Local modal filters for automated data-based damage localization using ambient vibrations

• Automated data-based damage localization method based on ambient vibrations.
• Use of noisy strain measurements simulated in time domain, with environmental changes.
• Non-model based method relying on data from the undamaged structure only.
• Localization of very small damages (2% stiffness reduction in a very small area).
• Multivariate statistical analysis for automated alarm triggering using control charts.

The motivation of the paper is to develop a fully automated data-based technique for damage localization using in-service ambient vibrations. The idea is an extension of the modal filtering technique previously developed for damage detection. A very large network of dynamic strain sensors is deployed on the structure to be monitored and split into several independent local sensor networks. Simple and fast signal processing techniques are coupled to statistical control charts for efficient and fully automated damage localization. The efficiency of the method is demonstrated using time-domain simulated data on a simply supported beam and a three-dimensional bridge structure. The method is able to detect and locate very small damages (2% stiffness reduction in an area corresponding to 1/100th of the length of the structure) even in the presence of noise on the measurements and variability of the baseline structure.