Interpretation of stabilization diagrams using density-based clustering algorithm - Boroschek, Ruben L.; Bilbao, Joaquin A. (Engineering structures, 2019)
•A density-based algorithm for manual and automatic identification is proposed.•The proposed methodology is based on OPTICS clustering algorithm.•A new parameter to estimate the reliability of an identified mode is presented. The estimation of modal parameters is a critical requirement in structural health monitoring, damage detection, design validation, among other topics. The most prevalent methodology for manual identification is via an interpretation of a stabilization diagram. A density-based algorithm for automatically interpreting this type of diagram is proposed. The method employs three stages of interpretation. First, hard criteria are used to discard distinct spurious modes. Second, a density-based algorithm, Ordering Points to Identify the Clustering Structure (OPTICS), is used to cluster data. Finally, the modal parameters are selected taking into account the density distribution of the clustered values. Automation on the procedure is proposed, tested and applied to the vibration measurements of a building structure that has been continuously monitored since 2009. The results indicate a satisfactory interpretation, despite the low signal-to-noise ratios, the effect of induced electric noise, the low density of the sensors, different ambient conditions, and the occurrence of earthquake events.