A Vibration Management Enhancement Program (VMEP) effort is currently under way at the South Carolina Army National Guard, Army Aviation Support Facility (SCARNG-AASF) in cooperation with the University of South Carolina (USC). The purpose of the program is to minimize aircraft operation cost, reduce maintenance flights, augment aircraft availability, and increase safety through inflight vibrations monitoring, on-line data processing and artificial intelligence based decisions. The program is targeting Apache (AH- 64), Blackhawk (UH-60), and Kiowa Warrior (OH-58D) helicopters. The instrumented aircraft are at the SCARNG-AASF at McEntire Air National Guard Station in South Carolina. University of South Carolina is responsible for the cost and effectiveness analysis of the VMEP program, the establishment of a data repository for the collected data, and the development of long-term helicopter health monitoring and failure prevention methodology based on in- flight vibrations measurements. This paper presents the general methodology adopted in the VMEP programs, the new neural network based rotor smoothing processing principles, and cost and effectiveness analysis approach. Technical details of the algorithms are succinctly presented, and projection of program development over the next period is briefly discussed.


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