Health Assessment of Engineering Structures Using Graphical Models - Structural Seismic Design Optimization and Earthquake Engineering - page 367

level and not at the local level, this step was not
considered in this chapter.

linear material behavior need to be studied. The
study also considered a single damage to occur
at a time. The inclusion of multiple damages will
be considered in a future work. Notwithstanding
these shortcomings, it is believed that bond graphs
will open the door for new useful applications
in system identification and structural control
of engineering structures. The issue of sensor
performance is particularly relevant in the field
of road infrastructure where the loading condi-
tions affecting the main structure (traffic load,
temperature cycling, etc.) affect also the sensor
performance. It is difficult, however, to consider
all these concerns in this chapter.

10. CONCLUDING REMARKS
AND FUTURE CHALLENGES

A new graphical energy-based framework for
dynamic analysis and health assessment of dy-
namic systems is developed in this chapter. This
framework is based on the bond graph theory, the
associated temporal causal graphs, the derived
damage signatures and the least-squares optimiza-
tion method. The framework is different from other
frameworks in the sense that it enables performing
qualitative system identification first, thus reduc-
ing the computations significantly. Subsequently,
damage quantification is carried out if necessary.
BG is shown to represent the system equations of
motion in an implicit graphical form. The TCG
links the system response to changes in the sys-
tem components and sensor measurements which
facilitates deriving qualitative effects of changes
in system response on system components. The
advantages of the BG framework are: (1) Simple
graphical-modeling tool for dynamic systems,
(2) Unified (domain-independent) framework
for dynamic analysis and health assessment of
dynamic systems across multiple domains (e.g.,
structural, mechanical, electrical, hydraulic, etc.),
(3) Rapid qualitative identification of the damage
location, thus reducing the computations, (4) The
ability to identify sensor faults, (5) The ability to
perform online diagnosis, based on continuous
monitoring, (6) Reduction of data processing,
online computations and associated errors due
to absence of transformation to other domain
or approximations in feature selection, and (7)
Rapid quantification of damage size since only
the substructure containing damage is analyzed.
In this chapter, linear structural behavior and
relatively simple structures are considered. More
complex systems, continuum elements and non-

ACKNOWLEDGMENT

This study was partly supported by funds from the
U. S. Air Force Research Laboratory (Grant No.
USAF- 0060-43-0001). This support is greatly
acknowledged.

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