Data-driven structural identification of nonlinear assemblies: Structures with bolted joints

The identification of nonlinearities that have a significant impact on dynamic behaviour complex mechanical structures is necessary for ensuring structural efficiency and safety. A new methodology nonlinear assemblies proposed in this paper enables the discovery stiffness damping models especially when it not possible to directly measure degrees freedom where non-trivial are located. Input-output time-domain data collected at accessible locations structure used learn unmeasured locations. This accomplished by making use virtual sensing model reduction schemes along with physics-informed method recently developed authors (Safari Londoño 2021). suited weakly systems localised which their location assumed be known. It also takes into account dominant modal couplings within process. demonstrated case study frictional bolted joint, numerical experimental settings. shown selection parameter estimation elements can carried out successfully based reduced-order includes only equation relevant contributions. Using identified models, both reduced full-order updated simulate dynamical responses structure. Results suggests model, albeit simple, generalises well terms being able estimate around modes were during interpretable sense physically meaningful since discovered from predefined library featuring different characteristics.