ABSTRACT The impact of both initial and parameter errors on the spring predictability barrier （SPB） is investigated using the Zebiak Cane model （ZC model）. Previous studies have shown that initial errors contribu...ABSTRACT The impact of both initial and parameter errors on the spring predictability barrier （SPB） is investigated using the Zebiak Cane model （ZC model）. Previous studies have shown that initial errors contribute more to the SPB than parameter errors in the ZC model. Although parameter errors themselves are less important, there is a possibility that nonlinear interactions can occur between the two types of errors, leading to larger prediction errors compared with those induced by initial errors alone. In this case, the impact of parameter errors cannot be overlooked. In the present paper, the optimal combination of these two types of errors [i.e., conditional nonlinear optimal perturbation （CNOP） errors] is calculated to investigate whether this optimal error combination may cause a more notable SPB phenomenon than that caused by initial errors alone. Using the CNOP approach, the CNOP errors and CNOP-I errors （optimal errors when only initial errors are considered） are calculated and then three aspects of error growth are compared： （1） the tendency of the seasonal error growth; （2） the prediction error of the sea surface temperature anomaly; and （3） the pattern of error growth. All three aspects show that the CNOP errors do not cause a more significant SPB than the CNOP-I errors. Therefore, this result suggests that we could improve the prediction of the E1 Nifio during spring by simply focusing on reducing the initial errors in this model.展开更多
For the high-resolution airborne synthetic aperture radar （SAR） stereo geolocation application, the final geolocation ac- curacy is influenced by various error parameter sources. In this paper, an airborne SAR stere...For the high-resolution airborne synthetic aperture radar （SAR） stereo geolocation application, the final geolocation ac- curacy is influenced by various error parameter sources. In this paper, an airborne SAR stereo geolocation parameter error model, involving the parameter errors derived from the navigation system on the flight platform, has been put forward. Moreover, a kind of near-direct method for modeling and sensitivity analysis of navigation parameter errors is also given. This method directly uses the ground reference to calculate the covariance matrix relationship between the parameter errors and the eventual geoloeation errors for ground target points. In addition, utilizing true flight track parameters＇ errors, this paper gave a verification of the method and a corresponding sensitivity analysis for airborne SAR stereo geolocation model and proved its efficiency.展开更多
The integration of deep learning into computational imaging has driven substantial advancements in coherent diffraction imaging(CDI).While physics-driven neural networks have emerged as a promising approach through th...The integration of deep learning into computational imaging has driven substantial advancements in coherent diffraction imaging(CDI).While physics-driven neural networks have emerged as a promising approach through their unsupervised learning paradigm,their practical implementation faces critical challenges:measurement uncertainties in physical parameters(e.g.,the propagation distance and the size of sample area)severely degrade reconstruction quality.To overcome this limitation,we propose a deep-learning-enabled spatial sample interval optimization framework that synergizes physical models with neural network adaptability.Our method embeds spatial sample intervals as trainable parameters within a PhysenNet architecture coupled with Fresnel diffraction physics,enabling simultaneous image reconstruction and system parameter calibration.Experimental validation demonstrates robust performance with structural similarity(SSIM)values consistently maintained at 0.6 across diffraction distances spanning of 10-200 mm,using a 1024×1024 region of interest(ROI)from a 1624×1440 CCD(pixel size:4.5μm)under 632.8 nm illumination.This framework has excellent fault tolerance,that is,it can still maintain high-quality image restoration even when the propagation distance measurement error is large.Compared to conventional iterative reconstruction algorithms,this approach can transform fixed parameters into learnable parameters,making almost all image restoration experiments easier to implement,enhancing system robustness against experimental uncertainties.This work establishes,to our knowledge,a new paradigm for adaptive diffraction imaging systems capable of operating in complex real scenarios.展开更多
