多输入多输出(Multiple-Input Multiple-Output,MIMO)雷达在阵元故障时虚拟阵列输出数据矩阵会出现大量的整行数据丢失,由于阵列接收数据矩阵的不完整而导致对波达方向(Direction of Arrival,DOA)的估计性能恶化。大多数低秩矩阵填充算...多输入多输出(Multiple-Input Multiple-Output,MIMO)雷达在阵元故障时虚拟阵列输出数据矩阵会出现大量的整行数据丢失,由于阵列接收数据矩阵的不完整而导致对波达方向(Direction of Arrival,DOA)的估计性能恶化。大多数低秩矩阵填充算法要求缺失数据随机分布于不完整的矩阵中,无法适用于整行缺失数据的恢复问题。为此,提出了一种基于低秩块Hankel矩阵正则化的阵元故障MIMO雷达DOA估计方法。首先,通过奇异值分解(Singular Value Decomposition,SVD)降低虚拟阵列输出矩阵的维度,以减少计算复杂度。然后,对降维数据矩阵建立基于块Hankel矩阵正则化的低秩矩阵填充模型,在该模型中将MIMO雷达降维数据矩阵排列成块Hankel矩阵并施加Schatten-p范数作为正则项。最后,结合交替方向乘子法(Alternate Direction Multiplier Method,ADMM)求解该模型,获得完整的MIMO雷达降维数据矩阵。仿真结果表明,所提方法能够有效恢复降维数据矩阵中的整行数据缺失,具有较高的DOA估计精度和实时性,在阵元故障率低于50.0%时DOA估计精度优于现有方法。展开更多
In this article,we investigate the(big) Hankel operator H_(f) on the Hardy spaces of bounded strongly pseudoconvex domains Ω in C^(n).We observe that H_(f )is bounded on H~p(Ω)(1 <p <∞) if f belongs to BMO an...In this article,we investigate the(big) Hankel operator H_(f) on the Hardy spaces of bounded strongly pseudoconvex domains Ω in C^(n).We observe that H_(f )is bounded on H~p(Ω)(1 <p <∞) if f belongs to BMO and we obtain some characterizations for Hf on H~2(Ω) of other pseudoconvex domains.In these arguments,Amar's L~p-estimations and Berndtsson's L^(2)-estimations for solutions of the ■_(b)-equation play a crucial role.In addition,we solve Gleason's problem for Hardy spaces H~p(Ω)(1 ≤p≤∞) of bounded strongly pseudoconvex domains.展开更多
In recent years,subsynchronous resonance(SSR)has frequently occurred in DFIG-connected series-compensated systems.For the analysis and prevention,it is of great importance to achieve wide area monitoring of the incide...In recent years,subsynchronous resonance(SSR)has frequently occurred in DFIG-connected series-compensated systems.For the analysis and prevention,it is of great importance to achieve wide area monitoring of the incident.This paper presents a Hankel dynamic mode decomposition(DMD)method to identify SSR parameters using synchrophasor data.The basic idea is to employ the DMD technique to explore the subspace of Hankel matrices constructed by synchrophasors.It is analytically demonstrated that the subspace of these Hankel matrices is a combination of fundamental and SSR modes.Therefore,the SSR parameters can be calculated once the modal parameter is extracted.Compared with the existing method,the presented work has better dynamic performances as it requires much less data.Thus,it is more suitable for practical cases in which the SSR characteristics are timevarying.The effectiveness and superiority of the proposed method have been verified by both simulations and field data.展开更多
针对EMD(Empirical Model Decomposition)存在模式频率混叠带来的频谱杂乱的根本缺陷,提出一种高速列车万向轴动不平衡动态检测的新方法。该方法的核心是:对万向节安装机座的振动信号进行EMD分解得到基本模式分量,应用基本模式分量信号...针对EMD(Empirical Model Decomposition)存在模式频率混叠带来的频谱杂乱的根本缺陷,提出一种高速列车万向轴动不平衡动态检测的新方法。该方法的核心是:对万向节安装机座的振动信号进行EMD分解得到基本模式分量,应用基本模式分量信号来构造Hankel矩阵,对该矩阵进行奇异值正交化分解,以奇异值关键叠层作为奇异值的选择准则对信号进行重构,应用重构信号的傅里叶谱来检测高速列车万向轴的动不平衡,消除EMD分解模式频率混叠带来频谱杂乱,提高了谱的清晰度,凸显了故障特征。应用万向轴动不平衡试验数据对该方法进行试验验证,结果表明:该方法能够有效检测万向轴动不平衡引起故障特征和万向轴的固有振动特性,与纯EMD方法相比,该方法在谱的清晰度和故障表征力上得到了显著提高。展开更多
