Prognostic Enhancements to Naval Condition-Based Maintenance Systems
IMPACT TECHNOLOGIES LLC ROCHESTER NY
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In recent years, numerous machinery health monitoring technologies have been developed by the U.S. Navy to aid In the detection and classification of developing machinery faults for various Naval platforms. Existing Naval condition assessment systems such as ICAS Integrated Condition Assessment System employ several fault detection and diagnostic technologies ranging from simple thresholding to rule-based algorithms. However, these technologies have not specifically focused on the ability to predict the future condition prognostics of a machine based on the current diagnostic state of the machinery and its available operating and failure history data. Prognostic capability is desired because the ability to forecast this future condition enables a higher level of condition-based maintenance for optimally managing total Life Cycle Costs LCC. A second issue is that a framework does not exist for plug n play integration of new diagnostic and prognostic technologies into existing Naval platforms. This paper will outline a generic framework for developing plug n play prognostic modules as well as examples of specific prognostic modules developed for stern turbine journal bearings and auxiliary gearboxes. The gearbox prognostic module was 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.
- Computer Programming and Software
- Marine Engineering