Skip to main content
padlock icon - secure page this page is secure

Technical diagnostics and monitoring based on capabilities of wavelet transforms and relaxation neural networks

Buy Article:

$22.00 + tax (Refund Policy)

A technology for technical diagnostics based on the multivariate analysis of system status is under consideration. It combines the capabilities of wavelet transforms and relaxation neural networks. Important practical advantages of the proposed technique include the capability to recognise damage using only a few training patterns and the possibility to apply the method for non-stationary input diagnostic signals. Recognition of damage in dynamic suppressors attached to an aircraft panel is presented as an example.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Keywords: Technical diagnostics; aircraft damage; non-stationary signals; relaxation neural networks; wavelet transforms

Document Type: Research Article

Affiliations: Russian Aviation Co, Research Group, 33/50 Klara Tsetkin Street, 125130 Moscow, Russia and the Moscow State University of Psychology and Education, 29 Sretenka Street, 127051 Moscow, Russia. rusavaha.ru

Publication date: March 1, 2008

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more