Using health information to reconfigure platform operation, adjust mission goals and extend the life of the system

James Kozlowski, Karl Reichard, Scott Laurin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

One of the primary advantages of having prognostic information about a platform is the ability to adapt operation and mission planning to compensate for the impending reduced capability. In addition, information about the operating ranges and mission requirements can be used to change the point in time the fault will occur. For example, a change in how the load on a power system is distributed may extend the point a fault will occur and therefore, provide additional mission time and/or life of the power system. Thus, there is a need to develop a unified approach to apply health information to operating conditions and mission planning to minimize the impact of the impending fault as well as use the operating limits and mission parameters to extend the life of the failing components or system to maximize the life of the platform and range of the mission. This paper analyzes and compares different approaches to applying health information to operation reconfiguration, mission planning and life extension. The weaknesses and strengths of these approaches are analyzed and a unified approach is proposed for classifying and analyzing health integration schemes for command and control structures. In addition, several health integration examples, from publicly available literature, are provided using the proposed classification and analysis approach to demonstrate its range and value.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence for Prognostics - Papers from the AAAI Fall Symposium
Pages63-72
Number of pages10
StatePublished - Dec 1 2007
EventArtificial Intelligence for Prognostics - Papers from the AAAI Fall Symposium - Arlington, VA, United States
Duration: Nov 9 2007Nov 11 2007

Publication series

NameAAAI Fall Symposium - Technical Report

Other

OtherArtificial Intelligence for Prognostics - Papers from the AAAI Fall Symposium
CountryUnited States
CityArlington, VA
Period11/9/0711/11/07

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Fingerprint Dive into the research topics of 'Using health information to reconfigure platform operation, adjust mission goals and extend the life of the system'. Together they form a unique fingerprint.

  • Cite this

    Kozlowski, J., Reichard, K., & Laurin, S. (2007). Using health information to reconfigure platform operation, adjust mission goals and extend the life of the system. In Artificial Intelligence for Prognostics - Papers from the AAAI Fall Symposium (pp. 63-72). (AAAI Fall Symposium - Technical Report).