3D linear identification of mechanical joint using FRF decoupling and inverse structural modification methods


33rd Conference on Mechanical Vibration and Sound, VIB 2021, Held as Part of the ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2021, Virtual, Online, 17 - 19 August 2021, vol.10 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 10
  • Doi Number: 10.1115/detc2021-70934
  • City: Virtual, Online
  • Keywords: Bolted joint, FRF decoupling, Joint identification


Copyright © 2021 by ASMEMechanical connections such as bolts and rivets are inevitable in most engineering structures and may significantly affect the dynamic behavior of the structures. Therefore, modeling a joint simply and accurately is essential for assembled structures. On the other hand, the most important step is the determination of these joint model parameters which will be used in the calculation of dynamic response of assembled structures. For this purpose, in this paper, FRF Decoupling Method (FRF-DM), proposed in an earlier study for bolted beam connections is extended in two ways: Firstly, the bolt model proposed for 2D beam elements is extended to 3D finite element models of structural systems, and thus the dynamics of a bolted connection is modeled as an equivalent 6×6 complex stiffness matrix including linear and torsional stiffnesses. Secondly, FRF-DM is extended to include measurements at connection degrees of freedoms, which improves the accuracy in identification. Several equations for the identification of joint parameters are derived utilizing FRF-DM. Joint parameters are calculated by using developed FRF decoupling relations, as well as by employing a recently developed method called Inverse Structural Modification Method (ISMM) in a case study consisting of two beams connected by a 6x6 stiffness and viscous damping matrices. The accuracy and the advantages of each method/formulation are discussed by using the case study based on simulated experiments.