CONCEPTS FOR AN INTEGRATED VEHICLE HEALTH
MONITORING SYSTEM
D. Abbott, B. Doyle, J. B. Dunlop, A. J. Farmer, M. Hedley, J. Herrmann, G. C. James,
M. E. Johnson, B. Joshi, G. T. Poulton, D. C. Price*, M. Prokopenko, T. Reda, D. E. Rees,
D. A. Scott, P. Valencia, D. Ward and J. G. Winter
CSIRO Telecommunications & Industrial Physics,
P.O. Box 218, Lindfield, NSW 2070, Australia
'Author to whom enquiries should be addressed: Don.Price@csiro.au
ABSTRACT. This paper describes some of the considerations involved in the development of an
intelligent integrated vehicle health monitoring system from a "top-down", systems perspective.
INTRODUCTION
Recent interest in smart sensor networks, and developments in technologies such as
MEMS, microelectronics, nanotechnology, communication networks and distributed
computing, have encouraged interest in the development of integrated vehicle health
monitoring (IVHM) systems. In the longer term, such systems will provide a basis for the
development of self-repairing, and perhaps even ageless, structures. In the shorter term,
IVHM could reduce or eliminate a number of present design constraints (e.g. relating to
redundancy and inspectability), allowing more efficient designs, and should reduce
maintenance and inspection requirements.
A multi-disciplinary team at CSIRO has begun developing concepts for IVHM
systems for aerospace vehicles as part of the NASA Robust Aerospace Vehicle Program
(RAV). RAV is a long-term program with an ultimate goal of the development of vehicles
capable of structural self-assessment and repair, and structural reconfiguration (morphing).
Generally these goals are well beyond the capabilities of current materials and
technologies, so it is neither necessary nor desirable to restrict consideration to present
materials, sensors, communications systems, etc.
An IVHM system is an example of an intelligent sensing system. The purpose of
such a system is to detect and measure certain quantities, and to use the information and
knowledge obtained from the measured data and any prior knowledge to make intelligent,
forward-looking decisions and initiate actions. The design of such a system must begin
from knowledge of the environment in which the system is to operate and the quantities it
is required to measure, and the actions that can be taken in response to the measurements.
One of the important characteristics of practical IVHM systems is that they will
generally consist of thousands, and perhaps millions, of sensors of different types
measuring different quantities. It is therefore essential that strategies for efficient handling
and usage of the vast amount of data generated are an integral component of the system
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