Description
Within Operational Modal Analysis (OMA) and Structural Health Monitoring (SHM) frameworks, novelty analysis aims to detect structural anomalies by inspecting the time evolution of the modal parameters of a structure subjected to ambient (unknown) excitations. However, real structures are subjected not only to structural anomalies, but also to environmental and operational variability (EOV), so it is necessary to remove EOV effects from damage-sensitive features.
The paper presents an application of Cointegration technique to account for EOVs on natural frequencies by constructing a new time-series mostly sensitive to structural anomalies. In detail, given a set of non-stationary time-series, Cointegration builds a stationary linear combination of them, namely the cointegration residual, which is purged from the common trends mainly associated with EOV.
The coefficients of the linear combination are determined by a maximum-likelihood multivariate technique, employing the natural frequencies to construct a cointegrating relationship within a training period, in which the structure is supposed to be in healthy conditions, under normal EOV. Once trained, the computed coefficients are used to test natural frequencies from unknown scenarios. The obtained cointegration residual will maintain its stationarity, as long as the structure behaves in normal conditions. Compared to traditional minimization techniques, the Cointegration relies on more general operations, such as the construction of a linear combination given a set of modal parameters.
The application of the presented procedure is exemplified with data measured in Baixo Sabor dam (Portugal) during the first two years of monitoring, which include the first filling of the reservoir.
