Structural Health Monitoring Using Smart Sensors - ideals ...

zj
=
yp l p u – p j + yp u p j – p l
=
p l
L a
m= p l – N +
L a
h' p l
– L a
mxm
p u
–
p j
p u
L a
+ h' p u – L a mxm
p j – p l
m= p u – N +
p j
= jM r
+ l i
p l = jM r + l i
p u = p l +
L a
(5.28)
Then linear interpolation is performed by casting all associated integers to double
precision data. The final outcome is adjusted to account for the scaling factor of the filter
coefficients. In this way, implementation of the proposed resampling approach becomes
less numerically challenging.
5.4 Summary
Middleware services for smart sensors were developed in this chapter. Model-based
data aggregation, including distribution and coordination, provided scalability to a large
number of smart sensors without sacrificing performance of the SHM algorithms. The
data loss problem, which was shown to have adverse effects on an SHM algorithm, was
addressed by developing reliable communication protocols. To realize synchronized
sensing, a resampling-based approach was proposed. These middleware services are
implemented on the Imote2 running TinyOS. In Chapter 7, these middleware services will
be used in realization of an SHM system.
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