relation: https://khub.utp.edu.my/scholars/8175/
title: Two-shaft stationary gas turbine engine gas path diagnostics using fuzzy logic
creator: Amare, F.D.
creator: Gilani, S.I.
creator: Aklilu, B.T.
creator: Mojahid, A.
description: Our objective was to develop a Fuzzy logic (FL) based industrial two-shaft gas turbine gas path diagnostic method based on gas path measurement deviations. Unlike most of the available FL based diagnostic techniques, the proposed method focused on a quantitative analysis of both single and multiple component faults. The data required to demonstrate and verify the method was generated from a simulation program, tuned to represent a GE LM2500 engine running at an existing oil & gas plant, taking into account the two most common engine degradation causes, fouling and erosion. Gaussian noise is superimposed into the data to account measurement uncertainty. Finally, the fault isolation and quantification effectiveness of the proposed method was tested for single, double and triple component fault scenarios. The test results show that the implanted single, double and triple component fault case patterns are isolated with an average success rate of 96 , 92  and 89  and quantified with an average accuracy of 83 , 80  and 78.5 , respectively. © 2017, The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature.
publisher: Korean Society of Mechanical Engineers
date: 2017
type: Article
type: PeerReviewed
identifier:   Amare, F.D. and Gilani, S.I. and Aklilu, B.T. and Mojahid, A.  (2017) Two-shaft stationary gas turbine engine gas path diagnostics using fuzzy logic.  Journal of Mechanical Science and Technology, 31 (11).  pp. 5593-5602.  ISSN 1738494X     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85035065074&doi=10.1007%2fs12206-017-1053-9&partnerID=40&md5=a9af3b4cb0e844dab9f59a24f2e25dc3
relation: 10.1007/s12206-017-1053-9
identifier: 10.1007/s12206-017-1053-9