Dynamic high order neural networks: Application for fault diagnosis

Abstract

The paper discusses the application of a multi layered high order neural network in modelling and fault diagnosis of dynamic processes. Dynamic properties can be obtained by adding a finite impulse response filter to the neuron. A combinatorial algorithm is used for selecting the network structure. If a linear activation function is used, the universal approximation capabilities of these networks are easy to prove. To show the applicability of such networks, the modelling and fault detection results for the two-tank-system are presented in the last part.