Use of a health and usage monitoring system (HUMS) is one method the Department of Defense is investigating to meet conflicting cost and performance goals for Army wheeled vehicles. One area where a HUMS would be of great benefit is monitoring critical components vulnerable to terrain-induced fatigue. While strain is typically the desired input to a fatigue model, acceleration sensors are less susceptible to damage from the military ground vehicle environment and provide more reliable data over long periods of usage. The feasibility of using vibratory inputs from an accelerometer to make component fatigue predictions for a military wheeled vehicle system is explored in this study, and the use of limited subsets of data for algorithm training are evaluated. An example component is used to demonstrate that the proposed HUMS algorithms are appropriate and provide suitably accurate fatigue predictions.

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