We propose a new and efficient algorithm to detect, identify, and correct measurement errors and branch parameter errors of power systems. A dynamic state estimation algorithm is used based on the Kalman filter theory...We propose a new and efficient algorithm to detect, identify, and correct measurement errors and branch parameter errors of power systems. A dynamic state estimation algorithm is used based on the Kalman filter theory. The proposed algorithm also successfully detects and identifies sudden load changes in power systems. The method uses three normalized vectors to process errors at each sampling time: normalized measurement residual, normalized Lagrange multiplier, and normalized innovation vector. An IEEE 14-bus test system was used to verify and demonstrate the effectiveness of the proposed method. Numerical results are presented and discussed to show the accuracy of the method.展开更多
In this paper the main sources causing the scatter of the experimental results of the material parameters are discussed. They can be divided into two parts: one is the experimental errors which are introduced because ...In this paper the main sources causing the scatter of the experimental results of the material parameters are discussed. They can be divided into two parts: one is the experimental errors which are introduced because of the inaccuracy of experimental equipment, the experimental techniques, etc., and the form of the scatter caused by this source is called external distribution. The other is due to the irregularity and inhomogeneity of the material structure and the randomness of deformation process. The scatter caused by this source is inherent and then this form of the scatter is called internal distribution. Obviously the experimental distribution of material parameters combines these two distributions in some way; therefore, it is a sum distribution of the external distribution and the internal distribution. In view of this , a general method used to analyse the influence of the experimental errors on the experimental results is presented, and three criteria used to value this influence are defined. An example in which the fracture toughness KIC is analysed shows that this method is reasonable, convenient and effective.展开更多
The similarity property of conformal parameterization makes it able to locally preserve the shapes between a surface and its parameter domain, as opposed to common parameterization methods. A parametric tool path plan...The similarity property of conformal parameterization makes it able to locally preserve the shapes between a surface and its parameter domain, as opposed to common parameterization methods. A parametric tool path planning method is proposed in this paper through such parameterization of triangular meshes which is furthermore based on the geodesic on meshes. The parameterization has the properties of local similarity and free boundary which are exploited to simplify the formulas for computing path parameters, which play a fundamentally important role in tool path planning, and keep the path boundary-conformed and smooth. Experimental results are given to illustrate the effectiveness of the proposed methods, as well as the error analysis.展开更多
High-speed pick-and-place parallel robot is a system where the inertia imposed on the motor shafts is real-time changing with the system configurations.High quality of computer control with proper controller parameter...High-speed pick-and-place parallel robot is a system where the inertia imposed on the motor shafts is real-time changing with the system configurations.High quality of computer control with proper controller parameters is conducive to overcoming this problem and has a significant effect on reducing the robot＇s tracking error.By taking Delta robot as an example,a method for parameter tuning of the fixed gain motion controller is presented.Having identifying the parameters of the servo system in the frequency domain by the sinusoidal excitation,the PD＋feedforward control strategy is proposed to adapt to the varying inertia loads,allowing the controller parameters to be tuned by minimizing the mean square tracking error along a typical trajectory.A set of optimum parameters is obtained through computer simulations and the effectiveness of the proposed approach is validated by experiments on a real prototype machine.Let the traveling plate undergoes a specific trajectory and the results show that the tracking error can be reduced by at least 50%in comparison with the conventional auto-tuning and Z-N methods.The proposed approach is a whole workspace optimization and can be applied to the parameter tuning of fixed gain motion controllers.展开更多
