and the oscillation of the jet force.As the pa...The dynamic performance of a nozzle-flapper servo valve can be affected by several factors such as the disturbance of the input signal,the motion of the armature assembly and the oscillation of the jet force.As the part of vibrating at high frequency,the armature assembly plays a vital role during the operation of the servo valve.In order to accurately predict the transient response of the armature assembly during the vibration,a mathematical model of armature assembly is established based on the distributed parameters method(DPM)and Hamilton principle.The new mathematical model is composed of three main parts,the modal eigenfunction,modal mechanical response expressions of the spring tube and the motion equation of the other armature assembly.After programing,the purpose of using the DPM to predict the dynamic response of different positions located on the armature assembly is achieved.For verifying the validity of the mathematical model,the finite element method(FEM)and classic model(CM)of armature assembly are applicated by commercial software under the same condition.The comparison results prove that the DPM can effectively predict the axial and tangential deflection of the armature assembly different positions which the CM can’t duing to its over-simplification.A certain error is generated when predicting the axial deformation at different heights by DPM,which is caused by an approximate method to simulate the torsion of the spring tube.The comparison results of the spring tube deflection at different vibration frequencies shows that the adaptability of DPM is significantly higher than the classic model,which verify the model is more adaptable for predicting the dynamic response of the armature assembly.展开更多
Stem diameter distribution information is useful in forest management planning. Weibull function is flexible, and has been used in characterising diameter distributions, especially in single-species planted stands, th...Stem diameter distribution information is useful in forest management planning. Weibull function is flexible, and has been used in characterising diameter distributions, especially in single-species planted stands, the world over. We evaluated some Weibull parameter estimation methods for stem diameter characterisation in （Oban） multi-species Forest in southern Nigeria. Four study sites （Aking, Ekang, Erokut and Ekuri） were selected. Four 2 km-long transects situated at 600 m apart were laid in each location. Five 50m x 50m plots were alternately laid along each transect at 400 m apart （20 plots/location） using systematic sampling technique. Tree growth variables： diameter at breast height （Dbh）, diameters at the base, middle and merchantable limit, total height, merchantable height, stem straightness, crown length and crown diameter were measured on all trees 〉 10 cm to compute model response variables such as mean diameters, basal area and stem volume. Weibull parameters estimation methods used were： moment-based, percentile-based, hybrid and maximum-likelihood （ML）. Data were analysed using descriptive statistics, regression models and ANOVA at α0.05. Percentile-based method was the best for Weibull [location （a）, scale （b） and shape （c）] parameters estimations with mLogL = 116.66±21.89, while hybrid method was least-suitable （mLogL = 690.14±128.81） for Weibull parameters estimations. Quadratic mean diameter （Dq） was the only suitable predictor of Weibull parameters in Oban Forest.展开更多
This paper presents an analysis method, based on MacCormack＇s technique, for the evaluation of the time domain sensitivity of distributed parameter elements in high-speed circuit networks. Sensitivities can be calcul...This paper presents an analysis method, based on MacCormack＇s technique, for the evaluation of the time domain sensitivity of distributed parameter elements in high-speed circuit networks. Sensitivities can be calculated from electrical and physical parameters of the distributed parameter elements. The proposed method is a direct numerical method of time-space discretization and does not require complicated mathematical deductive process. Therefore, it is very convenient to program this method. It can be applied to sensitivity analysis of general transmission lines in linear or nonlinear circuit networks. The proposed method is second-order-accurate. Numerical experiment is presented to demonstrate its accuracy and efficiency.展开更多
The control synthesis for switched systems is extended to distributed parameter switched systems in Hilbert space. Based on semigroup and operator theory, by means of multiple Lyapunov method incorporated average dwel...The control synthesis for switched systems is extended to distributed parameter switched systems in Hilbert space. Based on semigroup and operator theory, by means of multiple Lyapunov method incorporated average dwell time approach, sufficient con- ditions are derived in terms of linear operator inequalities frame- work for distributed parameter switched systems. Being applied to one dimensional heat propagation switched systems, these lin- ear operator inequalities are reduced to linear matrix inequalities subsequently. In particular, the state feedback gain matrices and the switching law are designed, and the state decay estimate is explicitly given whose decay coefficient completely depends on the system＇s parameter and the boundary condition. Finally, two numerical examples are given to illustrate the proposed method.展开更多
