Higham, J.E., Brevis, W. and Keylock, C.J. (2016) A rapid non-iterative proper orthogonal decomposition based outlier detection and correction for PIV data. Measurement Science and Technology, 27 (12). p. 125303. ISSN 0957-0233
Abstract
The present work proposes a novel method of detection and estimation of outliers in particle image velocimetry measurements by the modification of the temporal coefficients associated with a proper orthogonal decomposition of an experimental time series. Using synthetic outliers applied to two sequences of vector fields, the method is benchmarked against stateof-the-art approaches recently proposed to remove the influence of outliers. Compared with these methods, the proposed approach offers an increase in accuracy and robustness for the detection of outliers and comparable accuracy for their estimation.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2016 IOP Publishing Ltd. Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. |
Keywords: | outlier detection; proper orthogonal decomposition; particle image velocimetry; image processing; experimental fluid mechanics |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Civil and Structural Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 28 Nov 2016 15:16 |
Last Modified: | 28 Nov 2016 15:16 |
Published Version: | http://doi.org/10.1088/0957-0233/27/12/125303 |
Status: | Published |
Publisher: | IOP Publishing |
Refereed: | Yes |
Identification Number: | 10.1088/0957-0233/27/12/125303 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:108404 |