DEVICE AND METHOD FOR TRACKING BASIS OF ABNORMAL STATE DETERMINATION BY USING NEURAL NETWORK MODEL

DEVICE AND METHOD FOR TRACKING BASIS OF ABNORMAL STATE DETERMINATION BY USING NEURAL NETWORK MODEL

The present invention relates to a device for tracking the basis of an abnormal state determination by using a neural network model, comprising: an abnormality type classification unit for classifying an abnormal state into a plurality of failures in an abnormal operation scenario in which a plurali...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: PARK, Dae Seung, KIM, Yun Goo, SEONG, No Kyu
Format: Patent
Sprache:eng ; fre ; ger
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
NUCLEAR ENGINEERING
NUCLEAR PHYSICS
NUCLEAR POWER PLANT
NUCLEAR REACTORS
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Beschreibung
Zusammenfassung:The present invention relates to a device for tracking the basis of an abnormal state determination by using a neural network model, comprising: an abnormality type classification unit for classifying an abnormal state into a plurality of failures in an abnormal operation scenario in which a plurality of scenarios related to the abnormal state are stored; an operation variable deriving unit for deriving operation variables affecting an abnormal state determination result for each of the plurality of classified failures; a power plant operation variable weighting unit for weighting the variable related to the abnormal state from among the operation variables; and an abnormal state determination basis generation unit for tracking the basis of an abnormal state determination from the abnormal state determination result generated through the weighted power plant operation variable.