This paper presents a failure detection and diagnosis (FDD) technique for on-board vehicle applications. Failures are represented by abrupt changes in the characteristic parameters of a system that occur at random instants of time. This representation facilitates the formulation of the FDD problem as a combined state and parameter estimation problem of a system with uncertain parameters. This nonlinear estimation problem is solved using a Bayesian approach and implementing a suboptimal algorithm. The performance of the FDD system is demonstrated in simulations of an active suspension subjected to sensor failures. In the simulations, the system detected and diagnosed the failures correctly within .05 seconds from their occurrence.

This content is only available via PDF.
You do not currently have access to this content.