| description abstract | In gas turbine operations, engine performance and health status are very important information for engine operators. Such engine performance is normally represented by engine airflow rate, compressor pressure ratios, compressor isentropic efficiencies, turbine entry temperature, turbine isentropic efficiencies, etc., while the engine health status is represented by compressor and turbine efficiency indices and flow capacity indices. However, these crucial performance and health information cannot be directly measured and therefore are not easily available. In this research, a novel Adaptive Gas Path Analysis (Adaptive GPA) approach has been developed to estimate actual engine performance and gas path component health status by using gas path measurements, such as gas path pressures, temperatures, shaft rotational speeds, fuel flow rate, etc. Two steps are included in the Adaptive GPA approach, the first step is the estimation of degraded engine performance status by a novel application of a performance adaptation method, and the second step is the estimation of engine health status at component level by using a new diagnostic method introduced in this paper, based on the information obtained in the first step. The developed Adaptive GPA approach has been tested in four test cases where the performance and degradation of a model gas turbine engine similar to Rolls-Royce aero engine Avon-300 have been analyzed. The case studies have shown that the developed novel linear and nonlinear Adaptive GPA approaches can accurately and quickly estimate the degraded engine performance and predict the degradation of major engine gas path components with the existence of measurement noise. The test cases have also shown that the calculation time required by the approach is short enough for its potential online applications. | |
