Cascade network of dynamic neurons in fault detection systems

The cascade network of dynamic neurons (CNDN) as a neural-residual generator for fault detection in a dynamic systems is considered. The neural network is composed of dynamic neurons, which contain inner feedbacks. These neurons consists of an adder module, a linear dynamic system (IIR filter), and a non-linear activation function. The cascade-correlation algorithm is used for network architecture and parameter allocation. As a illustrative example of the diagnosed dynamic system, the two-tank system is chosen. The proposed approach is useful in neural modelling of dynamic system for FDI (Fault Detection and Isolation).