Publication | Closed Access
Sensor validation for power plants using adaptive backpropagation neural network
52
Citations
0
References
1990
Year
Signal ValidationEngineeringMachine LearningNeural Networks (Machine Learning)Smart ManufacturingEnergy MonitoringSocial SciencesControl SystemsVirtual SensorMore Process VariablesSystems EngineeringSensor ValidationProcess MonitoringComputer EngineeringNeural Networks (Computational Neuroscience)Neural NetworksEnergy PredictionControl System EngineeringIntelligent SensorEvolving Neural NetworkSmart GridEnergy ManagementProcess ControlAi-based Process OptimizationIndustrial Process Control
Signal validation and process monitoring problems in many cases require the prediction of one or more process variables in a system. The feasibility of using neural networks to characterize one variable as a function of other related variables is studied. The backpropagation network (BPN) is used to develop models of signals from both a commercial power plant and the Experimental Breeder Reactor-II (EBR-II). Several innovations are made in the algorithm, the most significant of which is the progressive adjustment of the sigmoidal threshold function and weight updating terms.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>