混沌压缩感知是一种利用混沌系统实现非线性测量,通过混沌脉冲同步和参数估计技术实现信号重构的压缩感知理论。针对混沌压缩感知重构系统中采用l1范数正则化信号系数导致在信号稀疏水平较高时重构性能急剧下降的问题,利用lp(0 p 1)范...混沌压缩感知是一种利用混沌系统实现非线性测量,通过混沌脉冲同步和参数估计技术实现信号重构的压缩感知理论。针对混沌压缩感知重构系统中采用l1范数正则化信号系数导致在信号稀疏水平较高时重构性能急剧下降的问题,利用lp(0 p 1)范数来正则化信号系数,将重构系统中的非线性约束l1范数最小化问题替换为非线性约束lp范数最小化问题,并提出-正则迭代再加权非线性最小二乘算法进行求解。以Henon混沌为例,研究了频域稀疏信号的重构性能,数值模拟表明lp范数正则化能够准确重构出比l1范数正则化时稀疏水平更高的信号。展开更多
Measuring the internal stress of Al alloy forgings accurately is critical for controlling the deformation during the subsequent machine process.In this work,the crack compliance method was used to calculate the intern...Measuring the internal stress of Al alloy forgings accurately is critical for controlling the deformation during the subsequent machine process.In this work,the crack compliance method was used to calculate the internal residual stress of Al-Cu high strength alloys,and the effect of various model parameters of crack compliance method on the calculated precision was studied by combining the numerical simulation and experimental method.The results show that the precision first increased and then decreased with increasing the crack range.The decreased precision when using a high crack range was due to the strain fluctuation during the machining process,and the optimized crack range was 71%of the thickness of forgings.Low orders of Legendre polynomial can result in residual stress curve more smooth,while high orders led to the occurrence of distortion.The Tikhonov regularization method effectively suppressed the distortion of residual stress caused by the fluctuation of strain data,which significantly improved the precision.In addition,The crack compliance method with optimized parameters was used to measure the residual stress of Al-Cu alloy with different quenching methods.The calculated results demonstrated that the distribution of residual stress was obtained accurately.展开更多
The classical elastic impedance （EI） inversion method, however, is based on the L2-norm misfit function and considerably sensitive to outliers, assuming the noise of the seismic data to be the Guassian-distribution....The classical elastic impedance （EI） inversion method, however, is based on the L2-norm misfit function and considerably sensitive to outliers, assuming the noise of the seismic data to be the Guassian-distribution. So we have developed a more robust elastic impedance inversion based on the Ll-norm misfit function, and the noise is assumed to be non-Gaussian. Meanwhile, some regularization methods including the sparse constraint regularization and elastic impedance point constraint regularization are incorporated to improve the ill-posed characteristics of the seismic inversion problem. Firstly, we create the Ll-norm misfit objective function of pre-stack inversion problem based on the Bayesian scheme within the sparse constraint regularization and elastic impedance point constraint regularization. And then, we obtain more robust elastic impedances of different angles which are less sensitive to outliers in seismic data by using the IRLS strategy. Finally, we extract the P-wave and S-wave velocity and density by using the more stable parameter extraction method. Tests on synthetic data show that the P-wave and S-wave velocity and density parameters are still estimated reasonable with moderate noise. A test on the real data set shows that compared to the results of the classical elastic impedance inversion method, the estimated results using the proposed method can get better lateral continuity and more distinct show of the gas, verifying the feasibility and stability of the method.展开更多
文摘混沌压缩感知是一种利用混沌系统实现非线性测量,通过混沌脉冲同步和参数估计技术实现信号重构的压缩感知理论。针对混沌压缩感知重构系统中采用l1范数正则化信号系数导致在信号稀疏水平较高时重构性能急剧下降的问题,利用lp(0 p 1)范数来正则化信号系数,将重构系统中的非线性约束l1范数最小化问题替换为非线性约束lp范数最小化问题,并提出-正则迭代再加权非线性最小二乘算法进行求解。以Henon混沌为例,研究了频域稀疏信号的重构性能,数值模拟表明lp范数正则化能够准确重构出比l1范数正则化时稀疏水平更高的信号。
基金Project(51875583)supported by the National Natural Science Foundation of ChinaProject(zzyjkt2018-03)supported by the State Key Laboratory of High Performance Complex Manufacturing,China。
文摘Measuring the internal stress of Al alloy forgings accurately is critical for controlling the deformation during the subsequent machine process.In this work,the crack compliance method was used to calculate the internal residual stress of Al-Cu high strength alloys,and the effect of various model parameters of crack compliance method on the calculated precision was studied by combining the numerical simulation and experimental method.The results show that the precision first increased and then decreased with increasing the crack range.The decreased precision when using a high crack range was due to the strain fluctuation during the machining process,and the optimized crack range was 71%of the thickness of forgings.Low orders of Legendre polynomial can result in residual stress curve more smooth,while high orders led to the occurrence of distortion.The Tikhonov regularization method effectively suppressed the distortion of residual stress caused by the fluctuation of strain data,which significantly improved the precision.In addition,The crack compliance method with optimized parameters was used to measure the residual stress of Al-Cu alloy with different quenching methods.The calculated results demonstrated that the distribution of residual stress was obtained accurately.
基金Projects(U1562215,41674130,41404088)supported by the National Natural Science Foundation of ChinaProjects(2013CB228604,2014CB239201)supported by the National Basic Research Program of China+1 种基金Projects(2016ZX05027004-001,2016ZX05002006-009)supported by the National Oil and Gas Major Projects of ChinaProject(15CX08002A)supported by the Fundamental Research Funds for the Central Universities,China
文摘The classical elastic impedance （EI） inversion method, however, is based on the L2-norm misfit function and considerably sensitive to outliers, assuming the noise of the seismic data to be the Guassian-distribution. So we have developed a more robust elastic impedance inversion based on the Ll-norm misfit function, and the noise is assumed to be non-Gaussian. Meanwhile, some regularization methods including the sparse constraint regularization and elastic impedance point constraint regularization are incorporated to improve the ill-posed characteristics of the seismic inversion problem. Firstly, we create the Ll-norm misfit objective function of pre-stack inversion problem based on the Bayesian scheme within the sparse constraint regularization and elastic impedance point constraint regularization. And then, we obtain more robust elastic impedances of different angles which are less sensitive to outliers in seismic data by using the IRLS strategy. Finally, we extract the P-wave and S-wave velocity and density by using the more stable parameter extraction method. Tests on synthetic data show that the P-wave and S-wave velocity and density parameters are still estimated reasonable with moderate noise. A test on the real data set shows that compared to the results of the classical elastic impedance inversion method, the estimated results using the proposed method can get better lateral continuity and more distinct show of the gas, verifying the feasibility and stability of the method.
