The gas turbine which has found numerous applications in Air, Land and Sea
applications, as a propulsion system, electricity generator and prime mover, is
subject to deterioration of its individual components. In the past, various
methodologies have been developed to quantify this deterioration with varying
degrees of success. No single method addresses all issues pertaining to gas
turbine diagnostics and thus, room for improvement exists. The first part of this
research investigates the feasibility of non-linear W eighted Least Squares as a
gas turbine component deterioration quantification tool. Two new weighting
schemes have been developed to address measurement noise. Four cases
have been run to demonstrate the non-linear weighted least squares method, in
conjunction with the new weighting schemes. Results demonstrate that the
non-linear weighted least squares method effectively addresses measurement
noise and quantifies gas path component faults with improved accuracy over its
linear counterpart and over methods that do not address measurement noise.
Since Gas turbine diagnostics is based on analysis of engine performance at
given ambient and power setting conditions; accurate and reliable engine
performance modelling and simulation models are essential for meaningful gas
turbine diagnostics. The second part of this research therefore sought to
develop a multi-fuel and multi-caloric simulation method with the view of
improving simulation accuracy. The method developed is based on non-linear
interpolation of fuel tables. Fuel tables for Jet-A, UK Natural gas, Kerosene and
Diesel were produced. Six case studies were carried out and the results
demonstrate that the method has significantly improved accuracy over linear
interpolation based methods and methods that assume thermal perfection
