Emisión Acústica y Redes Neuronales para Modelado y Caracterización del Proceso de Soldadura por Fricción Agitación

  1. Emilio Jiménez Macías 1
  2. Angel Sánchez Roca 2
  3. Hipólito Carvajal Fals 2
  4. Julio Blanco Fernández 1
  5. Juan C. Sáenz-Diez Muro 1
  1. 1 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

  2. 2 Universidad de Oriente
    info

    Universidad de Oriente

    Cumaná, Venezuela

    ROR https://ror.org/03xygw105

Journal:
Revista iberoamericana de automática e informática industrial ( RIAI )

ISSN: 1697-7920

Year of publication: 2013

Volume: 10

Issue: 4

Pages: 434-440

Type: Article

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DOI: 10.10167J.RIAI.2013.09.003 DIALNET GOOGLE SCHOLAR lock_openOpen access editor

More publications in: Revista iberoamericana de automática e informática industrial ( RIAI )

Related Projects

Soldadura por fricción-agitación de materiales disimilares. Caracterización por técnicas de Emisión Acústica e Inteligencia Artificial.

2012/00012/001

Abstract

This paper presents an analysis of the correlation between acoustic emission (AE) signals and the main parameters of friction stir welding (FSW) process, based on artificial neural networks (ANN). The AE signals have been acquired by the data acquisition instrument NI USB-9234, applied during the welding process carried out on plates of 3mm thick of aluminium AA1050 alloy. Statistical and temporal parameters of discomposed EA signals using Wavelet Transform (WT) have been used as input of the ANN, while the outputs of model include the welding parameters: tool rotation speed and travel speed, as well as the tool profile. A multilayer feed-forward ANN has been selected and trained, using different algorithms and network architectures. The parameters provided by the ANN constitute the model and the characterization of the FSW process; finally an analysis of the comparison between the measured and the calculated data is presented, validating the results. The model obtained can be used to develop the automatic control of the parameters of the FSW process, based on vibro-acoustic signals, which constitutes the following step in this research line.

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