This paper introduces a novel reasoning methodology, in combination with appropriate models and measurements (data) to perform accurately and expeditiously expert troubleshooting for complex military and industrial processes. This automated troubleshooting tool is designed to support the maintainer/ repairman by identifying and locating faulty system components. The enabling technologies build upon a Model Based Reasoning paradigm and a Dynamic Case Based Reasoning method acting as the intelligent database. A case study employs a helicopter Intermediate Gearbox as the application domain to illustrate the efficacy of the approach.
How to Cite
PHM, Troubleshooting, CBR, MBR, learning, Adaptation, model based reasoning, case based reasoning, dynamic case based reasoning
Davis, R. (1984). "Diagnostic Reasoning Based on Structure and Behavior", Artificial Intelligence, Vol. 24, 1984, pp 347-410.
De Kleer, J. & Williams, B.C. (1987). "Diagnosing Multiple Faults", Artificial Intelligence, Vol 32, 1987, pp 97- 130.
Kolodner, J. L. (1993). Case-based Reasoning. San Mateo, CA: Morgan Kaufmann Publishers.
Saha, B. & Vachtsevanos, G. (2006). “A Model-Based Reasoning Approach to System Fault Diagnosis, WSEAS Transactions on Systems, Issue 8, Vol. 5, pp. 1997 – 2004, August 2006.
Saxena, A. (2007). Knowledge-Based Architecture for Integrated Condition Based Maintenance of Engineering System. PhD Dissertation, Georgia Institute of Technology, Atlanta.
Saxena, A., Wu, B., & Vachtsevanos, G. (2005). Integrated Diagnosis and Prognosis Architecture for Fleet Vehicles Using Dynamic Case Based Reasoning. Paper presented at the IEEE Autotestcon ’05 Conference, Orlando, FL.
Vance, J.M. (1988). Rotordynamics of Turbomachinery, John Wiley & Sons, Inc., 1988.
The Prognostic and Health Management Society advocates open-access to scientific data and uses a Creative Commons license for publishing and distributing any papers. A Creative Commons license does not relinquish the author’s copyright; rather it allows them to share some of their rights with any member of the public under certain conditions whilst enjoying full legal protection. By submitting an article to the International Conference of the Prognostics and Health Management Society, the authors agree to be bound by the associated terms and conditions including the following:
As the author, you retain the copyright to your Work. By submitting your Work, you are granting anybody the right to copy, distribute and transmit your Work and to adapt your Work with proper attribution under the terms of the Creative Commons Attribution 3.0 United States license. You assign rights to the Prognostics and Health Management Society to publish and disseminate your Work through electronic and print media if it is accepted for publication. A license note citing the Creative Commons Attribution 3.0 United States License as shown below needs to be placed in the footnote on the first page of the article.
First Author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.