Prognosis of vehicle health using integrated operational and static data [military vehicles]

This project, Army common embedded diagnostics, (ACED) formerly know as Army diagnostics improvement program (ADIP), seeks to predict the maintenance state (health) of various vehicles. Up to a dozen different engine and transmission parameters are measured. Some of these measurements are made while the vehicle is idling (static) and some are made while the vehicle is underway at various speeds (operational). In the past these different tests, (static and operational) were not combined even though both shared a common goal, to predict future failures much before they occur. Certain tests ignored variables assuming they were unimportant. It is shown how to combine static and operational data by normalization to a common reference, or standard conditions. By consideration of relevant variables improvements in data quality of better than an order of magnitude have been made. Suggestions for other improvements in data quality are developed.