Analysis of a Human/2-wheeled-Vehicle System by ARdock

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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Health and Usage Monitoring Algorithm Based on Terrain Identification for Mechanical Components on an Army Ground Vehicle System

Journal of the IEST ◽

10.17764/jiet.51.2.g8h176k5411j8421 ◽

2008 ◽

Vol 51 (2) ◽

pp. 31-41 ◽

Cited By ~ 1

Author(s):

Richard Heine ◽

Donald Barker

Keyword(s):

Unit Cost ◽

Monitoring Systems ◽

Statistical Parameters ◽

Ground Vehicle ◽

Wheeled Vehicle ◽

Vehicle System ◽

Basic Set ◽

Vehicle Systems ◽

Monitoring Algorithm

The desire for enhanced functionality of Army vehicle systems has resulted in increasingly complex systems. This drive is in direct contention with another Army goal of improved reliability. Health and usage monitoring systems (HUMS) and remaining-life prognostics are being developed to address these conflicting goals. One of the major challenges of applying a HUMS to an Army wheeled vehicle system is that the development and per unit cost of the HUMS needs to be relatively low in comparison with typical high-cost applications such as aircraft. Simplified algorithms that derive terrain exposure from a basic set of sensors and estimate fatigue damage accumulated on components where loading comes primarily from terrain have been developed to meet this need. Various inputs and statistical parameters are evaluated for this model based on accuracy of terrain identification and quality of fatigue prediction on an example component. The generalized process and recommendations for application of this model to military ground vehicle systems are discussed.

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