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Article Dans Une Revue Data Année : 2022

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.
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Dates et versions

hal-03700844 , version 1 (21-06-2022)

Identifiants

  • HAL Id : hal-03700844 , version 1

Citer

Emmanuel Ramasso, Benoît Verdin, Gael Chevallier. Monitoring a bolted vibrating structure using multiple acoustic emission sensors : A benchmark. Data, 2022, 7 (3), pp.14. ⟨hal-03700844⟩
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