Operational modal analysis using asynchronous data for frequencies and mode shapes identification

Farouk Omar Frigui (1, 2) , Jean-Pierre Faye (1) , Carmen Martin (1) , Olivier Dalverny (1) , François Pérès (1) , Sébastien Judenherc (2)

1 LGP - Laboratoire Génie de Production
2 Stanéo (FRANCE)

The monitoring and the assessment of structures (SHM), in order to ensure human and material safety, is a very important issue in civil engineering. The mainly used SHM techniques are based on the study of the vibratory behavior of the structure by accelerometric or velocimetric measurement. Using operational modal analysis techniques (OMA), modal identification involving natural frequencies and mode shapes can be carried out. In order to do so, the response of the structure to ambient excitations is measured using several sensors. Conventional modal identification approaches use synchronous data, in which different channels are sampled at the same sampling rate and the same time window by means of long cables, GPS and real time clock. Modal analysis test can be conducted more flexibly if it could be performed even if the measured data are not synchronised. This research investigates the impact of asynchronous data on the identification of eigenfrequencies and mode shapes using operational modal analysis methods, namely the Stochastic Subspace Identification (SSI) and the Frequency Domain Decomposition (FDD), and its correction.

Mots clés: Structural Health Monitoring (SHM); Asynchronous data; Operational Modal Analysis (OMA)

Domaines: Mécanique des matériaux [physics.class-ph]

Farouk Omar Frigui, Jean-Pierre Faye, Carmen Martin, Olivier Dalverny, François Pérès, et al.. Operational modal analysis using asynchronous data for frequencies and mode shapes identification. 8th international Conference on structural Analysis of Advanced Materials, Aug 2018, Tarbes, France. pp.1-4. ⟨hal-02359880⟩