Title :
Electromagnetic rail-flaw detection signal analysis based on the artificial neural networks
Author :
Nichoga, V.P. ; Yakymiv, R.M. ; Romanyshyn, Y.M.
Author_Institution :
Radioelectron. Devices & Syst. Dept., Lviv Polytech. Nat. Univ., Lviv, Ukraine
Abstract :
In this paper the application of the artificial neural network for the identification of signals of rail fault 21 are given. At the beginning of the diagnostics process preliminary processing of fault detection signals is worked out and fragments of signals, which can correspond to defects, are picked out for their further research.
Keywords :
flaw detection; neural nets; railways; signal detection; artificial neural networks; electromagnetic rail-flaw detection signal analysis; signal identification; Artificial neural networks; Electromagnetics; Fault diagnosis; Magnetic sensors; Neurons; Rails; Non-destructive testing; artificial neural networks; electro-magnetic rail-flaw detection system;
Conference_Titel :
CAD Systems in Microelectronics (CADSM), 2011 11th International Conference The Experience of Designing and Application of
Conference_Location :
Polyana-Svalyava
Print_ISBN :
978-1-4577-0042-2
Electronic_ISBN :
978-966-2191-17-2