We start with analyzing stochastic dependence in a classic bivariate normal density framework. We focus on the way the conditional density of one of the random variables depends on realizations of the other. In the bi...We start with analyzing stochastic dependence in a classic bivariate normal density framework. We focus on the way the conditional density of one of the random variables depends on realizations of the other. In the bivariate normal case this dependence takes the form of a parameter (here the “expected value”) of one probability density depending continuously (here linearly) on realizations of the other random variable. The point is, that such a pattern does not need to be restricted to that classical case of the bivariate normal. We show that this paradigm can be generalized and viewed in ways that allows one to extend it far beyond the bivariate or multivariate normal probability distributions class.展开更多
The two-parameter exponential distribution is proposed to be an underlying model,and prediction bounds for future observations are obtained by using Bayesian approach.Prediction intervals are derived for unobserved li...The two-parameter exponential distribution is proposed to be an underlying model,and prediction bounds for future observations are obtained by using Bayesian approach.Prediction intervals are derived for unobserved lifetimes in one-sample prediction and two-sample prediction based on type Ⅱ doubly censored samples.A numerical example is given to illustrate the procedures,prediction intervals are investigated via Monte Carlo method,and the accuracy of prediction intervals is presented.展开更多
We study the least squares estimation of drift parameters for a class of stochastic differential equations driven by small a-stable noises, observed at n regularly spaced time points ti = i/n, i = 1,...,n on [0, 1]. U...We study the least squares estimation of drift parameters for a class of stochastic differential equations driven by small a-stable noises, observed at n regularly spaced time points ti = i/n, i = 1,...,n on [0, 1]. Under some regularity conditions, we obtain the consistency and the rate of convergence of the least squares estimator （LSE） when a small dispersion parameter ε→0 and n →∞ simultaneously. The asymptotic distribution of the LSE in our setting is shown to be stable, which is completely different from the classical cases where asymptotic distributions are normal.展开更多
Previous studies have shown that the fatigue life distribution of metal materials fabricated with Additive Manufacturing(AM) methods, such as Direct Energy Deposited(DED) Ti-6.5Al-2Zr-1Mo-1V alloys, exhibits two peaks...Previous studies have shown that the fatigue life distribution of metal materials fabricated with Additive Manufacturing(AM) methods, such as Direct Energy Deposited(DED) Ti-6.5Al-2Zr-1Mo-1V alloys, exhibits two peaks. To promote the application of AM in aerospace and other engineering fields, developing a fatigue strength evaluation method suitable for AM materials based on their unique fatigue behaviours and fatigue life distributions is necessary. In this paper, a novel Detail Fatigue Rating(DFR) method was developed to evaluate the fatigue strength of DED Ti-6.5Al-2Zr-1Mo-1V based on a bimodal Weibull distribution and the excessive restriction on the allowable stress of potential was improved. Meanwhile, a Bimodal Weibull distribution model for fatigue life and its parameter estimation method were established based on a twoparameter Weibull distribution. The fatigue life at a specific reliability level and confidence level was calculated by using the bootstrap method. The calculation results showed that fatigue life estimated by using the bimodal Weibull distribution at the high reliability level and high confidence level is higher than that estimated by using the two-parameter Weibull distribution. Furthermore,The S-N curve at the specified confidence level and reliability level was fitted.展开更多
In order to accurately and automatically measure the light emitting diode(LED) colorimetric parameters,the design of a measurement system by adopting a high-performance spectrometer and looking-up table method was pre...In order to accurately and automatically measure the light emitting diode(LED) colorimetric parameters,the design of a measurement system by adopting a high-performance spectrometer and looking-up table method was presented based on the LabVIEW.First,the data of the LED relative spectral power distribution(SPD) were read by the spectrometer to measure LED chromaticity coordinate,and the slopes table were formed by the LED chromaticity coordinate and the equal stimulus point.Then,the CIE1931 chromaticity diagram was divided into 4 different regions to ensure the slopes table that had the character of monotonic decreasing.Finally,the LED dominant wavelength and purity were automatically calculated using the LabVIEW programs.The data of LEDs' colorimetric parameters have demonstrated that the measurement method in this paper can achieve higher precision result.展开更多
