Optimization of IBOM Power Plant (PG9171) using Fault Prediction on Gas Path Analysis

Abstract Almost from the inception of the gas turbine engine (GT), users and engine manufacturers have sought an effective technique to determine the health of the gas-path components (fan, compressors, combustor, turbines) based on available gas-path measurements. The potential of such tools to save money by anticipating the need for overhaul and providing help in work scope definition is substantial, provided they produce reliable results. It furthermore therefore became desirable to monitor the engine performance and diagnose the fault even before the damage is done since the fault can cause permanent damage to the components. Preventive maintenance proves to be a better way considering the longer run. This project thus work describes how modern gas-path analysis can be used as a tool for gas turbine diagnosis. Gas path analysis is studied with the aid of fault predictions obtained from using fuzzy logic was found to be a more suitable method for gas turbine diagnosis because the set of fuzzy rules are described using common language. MATLAB Simulink environment is also used to predict the degree of fault in the gas turbine through its Gas path analysis. The linguistic variables used as inputs are temperature, pressure and speed while the linguistic variable used as output is failure. The universe of discourse for temperature is between [0, 55], pressure is [0, 1000], shaft speed is [0, 5000] and failure which is the fault is [0, 1]. A type 1 fuzzy logic model and the center of gravity method are used as the defuzzification module. From the results it is seen that the value for the highest possible fault is 0.909 and the lowest is 0.217 at 6.3 and 52.7 OC respectively. This research shows that the fault prediction probability increases at higher operating conditions of the gas turbine.

Keywords Gas Turbine, Fault Prediction, Gas Path Analysis, MATLAB Simulink, Fuzzy Logic.

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Engineering Journal: Optimization of IBOM Power Plant (PG9171) using Fault Prediction on Gas Path Analysis

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