Title :
Fault prognosis based on fault reconstruction: Application to a mechatronic system
Author :
Djeziri, M.A. ; Toubakh, Houari ; Ouladsine, Mustapha
Author_Institution :
LSIS, Marseille, France
Abstract :
The fault prognosis method developed in this work has a horizontal structure, and aims the estimate the RUL by the reconstruction of the fault trend after detecting the degradation beginning. The diagnosis part is realized using a Principal Component Analysis (PCA), the fault reconstruction is done using the fault direction matrix, and the RUL is estimated using an Auto-Regressive Recurrent Radial Based Function (ARRRBF) neural network. The developed method is implemented on a mechatronic system dedicated to the prognosis, which offers the possibility of introducing gradual and controlled degradations.
Keywords :
fault diagnosis; maintenance engineering; matrix algebra; mechanical engineering computing; mechatronics; principal component analysis; radial basis function networks; recurrent neural nets; ARRRBF neural network; PCA; RUL; auto-regressive recurrent radial based function neural network; fault direction matrix; fault prognosis; fault reconstruction; mechatronic system; principal component analysis; Degradation; Estimation; Market research; Neural networks; Principal component analysis; Prognostics and health management; Vectors;
Conference_Titel :
Systems and Control (ICSC), 2013 3rd International Conference on
Conference_Location :
Algiers
Print_ISBN :
978-1-4799-0273-6
DOI :
10.1109/ICoSC.2013.6750887
