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Neural network AE source location apart from structure size and material

  1. 1. 0363592 - UT-L 2012 RIV US eng J - Journal Article
    Chlada, Milan - Převorovský, Zdeněk - Blaháček, Michal
    Neural network AE source location apart from structure size and material.
    Journal of Acoustic Emission. Roč. 28, - (2010), s. 99-107 ISSN 0730-0050.
    [European Conference on Acoustic Emission Testing 2010 /29./. Vídeň, 08.09.2010-10.09.2010]
    R&D Projects: GA ČR(CZ) GAP104/10/1430; GA MPO(CZ) FR-TI1/274
    Institutional research plan: CEZ:AV0Z20760514
    Keywords : AE source location * artificial neural network * arrival time profiles
    Subject RIV: BI - Acoustics

    AE localization procedures using artificial neural networks (ANN) represent extremely effective alternative to classical triangulation methods. Nevertheless, their application always requires full-scale, time consuming ANN training on each specific structure. Disadvantage of particularly trained ANN algorithm is in its non-transferability to any other object. A new ANN-based AE source location approach is proposed in this paper to overcome such limitation. The method replaces standard arrival time differences at the ANN inputs by so called signal arrival time profiles, independent on material and scale changes. The ANN training can be also performed theoretically on geometrical models (i.e. without any experimental errors) and learned ANN is then applied on real structures with different dimensions and materials. Such approach enables considerable extension of ANN application possibilities. The use of new AE source location method is illustrated on experimental data obtained during aircraft structure part testing.
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