RT info:eu-repo/semantics/article
T1 Assessment of resistance spot welding quality based on ultrasonictesting and tree-based techniques
A1 Martín, Óscar
A1 Pereda, María
A1 Santos Martín, José Ignacio
A1 Galán Ordax, José Manuel
K1 Resistance spot welding
K1 Non-destructive ultrasonic testing
K1 Random forest technique
K1 CART trees
K1 Classification
K1 Quality control
K1 Empresas-Gestión
K1 Industrial management
AB Classification and regression tree (CART) and random forest techniques were proposed as pattern recognition tools for classification of ultrasonic oscillograms of resistance spot welding (RSW) joints. The results showed that CART models produced an acceptable error rate with high interpretability. These features may be used to understand and control the decision processes, instruct other human operators, compare margins of safety or modify them depending on the criticality of the industrial process. Compared with CART trees, random forests reduced the error rate at the cost of decreasing decision interpretability. The use of the agreement of the forest was proposed as a measure to reduce the workload of human operators, who would only have to focus on the analysis of ultrasonic oscillograms that are difficult to interpret
PB Elsevier
SN 0924-0136
YR 2014
FD 2014-11
LK http://hdl.handle.net/10259/3837
UL http://hdl.handle.net/10259/3837
LA eng
NO MICINN (Project CSD2010‐00034, SimulPast CONSOLIDER‐INGENIO 2010), Junta de Castilla y León (GREX251‐2009)
DS Repositorio Institucional de la Universidad de Burgos
RD 26-abr-2024