Comparison between iterative wavefront control algorithm and direct gradient wavefront control algorithm for adaptive optics system

Among all kinds of wavefront control algorithms in adaptive optics systems, the direct gradient wavefront control algorithm is the most widespread and common method. This control algorithm obtains the actuator voltages directly from wavefront slopes through pre-measuring the relational matrix between deformable mirror actuators and Hartmann wavefront sensor with perfect real-time characteristic and stability. However, with increasing the number of sub-apertures in wavefront sensor and deformable mirror actuators of adaptive optics systems, the matrix operation in direct gradient algorithm takes too much time, which becomes a major factor influencing control effect of adaptive optics systems. In this paper we apply an iterative wavefront control algorithm to high-resolution adaptive optics systems, in which the voltages of each actuator are obtained through iteration arithmetic, which gains great advantage in calculation and storage. For AO system with thousands of actuators, the computational complexity estimate is about O(n2) ～ O(n3) in direct gradient wavefront control algorithm, while the computational complexity estimate in iterative wavefront control algorithm is about O(n) ～(O(n)3/2), in which n is the number of actuators of AO system. And the more the numbers of sub-apertures and deformable mirror actuators, the more significant advantage the iterative wavefront control algorithm exhibits.

一种基于小生境的自适应入侵野草优化算法

针对入侵野草优化(Invasive Weed Optimization,IWO)算法在迭代前期局部搜索能力不足和后期缺乏种群多样性的缺点,论文提出了一种基于小生境思想的自适应入侵野草优化(Niche-based Adaptive Invasive Weed Optimization,NAIWO)算法。小生境思想用来增加算法的种群多样性;自适应机制中引入周期算子和自适应算法,使野草个体的空间扩散的标准差不仅随迭代次数变化,而且可以根据周期算子的参数和个体的适应度值来动态变化。通过多个数学基准函数的寻优测试验证了所提出的NAIWO算法的有效性。

变形镜高斯函数指数对迭代法自适应光学系统的影响

基于613单元自适应光学系统,描述了迭代矩阵和斜率响应矩阵的特性.在变形镜驱动器间距和交连值不变的情况下,研究了变形镜高斯函数指数对迭代矩阵和斜率响应矩阵稀疏度的影响,对自适应光学系统稳定性和校正能力的影响.研究表明,迭代矩阵和斜率响应矩阵的稀疏度随着变形镜高斯函数指数的增大而减小.高斯函数指数过大或者过小都会影响自适应光学系统的稳定性和校正能力.最后,综合迭代矩阵和斜率响应矩阵的稀疏度、自适应光学系统的稳定性和校正能力,给出了合理的变形镜高斯函数指数的取值范围.

交连值对斜率响应矩阵和迭代矩阵稀疏度的影响

基于529单元自适应光学(AO)系统,分析了变形镜到哈特曼波前传感器的斜率响应矩阵的稀疏特性、波前复原中迭代矩阵的稀疏特性.在变形镜驱动器间距不变的条件下,研究了驱动器交连值对斜率响应矩阵稀疏度、迭代矩阵稀疏度以及AO系统校正能力的影响.研究表明,斜率响应矩阵和迭代矩阵的稀疏度随交连值的增大而减小;交连值过大或者过小都会影响AO系统的稳定性和校正能力.最后,综合斜率响应矩阵和迭代矩阵的稀疏度、系统稳定性和校正能力,给出了交连值的合理取值范围.

基于CBAM-CNN的模拟电路故障诊断

针对模拟电路的故障特征难以提取,导致模型计算量复杂、诊断准确率不够高的问题,提出一种基于注意力机制和卷积神经网络(CBAM-CNN)的模拟电路故障诊断方法.首先,利用卷积核提取输入层的图片特征,同时在每个卷积层后面连接一个矫正线性单元(ReLU),并添加批归一化层(BN)解决内部协变量偏移的问题,以提高非线性模型表达能力;然后,在批归一化层后添加注意力机制模块(CBAM),提取重要的特征后连接池化层,降低网络计算复杂度,提高网络的准确率与效率;最后,以Sallen-Key低通滤波器和二级四运放双二阶低通滤波器为研究对象进行故障诊断实验验证.结果表明,所提出方法能够有效提升诊断精度,实现所有故障的高难分类与定位.