On-line fault detection and diagnosis obtained by implementing neural algorithms on a digital signal processor

A measurement instrument for on-line fault detection and diagnosis is proposed. It is based on the implementation of a neural network algorithm on a processor specialized in digital signal processing and provided with suitable data acquisition and generation units. Two specific implementations are detailed. The former uses the neural-network to simulate on-line the correct system behavior, thus allowing the fault detection to be achieved by comparing the neural network output with the measured one. The latter uses the neural network to classify on-line the system as correct or faulty, thus allowing the fault detection and diagnosis to be achieved simultaneously. These two implementations are applied to detect on-line and diagnose faults on a real system in order to point out different fields of application and to highlight the performance of the measurement apparatus.