Relative Measurement Orderings in Diagnosis of Distributed Physical Systems

Fault diagnosis in large-scale, distributed physical systems often requires the use of a large number of measurements to achieve complete diagnosability. The computational complexity of the diagnosis algorithm increases with the number of measurements, making centralized approaches infeasible for online analysis. This paper presents an extension to the Transcend framework for qualitative fault diagnosis in complex physical systems. The Transcend framework is based solely on qualitative time-derivative effects. Our approach combines relative measurement orderings with the traditional fault signature approach to increase the discriminatory power of a set of measurements. The measurement orderings are based on a qualitative analysis of the temporal propagation of fault effects derived from the temporal causal graph of the system. These orderings allow for diagnosis with fewer measurements. More importantly, in large-scale systems, the orderings can be used to reduce the number of measurements used by local diagnosers, leading to more efficient algorithms. The application of the approach to large-scale, distributed systems is illustrated using a multi-tank system.