A rapid non-iterative proper orthogonal decomposition based outlier detection and correction for PIV data

Higham, JE ORCID: 0000-0001-7577-0913, Brevis, W and Keylock, CJ (2016) A rapid non-iterative proper orthogonal decomposition based outlier detection and correction for PIV data. Measurement Science and Technology, 27 (12). p. 125303.

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Official URL: https://iopscience.iop.org/article/10.1088/0957-02...

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 state-of-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.

Item Type:	Article
Uncontrolled Keywords:	outlier detection, proper orthogonal decomposition, particle image velocimetry, image processing, experimental fluid mechanics
Depositing User:	Symplectic Admin
Date Deposited:	24 Jul 2020 07:47
Last Modified:	18 Jan 2023 23:39
DOI:	10.1088/0957-0233/27/12/125303
Open Access URL:	http://dx.doi.org/10.1088/0957-0233/27/12/125303
Related URLs:	Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3095034