摘要
针对火电厂汽轮发电机组经济性监测系统中参数失效的问题,提出了利用径向基函数神经网络的仿真手段作为虚拟传感器。分析了径向基函数神经网络的原理与特点,总结了求解各层权值和阈值的数学公式,阐述了参数学习和仿真的方法与过程。
In order to solve the problem of failure measure parameter in the economic monitoring system of steam turbine unit, a method employing radial basis function neural network (RBFN) to simulate the parameter is proposed. The principle and characteristics of RBFN are analyzed, the mathematics method to evaluate the network weights and biases of each layer is summarized, and the training and simulation methods and processes are expounded. Besides, a more convenient method that can use MATLAB to training the network offline was proposed.
出处
《汽轮机技术》
北大核心
2002年第6期356-358,共3页
Turbine Technology