Commonly used statistical procedure to describe the observed statistical sets is to use their conventional moments or cumulants. When choosing an appropriate parametric distribution for the data set is typically that ...Commonly used statistical procedure to describe the observed statistical sets is to use their conventional moments or cumulants. When choosing an appropriate parametric distribution for the data set is typically that parameters of a parametric distribution are estimated using the moment method of creating a system of equations in which the sample conventional moments lay in the equality of the corresponding moments of the theoretical distribution. However, the moment method of parameter estimation is not always convenient, especially for small samples. An alternative approach is based on the use of other characteristics, which the author calls L-moments. L-moments are analogous to conventional moments, but they are based on linear combinations of order statistics, i.e., L-statistics. Using L-moments is theoretically preferable to the conventional moments and consists in the fact that L-moments characterize a wider range of distribution. When estimating from sample L-moments, L-moments are more robust to the presence of outliers in the data. Experience also shows that, compared to conventional moments, L-moments are less prone to bias of estimation. Parameter estimates obtained using L-moments are mainly in the case of small samples often even more accurate than estimates of parameters made by maximum likelihood method. Using the method of L-moments in the case of small data sets from the meteorology is primarily known in statistical literature. This paper deals with the use of L-moments in the case for large data sets of income distribution （individual data） and wage distribution （data are ordered to form of interval frequency distribution of extreme open intervals）. This paper also presents a comparison of the accuracy of the method of L-moments with an accuracy of other methods of point estimation of parameters of parametric probability distribution in the case of large data sets of individual data and data ordered to form of interval frequency distribution.展开更多
Since the effectiveness of the flexible current arc suppression method heavily relies on the accurate measurement of the distribution line-to-ground parame-ters,the suppression of single line-to-ground(SLG)fault curre...Since the effectiveness of the flexible current arc suppression method heavily relies on the accurate measurement of the distribution line-to-ground parame-ters,the suppression of single line-to-ground(SLG)fault current may deteriorate due to factors such as line switching and other disturbances during SLG fault arc suppression.Additionally,during SLG fault arc suppres-sion,promptly identifying the fault type and rapidly de-activating the flexible arc suppression device(FASD)can reduce the overvoltage risk in non-faulted phase devices.To address these issues,this paper presents a parameter identification method based on recursive least squares(RLS)while a variable forgetting factor strategy is in-troduces to enhance the RLS algorithm’s disturbance rejection capability.Simulations verify that the variable forgetting factor recursive least squares(VFF-RLS)algo-rithm can accurately identify distribution line-to-ground parameters in real time and effectively suppress SLG fault current.The online identification of grounding transition conductance is simultaneously used to deter-mine the fault type and quickly detect when the SLG fault has been cleared.展开更多
The distributed parameters of the transmission lines have the significant impact to the signal propagation. In the conventional method of the distributed parameter extraction,the discontinuity of inverse trigonometric...The distributed parameters of the transmission lines have the significant impact to the signal propagation. In the conventional method of the distributed parameter extraction,the discontinuity of inverse trigonometric or hyperbolic can arise the problem about phase ambiguity which causes significant errors for transmission models. A difference iteration method（ DIM） is proposed for extracting distributed parameters of high frequency transmission line structure in order to overcome the phase ambiguity in the conventional method（ CM）. The formulations of the proposed method are first derived for two-conductor and multi-conductor lines. Then the validation is performed for the models of micro-strip transmission line. Numerical results demonstrate that the proposed DIM can solve the problem about the phase ambiguity and the extracted distributed parameters are accurate and efficient for a wide range of the frequencies of interest and line lengths.展开更多
