Development of performance and effectiveness metrics for gas turbine diagnostic technologies

In recent years, numerous anomaly detection and diagnostic technologies have been developed for military and industrial gas turbine applications to aid in the detection and classification of developing faults. In many cases, significant reductions in gas turbine total ownership costs have been achieved through the judicious application of these technologies. However, there is currently no consistent methodology available for assessing both the technical and economic benefits of these machinery diagnostic technologies. In response to this need, a virtual test bench is under development by the US Navy for assessing the performance and effectiveness of machinery diagnostic systems. The test bench utilizes a ´plug ´n play´ interface that can readily accept standardized diagnostic/prognostic tools and link them to real transitional and seeded fault data from appropriate condition based maintenance (CBM) platforms. The assessment process relies on a standard set of mathematical ground rules and a statistical framework to directly identify confidence bounds, robustness measures, and various diagnostic thresholds associated with specific mechanical diagnostic technologies.