This paper addresses the issue of intermittent data loss during transmission of wireless network sensors and the
application of the reconstruction signal for damage detection with the damage locating vector (DLV) method. The
algorithm makes use of frequencies which contribute significant amount of energy in the signal based on Fourier
transform. As the amplitudes are uncertain due to lost data, the Fourier amplitudes are estimated based on least-square fit
of only the measured portions of the signal. The lost portions are reconstructed through inverse Fourier transform. The
procedure is iterated until the discrepancy between estimated lost portions of two consecutive iterations is below a set
threshold. This threshold and the power spectral threshold to demarcate the significant frequencies are selected based on
results from numerically simulated signals. The reconstructed signals are used with the DLV method for damage
detection to investigate the practicality of this procedure. A cantilever truss structure with a pre-stressed cable was
monitored using six wireless sensors. The pre-stressed cable was cut mid-way during random load application and data
collection. The results obtained support the use of the reconstructed signal within the framework of the DLV method.
The damage locating vector (DLV) method based on dynamic response is (a) modified for structural damage detection
using normalized cumulative energy (instead of stress) indicator, (b) applied to the case where the number of sensors
used is small compared to the structural degrees of freedom, and (c) employed to identify multiple damaged elements of
an existing structure. From the measured structural dynamic response at the reference and damaged states, the change in
flexibility matrix at sensor locations is formulated based on which the DLV is calculated. The DLV is a set of static load
vector which has the property that when applied to the structure at its reference state, no energy is induced in the
damaged elements providing the basis to identify damaged elements. The efficiency and robustness of the proposed
method are examined using both simulated and experimental data.
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