Title :
Technology of intelligent diagnostics based on Volterra kernels moments
Author :
Oleksandr Fomin;Andrew Medvedev;Vitaliy Pavlenko
Author_Institution :
Odessa National Polytechnic University, Shevchenko av. 1, Odessa, Ukraine
Abstract :
The paper presents an informational technology for improving the reliability of nonlinear dynamic objects fault diagnosing using model-based diagnostics method of nonparametric identification. Diagnostic models build on the base of Volterra kernels moments. The efficiency of the proposed diagnostic models analyzes on an nonlinear dynamic objects simulation model.
Keywords :
"Kernel","Nonlinear dynamical systems","Computational modeling","Mathematical model","Artificial intelligence","Object recognition","Analytical models"
Conference_Titel :
Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), 2015 IEEE 8th International Conference on
Print_ISBN :
978-1-4673-8359-2
DOI :
10.1109/IDAACS.2015.7341412
