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A Quantile Dependency Model for Predicting Optimal Centrifugal Pump Operating Strategies

Authors :
Bruce Stephen
Blair Brown
Andrew Young
Andrew Duncan
Henrique Helfer-Hoeltgebaum
Graeme West
Craig Michie
Stephen D. J. McArthur
Source :
Machines, Vol 10, Iss 7, p 557 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

Used in many industrial applications, centrifugal pumps have optimal operating criteria specified at design. These criteria may not be precisely adhered to during operation which will ultimately reduce the life of the asset. Operators would therefore benefit from anticipating how often the design point is deviated from and hence how much asset degradation results. For centrifugal pumps, a novel set of covariates were proposed in this paper which formally partition observed operating zones with an Empirical Bivariate Quantile Partitioned distribution. This captured the dependency relation between operating parameters across plant configurations to predict the component wear that results from particular settings. The effectiveness of this was demonstrated through an operational case study in civil nuclear generation feedwater pumps where corroboration with bearing movements provides an indicator of plant wear. Such a technique is envisaged to inform operators of optimal plant configuration from multiple possibilities in advance of undertaking them.

Details

Language :
English
ISSN :
20751702
Volume :
10
Issue :
7
Database :
Directory of Open Access Journals
Journal :
Machines
Publication Type :
Academic Journal
Accession number :
edsdoj.4d8d6cdc25c44adfa39a78e85776d055
Document Type :
article
Full Text :
https://doi.org/10.3390/machines10070557