IMPLEMENTATION OF ARTIFICIAL INTELLIGENCE FOR EARLY DETECTION OF GENERATOR FAULTS IN POWER PLANTS
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Maickel - Tuegeh(1*)
Universitas Sam Ratulangi
(*) Corresponding Author
Abstract
In addition to achieving optimal generator scheduling, ensuring the safe operation of the generator itself is equally important. This paper proposes the implementation of artificial intelligence for early detection of generator faults in power plants. A neural network (NN) approach is employed to construct the virtual simulation of the generator capability curve. The developed visualization model enables simulation of generator operating behavior while accounting for various operational constraints and component limitations. Furthermore, the visualization of the capability curve can effectively illustrate different potential operating scenarios that may occur in real-world generator operations. It also allows simulations under special or specific conditions, providing an accurate and flexible representation of generator performance
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