Large complex components are characterized by their complexity and large size,making it challenging to precisely calibrate robots and measurement devices,compensate for their pose and error,and plan measurement paths....Large complex components are characterized by their complexity and large size,making it challenging to precisely calibrate robots and measurement devices,compensate for their pose and error,and plan measurement paths.Consequently,it is difficult to guarantee the integrity and accuracy of three-dimensional(3D)measurements.In this study,a novel measurement trajectory planning method is developed to accurately obtain the 3D point clouds of large complex components by accounting for the field of view and overlapping area constraints.A hybrid identification algorithm based on the quasi-Newton and Levenberg Marquardt method is then proposed to realize the synchronous identification of kinematic parameter errors of the measurement system,allowing it to accurately reach the planning viewpoint.Finally,robotic calibration and measurement experiments of a high-speed rail headstock are conducted to evaluate the effectiveness and practicality of the proposed methods.展开更多
本文研究了一个包含波动CISK(Convective Instability of the Second Kind)机制的扰动方程数值模式中,基本气流对低频振荡数值模拟的影响。结果显示,当基本气流为纬向均匀风场U时,振荡周期随U的增加而减小:当U取2 m s-1时,周期从50～60 ...本文研究了一个包含波动CISK(Convective Instability of the Second Kind)机制的扰动方程数值模式中,基本气流对低频振荡数值模拟的影响。结果显示,当基本气流为纬向均匀风场U时,振荡周期随U的增加而减小:当U取2 m s-1时,周期从50～60 d减小到30 d;当U减小到-1 m s-1时,振荡周期增加为70～80 d。这是由于低频振荡是从西向东传播,西风基本气流能加快扰动东传,反之东风基本气流会抑制扰动东传,使振荡周期增加。同时,模式中的边界层顶出现误差时,模拟结果会有敏感的响应。若边界层顶取值比标准值高,对流加热反馈作用过大,出现扰动增长过快的现象,传播到80°～90°E附近时,扰动不再继续传播,而是无限增长;而边界层顶取值比标准值低时,对流加热反馈过小,扰动增长小且衰减加快,扰动传播不远便耗散到零,扰动循环周期表现为热源的周期。展开更多
Due to the low spatial resolution of sea surface temperature(T_S)retrieval by real aperture microwave radiometers,in this study,an iterative retrieval method that minimizes the differences between brightness temperatu...Due to the low spatial resolution of sea surface temperature(T_S)retrieval by real aperture microwave radiometers,in this study,an iterative retrieval method that minimizes the differences between brightness temperature(T_B)measured and modeled was used to retrieve sea surface temperature with a one-dimensional synthetic aperture microwave radiometer,temporarily named 1 D-SAMR.Regarding the configuration of the radiometer,an angular resolution of 0.43°was reached by theoretical calculation.Experiments on sea surface temperature retrieval were carried out with ideal parameters;the results show that the main factors affecting the retrieval accuracy of sea surface temperature are the accuracy of radiometer calibration and the precision of auxiliary geophysical parameters.In the case of no auxiliary parameter errors,the greatest error in retrieved sea surface temperature is obtained at low T_S scene(i.e.,0.7106 K for the incidence angle of 35°under the radiometer calibration accuracy of0.5 K).While errors on auxiliary parameters are assumed to follow a Gaussian distribution,the greatest error on retrieved sea surface temperature was 1.3305 K at an incidence angle of 65°in poorly known sea surface wind speed(W)(the error on W of 1.0 m/s)over high W scene,for the radiometer calibration accuracy of 0.5 K.展开更多
基金jointly sponsored by the National Nature Scientific Foundation of China (Grant Nos.41230420 and 41006015)the National Basic Research Program of China (Grant No.2012CB417404)the Basic Research Program of Science and Technology Projects of Qingdao (Grant No11-1-4-95-jch)
文摘ABSTRACT The impact of both initial and parameter errors on the spring predictability barrier （SPB） is investigated using the Zebiak Cane model （ZC model）. Previous studies have shown that initial errors contribute more to the SPB than parameter errors in the ZC model. Although parameter errors themselves are less important, there is a possibility that nonlinear interactions can occur between the two types of errors, leading to larger prediction errors compared with those induced by initial errors alone. In this case, the impact of parameter errors cannot be overlooked. In the present paper, the optimal combination of these two types of errors [i.e., conditional nonlinear optimal perturbation （CNOP） errors] is calculated to investigate whether this optimal error combination may cause a more notable SPB phenomenon than that caused by initial errors alone. Using the CNOP approach, the CNOP errors and CNOP-I errors （optimal errors when only initial errors are considered） are calculated and then three aspects of error growth are compared： （1） the tendency of the seasonal error growth; （2） the prediction error of the sea surface temperature anomaly; and （3） the pattern of error growth. All three aspects show that the CNOP errors do not cause a more significant SPB than the CNOP-I errors. Therefore, this result suggests that we could improve the prediction of the E1 Nifio during spring by simply focusing on reducing the initial errors in this model.
