Real Time Collective Performance Feedback For Combat
Small Business Information
2690 Spencers Trace, #108, Marietta, GA, 30062
A. Thakker, PE
AbstractThis project is intended to demonstrate the prognostic enhancements to diagnostic systems. It adopts a systematic methodology to select and assess prognostic and human-system interface concepts and suggests means to integrate them into existing shipboardCondition Based Maintenance systems. Phase I effort resulted in the development of prognostic algorithms with a dynamic wavelet neural network and a virtual sensor comprising the main modules of the prognosticator architecture. Means to represent andmanage uncertainty in the prediction scheme and a techno-economic assessment methodology were conceptualized in Phase I. Finally, an open system interface platform and a simple human interface were designed for the prognostic system. The prognosticsystem was tested successfully under simulation conditions on pump and injector nozzle failures. Phase II activities will focus on the optimization of the prognostic algorithms, design of interfacing requirements and test/evaluation of the prognosticarchitecture on two shipboard systems: a motor-pump combination and a gas turbine. An integrated stand-alone diagnostic/prognostic system will be developed, tested and evaluated to function as an experimental prototype for productization andcommercialization purposes.Dual use applications of this novel health management technology are envisioned to maximize equipment uptime and improve the reliability and availability of critical military and industrial processes.The project team alsoincludes integrators, developers and users of this technology to transition this into many commercial and defense related Phase III applications.
* information listed above is at the time of submission.