RT Journal Article
T1 Instance and semantic segmentation of point clouds of large metallic truss bridges
A1 Lamas Novoa, Daniel
A1 Justo Dominguez, Andrés
A1 Soilán Rodríguez, Mario
A1 Cabaleiro Núñez, Manuel
A1 Riveiro Rodríguez, Belén
K1 3305.06 Ingeniería Civil
K1 33 Ciencias Tecnológicas
AB Several methods have been developed for the semantic segmentation of reinforced concrete bridges, however, there is a gap for truss bridges. Therefore, in this study a state-of-the-art methodology for the instance and semantic segmentation of point clouds of truss bridges for modelling purposes is presented, which, to the best of the authors' knowledge, is the first such methodology. This algorithm segments each truss element and classifies them as a chord, diagonal, vertical post, interior lateral brace, bottom lateral brace, or strut. The algorithm consists of a sequence of methods, including principal component analysis or clustering, that analyse each point and its neighbours in the point cloud. Case studies show that by adjusting only six manually measured parameters, the algorithm can automatically segment a truss bridge point cloud.
PB Automation in Construction
SN 09265805
YR 2023
FD 2023-07
LK http://hdl.handle.net/11093/4752
UL http://hdl.handle.net/11093/4752
LA eng
NO Automation in Construction, 151, 104865 (2023)
NO Agencia Estatal de Investigación | Ref. PID2021-124236OB-C3
DS Investigo
RD 14-ene-2025