Modeling and instrumentation for fault detection and isolation of a cooling system

Abstract

Functional redundancy techniques for fault detection and isolation (FDI) in dynamic systems requires close interaction between system instrumentation, modeling and analysis. Effective FDI requires detailed and accurate models to trade and analyze system behavior, including transient phenomena that result from faults. It also requires appropriate instrumentation technology to provide the measurements to capture and analyze system behavior. Models and measurements must be matched carefully to provide sufficient observability and effective analysis. In this paper we demonstrate the development of FDI systems for complex applications by presenting the modeling and instrumentation of an automobile combustion engine cooling system. We have developed a qualitative parameter estimation methodology for FDI. A system model is represented as a graph that captures the dynamic behavior of the system. To demonstrate the applicability a small leak is artificially introduced in the cooling system and accurately detected and isolated.