A Particle Filtering Based Approach for Gear Prognostics

View Sample PDF

Author(s): David He (The University of Illinois-Chicago, USA), Eric Bechhoefer (NRG Systems, USA), Jinghua Ma (The University of Illinois-Chicago, USA)and Junda Zhu (The University of Illinois-Chicago, USA)
Copyright: 2013
Pages: 10
Source title: Data Mining: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-4666-2455-9.ch019

Keywords: Data Mining / Data Mining and Databases / Information Science Reference / Library & Information Science

Purchase

View A Particle Filtering Based Approach for Gear Prognostics on the publisher's website for pricing and purchasing information.

Abstract

In this chapter, a particle filtering based gear prognostics method using a one-dimensional health index for spiral bevel gear subject to pitting failure mode is presented. The presented method effectively addresses the issues in applying particle filtering to mechanical component remaining useful life (RUL) prognostics by integrating a couple of new components into particle filtering: (1) data mining based techniques to effectively define the degradation state transition and measurement functions using a one-dimensional health index obtained by a whitening transform; and (2) an unbiased l-step ahead RUL estimator updated with measurement errors. The presented prognostics method is validated using data from a spiral bevel gear case study.

The IRMA Community

Research IRM

A Particle Filtering Based Approach for Gear Prognostics

Purchase

Abstract

Related Content

IRMA Sponsors