基于徑向基神經網絡的熱力參數虛擬傳感器

針對火電廠汽輪發(fā)電機組經濟性監(jiān)測系統中參數失效的問題,提出了利用徑向基函數神經網絡的仿真手段作為虛擬傳感器。分析了徑向基函數神經網絡的原理與特點,總結了求解各層權值和閾值的數學公式,闡述了參數學習和仿真的方法與過程。
關鍵詞:徑向基;神經網絡;汽輪發(fā)電機組;經濟性監(jiān)測;仿真;虛擬傳感器
Abstract :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 charac2 teristics 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 off2line was proposed.
Key words :radial basis; neural network; steam turbine unit ; economic monitoring; simulation; virtual sensor