An OSA-CBM Multi-Agent Vehicle Health Management Architecture for Self-Health Awareness

Integrated Vehicle Health Management (IVHM) systems on modern aircraft or autonomous unmanned vehicles should provide diagnostic and prognostic capabilities with lower support costs and amount of data traffic. When mission objectives cannot be reached for the control system since unanticipated operating conditions exists, namely a failure, the mission plan must be revised or altered according to the health monitoring system assessment. Representation of the system health knowledge must facilitate interaction with the control system to compensate for subsystem degradation. Several generic architectures have been described for the implementation of health monitoring systems and their integration with the control system. In particular, the Open System Architecture - Condition-Based Maintenance (OSA-CBM) approach is considered in this work as initial point, and it is evolved in the sense of self-health awareness, by defining an appropriated multi-agent smart health management architecture based on smart device models, communication agents and a distributed control system. A case study about its application on fuel-cells as auxiliary power generator will demonstrate the integration.

[1]  D. M. Hutton,et al.  Multiagent Systems for Manufacturing Control A Design Methodology , 2006 .

[2]  Karl Reichard,et al.  Utilizing dcom in an open system architecture framework for machinery monitoring and diagnostics , 2003, 2003 IEEE Aerospace Conference Proceedings (Cat. No.03TH8652).

[3]  Josep Lluís de la Rosa i Esteva,et al.  Opinion-Based Filtering through Trust , 2002, CIA.

[4]  Gustavo González Sánchez,et al.  Towards smart user models in open environments , 2003 .

[5]  Jason Weston,et al.  Multi-Class Support Vector Machines , 1998 .

[6]  Ashok Srivastava,et al.  Aviation Safety Program Integrated Vehicle Health Management Technical Plan Summary , 2007 .

[7]  David G. Stork,et al.  Pattern Classification , 1973 .

[8]  Gustavo González,et al.  A Multi-agent Smart User Model for Cross-domain Recommender Systems , 2005 .

[9]  Byeong Seok Ahn,et al.  Multiattribute decision aid with extended ISMAUT , 2006, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[10]  Alfred Kobsa,et al.  Generic User Modeling Systems , 2001, User Modeling and User-Adapted Interaction.

[11]  Marcus Bengtsson Condition Based Maintenance System Technology - Where is Development Heading? , 2004 .

[12]  Karl M. Reichard Integrating self-health awareness in autonomous systems , 2004, Robotics Auton. Syst..

[13]  David G. Stork,et al.  Pattern classification, 2nd Edition , 2000 .

[14]  Vicent J. Botti,et al.  Towards an abstract recursive agent , 2004, Integr. Comput. Aided Eng..

[15]  Arch W. Naylor,et al.  On Decomposition Theory: Generalized Dependence , 1981, IEEE Transactions on Systems, Man, and Cybernetics.

[16]  Michael Wooldridge,et al.  Introduction to multiagent systems , 2001 .

[17]  J. Dale,et al.  Towards an Abstract Service Architecture for Multi-Agent Systems , 2003 .

[18]  Josep Lluís de la Rosa i Esteva,et al.  Smart User Models for Tourism: A Holistic Approach for Personalized Tourism Services , 2003, J. Inf. Technol. Tour..

[19]  Andreu Català,et al.  K-SVCR. A Multi-class Support Vector Machine , 2000, ECML.

[20]  Josep Lluís de la Rosa i Esteva,et al.  Collaboration Analysis in Recommender Systems Using Social Networks , 2004, CIA.

[21]  L.C. Trevino,et al.  A framework for integration of IVHM technologies for intelligent integration for vehicle management , 2005, 2005 IEEE Aerospace Conference.

[22]  David J. Weiss,et al.  SMARTS and SMARTER: Improved Simple Methods for Multiattribute Utility Measurement , 2008 .