Development of a sensor-based learning approach to prognostics in intelligent vehicle health monitoring

摘要

This paper reports the development and testing of an intelligent sensing network for monitoring corrosion of aircraft structures. The agent-based system uses sensed microclimate and corrosion data with an innovative analysis approach to diagnose corrosion and to infer the presence of corrosion in locations such as crevices and fasteners where it cannot be sensed directly. An important feature of the system is its ability to provide prognostic information to enable timely corrective maintenance scheduling.