Abstract:
The rotor shaft is a major mechanical component of the gas turbine engine responsible for power generation and power. Failure of the rotor shaft system is catastrophic with long down times and high maintenance cost as the consequences. Therefore, the aim of this research is to develop a model-based software for Torsional Vibration analyses of gas turbine rotor shaft system for early fault detection including artificial intelligence. The purpose is to predict and detect early faults that can cause catastrophic failures and stoppage of work. This paper, therefore, presents a computer based analytical solution method for Torsional vibration analysis of the gas turbine engine. In arriving at the method, a single degree of freedom system was modeled and relevant equations were derived. These equations were programmed using Java programming technique and results were compared with the data of an operational existing plant. From the results it is seen that the value for the highest possible fault is 0.909 on the y axis. In this process, it was discovered that input parameters such as air flow rates of 21.9Kg/s, fuel flow rate of 0.324Kg/s, and heat value of fuel at 11750kJ/kW-hr would yield thermal efficiency as high as 51% and an optimum operating point of 298K. The software developed will be useful for training in tertiary institutions and easy for both technical and non-technical personnel on both thermodynamic and Torsional Vibration analysis of Gas Turbine rotor shaft.
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