Monitoring Regenerative Heat Exchanger in Steam Power Plant by Making Use of the Recurrent Neural Network
Tacjana Niksa-Rynkiewicz, Natalia Szewczuk-Krypa, Anna Witkowska, Krzysztof Cpałka, Marcin Zalasiński, Andrzej Cader
Abstract
Abstract Artificial Intelligence algorithms are being increasingly used in industrial applications. Their important function is to support operation of diagnostic systems. This paper presents a new approach to the monitoring of a regenerative heat exchanger in a steam power plant, which is based on a specific use of the Recurrent Neural Network (RNN). The proposed approach was tested using real data. This approach can be easily adapted to similar monitoring applications of other industrial dynamic objects.
Topics & Concepts
Heat exchangerSteam powerRecurrent neural networkPower stationArtificial neural networkComputer scienceThermal power stationProcess engineeringControl engineeringPower (physics)Expert systemEngineeringArtificial intelligenceMechanical engineeringWaste managementElectrical engineeringPhysicsQuantum mechanicsFault Detection and Control SystemsNeural Networks and ApplicationsAdvanced Control Systems Optimization