基金Supported by the National Basic Research Program of China (No. 2006CB701303)
文摘For the high-resolution airborne synthetic aperture radar （SAR） stereo geolocation application, the final geolocation ac- curacy is influenced by various error parameter sources. In this paper, an airborne SAR stereo geolocation parameter error model, involving the parameter errors derived from the navigation system on the flight platform, has been put forward. Moreover, a kind of near-direct method for modeling and sensitivity analysis of navigation parameter errors is also given. This method directly uses the ground reference to calculate the covariance matrix relationship between the parameter errors and the eventual geoloeation errors for ground target points. In addition, utilizing true flight track parameters＇ errors, this paper gave a verification of the method and a corresponding sensitivity analysis for airborne SAR stereo geolocation model and proved its efficiency.
基金supported by the Basic and Applied Basic Research Foundation of Guangdong Province(No.2022A1515110203)the Science and Technology Research Project of Jiangxi Provincial Department of Education(No.GJJ203501)。
文摘The integration of deep learning into computational imaging has driven substantial advancements in coherent diffraction imaging(CDI).While physics-driven neural networks have emerged as a promising approach through their unsupervised learning paradigm,their practical implementation faces critical challenges:measurement uncertainties in physical parameters(e.g.,the propagation distance and the size of sample area)severely degrade reconstruction quality.To overcome this limitation,we propose a deep-learning-enabled spatial sample interval optimization framework that synergizes physical models with neural network adaptability.Our method embeds spatial sample intervals as trainable parameters within a PhysenNet architecture coupled with Fresnel diffraction physics,enabling simultaneous image reconstruction and system parameter calibration.Experimental validation demonstrates robust performance with structural similarity(SSIM)values consistently maintained at 0.6 across diffraction distances spanning of 10-200 mm,using a 1024×1024 region of interest(ROI)from a 1624×1440 CCD(pixel size:4.5μm)under 632.8 nm illumination.This framework has excellent fault tolerance,that is,it can still maintain high-quality image restoration even when the propagation distance measurement error is large.Compared to conventional iterative reconstruction algorithms,this approach can transform fixed parameters into learnable parameters,making almost all image restoration experiments easier to implement,enhancing system robustness against experimental uncertainties.This work establishes,to our knowledge,a new paradigm for adaptive diffraction imaging systems capable of operating in complex real scenarios.
文摘We propose a new and efficient algorithm to detect, identify, and correct measurement errors and branch parameter errors of power systems. A dynamic state estimation algorithm is used based on the Kalman filter theory. The proposed algorithm also successfully detects and identifies sudden load changes in power systems. The method uses three normalized vectors to process errors at each sampling time: normalized measurement residual, normalized Lagrange multiplier, and normalized innovation vector. An IEEE 14-bus test system was used to verify and demonstrate the effectiveness of the proposed method. Numerical results are presented and discussed to show the accuracy of the method.
文摘In this paper the main sources causing the scatter of the experimental results of the material parameters are discussed. They can be divided into two parts: one is the experimental errors which are introduced because of the inaccuracy of experimental equipment, the experimental techniques, etc., and the form of the scatter caused by this source is called external distribution. The other is due to the irregularity and inhomogeneity of the material structure and the randomness of deformation process. The scatter caused by this source is inherent and then this form of the scatter is called internal distribution. Obviously the experimental distribution of material parameters combines these two distributions in some way; therefore, it is a sum distribution of the external distribution and the internal distribution. In view of this , a general method used to analyse the influence of the experimental errors on the experimental results is presented, and three criteria used to value this influence are defined. An example in which the fracture toughness KIC is analysed shows that this method is reasonable, convenient and effective.
基金supported by the National Program on Key Basic Research Project of China (No. 2011CB302400)the National Natural Science Foundation of China (No. 51175495)
文摘The similarity property of conformal parameterization makes it able to locally preserve the shapes between a surface and its parameter domain, as opposed to common parameterization methods. A parametric tool path planning method is proposed in this paper through such parameterization of triangular meshes which is furthermore based on the geodesic on meshes. The parameterization has the properties of local similarity and free boundary which are exploited to simplify the formulas for computing path parameters, which play a fundamentally important role in tool path planning, and keep the path boundary-conformed and smooth. Experimental results are given to illustrate the effectiveness of the proposed methods, as well as the error analysis.
