Role of On-board Sensors in Remaining Life Prognostic Algorithm Development for Selected Assemblies as Input to a Health and Usage Monitoring System for Military Ground Vehicles

Title of Document: ROLE OF ON-BOARD SENSORS IN REMAINING LIFE PROGNOSTIC ALGORITHM DEVELOPMENT FOR SELECTED ASSEMBLIES AS INPUT TO A HEALTH AND USAGE MONITORING SYSTEM FOR MILITARY GROUND VEHICLES Richard Heine, Ph.D., 2008 Directed By: Professor Donald Barker, Department of Mechanical Engineering Improved reliability of military ground vehicle systems is often in direct conflict with increased functionality and performance. Health and Usage Monitoring Systems or HUMS are being developed to address this issue. HUMS can be practically defined as a system of sensors, processors and algorithms that give an indication of remaining component life. Fatigue of metal components is a common failure mode on military vehicles, and failures of this type have a major effect on vehicle reliability and availability. The purpose of this research is to develop the methods and algorithms necessary for applying HUMS and remaining life prognostics to metal fatigue on a military wheeled vehicle. A range of models were developed and fidelity of the models was shown to be correlated with computational complexity. Simplistic models based on feature recognition had the least potential for accurate fatigue damage predictions while high fidelity physics-based models had the most potential. Recommendations for the information needed to select the most appropriate model for a component and optimize the effect on vehicle reliability and availability were discussed. Methods for identifying the set of instrumentation that could reasonably be used as part of a HUMS and techniques for selecting the instrumentation that provides inputs for metal fatigue damage models were evaluated. Techniques for identifying critical data and instrumentation were also described. The methods and algorithms developed were demonstrated for a variety of components on a military wheeled vehicle, and validation was performed by comparing the results of the remaining life prognostics with those from high fidelity physics of failure models. The processes developed could be easily adapted to other platforms including commercial fleets of vehicles or aircraft. These algorithms and techniques provide potential for improving reliability and availability, but it should be noted that other methods may be more appropriate depending on the specific vehicle and failure mode. Significant work remains to implement HUMS technologies on a military wheeled vehicle, but increasing reliability and availability is a worthy goal. ROLE OF ON-BOARD SENSORS IN REMAINING LIFE PROGNOSTIC ALGORITHM DEVELOPMENT FOR SELECTED ASSEMBLIES AS INPUT TO A HEALTH AND USAGE MONITORING SYSTEM FOR MILITARY GROUND VEHICLES