Automated Contingency Management and Self-Repair for Navy Ship Systems Navy SBIR FY2008.1 Sol No.: Navy SBIR FY2008.1 Topic No.: N08-051 Topic Title: Automated Contingency Management and Self-Repair for Navy Ship Systems Proposal No.: N081-051-0442 Firm: Impact Technologies, LLC 200 Canal View Blvd Rochester, New York 14623 Contact: G Valentine Phone: (585) 627-1910 Web Site: www.impact-tek.com Abstract: Impact Technologies proposes a Phase I program that will develop an architecture capable of extending the operational capabilities of unmanned or low-manned vehicles in the presence of functionally degraded systems. The proposed system will be capable of performing at three levels: First, the system will determine the current health state, presence of system anomalies, of mission and safety critical subsystems based on health indicators processed from raw sensor data. System anomalies can include identification of component failure mechanisms or simply scheduled maintenance requirements. Second, the system will employ model based reasoning approaches to determine the implications of any degraded elements on the overall capabilities of the vehicle to perform its mission schedule. Third, the system will be able to identify and initiate corrective self-repair actions based on the operational requirements of the mission schedule and the level of corrective technology supported by the vehicle and its subsystems. The approach will be to develop the architecture and subsystem specific diagnostic and reasoning software modules necessary for performing fault detection and self healing on critical failure modes and verify their operation, first demonstrating this approach on a representative complex system relevant to unmanned and low-manned programs, a Ship's Supply Diesel Generator (SSDG). Benefits: The development and integration of embedded diagnostics, prognostics and self healing control for Navy electric systems will provide many benefits including: Improved safety and readiness associated with system operations; reduced life cycle or total ownership costs; optimized maintenance intervals and prioritized task performance. Furthermore, the work will contain many generic elements that can be transitioned to a broad range of other commercial applications. The integrated diagnostics and prognostics approaches, techniques, and specific algorithms could also be implemented in a wide range of civilian hybrid power applications as well as in power plants, utilities, transportation, and telecommunication industries where reliable backup power is essential to sustain critical services. Return