The U.S. Army is currently expanding its fleet of Health Usage Monitoring Systems (HUMS) equipped aircraft at significant rates, to now include over 1,000 rotorcraft. Two different on-board HUMS, the Honeywell Modern Signal Processing Unit (MSPU) and the Goodrich Integrated Vehicle Health Management System (IVHMS), are collecting vibration health data on aircraft that include the Apache, Blackhawk, Chinook, and Kiowa Warrior. The objective of this paper is to recommend the most effective gear condition indicators for fleet use based on both a theoretical foundation and field data. Gear diagnostics with better performance will be recommended based on both a theoretical foundation and results of in-fleet use. In order to evaluate the gear condition indicator performance on rotorcraft fleets, results of more than five years of health monitoring for gear faults in the entire HUMS equipped Army helicopter fleet will be presented. More than ten examples of gear faults indicated by the gear CI have been compiled and each reviewed for accuracy. False alarms indications will also be discussed. Performance data from test rigs and seeded fault tests will also be presented. The results of the fleet analysis will be discussed, and a performance metric assigned to each of the competing algorithms. Gear fault diagnostic algorithms that are compliant with ADS-79A will be recommended for future use and development. The performance of gear algorithms used in the commercial units and the effectiveness of the gear CI as a fault identifier will be assessed using the criteria outlined in the standards in ADS-79A-HDBK, an Army handbook that outlines the conversion from Reliability Centered Maintenance to the On-Condition status of Condition Based Maintenance
