Signal Interpretation for Monitoring and Diagnosis, a Cooling System Testbed

Abstract

This paper discusses our method for monitoring and diagnosis of dynamic systems. A key aspect in our approach is the interaction between a qualitative diagnosis engine that requires symbolic input data and a monitoring component that performs a signal to symbol transformation on the observed signals. We have applied the methodology to the cooling system of an automobile engine on which we have installed thermocouples and pressure sensors. Faults can be introduced into the cooling system in a controlled manner. We show that a combination of linear approximation techniques and statistical signal processing can provide robust symbolic signal values for the diagnosis algorithm.