A Study on Tension Monitoring of Cable-Beam Structure by Using a Sequential Data Assimilation Technique

Abstract

In this study, the sequential data assimilation (SDA) methods for tension monitoring of the cable-beam structure are presented via two different approaches. In the first approach, the axial stiffness of the cable is set as a model parameter for the SDA. In this approach, the change in cable tension is monitored directly as a variation in cable stiffness, while a nonlinear sequential Bayesian filter is needed for the SDA. Although nonlinear sequential Bayesian filters can adequately handle nonlinear problems; they are often computationally expensive. In the second approach, we propose another method to circumvent nonlinearities in the estimation by setting a pseudo-temperature variation of cable as a model parameter, where the linear Kalman filter is used for the SDA. A simple cable-beam structure model with two support cables attached to a cantilever beam is given for numerical examples. The comparisons of efficiency for tension monitoring of the cable-beam structure in both approaches are indicated.