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- W3184577826 abstract "Statistical subspace-based change detection residuals have been developed to infer a change in the eigenstructure of linear systems. Their statistical properties have been properly evaluated in the case of a known reference and constant noise properties. Previous residuals have favored the family of null space-based approaches, whereas the possibility of using other metrics such as the Mahalanobis distance has been omitted. This paper investigates the development and study of such a norm under the premise of a varying noise covariance. Its statistical properties have been studied and tested on a numerical example of a mechanical system." @default.
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- W3184577826 date "2021-01-01" @default.
- W3184577826 modified "2023-10-14" @default.
- W3184577826 title "Hankel matrix-based Mahalanobis distance for fault detection robust towards changes in process noise covariance" @default.
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- W3184577826 doi "https://doi.org/10.1016/j.ifacol.2021.08.337" @default.
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