Dealing with missing data for prognostic purposes

Conference paper


Loukopoulos, P, Sampath, S, Pilidis, P, Zolkiewski, G, Bennett, I, Duan, F and Mba, D (2016). Dealing with missing data for prognostic purposes. Prognostics and System Health Management Conference. Chengdu, China 19 - 21 Oct 2016 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/PHM.2016.7819934
AuthorsLoukopoulos, P, Sampath, S, Pilidis, P, Zolkiewski, G, Bennett, I, Duan, F and Mba, D
TypeConference paper
Abstract

© 2016 IEEE. Centrifugal compressors are considered one of the most critical components in oil industry, making the minimisation of their downtime and the maximisation of their availability a major target. Maintenance is thought to be a key aspect towards achieving this goal, leading to various maintenance schemes being proposed over the years. Condition based maintenance and prognostics and health management (CBM/PHM), which is relying on the concepts of diagnostics and prognostics, has been gaining ground over the last years due to its ability of being able to plan the maintenance schedule in advance. The successful application of this policy is heavily dependent on the quality of data used and a major issue affecting it, is that of missing data. Missing data's presence may compromise the information contained within a set, thus having a significant effect on the conclusions that can be drawn from the data, as there might be bias or misleading results. Consequently, it is important to address this matter. A number of methodologies to recover the data, called imputation techniques, have been proposed. This paper reviews the most widely used techniques and presents a case study with the use of actual industrial centrifugal compressor data, in order to identify the most suitable ones.

Year2016
JournalProceedings of 2016 Prognostics and System Health Management Conference, PHM-Chengdu 2016
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Digital Object Identifier (DOI)https://doi.org/10.1109/PHM.2016.7819934
Accepted author manuscript
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Publication dates
Print19 Oct 2016
Publication process dates
Deposited05 May 2018
Accepted19 Sep 2016
ISBN9781509027781
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