基于光纤耦合金刚石NV色心系综磁强计的电路诊断方法

为考查应用新型磁强计——金刚石氮空穴(nitrogen-vacancy,NV)色心系综磁强计进行电路诊断的可行性和可靠性,从金刚石NV色心系综磁强计的基本原理出发,搭建了一套光纤耦合金刚石NV色心系综磁强计测试实验系统,将探头紧贴于电路导线外壳,通过测量磁强计处磁场信号的变化实现对电路的诊断.实验结果表明,金刚石NV色...     

一种面向复杂体系作战的多源信息融合处理方法

研讨了面向复杂体系化作战的信息融合技术，提出了一种基于中心航迹关联的融合架构，设计了面 向多源异构数据的信息融合处理方法。经过多机飞行场景下的数据仿真测试，能够有效解决多源传感器多目标 环境下目标关联判断问题。     

纤维织物超高速碰撞热-力学模型与分析

A new thermo mechanical model for fiber fabric of hypervelocity impact is established by using the Johnson Cook model, the Gruneisen equation of state and the FEM SPH coupling algorithm, while some new factors are taken into account such as the heat generation, strain rate strengthening and high temperature softening of materials. Mechanical and thermal information could be obtained with the model, such as penetration, fragmentation, stress and strain, heat generation and temperature field of fiber fabric. The analysis results are in good agreement with the experimental results.     

TopPixelLoss:类别不均衡的遥感影像语义分割损失函数

针对遥感影像中类别不均衡的小目标分割效果不理想的问题，提出了一种类别不均衡小目标二分类分割的损失函数——TopPixelLoss损失函数。首先计算出每个像素的交叉熵，然后将所有像素的交叉熵按从大到小进行排序，随后确定一个K值作为阈值，筛选出前K个交叉熵最大的像素，最后对于筛选出的K个像素交叉熵取平均，做为损失值。在ISPRS 提供的 Vaihingen 数据集上，使用PSPNet网络与普通交叉熵、FocalLoss、TopPixelLoss三种损失函数分别对车辆进行二分类分割试验。结果表明，不同的K值，使用TopPixelLoss损失函数的平均交并比（MIoU）、F1-score、准确度（ACC）都最高;当K值为5×104时效果最佳，MIoU、F1-score、ACC分别比FocalLoss提高了3.0%、5.0%、0.1%。TopPixelLoss损失函数是一种针对类别不均衡分割非常有效的损失函数     

航天器时态规划技术研究进展

结合航天器自主运行的迫切需求,阐述了航天器任务规划问题给智能规划技术带来的挑战,并重点分析了具有时间属性的规划方法研究必要性。给出航天器时态规划定义,分别总结了状态空间时态规划建模方法和基于时间线的时态规划建模方法,并给出时态规划知识模型关键元素定义。根据规划方法发展现状,归纳总结前向链、模型转换、规划空间规划和分层任务网络四种方法在时态规划技术方面的特点和研究进展,着重描述各种方法对规划中时间要素的处理。在对目前的航天器时态规划技术发展趋势总结分析基础上,给出了未来航天器时态规划技术的发展建议。     

期望状态序列导向的深空探测器规划修复方法

Aiming at the challenges caused by the persistence, concurrency and energy consumption of probe actions, a plan repair method of deep space probe based on the expected state sequence is proposed. In this method, the expected state sequence is formed of the expected effect of the unfinished action and the expected precondition of the unexecuted action in the pre designed plan, according to the execution status of the action. The expected state sequence is an ordered set of states with mixed logic and energy, providing subgoals for plan repair and also transforming the plan repair problem into the state transition path searching problem. During the search, the plan repair strategy with energy supply priority is proposed, which separates the logic repair from energy repair to reduce the difficulty of solving the problem. And this method enables the probe to recover from plan failure autonomously. Finally, the effectiveness and rationality of the proposed method are verified through simulation by taking the Mars Orbiter as an example.     

基于时标分解的弹性高超声速飞行器智能控制

考虑弹性高超声速飞行器纵向动力学模型，提出了一种基于时标分解的智能控制方法。考虑刚体状态和弹性模态具有不同的时标特性，采用奇异摄动理论进行快慢时标分解，将模型转换为刚体慢变子系统和弹性快变子系统。针对刚体子系统考虑动力学不确定，基于平行估计模型构造表征不确定逼近效果的预测误差，结合跟踪误差给出复合学习控制策略。针对弹性子系统设计自适应滑模控制稳定弹性模态。通过李雅普诺夫稳定性分析可证系统状态一致终值有界。仿真表明所提出的控制方法能够实现刚弹模态的稳定收敛，且具有更高的跟踪精度、更好的学习性能和更快的收敛速度。