Multi-layer contribution propagation analysis for fault diagnosis

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dc.contributor.authorTan, Ruomu
dc.contributor.authorCao, Yi
dc.date.accessioned2019-04-29T10:47:52Z
dc.date.available2019-04-29T10:47:52Z
dc.date.issued2018-09-27
dc.description.abstractThe recent development of feature extraction algorithms with multiple layers in machine learning and pattern recognition has inspired many applications in multivariate statistical process monitoring. In this work, two existing multilayer linear approaches in fault detection are reviewed and a new one with extra layer is proposed in analogy. To provide a general framework for fault diagnosis in succession, this work also proposes the contribution propagation analysis which extends the original definition of contribution of variables in multivariate statistical process monitoring. In fault diagnosis stage, the proposed contribution propagation analysis for multilayer linear feature extraction algorithms is compared with the fault diagnosis results of original contribution plots associated with single layer feature extraction approach. Plots of variable contributions obtained by the aforementioned approaches on the data sets collected from a simulated benchmark case study (Tennessee Eastman process) as well as an industrial scale multiphase flow facility are presented as a demonstration of the usage and performance of the contribution propagation analysis on multilayer linear algorithms.en_UK
dc.identifier.citationTan RM, Cao Y. Multi-layer contribution propagation analysis for fault diagnosis. International Journal of Automation and Computing, February 2019, Volume 16, Issue 1, pp. 40–51en_UK
dc.identifier.issn1476-8186
dc.identifier.urihttps://doi.org/10.1007/s11633-018-1142-y
dc.identifier.urihttp://dspace.lib.cranfield.ac.uk/handle/1826/14115
dc.language.isoenen_UK
dc.publisherSpringeren_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectProcess monitoringen_UK
dc.subjectfault detection and diagnosisen_UK
dc.subjectcontribution plotsen_UK
dc.subjectfeature extractionen_UK
dc.subjectmultivariate statisticsen_UK
dc.titleMulti-layer contribution propagation analysis for fault diagnosisen_UK
dc.typeArticleen_UK

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