Latent variable models for simultaneous EOV identification and removal in population-based SHM
The robust treatment of environmental and operational variability (EOV) is an open challenge in population-based structural health monitoring (PBSHM). The difficulty is compounded in the case that the EOV signals are unmeasured. A common approach in conventional SHM is to apply \emph{projection-based} methods that discard subspaces of healthy feature data, reasoning that the EOV signal dominates the variance of the measured features. However, a common pitfall of projection-based approaches is that when damage acts close to the same variance-dominant direction, damage sensitivity is removed along with the EOV. An alternative identifying assumption for the removal of particular unmeasured E...
| Authors | M. D. Champneys, M. R. Jones, A. J. Hughes et al. |
|---|---|
| Primary category | eess.SP |
| Published | 12 August 2026 |
| Last updated at source | 12 August 2026 |
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