The innovative energy systems equipped with large volume size connected with a gas turbine present critical issues related to the surge risk especially during transient operations. In comparison with standard gas turbines, the volume size generates different behaviour during dynamic operations (with significant surge risk), especially considering that innovative additional components include important dynamic constraints. The main examples of power systems including the effect of an additional volume connected with a turbine are: fuel cell based hybrid plants, humid cycles, externally fired layouts and innovative systems including high temperature thermal storage devices. The aim of the work in this thesis is to cope with the surge instability in fluid dynamic machines through the analysis of vibro-acoustic signals generated from the turbine compressor. Investigations based on acoustic and vibrational measurements appear to provide an interesting diagnostic and predictive solution by adopting a suitable quantifier calculated from microphone and accelerometer signals. For this scope, a wide experimental activity was carried out with a test rig composed by a T100 microturbine connected to a modular vessel. Starting from the stable operation, the instability of surge was produced progressively by closing a valve in the main air line while the system was equipped with different dynamic probes to measure the vibrations during normal and surge operations. A machine dynamical characterization was useful for a better interpretation of signals during its transient to the surge. Hence different possible methods of incipient surge identification have been developed through the use of different signal processing techniques in time, frequency and angle domain. A Vibro-acoustic analysis was carried out to develop precursors which are able to highlight the unstable operative zone approaching and to produce control data (e.g. an on/off signal for a bleed valve) for surge prevention. Finally, four of surge precursors found were implemented into a new diagnostic real-time software. By using the measured data, this innovative tool has proved to be able to recognise a surge incipience condition by comparing the precursor values with a set of moving thresholds.
|Titolo della tesi:||Experimental and theoretical investigations for surge prevention in gas turbines|
|Data di discussione:||25-mag-2021|
|Appare nelle tipologie:||Tesi di dottorato|