A structural health monitoring (SHM) program can improve the structural integrity of offshore structures, however, the SHM scheme implies extraction of linear time-invariant modal parameters by Operational Modal Analysis (OMA). Inherently, the offshore platforms are nonlinear, and in many cases, the dynamics of the platforms are involving a friction-induced coupling that stems from bearings in the bridges connecting the platforms. This mechanism is causing the platforms to interchange between acting either as one system or separate systems, depending on the sliding or sticking state of the bearings. Along these lines, the present paper proposes an identification framework employing nonlinearity optimised random decrement (NORD) and OMA parameter estimation methods to identify two sets of underlying linear modes, relative to the state of the friction-induced coupling, both from the same measurement record.
Improvement of the structural integrity of civil engineering structures like offshore platforms and wind turbines can be accomplished through the application of structural health monitoring (SHM). The approach of SHM is practically carried out by monitoring and analysing the vibrations of the structures, whereby information of fatigue wear, possible damages etc. can be acquired. Within this framework, one of the fundamental steps to obtain this structural information is to extract the modal parameters by employing Operational Modal Analysis (OMA). However, the dynamic behaviour of offshore platforms is generally nonlinear and nonstationary, thus, contradicting the fundamental assumption of linear time-invariant systems in OMA (Brincker and Ventura, 2015). Especially, the concern of this study is on systems that consist of platforms with a friction-induced coupling caused by sliding bridge bearings in the bridge connecting the platforms. This particular mechanism is causing significantly different, interchanging behaviour, since the platforms can act either as one complete system or two separate systems depending on the sliding or sticking state of the bearings. With these interchanging modal characteristics throughout a single vibration measurement record of the offshore platforms, it becomes difficult to carry out an SHM program. Along these lines, the present article proposes an identification framework, for which the interchanging modes can be estimated in an output only manner. Consecutively, the framework is aiming to identify the underlying linear systems of both possible states from one measurement, which can be incorporated in traditional SHM context.