基金Supported by National Natural Science Foundation of China(Grant Nos.51305293,51135008)
文摘High-speed pick-and-place parallel robot is a system where the inertia imposed on the motor shafts is real-time changing with the system configurations.High quality of computer control with proper controller parameters is conducive to overcoming this problem and has a significant effect on reducing the robot＇s tracking error.By taking Delta robot as an example,a method for parameter tuning of the fixed gain motion controller is presented.Having identifying the parameters of the servo system in the frequency domain by the sinusoidal excitation,the PD＋feedforward control strategy is proposed to adapt to the varying inertia loads,allowing the controller parameters to be tuned by minimizing the mean square tracking error along a typical trajectory.A set of optimum parameters is obtained through computer simulations and the effectiveness of the proposed approach is validated by experiments on a real prototype machine.Let the traveling plate undergoes a specific trajectory and the results show that the tracking error can be reduced by at least 50%in comparison with the conventional auto-tuning and Z-N methods.The proposed approach is a whole workspace optimization and can be applied to the parameter tuning of fixed gain motion controllers.
基金supported by the National Natural Science Foundation of China(Grant Nos.52105514,52075204)the Fundamental Research Funds for the Central Universities(Grant No.2042023kf0114)+1 种基金Wuhan Natural Science Foundation(Grant No.20240408010202220)Hubei Province Key R&D Program(Grant No.2022BAA067).
文摘Large complex components are characterized by their complexity and large size,making it challenging to precisely calibrate robots and measurement devices,compensate for their pose and error,and plan measurement paths.Consequently,it is difficult to guarantee the integrity and accuracy of three-dimensional(3D)measurements.In this study,a novel measurement trajectory planning method is developed to accurately obtain the 3D point clouds of large complex components by accounting for the field of view and overlapping area constraints.A hybrid identification algorithm based on the quasi-Newton and Levenberg Marquardt method is then proposed to realize the synchronous identification of kinematic parameter errors of the measurement system,allowing it to accurately reach the planning viewpoint.Finally,robotic calibration and measurement experiments of a high-speed rail headstock are conducted to evaluate the effectiveness and practicality of the proposed methods.
文摘本文研究了一个包含波动CISK(Convective Instability of the Second Kind)机制的扰动方程数值模式中,基本气流对低频振荡数值模拟的影响。结果显示,当基本气流为纬向均匀风场U时,振荡周期随U的增加而减小:当U取2 m s-1时,周期从50～60 d减小到30 d;当U减小到-1 m s-1时,振荡周期增加为70～80 d。这是由于低频振荡是从西向东传播,西风基本气流能加快扰动东传,反之东风基本气流会抑制扰动东传,使振荡周期增加。同时,模式中的边界层顶出现误差时,模拟结果会有敏感的响应。若边界层顶取值比标准值高,对流加热反馈作用过大,出现扰动增长过快的现象,传播到80°～90°E附近时,扰动不再继续传播,而是无限增长;而边界层顶取值比标准值低时,对流加热反馈过小,扰动增长小且衰减加快,扰动传播不远便耗散到零,扰动循环周期表现为热源的周期。
基金The National Natural Science Foundation of China under contract Nos 41475019,41575028,41705007,41605016,and 41505016。
文摘Due to the low spatial resolution of sea surface temperature(T_S)retrieval by real aperture microwave radiometers,in this study,an iterative retrieval method that minimizes the differences between brightness temperature(T_B)measured and modeled was used to retrieve sea surface temperature with a one-dimensional synthetic aperture microwave radiometer,temporarily named 1 D-SAMR.Regarding the configuration of the radiometer,an angular resolution of 0.43°was reached by theoretical calculation.Experiments on sea surface temperature retrieval were carried out with ideal parameters;the results show that the main factors affecting the retrieval accuracy of sea surface temperature are the accuracy of radiometer calibration and the precision of auxiliary geophysical parameters.In the case of no auxiliary parameter errors,the greatest error in retrieved sea surface temperature is obtained at low T_S scene(i.e.,0.7106 K for the incidence angle of 35°under the radiometer calibration accuracy of0.5 K).While errors on auxiliary parameters are assumed to follow a Gaussian distribution,the greatest error on retrieved sea surface temperature was 1.3305 K at an incidence angle of 65°in poorly known sea surface wind speed(W)(the error on W of 1.0 m/s)over high W scene,for the radiometer calibration accuracy of 0.5 K.
