Prediction of steam generator liquid level under main steam line break accident based on wavelet decomposition combined with deep learning
发布时间：2025-10-16
点击次数：
- 发布时间：
- 2025-10-16
- 论文名称：
- Prediction of steam generator liquid level under main steam line break accident based on wavelet decomposition combined with deep learning
- 发表刊物：
- Nuclear Engineering and Design
- 摘要：
- Liquid level monitoring is essential for maintaining the safe operation of nuclear power circuits. During a Main
Steam Line Break (MSLB) accident, signiffcant ffuctuations in the liquid level within the steam generator pose
challenges for traditional measurement methods, which often fail to accurately capture the true liquid level. This
study conducted experiments of MSLB accidents under controlled conditions, with parameters including heating
power ranging from 8 to 16 kW, break pressures from 0.05 to 0.1 MPa, and relative break sizes between 20 % and
100 %. In selected conditions, rolling motions were introduced to simulate marine environments. Wavelet
decomposition was utilized to extract features at varying frequency levels, and deep learning models were
employed to predict each component. The proposed approach achieved a prediction accuracy of 88.3 %, outperforming
direct predictions from raw data with improvements of 21.9 % in Mean Squared Error (MSE), 12.3 %
in Mean Absolute Error (MAE), and 10.0 % in the coefffcient of determination (R2
). The detail component cD1
was found to have the most signiffcant impact on overall prediction accuracy, highlighting it as a key parameter
for further optimization. Furthermore, the use of wavelet-decomposed data signiffcantly reduced computational
complexity, enhancing time efffciency. These results demonstrate the effectiveness of the proposed method in
improving prediction accuracy and operational efffciency, offering valuable support for the safe management of
nuclear power systems during MSLB accidents.
- 合写作者：
- Biaoxin Wang,Yuang Jiang, Mei Lin, Qiuwang Wang
- 卷号：
- 436
- 页面范围：
- 113998
- 是否译文：
- 否
- 发表时间：
- 2025-03-02