20-09-2014, 04:10 PM
Abstracts: Objective of this work is to model and simulate dynamic variation of temperatures of bearings (generator guide bearing, turbine guide bearing, thrust bearing) of a hydropower generating unit. The temperature of a bearing is depends on multiple variables such as temperatures of ambient air, cooling water and cooling water flow-rate, initial bearing temperatures, duration of operation and electrical load. The bearing heat exchange system of a hydropower plant is multi-input (MI) and multi-output (MO) system with complex nonlinear characteristics. So that Neural Network (NN) method has been selected as the best where past input and output details available, and the input characteristics can be mapped in order to develop a model. In this report we have simulate the Temperature of the Thrust Bearing by Using Backpropagation in Neural Network tool of MATLAB.