Artificial Intelligence for Prognostics
Papers from the 2007 AAAI Fall Symposium
George Vachtsevanos, Serdar Uckun, and Kai Goebel, Program Cochairs
Technical Report FS-07-02. Published by The AAAI Press, Menlo Park, California
This technical report is also available in book and CD format.
Please Note: Abstracts are linked to individual titles, and will appear in a separate browser window. Full-text versions of the papers are linked to the abstract text. Access to full text may be restricted to AAAI members. PDF file sizes may be large!
Contents
Organizing Committee / 1
George Vachtsevanos, Serdar Uckun, and Kai Goebel
FPGA Based Fault Detection, Isolation and Healing for Integrated Vehicle Health / 1
Ali Akoglu, Sonia Vohnout, Justin Judkins
Multi-level Methods for Combined Diagnostics and Prognostics / 9
Gautam Biswas, Sankaran Mahadevan
Soft Computing Applications to Prognostics and Health Management (PHM): Leveraging Field Data and Domain Knowledge / 17
Piero P. Bonissone, Naresh Iyer
Multivariate State Estimation Technique for Remaining Useful Life Prediction of Electronic Products / 26
Shunfeng Cheng, Michael Pecht
Changing Failure Rates, Changing Costs: Choosing the Right Maintenance Policy / 33
Chris Drummond
Applying Outbreak Detection Algorithms to Prognostics / 36
Artur Dubrawski, Michael Baysek, Maj. Shannon Mikus, Charles McDaniel, Bradley Mowry, Laurel Moyer, John Ostlund, Norman Sondheimer, Timothy Stewart
Dynamic Prognoser Architecture via the Path Classification and Estimation (PACE) Model / 44
Dustin R. Garvey, J. Wesley Hines
Uncertainty Assessment of Prognostics of Electronics Subject to Random Vibration / 50
Jie Gu, Donald Barker, Michael Pecht
Health-Management Driven Control Reconfiguration Approach for Flight Vehicles / 58
Asif Khalak, Kai Goebel
Using Health Information to Reconfigure Platform Operation, Adjust Mission Goals and Extend the Life of the System / 63
James Kozlowski, Karl Reichard, Scott Laurin
Health Monitoring of Electronic Products Using Symbolic Time Series Analysis / 73
Sachin Kumar, Michael Pecht
On-Demand Regression to Improve Preciseness of Time to Failure Predictions / 81
Sylvain Létourneau, Chunsheng Yang, Zhenkai Liu
Selected Artificial Intelligence Methods Applied within an Integrated Vehicle Health Management System / 88
Michael J. Roemer, Carl S. Byington, Michael S. Schoeller
A Bayesian Framework for Remaining Useful Life Estimation / 97
Bhaskar Saha, Kai Goebel, Scott Poll, Jon Christophersen
Optimum Feature Selection and Extraction for Fault Diagnosis and Prognosis / 103
Abhinav Saxena, George Vachtsevanos
A Survey of Artificial Intelligence for Prognostics / 108
Mark Schwabacher, Kai Goebel
Dynamic CMG Model / 116
Vadim Smelyanskiy, Serdar Uckun, Nancy Lybeck, Brogan Morton, Sean Marble
Support Vector Prognostics Analysis of Electronic Products and Systems / 121
Vasilis A. Sotiris, Michael Pecht
Prognostics in the Control Loop / 129
Liang Tang, Gregory J. Kacprzynski, Kai Goebel, Johan Reimann, Marcos E. Orchard, Abhinav Saxena, Bhaskar Saha
Uncertainty Management in Shock Models Applied to Prognostic Problems / 137
Alexander Usynin, J. Wesley Hines