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根据汽轮机低压缸相对内效率与其影响因素之间的映射关系,提出了一种基于免疫原理的多层径向基函数(RBF)神经网络数学模型来计算汽轮机的低压缸相对内效率,并以某电厂300MW汽轮机低压缸为例,对其相对内效率进行了实际计算分析.结果表明:该模型收敛速度快、计算精度高,并有较好的泛化能力.该神经网络数学模型为汽轮机相对内效率的在线性能监测提供了一种可行的方法.
According to the mapping relationship between the relative internal efficiency of turbocharger low pressure cylinder and its influencing factors, a multi-layer radial basis function (RBF) neural network mathematical model based on immune principle is proposed to calculate the relative internal efficiency of low pressure cylinder of steam turbine. The results show that this model has the advantages of fast convergence, high calculation accuracy and good generalization ability.The mathematical model of this neural network is the relative internal efficiency of the steam turbine Online performance monitoring of efficiency provides a viable approach.