eprintid: 8526
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/85/26
datestamp: 2023-11-09 16:20:26
lastmod: 2023-11-09 16:20:26
status_changed: 2023-11-09 16:12:52
type: conference_item
metadata_visibility: show
creators_name: Rahimi, F.
creators_name: Lemma, T.A.
title: Gas turbine fault diagnostics using fuzzy systems
ispublished: pub
keywords: Bandpass filters; Corrosion fatigue; Cost effectiveness; Fault detection; Fuzzy systems; Gases; Maintenance; Regression analysis, Cost effective; Cost-efficient; Elevated temperature; Exposed to; Fault detection and diagnostics; Faults diagnostics; High Speed; Orthonormal; Orthonormal filter; Wiener-schetzen model, Gas turbines
note: cited By 5; Conference of 7th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2017 ; Conference Date: 24 November 2017 Through 26 November 2017; Conference Code:134605
abstract: Gas turbines are clean, compact, cost effective and efficient assets that are being used widely in distributed power generation. They operate at elevated temperature, pressure, high speed and often exposed to erosive materials resulting in several types of failures such as corrosion, fretting fatigue, and fatigue-creep failures. Early detection and diagnostics of a fault is the key to optimize the maintenance cost and reduction in production downtime. While there are assorted approaches in fault detection and diagnostics in gas turbines, this literature provides a useful review on the fault detection and diagnostics methods that have used fuzzy systems only. Publications from years 2001 to 2017 are included. The results show that (i) the gas path analysis models rely on the availability of large amount of data, that is not often the case in the real-life situation, (ii) there is lack of proper documentation for expert opinions done in fuzzy diagnostics, (iii) the hybrid fuzzy systems are gaining more popularity, (iv) the studies on fault diagnostics under dynamic conditions are quite limited, and (v) Wiener-Schetzen model that adopts orthonormal basis functions for the dynamic part is not yet applied to gas turbines. The remarks are useful to further enhance the conventional approach to diagnostics systems design. © 2017 IEEE.
date: 2017
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050398938&doi=10.1109%2fICCSCE.2017.8284426&partnerID=40&md5=3e9c30f908f5a02d571d470328a4faaa
id_number: 10.1109/ICCSCE.2017.8284426
full_text_status: none
publication: Proceedings - 7th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2017
volume: 2017-N
pagerange: 314-319
refereed: TRUE
isbn: 9781538638972
citation:   Rahimi, F. and Lemma, T.A.  (2017) Gas turbine fault diagnostics using fuzzy systems.  In: UNSPECIFIED.