@article{scholars8175,
            year = {2017},
         journal = {Journal of Mechanical Science and Technology},
       publisher = {Korean Society of Mechanical Engineers},
           pages = {5593--5602},
          volume = {31},
            note = {cited By 14},
          number = {11},
             doi = {10.1007/s12206-017-1053-9},
           title = {Two-shaft stationary gas turbine engine gas path diagnostics using fuzzy logic},
            issn = {1738494X},
          author = {Amare, F. D. and Gilani, S. I. and Aklilu, B. T. and Mojahid, A.},
        keywords = {Computer circuits; Engines; Fuzzy logic; Gas turbines; Gases; Gaussian noise (electronic); Uncertainty analysis, Component faults; Diagnostic techniques; Gas path; Gas turbine performance; Gas-path measurements; Measurement uncertainty; Multiple components; Stationary gas turbines, Turbine components},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85035065074&doi=10.1007\%2fs12206-017-1053-9&partnerID=40&md5=a9af3b4cb0e844dab9f59a24f2e25dc3},
        abstract = {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. {\^A}{\copyright} 2017, The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature.}
}