Fault Diagnostics, Prognostics and Self Healing Control of Navy Electric Machinery

Impact Technologies, collaborating with the Georgia Institute of Technology and Northrop Grumman Ship Systems, propose to develop and demonstrate a real-time diagnostic and prognostic system for assessing, predicting and accommodating for faults/failures of critical electric power system components including power converters and electro-mechanical drives. The innovation of integrating advanced diagnostics and prognostics with a self-healing capability to improve system reliability and mission readiness for the Navy's next generation electric machines is the focus of this effort. Implementation of this concept requires incipient fault detection techniques to provide longer predicted horizons prior to failures, operational history, and fault progression models in order to make accurate and repeatable decisions regarding the remaining life predictions. The Impact/GA-Tech/NGC team's approach uses innovative electronic fault detection and reasoning algorithms to analyze data from several sources including electrical and environmental sensor measurements, model estimates, and usage conditions. Up-to-date assessments of the electrical system health and remaining useful life of critical components will be made possible via an on-board embedded processing system, which continuously updates prognostic models with sensed data, assesses fault severity, and predicts the best fault accommodation strategy to meet mission objectives. The proposed electrical system fault detection, isolation and accommodation approach will be demonstrated with a Motor/Generator/Drive test bench adapted for use in this program and with data from the DD(X) Advanced Induction Motor (AIM) supplied by NGC. Additional plans have been discussed with NGC to demonstrate the technologies on their full-scale AIM system and ONR sponsored virtual test bench VTB during Phase II, if awarded.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.