该文提出一个有效的基于径向基函数神经网络的模型和状态数据融合的汽轮发电机智能估计方法。
An efficient model based on radial basis function neural network and intelligent estimating method for data fusion of the turbine-generator is presented.
应用广义函数及蠕变理论，建立了汽轮机阶梯式变厚度轮盘在蠕变状态下的平衡方程、几何方程及本构方程。
By using the generalized functions and creep theory, the equations of equilibrium, geometry and constitution for stepped rotating disks of steam turbine are established under the creep condition.
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