Real-time Onboard and Remote Vehicle Health Management
The Phase I of this effort has proven key concepts of our proposed comprehensive health management solution: namely remote and shadow diagnosis over low-bandwidth network and prognosis based on statistical techniques. Our telediagnosis solution has been demonstrated to Honeywell and NASA-JSC, and is being considered for remote monitoring of the Space Station. It is also the centerpiece of Honeywell?s NOVA program (www.wipnova.com). Encouraged by the strong response from NASA and the Aerospace industry, we would like to develop on the shadow reasoning framework and statistical prognosis techniques from our Phase I effort and make RDS the most capable and scalable Intelligent Vehicle Health Management solution, onboard or remote. In Phase II we will add a novel new feature in our reasoner to explain in intuitive terms the diagnosis inferred by the reasoner. Such a capability will speed the adoption of the reasoner by experts, and will have applications in training. We will also address challenging issues of test sequencing in the presence of uncertainties and diagnosis in the presence of variable delay in detection of the fault(s) by tests. The new algorithms will be incorporated into our telediagnosis product, the Remote Diagnosis Server (www.teamqsi.com/rds).
Small Business Information at Submission:
Principal Investigator:Somnath Deb
Kevin F. Cavanaugh
Chief Operating Officer
Research Institution Information:
Qualtech Systems, Inc.
100 Great Meadow Road, Suite 501 Wethersfield, CT 06109
Number of Employees:
University of Connecticut
U-157, 260 Glenbrook Road,
Storrs, CT 06269
Nonprofit college or university