Damage detection under environmental and operational effects using cointegration analysis – Application to experimental data from a cable-stayed bridge

Abstract

Abstract One of the main challenges that Structural Health Monitoring (SHM) faces when transitioning from academia to real-world applications is the discernment between structural changes due to damage and normal environmental, operational and long-term effects. In this context, a strategy for early damage detection based on multivariate cointegration analysis and statistical process control is proposed. The effects of environmental and operational variations are suppressed using cointegration analysis, being the cointegrating vector estimated following the multivariate Johansen procedure. The cointegrated residuals are then used for novelty detection by means of the Hotelling T2 control chart. The proposed strategy is systematised and is applied to a large prestressed concrete cable-stayed bridge of which 3.5 years of data are available, being the stay-cable forces used as damage sensitive-features. Several damage scenarios are studied involving increasing section loss of the stay cables. The damage intensities that can be detected using the proposed methodology and the available sensory system are quantified.