论文标题
部分可观测时空混沌系统的无模型预测
Real-time rapid leakage estimation for deep space habitats using exponentially-weighted adaptively-refined search
论文作者
论文摘要
与太空相关的研发活动的最新加速增长使得对长期外星栖息地的近期需求明显。这样的栖息地必须在极端环境中引起的连续破坏性条件下运行,例如流星的影响,极端温度波动,银河宇宙射线,破坏性灰尘和地震事件。栖息地失去空气或大气泄漏会带来要求适当关注的安全挑战。这种泄漏可能是由微度素的影响,裂纹生长,螺栓/铆钉松动和密封劣化引起的。在本文中,深空栖息地中的泄漏估计是一个反问题。为大气泄漏制定了基于正压的动力学模型。实验是在模拟不同泄漏场景并测量相应压力值的小型压力室上进行的。为实时泄漏估计的反问题开发并验证了一种指数加权的自适应搜索(EWAR)算法。证明所提出的方法可以准确地实现对常数泄漏的实时估计和跟踪。
The recent accelerated growth in space-related research and development activities makes the near-term need for long-term extraterrestrial habitats evident. Such habitats must operate under continuous disruptive conditions arising from extreme environments like meteoroid impacts, extreme temperature fluctuations, galactic cosmic rays, destructive dust, and seismic events. Loss of air or atmospheric leakage from a habitat poses safety challenges that demand proper attention. Such leakage may arise from micro-meteoroid impacts, crack growth, bolt/rivet loosening, and seal deterioration. In this paper, leakage estimation in deep space habitats is posed as an inverse problem. A forward pressure-based dynamical model is formulated for atmospheric leakage. Experiments are performed on a small-scaled pressure chamber where different leakage scenarios are emulated and corresponding pressure values are measured. An exponentially-weighted adaptively-refined search (EWARS) algorithm is developed and validated for the inverse problem of real-time leakage estimation. It is demonstrated that the proposed methodology can achieve real-time estimation and tracking of constant and variable leaks with accuracy.