Vibration-based Structural Health Monitoring Technique Using Statistical Features from Strain Measurements

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 method exploits the regression analysis of peak values of the magnitudes of frequency response function (FRF) of target sensors relative to the reference wherein the statistical features are employed for data reliability assessment and damage localization. Through experimental investigation of a flexural structure using conventional 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 statistical approach is very effective for damage localization using strain data.