Advanced Intelligent Web-Based Options to Acquire and Analyze Aircraft Health and Test Data

Advanced Intelligent Web-Based Options to Acquire and Analyze Aircraft Health and Test Data
Navy SBIR FY2008.2

Sol No.:	Navy SBIR FY2008.2
Topic No.:	N08-122
Topic Title:	Advanced Intelligent Web-Based Options to Acquire and Analyze Aircraft Health and Test Data
Proposal No.:	N082-122-0997
Firm:	Sentient Corporation 850 Energy Drive Suite 307 Idaho Falls, Idaho 83401
Contact:	Nancy Lybeck
Phone:	(208) 522-8560
Web Site:	www.sentientscience.com
Abstract:	Topic Synopsis: Current aircraft disposition tools are not designed to take advantage of predictive prognostic information that will be available on new systems such as the F-35 PHM system or the proposed Maintenance and Monitoring system for the E-2D Hawkeye. The central challenges in this topic are to (1) develop automated reasoner technologies to distill large volumes of PHM data into actionable information, and (2) allow secure web-based access by commanders and maintainers so that multiple users can take advantage of the new knowledge provided by PHM to more efficiently disposition their aircraft regardless of their location. Proposal Abstract: Prognostic health management (PHM) systems generate volumes of data on component health. Web-based tools are needed to automatically assimilate and analyze this data, and present findings and recommended actions to the user, regardless of the user's location. Automated reasoner tools are necessary to ensure that PHM data is utilized for maximum benefit, allowing maintainers to focus on maintenance rather than data interpretation, and to present capability and readiness information to commanders and decision makers. Sentient Corporation will leverage its prototype AutoReasoner, including its defined automated reasoner algorithms and software tools for fusing PHM data into current and predicted capability information, to create a web-based interface for accessing and analyzing PHM data. Phase I activities will include research on migration of the existing demonstrated prototype to a web-based format and a demonstration of Sentient's novel model-based prognostic data fusion technique, a fuzzy expert system for interpretation, via a web-based user interface. Phase I will utilize Sentient's extensive data drawn from the CH-53 E HUMS database and will include multiple realistic maintenance scenarios. Phase II will include further development and web-based access. NOTE: We would be happy to provide additional detail on our approach if desired. Partnering: If awarded this project, Sentient Corporation would like to partner with one or more E-2D OEMs to gather information on available PHM data, learn about potential ground station software tools, and discuss database interfacing standards. Sentient has successfully partnered with multiple OEMs in the past. Sentient will leverage its access to the Goodrich HUMS and MDAT systems for this project. We would also like the OEM to critique our ideas for the reasoner system and data presentation. It is likely that a meeting at the OEM's facility could be arranged during Phase I. We are open to a subcontracting arrangement to help the OEM cover the cost of their time. Sentient Corporation has an outstanding record of winning SBIRs in the PHM area. We are the largest SBIR contractor in Idaho even though we focus exclusively on PHM. Sentient has a reputation for doing excellent work and has been awarded over 8 Phase II contracts to date. In addition, Sentient actively works to transition successful projects to the field. For example, our bearing prognostic modeling software that was developed for the DARPA Prognosis Program has already been licensed to an engine OEM.
Benefits:	Automated reasoner and data presentation tools for PHM would free maintenance personnel to focus on maintenance, rather than data analysis and interpretation. Web-based access would increase information sharing and knowledge capture, as well as increased access to near real-time data. This will help insure consistent diagnoses, faster turn-around, and higher sortie generation rates by taking full advantage of the tremendous knowledge embedded in PHM data.

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