POD-Based Constrained Sensor Placement and Field Reconstruction from Noisy Wind Measurements: A Perturbation Study

Mathematics

Xiu Yang¹  Zhongqiang Zhang²  Guang Lin³ 

[1] Advanced Computing, Mathematics and Data Division, Physical and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA 99352, USA;Department of Mathematical Sciences, Worcester Polytechnic Institute, Worcester, MA 01609, USA;;Department of Mathematics &

关键词: proper orthogonal decomposition;    sensor placement;    uncertainty;    anomaly detection;   

DOI  :  10.3390/math4020026

来源: DOAJ

【 摘 要 】

It is shown in literature that sensor placement at the extrema of Proper Orthogonal Decomposition (POD) modes is efficient and leads to accurate reconstruction of the field of quantity of interest (velocity, pressure, salinity, etc.) from a limited number of measurements in the oceanography study. In this paper, we extend this approach of sensor placement and take into account measurement errors and detect possible malfunctioning sensors. We use the 24 hourly spatial wind field simulation data sets simulated using the Weather Research and Forecasting (WRF) model applied to the Maine Bay to evaluate the performances of our methods. Specifically, we use an exclusion disk strategy to distribute sensors when the extrema of POD modes are close. We demonstrate that this strategy can improve the accuracy of the reconstruction of the velocity field. It is also capable of reducing the standard deviation of the reconstruction from noisy measurements. Moreover, by a cross-validation technique, we successfully locate the malfunctioning sensors.

【 授权许可】

Unknown