The nonlinear dynamics of cantilevered piezoelectric beams is investigated under simultaneous parametric and external excitations. The beam is composed of a substrate and two piezoelectric layers and assumed as an Eul...The nonlinear dynamics of cantilevered piezoelectric beams is investigated under simultaneous parametric and external excitations. The beam is composed of a substrate and two piezoelectric layers and assumed as an Euler-Bernoulli model with inextensible deformation. A nonlinear distributed parameter model of cantilevered piezoelectric energy harvesters is proposed using the generalized Hamilton＇s principle. The proposed model includes geometric and inertia nonlinearity, but neglects the material nonlinearity. Using the Galerkin decomposition method and harmonic balance method, analytical expressions of the frequency-response curves are presented when the first bending mode of the beam plays a dominant role. Using these expressions, we investigate the effects of the damping, load resistance, electromechanical coupling, and excitation amplitude on the frequency-response curves. We also study the difference between the nonlinear lumped-parameter and distributed- parameter model for predicting the performance of the energy harvesting system. Only in the case of parametric excitation, we demonstrate that the energy harvesting system has an initiation excitation threshold below which no energy can be harvested. We also illustrate that the damping and load resistance affect the initiation excitation threshold.展开更多
The study on ^(13)C-NMR spectra of aliphatic carbon region of emuision-processed and solution-processed (by lithium catalyst) SBR was carried out. The assignments for more than thirty odd peaks observed experimentally...The study on ^(13)C-NMR spectra of aliphatic carbon region of emuision-processed and solution-processed (by lithium catalyst) SBR was carried out. The assignments for more than thirty odd peaks observed experimentally were made by using 'corresponding analysis' method, combined with the empirical parameters reported in literature. The peak intensifies were calculated based on BemouUian statistic assumption.展开更多
文摘Introducing frequency agility into a distributed multipleinput multiple-output(MIMO)radar can significantly enhance its anti-jamming ability.However,it would cause the sidelobe pedestal problem in multi-target parameter estimation.Sparse recovery is an effective way to address this problem,but it cannot be directly utilized for multi-target parameter estimation in frequency-agile distributed MIMO radars due to spatial diversity.In this paper,we propose an algorithm for multi-target parameter estimation according to the signal model of frequency-agile distributed MIMO radars,by modifying the orthogonal matching pursuit(OMP)algorithm.The effectiveness of the proposed method is then verified by simulation results.
基金supported by the National Special Fund for Major Research Instrument Development(2011YQ140145)111 Project (B07009)+1 种基金the National Natural Science Foundation of China(11002013)Defense Industrial Technology Development Program(A2120110001 and B2120110011)
文摘A new numerical technique named interval finite difference method is proposed for the steady-state temperature field prediction with uncertainties in both physical parameters and boundary conditions. Interval variables are used to quantitatively describe the uncertain parameters with limited information. Based on different Taylor and Neumann series, two kinds of parameter perturbation methods are presented to approximately yield the ranges of the uncertain temperature field. By comparing the results with traditional Monte Carlo simulation, a numerical example is given to demonstrate the feasibility and effectiveness of the proposed method for solving steady-state heat conduction problem with uncertain-but-bounded parameters.
基金partially sponsored by the Natural Science Foundation of Shanghai(No.23ZR1429300)the Innovation Fund of CNNC(Lingchuang Fund)。
文摘The estimation of model parameters is an important subject in engineering.In this area of work,the prevailing approach is to estimate or calculate these as deterministic parameters.In this study,we consider the model parameters from the perspective of random variables and describe the general form of the parameter distribution inference problem.Under this framework,we propose an ensemble Bayesian method by introducing Bayesian inference and the Markov chain Monte Carlo(MCMC)method.Experiments on a finite cylindrical reactor and a 2D IAEA benchmark problem show that the proposed method converges quickly and can estimate parameters effectively,even for several correlated parameters simultaneously.Our experiments include cases of engineering software calls,demonstrating that the method can be applied to engineering,such as nuclear reactor engineering.
