Research on false alarm detection algorithm of nuclear power system based on BERT-SAE-iForest combined algorithm

During the operation of nuclear power system, the instrument detection data often deviates from the normal operating state for a short time due to system or environmental fluctuations. And the control system will send an alarm signal, resulting in the false alarm. Aiming at the problem of false alarm, three algorithms are improved and combined to form a false alarm algorithm in this paper. The algorithm consists of the transient operating parameters processing algorithm and the nuclear power system anomaly identification algorithm. The transient operating parameters processing algorithm is based on the Bidirectional Encoder Representations from Transformers (BERT) algorithm and is used to determine whether the deviation between the measured values of the instrument and the theoretical calculated values exceeds the set threshold. The anomaly identification algorithm of nuclear power system is based on Sparse Auto Encoder (SAE) and Isolation Forest (iForest) algorithm to judge the operating state of nuclear power system. When the transient operating parameters processing algorithm judges that the deviation values have exceeded the set threshold, but the anomaly identification algorithm judges that the nuclear power system is in normal operation, it can determine that the current alarm signal is the false alarm. The false alarm detection algorithm of nuclear power system can not only provide judgment basis for the operators to analyze the state of nuclear power system, but also improve the intelligent level of nuclear power system, so as to further improve the safety and reliability of nuclear power system.