Integrated approach for diagnostics and prognostics of HP LNG pump based on health state probability estimation

Kim, Hack-Eun, Hwang, Sung-Soo, Tan, Andy C. C., Mathew, Joseph, & Choi, Byeong-Keun (2012) Integrated approach for diagnostics and prognostics of HP LNG pump based on health state probability estimation. Journal of Mechanical Science and Technology, 26(11), pp. 3571-3585.

View at publisher

Abstract

Effective machine fault prognostic technologies can lead to elimination of unscheduled downtime and increase machine useful life and consequently lead to reduction of maintenance costs as well as prevention of human casualties in real engineering asset management. This paper presents a technique for accurate assessment of the remnant life of machines based on health state probability estimation technique and historical failure knowledge embedded in the closed loop diagnostic and prognostic system. To estimate a discrete machine degradation state which can represent the complex nature of machine degradation effectively, the proposed prognostic model employed a classification algorithm which can use a number of damage sensitive features compared to conventional time series analysis techniques for accurate long-term prediction. To validate the feasibility of the proposed model, the five different level data of typical four faults from High Pressure Liquefied Natural Gas (HP-LNG) pumps were used for the comparison of intelligent diagnostic test using five different classification algorithms. In addition, two sets of impeller-rub data were analysed and employed to predict the remnant life of pump based on estimation of health state probability using the Support Vector Machine (SVM) classifier. The results obtained were very encouraging and showed that the proposed prognostics system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.

Impact and interest:

2 citations in Scopus
3 citations in Web of Science®
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

ID Code: 70618
Item Type: Journal Article
Refereed: Yes
Additional URLs:
Keywords: Diagnostics, Prognostics, Remaining useful life (RUL), High pressure LNG pump
DOI: 10.1007/s12206-012-0850-4
ISSN: 1976-3824 (online) 1738-494X (print)
Divisions: Current > Institutes > Institute of Health and Biomedical Innovation
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2012 KSME & Springer
Copyright Statement: Author's Pre-print: author can archive pre-print (ie pre-refereeing)
Author's Post-print: author can archive post-print (ie final draft post-refereeing)
Publisher's Version/PDF: author cannot archive publisher's version/PDF
General Conditions: •Publisher's version/PDF cannot be used
•On author's personal website immediately
•On any open access repository after 12 months from publication
•Published source must be acknowledged
•Must link to publisher version
•Set phrase to accompany link to published version (see policy)
•Articles in some journals can be made Open Access on payment of additional charge
Deposited On: 29 Apr 2014 23:44
Last Modified: 21 Jun 2017 02:01

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page