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- Title
基于 NARX 网络方法的汽轮机转子 关键部位应力预测.
- Authors
赵 翔; 茹东恒; 王 鹏; 吴 昊; 甘 磊; 仲 政
- Abstract
Stress prediction of steam turbine rotors during startup processes is of great significance. To predict the stresses of key components in a350 MW supercritical steam turbine rotor, a NARX neural network?based method was proposed with a2D axisymmetric finite element model established according to the actual dimen? sions of the rotor. Appropriate boundary conditions were applied to the model and the temperature and stress distributions under cold startup conditions were calculated. The simulated results were experimentally verified and the danger points of the rotor were then determined after288finite element calculations according to typi? cal startup conditions. The stresses calculated near the danger points as well as several user?selected operating parameters were used to establish the neural network sample dataset. An effective NARX neural network was employed to estimate the stresses at the danger points. The results show that,the proposed method can accu? rately predict the stresses with their tendency. The stresses predicted by the NARX neural network are in good agreement with the finite element simulated results,and can meet the requirements for rotor stress monitoring.
- Publication
Applied Mathematics & Mechanics (1000-0887), 2021, Vol 42, Issue 8, p771
- ISSN
1000-0887
- Publication type
Academic Journal
- DOI
10.21656/1000.0887.410372