基金supported by National Natural Science Foundation of China(No.51675119)。
文摘The dynamic performance of a nozzle-flapper servo valve can be affected by several factors such as the disturbance of the input signal,the motion of the armature assembly and the oscillation of the jet force.As the part of vibrating at high frequency,the armature assembly plays a vital role during the operation of the servo valve.In order to accurately predict the transient response of the armature assembly during the vibration,a mathematical model of armature assembly is established based on the distributed parameters method(DPM)and Hamilton principle.The new mathematical model is composed of three main parts,the modal eigenfunction,modal mechanical response expressions of the spring tube and the motion equation of the other armature assembly.After programing,the purpose of using the DPM to predict the dynamic response of different positions located on the armature assembly is achieved.For verifying the validity of the mathematical model,the finite element method(FEM)and classic model(CM)of armature assembly are applicated by commercial software under the same condition.The comparison results prove that the DPM can effectively predict the axial and tangential deflection of the armature assembly different positions which the CM can’t duing to its over-simplification.A certain error is generated when predicting the axial deformation at different heights by DPM,which is caused by an approximate method to simulate the torsion of the spring tube.The comparison results of the spring tube deflection at different vibration frequencies shows that the adaptability of DPM is significantly higher than the classic model,which verify the model is more adaptable for predicting the dynamic response of the armature assembly.
文摘Stem diameter distribution information is useful in forest management planning. Weibull function is flexible, and has been used in characterising diameter distributions, especially in single-species planted stands, the world over. We evaluated some Weibull parameter estimation methods for stem diameter characterisation in （Oban） multi-species Forest in southern Nigeria. Four study sites （Aking, Ekang, Erokut and Ekuri） were selected. Four 2 km-long transects situated at 600 m apart were laid in each location. Five 50m x 50m plots were alternately laid along each transect at 400 m apart （20 plots/location） using systematic sampling technique. Tree growth variables： diameter at breast height （Dbh）, diameters at the base, middle and merchantable limit, total height, merchantable height, stem straightness, crown length and crown diameter were measured on all trees 〉 10 cm to compute model response variables such as mean diameters, basal area and stem volume. Weibull parameters estimation methods used were： moment-based, percentile-based, hybrid and maximum-likelihood （ML）. Data were analysed using descriptive statistics, regression models and ANOVA at α0.05. Percentile-based method was the best for Weibull [location （a）, scale （b） and shape （c）] parameters estimations with mLogL = 116.66±21.89, while hybrid method was least-suitable （mLogL = 690.14±128.81） for Weibull parameters estimations. Quadratic mean diameter （Dq） was the only suitable predictor of Weibull parameters in Oban Forest.
文摘This paper presents an analysis method, based on MacCormack＇s technique, for the evaluation of the time domain sensitivity of distributed parameter elements in high-speed circuit networks. Sensitivities can be calculated from electrical and physical parameters of the distributed parameter elements. The proposed method is a direct numerical method of time-space discretization and does not require complicated mathematical deductive process. Therefore, it is very convenient to program this method. It can be applied to sensitivity analysis of general transmission lines in linear or nonlinear circuit networks. The proposed method is second-order-accurate. Numerical experiment is presented to demonstrate its accuracy and efficiency.
基金supported by the National Natural Science Foundation of China(6127311961374038+2 种基金6147307961473083)the Natural Science Foundation of Shanxi Province(2012011002-2)
文摘The control synthesis for switched systems is extended to distributed parameter switched systems in Hilbert space. Based on semigroup and operator theory, by means of multiple Lyapunov method incorporated average dwell time approach, sufficient con- ditions are derived in terms of linear operator inequalities frame- work for distributed parameter switched systems. Being applied to one dimensional heat propagation switched systems, these lin- ear operator inequalities are reduced to linear matrix inequalities subsequently. In particular, the state feedback gain matrices and the switching law are designed, and the state decay estimate is explicitly given whose decay coefficient completely depends on the system＇s parameter and the boundary condition. Finally, two numerical examples are given to illustrate the proposed method.
文摘We start with analyzing stochastic dependence in a classic bivariate normal density framework. We focus on the way the conditional density of one of the random variables depends on realizations of the other. In the bivariate normal case this dependence takes the form of a parameter (here the “expected value”) of one probability density depending continuously (here linearly) on realizations of the other random variable. The point is, that such a pattern does not need to be restricted to that classical case of the bivariate normal. We show that this paradigm can be generalized and viewed in ways that allows one to extend it far beyond the bivariate or multivariate normal probability distributions class.
