A research of FL neural network for fault diagnosis

FL network architecture is a supervised learning extension of the BP network method we have studied thus far. It allows specification of the category into which inputs will be classified. In the designated category, the training set is extended into the input pattern of single layer perceptron with nonlinear change. It is high efficient in the aspects of processing speed and avoiding local stability, and especially useful in fault diagnosis