Abstract
The working temperature of an electric generator's parts is important for its proper operation. The turbogenerator rotor's temperature is of particular interest regarding its protection and maintenance. Because of the difficulty of measuring the temperature of dynamic parts with real and implicitly robust artificial neural network (ANN) sensors it was decided to use a virtual sensor (VS) by which average rotor winding temperature is estimated. Because ANN are characterised by learning through training rather than formal descriptions, this has made them the preferred choice for modelling processes involving complex interrelated variables; some are found in the field of instrumentation, as in this research. This paper presents the development of an ANN-based VS applied to an electricity generating company's 4 MW turbogenerator.
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