|
|
|
|
|
Diego Mellado, Carolina Saavedra, Steren Chabert, Romina Torres and Rodrigo Salas
Deep learning models are part of the family of artificial neural networks and, as such, they suffer catastrophic interference when learning sequentially. In addition, the greater number of these models have a rigid architecture which prevents the increme...
ver más
|
|
|
|
|
|
|
|
|
|
|
Haobin Wen, Long Zhang and Jyoti K. Sinha
On top of the condition-based maintenance (CBM) practice for rotating machinery, the robust estimation of remaining useful life (RUL) for rolling-element bearings (REB) is of particular interest. The failure of a single bearing often results in secondary...
ver más
|
|
|
|
|
|
|
|
|
|
|
Nan Qiao, Yun-Ling Duan, Xiao-Meng Shi, Xue-Fei Wei and Jin-Ming Feng
The excavation of large-scale underground projects produces a large amount of rubble waste material that is temporarily deposited near the project site, which forms a large-scale waste rockfill artificial slope. The slope has a granular structure, thus, ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Marilyne Philibert, Constantinos Soutis, Matthieu Gresil and Kui Yao
Low velocity impact induces barely visible damage in the form of matrix cracking or delamination that can grow under hydro-thermo-mechanical loading and possibly lead to catastrophic failure if not detected at an early stage. A network of piezoelectric t...
ver más
|
|
|
|
|
|
|
|
|
|
|
Marilyne Philibert, Constantinos Soutis, Matthieu Gresil and Kui Yao
Low velocity impact induces barely visible damage in the form of matrix cracking or delamination that can grow under hydro-thermo-mechanical loading and possibly lead to catastrophic failure if not detected at an early stage. A network of piezoelectric t...
ver más
|
|
|
|
|
|