@inproceedings{42cca64a3c284f4d975e4fbff20e5ca8,
title = "Fault parameter identification for model based prognostics of a ball bearing with an outer race defect",
abstract = "This paper deals with identifying the fault parameters of a rotor-bearing system with an outer race defect. The fault parameters can then be used for prognostics. The faults in the bearing are modeled as pits in the outer race of a bearing in a rotorbearing system with four degrees of freedom. Discrete wavelet transforms are used to obtain the energy and entropy features of the rotor-bearing system. The relationship between the features and the fault parameter is studied. Particle swarm optimization is used to generate an optimal set of features. This optimal feature set is used to train an artificial neural network to determine the amount of fault in the system.",
author = "Karthik Kappaganthu and C. Nataraj and Biswanath Samanta",
year = "2009",
doi = "10.1115/DETC2009-87599",
language = "English",
isbn = "9780791848982",
series = "Proceedings of the ASME Design Engineering Technical Conference",
number = "PARTS A AND B",
pages = "1259--1267",
booktitle = "ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2009",
edition = "PARTS A AND B",
note = "ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2009 ; Conference date: 30-08-2009 Through 02-09-2009",
}