This paper deals with the problem of damage detection using output-only vibration measurements under changing environmental conditions. Two types of features are extracted from the measurements: eigenproperties of the structure using an automated stochastic subspace identification procedure and peak indicators computed on the Fourier transform of modal filters. The effects of environment are treated using factor analysis and damage is detected using statistical process control with the multivariate Shewhart-T control charts.A numerical example of a bridge subject to environmental changes and damage is presented. The sensitivity of the damage detection procedure to noise on the measurements, environment and damage is studied. An estimation of the computational time needed to extract the different features is given, and a table is provided to summarize the advantages and drawbacks of each of the features studied. r

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Structural health monitoring aims to provide an accurate diagnosis of the condition of civil infrastructures during their life span using data acquired by sensors. Wireless sensor networks represent a suitable monitoring technology to collect reliable information about the structure's condition, replacing visual inspections, and reducing installation and maintenance time and costs. This article introduces a time synchronized and configurable wireless sensor network for structural health monitoring enabling a highly accurate identification of the modal properties of the monitored structure. The wireless sensor nodes forming the network are equipped with a 3-axis digital accelerometer and a temperature and humidity sensor. The implemented Medium Access Control layer time synchronization protocol (μ-Sync) ensures a highly accurate synchronicity among the samples collected by the nodes, the absolute error being constantly below 10 μs, also when high sampling frequency (up to

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