Canonical variate analysis for performance degradation under faulty conditions

Show simple item record Ruiz Cárcel, Cristóbal Lao, Liyun Cao, Yi Mba, David 2016-07-26T14:47:49Z 2016-07-26T14:47:49Z 2016-06-01
dc.identifier.citation C. Ruiz-Cárcel, L. Lao, Y. Cao, D. Mba, Canonical variate analysis for performance degradation under faulty conditions, Control Engineering Practice, Volume 54, September 2016, pp70-80 en_UK
dc.identifier.issn 0967-0661
dc.description.abstract Condition monitoring of industrial processes can minimize maintenance and operating costs while increasing the process safety and enhancing the quality of the product. In order to achieve these goals it is necessary not only to detect and diagnose process faults, but also to react to them by scheduling the maintenance and production according to the condition of the process. The objective of this investigation is to test the capabilities of canonical variate analysis (CVA) to estimate performance degradation and predict the behavior of a system affected by faults. Process data was acquired from a large-scale experimental multiphase flow facility operated under changing operational conditions where process faults were seeded. The results suggest that CVA can be used effectively to evaluate how faults affect the process variables in comparison to normal operation. The method also predicted future process behavior after the appearance of faults, modeling the system using data collected during the early stages of degradation. en_UK
dc.language.iso en en_UK
dc.publisher Elsevier en_UK
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.subject Fault detection en_UK
dc.subject Fault diagnosis en_UK
dc.subject System identification en_UK
dc.subject Multivariate analysis en_UK
dc.subject Canonical variate en_UK
dc.subject Experimental study en_UK
dc.title Canonical variate analysis for performance degradation under faulty conditions en_UK
dc.type Article en_UK

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