Development of expert system for fault diagnosis of an 8-MW bulb turbine downstream irrigation hydro power plant

Abstract

© 2017 IEEE. This research studies fault diagnosis about an unmanned 8 MW bulb turbine generator of run of river hydro power plant locate far from control and maintenance center by expert system scheme. To assist the inexpert maintenance crews to solve the failure by collecting knowledge from power plant equipment data, maintenance instruction manual, maintenance standard, historical failure events, and body of knowledge from expertise. Translate these information to knowledge base of an expert system by propositional logic. Together with failure analysis of mechanical and electrical equipment that initiate lockout relay signal to shutdown the power plant by fault tree analysis technique for more accuracy and correctness of fault diagnosis. Establishing an inference engine that comprise of failure search rules and problem solving rules. Developing graphical user interface that similar to the SCADA graphic of operator station making inexpert maintenance crews to familiar with the expert system software and easy to use. These will speed up the inexpert maintenance crews to correct the problem as fast as the expertise does. For example, such a case that the generator cannot synchronize to the grid that took the inexpert maintenance crews about 43 hours to correct the problem which lost income about 1,036,080 THB. With the help of the expert system the inexpert maintenance crews could take less than 4 hours to correct this problem and could save loss about 900,000 THB.