2024-03-28T18:37:47Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/63862022-11-30T11:15:35Zcom_10259_6336com_10259_6335com_10259.4_106com_10259_2604com_10259_3830com_10259_5086col_10259_6337col_10259_3832
Comparative study of classification algorithms for quality assessment of resistance spot welding joints from preand post-welding inputs
Martín, Óscar
Ahedo García, Virginia
Santos Martín, José Ignacio
Galán Ordax, José Manuel
Resistance spot welding
Quality control
Welding parameters
Ultrasonic testing
Tree ensembles
Stacking
Welding
Acoustics
Classification algorithms
Electrodes
Steel
Boosting
Testing
Materiales
Ingeniería mecánica
Ensayos (Tecnología)
Materials
Mechanical engineering
Testing
Resistance spot welding (RSW) is a widespread manufacturing process in the automotive industry. There are different approaches for assessing the quality level of RSW joints. Multi-input-single-output methods, which take as inputs either the intrinsic parameters of the welding process or ultrasonic nondestructive testing variables, are commonly used. This work demonstrates that the combined use of both types of inputs can significantly improve the already competitive approach based exclusively on ultrasonic analyses. The use of stacking of tree ensemble models as classifiers dominates the classification results in terms of accuracy, F-measure and area under the receiver operating characteristic curve metrics. Through variable importance analyses, the results show that although the welding process parameters are less relevant than the ultrasonic testing variables, some of the former provide marginal information not fully captured by the latter.
This work was supported in part by the Spanish Ministry of Science, Innovation and Universities (Excellence Networks) under Grant HAR2017-90883-REDC and Grant RED2018-102518-T, and in part by the Junta de Castilla y León Consejería de Educación under Grant BDNS 425389. The work of Virginia Ahedo was supported by the European Social Fund.
2022-02-02T10:20:06Z
2022-02-02T10:20:06Z
2022-01
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://hdl.handle.net/10259/6386
10.1109/ACCESS.2022.3142515
2169-3536
eng
IEEE Access. 2022, V. 10, p. 6518-6527
https://doi.org/10.1109/ACCESS.2022.3142515
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/HAR2017-90883-REDC/ES/Simular el pasado para entender el comportamiento humano
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RED2018-102518-T/ES/SISTEMAS COMPLEJOS SOCIOTECNOLOGICOS
Atribución 4.0 Internacional
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
application/pdf
Institute of Electrical and Electronics Engineers (IEEE)
https://riubu.ubu.es/bitstream/10259/6386/4/Martin-ia_2022.pdf.jpg
Hispana
TEXT
http://creativecommons.org/licenses/by/4.0/
RIUBU. Repositorio Institucional de la Universidad de Burgos
http://hdl.handle.net/10259/6386