A wireless sensing unit is designed for application in structural monitoring and damage detection system. Embedded in the wireless monitoring module, a two-tier prediction model, using auto-regressive (AR) and the autoregressive model with exogenous inputs (ARX) is used for obtaining the damage sensitive feature. To validate the performance of the proposed wireless monitoring and damage detecti...

An integrated method is proposed for structural nonlinear damage detection based on time series analysis and the higher statistical moments of structural responses in this study. It combines the time series analysis, the higher statistical moments of AR model residual errors and the fuzzy c-means (FCM) clustering techniques. A few comprehensive damage indexes are developed in the arithmetic and...

Output-based structural damage detection is becoming increasingly appealing due to its potential in real engineering applications without any restriction regarding excitation measurements. A new transmissibility-based damage detection approach is presented in this study by combining transmissibility with correlation analysis in order to strengthen its performance in discriminating damaged from ...

The real virtue of a wireless sensor network is the fact that it is a new sensing paradigm offering distributed data processing capacity, which can be used for structural health monitoring. For this purpose, a smart wireless sensor network is established for autonomous structural damage detection in this paper. The designed wireless sensor network has a two-level cluster-tree architecture. Dist...

In this paper, a novel approach proposed for structural damage detection from limited number of sensors using extreme learning machine (ELM). As the number of sensors used to measure modal data is normally limited and usually are less than the number of DOFs in the finite element model, the model reduction approach should be used to match with incomplete measured mode shapes. The second-order a...