ELECTRONIC SMOKING CESSATION MONITOR AND COMMUNICATION

Not Available Impact Technologies in cooperation with the Applied Research Laboratory (ARL) at Penn State University propose the development, implementation and validation of multiple enhanced diagnostic and prognostic strategies that can be integrated directly into existing Naval platforms. The prognostic approaches and specific algorithms utilize a combination of health monitoring data. CBM database data, and outputs from various enhanced diagnostic technologies to predict the time to failure an/or time to degraded condition requiring maintenance action. The prognostic modeling strategy will be implemented within a probabilistic framework to directly identify confidence bounds associated with specific component time-to-failure predictions. The approach integrates state-of-the-art analytical and stochastic models with component reliability and inspection results and provides real-time Bayesian updating to accommodate modeling, operational and material property uncertainties known to exist. The failure of prognostic modules will be calibrated and verified using gearbox seeded fault and accelerated failure data taken with the MDTB (Mechanical Diagnostic Test Bed) at the ARL Lab at Penn State University. In addition, in-service data from either a CH-46 helicopter or Pratt & Whitney F100 jet engine will be used to develop and verify degraded condition prognostic strategies. Finally, the prognostic module results will be analyzed by a risk-based economic analysis to optimize the time to perform maintenance based on the consequences of either performing or delaying a maintenance action.