DAVID IVERSON

Member since: Sep 24, 2010, NASA Ames Code TI

Inductive System Health Monitoring

Shared by DAVID IVERSON, updated on Mar 28, 2016

Summary

Author(s) :
David L. Iverson
Abstract

The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS uses nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. IMS is able to monitor the system by comparing real time operational data with these classes. We present a description of learning and monitoring methods used by IMS and summarize some recent IMS results.

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  • DAVID IVERSON 8 years

    Proceedings of the International Conference on Artificial Intelligence, IC-AI '04, Volume 2 & Proceedings of the International Conference on Machine Learning; Models, Technologies & Applications, MLMTA '04, June 21-24, 2004, Las Vegas, Nevada, USA

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