ArXiv Preprint
There have been recent efforts to move to population-based structural health
monitoring (PBSHM) systems. One area of PBSHM which has been recognised for
potential development is the use of multi-task learning (MTL); algorithms which
differ from traditional independent learning algorithms. Presented here is the
use of the MTL, ''Joint Feature Selection with LASSO'', to provide automatic
feature selection for a structural dataset. The classification task is to
differentiate between the port and starboard side of a tailplane, for samples
from two aircraft of the same model. The independent learner produced perfect
F1 scores but had poor engineering insight; whereas the MTL results were
interpretable, highlighting structural differences as opposed to differences in
experimental set-up.
S. C. Bee, E. Papatheou, M Haywood-Alexander, R. S. Mills, L. A. Bull, K. Worden, N. Dervilis
2023-03-08