文摘The two-parameter exponential distribution is proposed to be an underlying model,and prediction bounds for future observations are obtained by using Bayesian approach.Prediction intervals are derived for unobserved lifetimes in one-sample prediction and two-sample prediction based on type Ⅱ doubly censored samples.A numerical example is given to illustrate the procedures,prediction intervals are investigated via Monte Carlo method,and the accuracy of prediction intervals is presented.
基金supported by FAU Start-up funding at the C. E. Schmidt Collegeof Science
文摘We study the least squares estimation of drift parameters for a class of stochastic differential equations driven by small a-stable noises, observed at n regularly spaced time points ti = i/n, i = 1,...,n on [0, 1]. Under some regularity conditions, we obtain the consistency and the rate of convergence of the least squares estimator （LSE） when a small dispersion parameter ε→0 and n →∞ simultaneously. The asymptotic distribution of the LSE in our setting is shown to be stable, which is completely different from the classical cases where asymptotic distributions are normal.
基金the support from the National Key Research and Development Program of China(No.2017YFB1104003)National Natural Science Foundation of China(No.11772027)Aeronautical Science Foundation of China(No.201909051002)。
文摘Previous studies have shown that the fatigue life distribution of metal materials fabricated with Additive Manufacturing(AM) methods, such as Direct Energy Deposited(DED) Ti-6.5Al-2Zr-1Mo-1V alloys, exhibits two peaks. To promote the application of AM in aerospace and other engineering fields, developing a fatigue strength evaluation method suitable for AM materials based on their unique fatigue behaviours and fatigue life distributions is necessary. In this paper, a novel Detail Fatigue Rating(DFR) method was developed to evaluate the fatigue strength of DED Ti-6.5Al-2Zr-1Mo-1V based on a bimodal Weibull distribution and the excessive restriction on the allowable stress of potential was improved. Meanwhile, a Bimodal Weibull distribution model for fatigue life and its parameter estimation method were established based on a twoparameter Weibull distribution. The fatigue life at a specific reliability level and confidence level was calculated by using the bootstrap method. The calculation results showed that fatigue life estimated by using the bimodal Weibull distribution at the high reliability level and high confidence level is higher than that estimated by using the two-parameter Weibull distribution. Furthermore,The S-N curve at the specified confidence level and reliability level was fitted.
基金National Natural Science Foundation of China (No. 51105289)Doctoral Program Foundation of Self-determined and Innovative Research Funds of WUT,China (No. 2010-ZY-JD-034)
文摘In order to accurately and automatically measure the light emitting diode(LED) colorimetric parameters,the design of a measurement system by adopting a high-performance spectrometer and looking-up table method was presented based on the LabVIEW.First,the data of the LED relative spectral power distribution(SPD) were read by the spectrometer to measure LED chromaticity coordinate,and the slopes table were formed by the LED chromaticity coordinate and the equal stimulus point.Then,the CIE1931 chromaticity diagram was divided into 4 different regions to ensure the slopes table that had the character of monotonic decreasing.Finally,the LED dominant wavelength and purity were automatically calculated using the LabVIEW programs.The data of LEDs' colorimetric parameters have demonstrated that the measurement method in this paper can achieve higher precision result.
文摘Commonly used statistical procedure to describe the observed statistical sets is to use their conventional moments or cumulants. When choosing an appropriate parametric distribution for the data set is typically that parameters of a parametric distribution are estimated using the moment method of creating a system of equations in which the sample conventional moments lay in the equality of the corresponding moments of the theoretical distribution. However, the moment method of parameter estimation is not always convenient, especially for small samples. An alternative approach is based on the use of other characteristics, which the author calls L-moments. L-moments are analogous to conventional moments, but they are based on linear combinations of order statistics, i.e., L-statistics. Using L-moments is theoretically preferable to the conventional moments and consists in the fact that L-moments characterize a wider range of distribution. When estimating from sample L-moments, L-moments are more robust to the presence of outliers in the data. Experience also shows that, compared to conventional moments, L-moments are less prone to bias of estimation. Parameter estimates obtained using L-moments are mainly in the case of small samples often even more accurate than estimates of parameters made by maximum likelihood method. Using the method of L-moments in the case of small data sets from the meteorology is primarily known in statistical literature. This paper deals with the use of L-moments in the case for large data sets of income distribution （individual data） and wage distribution （data are ordered to form of interval frequency distribution of extreme open intervals）. This paper also presents a comparison of the accuracy of the method of L-moments with an accuracy of other methods of point estimation of parameters of parametric probability distribution in the case of large data sets of individual data and data ordered to form of interval frequency distribution.
