RBF网络在凝汽器故障诊断中的应用

Application of Radial Basis Function Network in Failure Diagnosis of Condender

针对RBF神经网络基函数的中心值和宽度确定的特殊问题,将免疫遗传算法与RBF神经网络相结合,提出一种基于免疫原理的RBF神经网络模型并应用于凝汽器系统故障诊断中。通过实例验证,结果表明该法有效地提高了故障诊断的精度和速度,具有应用价值。

A new network training method, based on the combination of immune algorithm and RBF neural network , is put forwasrd to decide the center and extent of Radial Basis Function. It is applied to realize failure diagnosis of a condenser. The result of verification shows that the proposed method can impove the accuracy and the speed of failure diagnosis effectively.