Reciprocating compressor prognostics of an instantaneous failure mode utilising temperature only measurements

dc.cclicenceCC-BY-NC-NDen
dc.contributor.authorLoukopoulosa, Panagiotisen
dc.contributor.authorZolkiewski, Georgeen
dc.contributor.authorBennett, Ianen
dc.contributor.authorSampath, Sureshen
dc.contributor.authorPilidisa, Periclesen
dc.contributor.authorDuan, Fangen
dc.contributor.authorSattar, Tariqen
dc.contributor.authorMba, Daviden
dc.date.acceptance2017-12-04en
dc.date.accessioned2017-12-18T10:25:40Z
dc.date.available2017-12-18T10:25:40Z
dc.date.issued2017-12-14
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.en
dc.description.abstractReciprocating compressors are critical components in the oil and gas sector, though their maintenance cost is known to be relatively high. Compressor valves are the weakest component, being the most frequent failure mode, accounting for almost half the maintenance cost. One of the major targets in industry is minimisation of downtime and cost, while maximising availability and safety of a machine, with maintenance considered a key aspect in achieving this objective. The concept of Condition Based Maintenance and Prognostics and Health Management (CBM/PHM) which is founded on the diagnostics and prognostics principles, is a step towards this direction as it offers a proactive means for scheduling maintenance. Despite the fact that diagnostics is an established area for reciprocating compressors, to date there is limited information in the open literature regarding prognostics, especially given the nature of failures can be instantaneous. This work presents an analysis of prognostic performance of several methods (multiple linear regression, polynomial regression, K-Nearest Neighbours Regression (KNNR)), in relation to their accuracy and variability, using actual temperature only valve failure data, an instantaneous failure mode, from an operating industrial compressor. Furthermore, a variation for Remaining Useful Life (RUL) estimation based on KNNR, along with an ensemble technique merging the results of all aforementioned methods are proposed. Prior to analysis, principal components analysis and statistical process control were employed to create T^2 and Q metrics, which were proposed to be used as health indicators reflecting degradation process of the valve failure mode and are proposed to be used for direct RUL estimation for the first time. Results demonstrated that even when RUL is relatively short due to instantaneous nature of failure mode, it is feasible to perform good RUL estimates using the proposed techniques.en
dc.funderN/Aen
dc.identifier.citationLoukopoulosa, P. et al. (2017) Reciprocating compressor prognostics of an instantaneous failure mode utilising temperature only measurements. Applied Acoustics, 147, pp. 77-86en
dc.identifier.doihttps://doi.org/10.1016/j.apacoust.2017.12.003
dc.identifier.urihttp://hdl.handle.net/2086/15012
dc.language.isoenen
dc.peerreviewedYesen
dc.projectidN/Aen
dc.publisherElsevieren
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en
dc.subjectremaining useful lifeen
dc.subjectprognosticsen
dc.subjectmultiple linear regressionen
dc.subjectK-nearest neighboursen
dc.titleReciprocating compressor prognostics of an instantaneous failure mode utilising temperature only measurementsen
dc.typeArticleen

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