Author: eloifigueiredo

02 APRIL 2022

45-min ambient vibration test in 20 s. This test intended to validate new sensing technologies. 56 people were standing on the bridge deck in order to introduce changes into the modal properties.

20 APRIL 2022

After three years in the making, the main conclusions of the Reconhecer Project were publicly disclosed with the presence of the Mayor of Barcelos, Mário Constantino, and two of its authors Eloi Figueiredo and Luís Oliveira Santos (Câmara Municipal de Barcelos).

27 MARCH 2022

Based on experience over 30 years in bridge monitoring, Eloi Figueiredo and James Brownjohn just had an article published on the last three decades of statistical pattern recognition paradigm for structural health monitoring of bridges.

24 MARCH 2022

This is another step to move forward the integration of physics-based modeling into SHM of bridges, and  to support the unsupervised learning strategies of machine learning algorithms for damage detection under operational and environmental variability.

Bud, M.; Moldovan, I.; Radu, L.; Nedelcu, M.; Figueiredo, E. (2022). Reliability of probabilistic numerical data for training machine learning algorithms to detect damage in bridges. Structural Control and Health Monitoring. e2950. DOI: 10.1002/stc.2950.

24 MARCH 2022

An attempt to exploit dynamic point clouds for structural dynamics and estimating 3D vibration modes.

Silva, M.; Green, A.; Morales, J.; Meyerhofer, P.; Yang, Y.; Figueiredo, E.; Costa, J.; Mascarenas, D. (2022). 3D Structural Vibration Identification from Dynamic Point Clouds. Mechanical Systems and Signal Processing, 166, 108352.