Paper
30 March 2009 Structural damage detection using wireless sensors accounting for data loss
Author Affiliations +
Abstract
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.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
S. T. Quek, V. A. Tran, W. H. Duan, and X. Y. Hou "Structural damage detection using wireless sensors accounting for data loss", Proc. SPIE 7292, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2009, 72920A (30 March 2009); https://doi.org/10.1117/12.814991
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Sensors

Damage detection

Reconstruction algorithms

Signal attenuation

Signal detection

Fourier transforms

Matrices

Back to Top