Intelligent monitoring and maintenance of power plants

Conventional predictive maintenance involves continuous processing of real-time data from plant sensors of critical variables that are indicators of the health of the equipment. Some intelligent monitoring systems using rules elicited from maintenance personnel have being developed to infer the causes of impending faults. In this paper we propose a novel approach to intelligent predictive maintenance based on reinforcement learning. Following an outline of reinforcement learning, we explore the possibility of using the technique of reinforcement learning as the basis of an intelligent plant monitoring and predictive maintenance system.