Load-Identification Method for Flexible Multiple Corrugated Skin Using Spectra Features of FBGs

Flexible corrugated skins are ideal structures for morphing wings, and the associated load measurements of great significance in structural health monitoring. This paper proposes a novel load-identification method flexible based on improved Fisher discrimination dictionary learning (FDDL). Several fiber Bragg grating sensors pasted skin to monitor multiple crests. The loads different crests cause nonuniform strain fields, these discriminative spectra recorded used as training data. proposed involves load-positioning load-size identification. In load-size-identification stage, classifier is trained every crest. An interleaved block grouping samples introduced enhance dictionaries, two-resolution improve performance resolution labels. adjustable weight FDDL classification scheme optimize contribution from classifiers. With method, individual eight can be identified by two sensors. positioning accuracy 100%, mean error identification 0.2106 N, which sufficiently precise