A statistical vibration-based damage identification algorithm to assess the stability of the measurement data, detect and
locate damage in civil structures, where variability in response and modal parameters due to measurement noise and
environmental influence is often inevitable, is presented in this paper. The algorithm utilizes the statistical correlation of
the magnitudes of frequency response function (FRF) of target sensors relative to a reference sensor to assess the
consistency of the data while the slopes of lines of fit are exploited for damage localization. Through numerical
simulation and experimental investigation of a flexural structure using accelerometers and "point" strain gauges, and
long gauge fiber Bragg gratings (FBG) sensors, the importance of the technique for civil SHM is established and
presented in an easy-to-interpret graphical format for effective implementation of results. The proposed method using
long-gauge FBG sensors is suitable for practical civil SHM with limited number of sensors and where variability in
response and modal parameters due to measurement noise and environmental influence is often inevitable. Also, the
ability to effectively manage and make sense of enormous amounts of data collected under continuous monitoring
process for an effective diagnostic and/or prognostic system is an added advantage.
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