Abstract:
Reducing the direct operating-costs is now crucial in order to ensure
competitive advantages for airlines and manufacturers, and so effective
advanced engine-condition monitoring methodologies are necessary. Hence
gas-path diagnostics and prognostics methods are reviewed and the
specifications for such effective tools deduced, together with their pertinent
future prospects.
First, the considerable value that a preliminary observability study adds to the
diagnostics process was recognised. A secure procedure has been devised: it
is capable of (i) the identification of the severity of correlations between any two
of the available measurements, as well as the correlations between any two of
the component changes, (ii) the identification of more complex correlations that
involve more than two changes in performance parameters, and (iii) the
quantification of the quality of the system observability through a pertinent
parameter. This enables comparisons among a significant number of
measurement set selections.
The core of the research is a novel gas-path diagnostics (GPD) method that
uses fuzzy logic in order to provide secure quantification of the gas-path
component faults. A fuzzy diagnostics system was set up for the Rolls-Royce
Trent 800 engine that relies on an extensive statement of fuzzy rules generated
using an engine model to achieve a quantitative solution through a non-linear
approach, which is competent to achieve (i) SFI (single fault isolation) in the
presence of noisy data, (ii) tuning over a known global deterioration level for all
the performance parameters (baseline) computed for the previous flight, (iii)
partial MFI (multiple fault isolation) with up to 2 degraded components (i.e. 4
performance parameters) considerably faulty at the same time, (iv) SFI while
isolating systematic errors in the measurements (biasses). A bias-tolerant
system was devised by means of the NOT logical operator and a new
formulation of the fuzzy rules that includes the location of the bias.
An innovative prognostics framework was devised, which uses ARIMA models
and regression models respectively for short and long term investigations, to
compute forecasts and the associated prediction intervals, which are aimed at
assisting the prognostics decision-making process. This is strictly related to the
diverse business intentions: in this study safety and economic related
applications are investigated. For example, the optimisation of the TBO (time
between overhauls) considering maintenance cost and additional fuel cost due
to the deterioration is studied and the potential cost savings for the operators
highlighted.
HMP 1.1 for performance analysis was developed: it is a health-monitoring andprognostics
framework consisting of three modules that perform respectively
observability study, gas-path diagnostics and prognostics. The substantial
benefits that can be achieved with such a tool, relative to the enhanced
maintenance planning and improved mission scheduling, are discussed in the
thesis via applications to the Trent 800 engine.