Hydroelectric power contributes around 20% to the world electricity supply and is considered as
the most important, clean, emission free and an economical renewable energy source. Hydro electric power
plants operating all over the world has been built in the 20th century in many countries and running at a higher
plant-factor. This is achieved by minimizing the failures and operating the plants continuously for a longer
period at a higher load. However, continuous operation of old plants have constrained with the failures due to
bearing overheating. The aim of this research is to model and simulate the dynamic variation of temperatures of
bearing temperature of a hydro electric generating unit.
Multi-input, multi-output (MIMO) system with complex nonlinear characteristics of this nature is difficult to
model using conventional modeling methods. Hence, in this research neural network (NN) technique has been
used for modeling the system
