Monitoring a bolted vibrating structure using multiple acoustic emission sensors : A benchmark
Résumé
The data set presented in this work, called ORION-AE, is made of
raw AE data streams collected by three different AE sensors and a
laser vibrometer during five campaigns of measurements by varying
the tightening conditions of two bolted plates submitted to
harmonic vibration tests. With seven different operating
conditions, this data set was designed to challenge supervised and
unsupervised machine/deep learning as well as signal processing
methods which are developed for material characterization or
Structural Health Monitoring (SHM). One motivation of this work was
to create a common benchmark for comparing data-driven methods
dedicated to AE data interpretation. The data set is made of time-series collected during an experiment
designed to reproduce the loosening phenomenon observed in
aeronautics, automotive or civil engineering structures where parts
are assembled together by means of bolted joints. Monitoring
loosening in jointed structures during operation remains
challenging because contact and friction in bolted joints induce a
nonlinear stochastic behavior.
Domaines
Mécanique [physics]
Origine : Fichiers produits par l'(les) auteur(s)