Real-time load determination for in-service components using photostress analysis and artificial neural networks in tandem

Authors: Noroozi, S., Amali, R. and Vinney, J.

Volume: 2

Pages: 841-845

Abstract:

In this study, an Artificial Neural Network (ANN) has been trained to determine the applied loads on a mechanical component using Photoelastic fringe orders. Two different beam configurations were used to demonstrate this idea, one beam was subjected to pure bending and the other subjected to four non-symmetrical and random loads. These beams were fabricated from birefringent material. In all cases the inverse method approach accurately predicted the loading based on the fringe order.

Source: Scopus

Real-Time Load Determination for In-Service Components Using Photostress Analysis and Artificial Neural Networks in Tandem

Authors: Noroozi, S., Amali, R. and Vinney, J.

Pages: 841-845

Publisher: CSREA Press

Place of Publication: Las Vegas

Source: Manual

Preferred by: John Vinney and Siamak Noroozi

Real-Time Load Determination for In-Service Components Using Photostress Analysis and Artificial Neural Networks in Tandem.

Authors: Noroozi, S., Amali, R. and Vinney, J.

Editors: Arabnia, H.R., Joshua, R. and Mun, Y.

Pages: 841-845

Publisher: CSREA Press

http://www.informatik.uni-trier.de/~ley/db/conf/icai/icai2003-2.html

Source: DBLP