Samueli Civil and Environmental Engineering, University of California Los Angeles, Los Angeles, CA 90095, USA.
Civil and Environmental Engineering, Rice University, Houston, TX 77005, USA.
Sensors (Basel). 2022 Dec 29;23(1):384. doi: 10.3390/s23010384.
In civil, mechanical, and aerospace structures, full-field measurement has become necessary to estimate the precise location of precise damage and controlling purposes. Conventional full-field sensing requires dense installation of contact-based sensors, which is uneconomical and mostly impractical in a real-life scenario. Recent developments in computer vision-based measurement instruments have the ability to measure full-field responses, but implementation for long-term sensing could be impractical and sometimes uneconomical. To circumvent this issue, in this paper, we propose a technique to accurately estimate the full-field responses of the structural system from a few contact/non-contact sensors randomly placed on the system. We adopt the Compressive Sensing technique in the spatial domain to estimate the full-field spatial vibration profile from the few actual sensors placed on the structure for a particular time instant, and executing this procedure repeatedly for all the temporal instances will result in real-time estimation of full-field response. The basis function in the Compressive Sensing framework is obtained from the closed-form solution of the generalized partial differential equation of the system; hence, partial knowledge of the system/model dynamics is needed, which makes this framework physics-guided. The accuracy of reconstruction in the proposed full-field sensing method demonstrates significant potential in the domain of health monitoring and control of civil, mechanical, and aerospace engineering systems.
在土木、机械和航空航天结构中，为了精确估计精确损伤的位置和控制目的，全场测量变得非常必要。传统的全场传感需要密集安装基于接触的传感器，这在实际场景中既不经济也不切实际。基于计算机视觉的测量仪器的最新发展具有测量全场响应的能力，但长期传感的实施可能不切实际且有时不经济。为了解决这个问题，在本文中，我们提出了一种从随机放置在系统上的少数接触/非接触传感器准确估计结构系统全场响应的技术。我们在空间域中采用压缩感知技术，从放置在结构上的少数实际传感器在特定时间点估计全场空间振动轮廓，并对所有时间实例重复执行此过程，将实时估计全场响应。压缩感知框架中的基函数是从系统的广义偏微分方程的闭式解中获得的；因此，需要系统/模型动力学的部分知识，这使得该框架具有物理引导性。所提出的全场传感方法的重建准确性在土木、机械和航空航天工程系统的健康监测和控制领域具有显著的潜力。
