TY - JOUR
T1 - Abnormality diagnosis model for nuclear power plants using two-stage gated recurrent units
AU - Kim, Jae Min
AU - Lee, Gyumin
AU - Lee, Changyong
AU - Lee, Seung Jun
N1 - Publisher Copyright:
© 2020
PY - 2020/9
Y1 - 2020/9
N2 - A nuclear power plant is a large complex system with tens of thousands of components. To ensure plant safety, the early and accurate diagnosis of abnormal situations is an important factor. To prevent misdiagnosis, operating procedures provide the anticipated symptoms of abnormal situations. While the more severe emergency situations total less than ten cases and can be diagnosed by dozens of key plant parameters, abnormal situations on the other hand include hundreds of cases and a multitude of parameters that should be considered for diagnosis. The tasks required of operators to select the appropriate operating procedure by monitoring large amounts of information within a limited amount of time can burden operators. This paper aims to develop a system that can, in a short time and with high accuracy, select the appropriate operating procedure and sub-procedure in an abnormal situation. Correspondingly, the proposed model has two levels of prediction to determine the procedure level and the detailed cause of an event. Simulations were conducted to evaluate the developed model, with results demonstrating high levels of performance. The model is expected to reduce the workload of operators in abnormal situations by providing the appropriate procedure to ultimately improve plant safety.
AB - A nuclear power plant is a large complex system with tens of thousands of components. To ensure plant safety, the early and accurate diagnosis of abnormal situations is an important factor. To prevent misdiagnosis, operating procedures provide the anticipated symptoms of abnormal situations. While the more severe emergency situations total less than ten cases and can be diagnosed by dozens of key plant parameters, abnormal situations on the other hand include hundreds of cases and a multitude of parameters that should be considered for diagnosis. The tasks required of operators to select the appropriate operating procedure by monitoring large amounts of information within a limited amount of time can burden operators. This paper aims to develop a system that can, in a short time and with high accuracy, select the appropriate operating procedure and sub-procedure in an abnormal situation. Correspondingly, the proposed model has two levels of prediction to determine the procedure level and the detailed cause of an event. Simulations were conducted to evaluate the developed model, with results demonstrating high levels of performance. The model is expected to reduce the workload of operators in abnormal situations by providing the appropriate procedure to ultimately improve plant safety.
KW - Abnormality diagnosis
KW - Data classification
KW - Gated recurrent unit
KW - Nuclear power plant
KW - Principal component analysis
UR - http://www.scopus.com/inward/record.url?scp=85080138907&partnerID=8YFLogxK
U2 - 10.1016/j.net.2020.02.002
DO - 10.1016/j.net.2020.02.002
M3 - Article
AN - SCOPUS:85080138907
SN - 1738-5733
VL - 52
SP - 2009
EP - 2016
JO - Nuclear Engineering and Technology
JF - Nuclear Engineering and Technology
IS - 9
ER -