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Title: POD-based constrained sensor placement and field reconstruction from noisy wind measurements: A perturbation study

Abstract

Sensor placement at the extrema of Proper Orthogonal Decomposition (POD) is efficient and leads to accurate reconstruction of the wind field from a limited number of measure- ments. In this paper we extend this approach of sensor placement and take into account measurement errors and detect possible malfunctioning sensors. We use the 48 hourly spa- tial wind field simulation data sets simulated using the Weather Research an 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. It turns out that this strategy can also reduce the error of recon- struction from noise measurements. Also, by a cross-validation technique, we successfully locate the malfunctioning sensors.

Authors:
 [1];  [2];  [3]
  1. Worcester Polytechnic Institute, Worcester, MA (United States)
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  3. Purdue Univ., West Lafayette, IN (United States)
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1358522
Report Number(s):
PNNL-SA-114546
Journal ID: ISSN 2227-7390; KJ0401000; TRN: US1702305
Grant/Contract Number:  
AC05-76RL01830
Resource Type:
Accepted Manuscript
Journal Name:
Mathematics
Additional Journal Information:
Journal Volume: 4; Journal Issue: 2; Journal ID: ISSN 2227-7390
Publisher:
MDPI
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 97 MATHEMATICS AND COMPUTING; proper orthogonal decomposition; sensor placement; uncertainty; anomaly detection

Citation Formats

Zhang, Zhongqiang, Yang, Xiu, and Lin, Guang. POD-based constrained sensor placement and field reconstruction from noisy wind measurements: A perturbation study. United States: N. p., 2016. Web. doi:10.3390/math4020026.
Zhang, Zhongqiang, Yang, Xiu, & Lin, Guang. POD-based constrained sensor placement and field reconstruction from noisy wind measurements: A perturbation study. United States. doi:10.3390/math4020026.
Zhang, Zhongqiang, Yang, Xiu, and Lin, Guang. Thu . "POD-based constrained sensor placement and field reconstruction from noisy wind measurements: A perturbation study". United States. doi:10.3390/math4020026. https://www.osti.gov/servlets/purl/1358522.
@article{osti_1358522,
title = {POD-based constrained sensor placement and field reconstruction from noisy wind measurements: A perturbation study},
author = {Zhang, Zhongqiang and Yang, Xiu and Lin, Guang},
abstractNote = {Sensor placement at the extrema of Proper Orthogonal Decomposition (POD) is efficient and leads to accurate reconstruction of the wind field from a limited number of measure- ments. In this paper we extend this approach of sensor placement and take into account measurement errors and detect possible malfunctioning sensors. We use the 48 hourly spa- tial wind field simulation data sets simulated using the Weather Research an 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. It turns out that this strategy can also reduce the error of recon- struction from noise measurements. Also, by a cross-validation technique, we successfully locate the malfunctioning sensors.},
doi = {10.3390/math4020026},
journal = {Mathematics},
number = 2,
volume = 4,
place = {United States},
year = {2016},
month = {4}
}

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