A cointegration approach for cable anomaly warning based on structural health monitoring data: An application to cable-stayed bridges

For long-span cable-stayed bridges, cables are one of the most important components to resist various actions. With the application of structural health monitoring technique, real-time recording of cable forces is achieved, and hence, the warning system on cable anomaly established. However, it is still difficult and there are challenges to conduct the warning system effectively, especially due to the phenomena of false alarm or omission. A practical reason is the warning index’s sensitivity to the ambient environment. Temperature variations, for instance, usually disturb the force-based cable anomaly warning and result in the false evaluation of structural condition. In view of eliminating the effects of environmental temperature, cointegration, a statistical concept from econometrics, is employed in cable anomaly warning studies. An approach that extracts warning index by linear combination of two non-stationary time series using the cointegration algorithm is developed in order to produce a more stationary cointegrated residual series (warning index series). The calculated stationary relationship between two time series is insensitive to the influence of environmental temperature and is capable of cable anomaly warning. Specifically, the framework of the cable anomaly warning system is first proposed. Subsequently, time-series test methods are introduced to check the non-stationary order and calculate the cointegration parameters of measured cable forces and environmental temperature. The computed cointegrated residual series is fed into statistical analysis as a warning index and the procedure of cable anomaly warning under the influence of environmental temperature is illustrated in detail. Finally, a case study for a cable-stayed bridge is demonstrated with results and discussions.