Integrated System Health Management: Foundational Concepts, Approach, and Implementation

A sound basis to guide the community in the conception and implementation of ISHM (Integrated System Health Management) capability in operational systems was provided. The concept of "ISHM Model of a System" and a related architecture defined as a unique Data, Information, and Knowledge (DIaK) architecture were described. The ISHM architecture is independent of the typical system architecture, which is based on grouping physical elements that are assembled to make up a subsystem, and subsystems combine to form systems, etc. It was emphasized that ISHM capability needs to be implemented first at a low functional capability level (FCL), or limited ability to detect anomalies, diagnose, determine consequences, etc. As algorithms and tools to augment or improve the FCL are identified, they should be incorporated into the system. This means that the architecture, DIaK management, and software, must be modular and standards-based, in order to enable systematic augmentation of FCL (no ad-hoc modifications). A set of technologies (and tools) needed to implement ISHM were described. One essential tool is a software environment to create the ISHM Model. The software environment encapsulates DIaK, and an infrastructure to focus DIaK on determining health (detect anomalies, determine causes, determine effects, and provide integrated awareness of the system to the operator). The environment includes gateways to communicate in accordance to standards, specially the IEEE 1451.1 Standard for Smart Sensors and Actuators.

[1]  Fred M. Discenzo,et al.  Open Systems Architecture Enables Health Management for Next Generation System Monitoring and Maintenance Development Program White Paper , 2001 .

[2]  William A. Maul,et al.  Hybrid diagnostic system: beacon-based exception analysis for multimissions - Livingstone integration , 2004 .

[3]  Mark Hedley,et al.  Structural Health Management for Future Aerospace Vehicles , 2004 .

[4]  Fernando Figueroa,et al.  Rocket Testing and Integrated System Health Management , 2006 .

[5]  Kang Lee Sensor networking and interface standardization , 2001, IMTC 2001. Proceedings of the 18th IEEE Instrumentation and Measurement Technology Conference. Rediscovering Measurement in the Age of Informatics (Cat. No.01CH 37188).

[6]  Han G. Park,et al.  Gray-Box Approach for Fault Detection of Dynamical Systems , 2003 .

[7]  Robi Polikar,et al.  An architecture for intelligent systems based on smart sensors , 2005, IEEE Transactions on Instrumentation and Measurement.

[8]  Edward N Brown,et al.  Applying Health Management Technology to the NASA Exploration System-of-Systems , 2005 .

[9]  Fernando Figueroa,et al.  Test Stand and J-2X Engine End-to-End Integrated System Health Management Demonstration , 2007 .

[10]  A. Bajwa,et al.  The livingstone model of a main propulsion system , 2003, 2003 IEEE Aerospace Conference Proceedings (Cat. No.03TH8652).

[11]  Fritz Kuck,et al.  Space Shuttle Main Engine (SSME) Options for the Future Shuttle , 2002 .

[12]  John Stephens,et al.  Advanced Health Management System for the Space Shuttle Main Engine , 2004 .

[13]  David Coote,et al.  NASA Stennis Space Center integrated system health management test bed and development capabilities , 2006, SPIE Defense + Commercial Sensing.

[14]  Ajay Mahajan,et al.  Intelligent Sensors: Strategies for an Integrated Systems Approach , 2005 .

[15]  W. Lance Richards,et al.  Flight Demonstration of X-33 Vehicle Health Management System Components on the F/A-18 Systems Research Aircraft , 2001 .

[16]  C.T. Mata,et al.  A Kennedy Space Center implementation of IEEE 1451 networked smart sensors and lessons learned , 2006, 2006 IEEE Aerospace Conference.

[17]  Donald J. Malloy,et al.  DEVELOPMENT OF A NEAR REAL-TIME TURBINE ENGINE TESTING DIAGNOSTIC SYSTEM USING FEATURE EXTRACTION ALGORITHMS * , 1997 .

[18]  Kang B. Lee Smart Transducer Interface Standards for Condition Monitoring and Control of Machines , 2006 .

[19]  Mark Shirley,et al.  Applying Model-Based Reasoning to the FDIR of the Command and Data Handling Subsystem of the International Space Station , 2003 .

[20]  Mark James,et al.  BEAM: technology for autonomous vehicle health monitoring , 2002 .

[21]  Benjamin Kuipers,et al.  Reasoning with Qualitative Models , 1993, Artif. Intell..

[22]  Ajay Mohan Mahajan,et al.  Dynamic across time autonomous-sensing, interpretation, model learning and maintenance theory , 1994 .

[23]  J. Schmalzel,et al.  Integrated system health management (ISHM): systematic capability implementation , 2006, Proceedings of the 2006 IEEE Sensors Applications Symposium, 2006..