基金supported in part by the National Natural Science Foundation of China(No.51677030)in part by the Natural Science Foundation of Fujian Province,China(No.2023J05106).
文摘Since the effectiveness of the flexible current arc suppression method heavily relies on the accurate measurement of the distribution line-to-ground parame-ters,the suppression of single line-to-ground(SLG)fault current may deteriorate due to factors such as line switching and other disturbances during SLG fault arc suppression.Additionally,during SLG fault arc suppres-sion,promptly identifying the fault type and rapidly de-activating the flexible arc suppression device(FASD)can reduce the overvoltage risk in non-faulted phase devices.To address these issues,this paper presents a parameter identification method based on recursive least squares(RLS)while a variable forgetting factor strategy is in-troduces to enhance the RLS algorithm’s disturbance rejection capability.Simulations verify that the variable forgetting factor recursive least squares(VFF-RLS)algo-rithm can accurately identify distribution line-to-ground parameters in real time and effectively suppress SLG fault current.The online identification of grounding transition conductance is simultaneously used to deter-mine the fault type and quickly detect when the SLG fault has been cleared.
基金supported by the National Natural Science Foundation of China(61201082)the Youth Science and Engineering Planning Project of Communication University of China(3132018XNG1817)
文摘The distributed parameters of the transmission lines have the significant impact to the signal propagation. In the conventional method of the distributed parameter extraction,the discontinuity of inverse trigonometric or hyperbolic can arise the problem about phase ambiguity which causes significant errors for transmission models. A difference iteration method（ DIM） is proposed for extracting distributed parameters of high frequency transmission line structure in order to overcome the phase ambiguity in the conventional method（ CM）. The formulations of the proposed method are first derived for two-conductor and multi-conductor lines. Then the validation is performed for the models of micro-strip transmission line. Numerical results demonstrate that the proposed DIM can solve the problem about the phase ambiguity and the extracted distributed parameters are accurate and efficient for a wide range of the frequencies of interest and line lengths.
基金supported by the National Natural Science Foundation of China (Grant 11172087)
文摘The nonlinear dynamics of cantilevered piezoelectric beams is investigated under simultaneous parametric and external excitations. The beam is composed of a substrate and two piezoelectric layers and assumed as an Euler-Bernoulli model with inextensible deformation. A nonlinear distributed parameter model of cantilevered piezoelectric energy harvesters is proposed using the generalized Hamilton＇s principle. The proposed model includes geometric and inertia nonlinearity, but neglects the material nonlinearity. Using the Galerkin decomposition method and harmonic balance method, analytical expressions of the frequency-response curves are presented when the first bending mode of the beam plays a dominant role. Using these expressions, we investigate the effects of the damping, load resistance, electromechanical coupling, and excitation amplitude on the frequency-response curves. We also study the difference between the nonlinear lumped-parameter and distributed- parameter model for predicting the performance of the energy harvesting system. Only in the case of parametric excitation, we demonstrate that the energy harvesting system has an initiation excitation threshold below which no energy can be harvested. We also illustrate that the damping and load resistance affect the initiation excitation threshold.
文摘The study on ^(13)C-NMR spectra of aliphatic carbon region of emuision-processed and solution-processed (by lithium catalyst) SBR was carried out. The assignments for more than thirty odd peaks observed experimentally were made by using 'corresponding analysis' method, combined with the empirical parameters reported in literature. The peak intensifies were calculated based on BemouUian statistic assumption.
