Fault Classification Using Pseudomodal Energies and Probabilistic Neural Networks.

This paper introduces a new fault identification method that uses pseudomodal energies to train probabilistic neural networks (PNNs). The proposed procedure is tested on a population of 20 cylindrical shells and its performance is compared to the procedure which uses modal properties to train probabilistic neural networks. The PNNs trained using pseudomodal energies provide better classification of faults than the PNNs trained using the conventional modal properties. [ABSTRACT FROM AUTHOR]