Neural network technique for gas turbine fault diagnosis

• Autores: Sot Ogaji, R. Singh
• Localización: International journal of engineering intelligent systems for electrical engineering and communications, ISSN 0969-1170, Vol. 10, Nº 4, 2002, págs. 209-214
• Idioma: inglés
• Texto completo no disponible (Saber más ...)
• Resumen

  • Gas turbines are extensively used for aero propulsion and power generation for a wide range of industries. Competitive pressures require enhanced techniques for life cycle cost and availability management. The application of artificial neural networks (ANN) in engine diagnostic activities has over the last decade, generated research interest especially when the capabilities of a network are put into focus. In this paper, we review some common gas turbine faults, present some contemporary diagnostic techniques, highlight features of ANN that are required for effective diagnostic applications and finally discuss the benefits derived from the application of ANNs with a developed case study. The results show that the proposed approach would be attractive in real time diagnostic problems.