针对聚合经验模式分解(Ensemble empirical model decomposition,EEMD)的等效滤波特性依然存在模式分量间频带重叠较大的根本缺陷,提出一种高速列车万向轴动不平衡动态检测的新方法。该方法的核心是对万向节安装机座的振动信号进行EEMD...针对聚合经验模式分解(Ensemble empirical model decomposition,EEMD)的等效滤波特性依然存在模式分量间频带重叠较大的根本缺陷,提出一种高速列车万向轴动不平衡动态检测的新方法。该方法的核心是对万向节安装机座的振动信号进行EEMD分解得到基本模式分量,应用基本模式分量信号来构造Hankel矩阵,对该矩阵进行正交化奇异值(Singular value decomposition,SVD)分解,以奇异值关键叠层作为奇异值的选择准则对信号进行重构,应用重构信号的傅里叶谱来检测高速列车万向轴的动不平衡,消除EEMD分解模式频带重叠对故障特征的淹没和混淆效应,提高了谱的清晰度,凸显了故障特征。应用万向轴动不平衡试验数据对该方法进行试验验证,结果表明,该方法能够有效检测万向轴动不平衡引起的故障特征和万向轴的固有振动特征,与纯EEMD方法相比,该方法在谱的清晰度和故障表征力上得到了显著提高。展开更多
文摘多输入多输出(Multiple-Input Multiple-Output,MIMO)雷达在阵元故障时虚拟阵列输出数据矩阵会出现大量的整行数据丢失,由于阵列接收数据矩阵的不完整而导致对波达方向(Direction of Arrival,DOA)的估计性能恶化。大多数低秩矩阵填充算法要求缺失数据随机分布于不完整的矩阵中,无法适用于整行缺失数据的恢复问题。为此,提出了一种基于低秩块Hankel矩阵正则化的阵元故障MIMO雷达DOA估计方法。首先,通过奇异值分解(Singular Value Decomposition,SVD)降低虚拟阵列输出矩阵的维度,以减少计算复杂度。然后,对降维数据矩阵建立基于块Hankel矩阵正则化的低秩矩阵填充模型,在该模型中将MIMO雷达降维数据矩阵排列成块Hankel矩阵并施加Schatten-p范数作为正则项。最后,结合交替方向乘子法(Alternate Direction Multiplier Method,ADMM)求解该模型,获得完整的MIMO雷达降维数据矩阵。仿真结果表明,所提方法能够有效恢复降维数据矩阵中的整行数据缺失,具有较高的DOA估计精度和实时性,在阵元故障率低于50.0%时DOA估计精度优于现有方法。
基金supported by the National Natural Science Foundation of China(12271101)。
文摘In this article,we investigate the(big) Hankel operator H_(f) on the Hardy spaces of bounded strongly pseudoconvex domains Ω in C^(n).We observe that H_(f )is bounded on H~p(Ω)(1 <p <∞) if f belongs to BMO and we obtain some characterizations for Hf on H~2(Ω) of other pseudoconvex domains.In these arguments,Amar's L~p-estimations and Berndtsson's L^(2)-estimations for solutions of the ■_(b)-equation play a crucial role.In addition,we solve Gleason's problem for Hardy spaces H~p(Ω)(1 ≤p≤∞) of bounded strongly pseudoconvex domains.
基金supported by the China Key Technology Research on Risk Perception of Sub-Synchronous Oscillation of Grid with Large-Scale New Energy Access SGTYHT/21-JS-223.
文摘In recent years,subsynchronous resonance(SSR)has frequently occurred in DFIG-connected series-compensated systems.For the analysis and prevention,it is of great importance to achieve wide area monitoring of the incident.This paper presents a Hankel dynamic mode decomposition(DMD)method to identify SSR parameters using synchrophasor data.The basic idea is to employ the DMD technique to explore the subspace of Hankel matrices constructed by synchrophasors.It is analytically demonstrated that the subspace of these Hankel matrices is a combination of fundamental and SSR modes.Therefore,the SSR parameters can be calculated once the modal parameter is extracted.Compared with the existing method,the presented work has better dynamic performances as it requires much less data.Thus,it is more suitable for practical cases in which the SSR characteristics are timevarying.The effectiveness and superiority of the proposed method have been verified by both simulations and field data.
文摘针对EMD(Empirical Model Decomposition)存在模式频率混叠带来的频谱杂乱的根本缺陷,提出一种高速列车万向轴动不平衡动态检测的新方法。该方法的核心是:对万向节安装机座的振动信号进行EMD分解得到基本模式分量,应用基本模式分量信号来构造Hankel矩阵,对该矩阵进行奇异值正交化分解,以奇异值关键叠层作为奇异值的选择准则对信号进行重构,应用重构信号的傅里叶谱来检测高速列车万向轴的动不平衡,消除EMD分解模式频率混叠带来频谱杂乱,提高了谱的清晰度,凸显了故障特征。应用万向轴动不平衡试验数据对该方法进行试验验证,结果表明:该方法能够有效检测万向轴动不平衡引起故障特征和万向轴的固有振动特性,与纯EMD方法相比,该方法在谱的清晰度和故障表征力上得到了显著提高。
文摘针对聚合经验模式分解(Ensemble empirical model decomposition,EEMD)的等效滤波特性依然存在模式分量间频带重叠较大的根本缺陷,提出一种高速列车万向轴动不平衡动态检测的新方法。该方法的核心是对万向节安装机座的振动信号进行EEMD分解得到基本模式分量,应用基本模式分量信号来构造Hankel矩阵,对该矩阵进行正交化奇异值(Singular value decomposition,SVD)分解,以奇异值关键叠层作为奇异值的选择准则对信号进行重构,应用重构信号的傅里叶谱来检测高速列车万向轴的动不平衡,消除EEMD分解模式频带重叠对故障特征的淹没和混淆效应,提高了谱的清晰度,凸显了故障特征。应用万向轴动不平衡试验数据对该方法进行试验验证,结果表明,该方法能够有效检测万向轴动不平衡引起的故障特征和万向轴的固有振动特征,与纯EEMD方法相比,该方法在谱的清晰度和故障表征力上得到了显著提高。
