Modeling of multiple characteristics of an arc weld joint

Author:

Nele L.,Sarno E.,Keshari A.

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Software,Control and Systems Engineering

Reference13 articles.

1. Keshari A, Segreto T, Teti R (2010) Classification of sensor signal features for Ti alloy turning process optimization, 7th CIRP International Conference on Intelligent Computation in Manufacturing Engineering, CIRP ICME’10, ISBN: 978-88-95028-65-1

2. Leone C, Caprino G, Deiorio I (2006) Interpreting acoustic emission signals by artificial neural networks to predict the residual strength of pre-fatigued GFRP laminates. Compos Sci Technol 66(2):233–239

3. Eguchi K, Yamane S, Sugi H, Kubota T, Oshima K (1999) Application of neural network to arc sensor. Sci Technol Weld Join 4(6):327–334

4. Wu CS, Polte T, Rehfeldt D (2001) A fuzzy logic system for process monitoring and quality evaluation in GMAW, Welding Research. Suppl Weld J 80(2):33–38

5. Wang B, Chen SB, Wang JJ (2005) Rough set based knowledge modeling for the aluminium alloy pulsed GTAW process. Int J Adv Manuf Technol 25:902–908

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