Application of Modal Analysis and Neural Networks in Detection of Damages in Structure and Parts 942373
The use of modal analysis and neural networks is proposed to detect damages in parts and structures. Comparing the natural frequencies of a test structure with the ones of a non-damaged structure, a neural net, using its capabilities in recognize standards, can deliver the location and extension of the probable damages.
Two examples are presented. At the first one, a notch is located on a free-free beam. The second example deals with a truss-like tower where the damage is a loss of stiffness in some structural members.
The results obtained point as very promising the use of neural network as computational tool in nondestructive testing.
Citation: Alves, M. and Kaminski, P., "Application of Modal Analysis and Neural Networks in Detection of Damages in Structure and Parts," SAE Technical Paper 942373, 1994, https://doi.org/10.4271/942373. Download Citation
Author(s):
Marcelo A. Leal Alves, Paulo C. Kaminski
Affiliated:
ESCOLA POLITÉCNICA - USP
Pages: 10
Event:
SAE Brasil '94
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Neural networks
Parts
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