Precedent-free fault isolation in a diesel engine EGR valve system

Abstract

An application of a recently introduced framework for isolating unprecedented faults for an automotive engine EGR valve system is presented. Using normal behavior data generated by a high fidelity engine simulation, the Growing Structure Multiple Model System (GSMMS) is used to construct models of normal behavior for EGR valve system and its various subsystems. Using the GSMMS models as a foundation, anomalous behavior of the entire system is then detected as statistically significant departures of the most recent modeling residuals from the modeling residuals during normal behavior. By reconnecting anomaly detectors to the constituent subsystems, the anomaly can be isolated without the need for prior training using faulty data. Furthermore, faults that were previously encountered (and modeled) are recognized using the same approach as the anomaly detectors.