Fully Automated Bearing Residual Life Prognosis Wireless Sensor

Recently, a number of active military helicopters have been outfitted with a number of sensors which may be used to perform usage monitoring for the individual helicopters. However, a methodology must be developed to utilize this information in aneffective manner to reduce maintenance costs while maintaining the overall safety of the aircraft. Systems Planning and Analysis, Inc. (SPA) proposes to utilize artificial neural networks to analyze the helicopter sensor data to perform regime recognitionand flight load determination. Based on a detailed Monte Carlo simulation using assumed flight loads and fatigue data, the current helicopter usage monitoring data, and statistical analysis, SPA will develop an updated component life prediction whilemaintaining a quantitative reliability estimate. Maintenance costs for replacing life-liminted components in rotorcraft is a substantial component of the total operating costs for all helicopters, both military and civilian. These components are replacedafter set number of flight hours to ensure that they will not fail in use. However, the replacement times for these components must be based on a worst-case scenario. The proposed usage monitoring system provides a methodology to monitor the loads placedon these components and to then replace the components when a reasonable amount of fatigue life has been expended. This capability will save rotorcraft operators both the component and maintenance costs associated with early replacements.