Structural Health Monitoring (SHM) systems are widely regarded as capable of
significantly reducing inspection costs of safety-critical structures in industries such
as aerospace, nuclear, and oil and gas, among others. Successful SHM systems can
be considered those which combine good sensitivity to defects, preferably with the
capability of localization and identification, with a low sensor density. Techniques
based on sparse arrays of sensors which generate and receive guided waves are among
the most promising candidates. Guided waves propagate over large distances and
certain modes have the ability to transmit through a variety of structural features
leading to a relatively small number of distributed sensors being able to cover the
structure.
In complex structures, which contain high densities of structural elements, the timetraces
obtained are often too complex to be directly interpreted due to the large
number of overlapping reflections. In this case, the Baseline Subtraction technique
becomes attractive. In this method a current signal from the structure is subtracted
from a signal which has been acquired during the initial stages of operation of the
structure. This eliminates the need for interpretation of the complex raw time signal
and any defects will be clearly seen provided the amplitude of the residual signal obtained
after subtraction of the baseline signal is sufficiently low when the structure is
undamaged. However, it is well known that environmental effects such as stress, ambient
temperature variations and liquid loading affect the velocity of guided waves;
this modifies the time-traces and leads to high levels of residual signal if a single
baseline, taken under different conditions, is used. Of these effects, temperature
variations are the most commonly encountered and are critical since they affect not
only the wave propagation but also the response of transducers.
The present work aims to demonstrate the potential of guided wave health monitoring
of large area complex structures. It starts with a general literature review
on inspection and monitoring of large area structures, in which the advantages and
disadvantages of this technique compared to other well-established SHM techniques are presented. The design and behaviour of two different temperature-stable transducers
generating high A0 or S0 mode purity in the sub-200kHz frequency region
are described. The effciency of different signal processing techniques aimed at reducing
or eliminating the influence of temperature on wave propagation is evaluated
and a temperature compensation signal processing strategy is proposed. Finally, a
large metallic structure is used to demonstrate a sparse-array SHM system based
on this signal processing strategy, and imaging algorithms are used to combine the
information from a large number of sensor combinations, ultimately leading to the
localization of defects artificially introduced in the structure.