Identification of nonlinear bolted lap joint parameters using instantaneous power flow balance-based substructure approach

This paper presents a novel nonlinear lap joint parameter identification method based on the instantaneous power flow balance approach, which includes structural nonlinear parameters for realistic modelling. In the present approach, substructure instantaneous power flow balance, whereby the algebraic sum of input power, dissipated power, transmitted power, and time rate of kinetic and strain energy is equated to zero, is used as an objective criterion to formulate an inverse problem for nonlinear joint parameter identification. The correct values of the nonlinear coefficients are estimated by minimizing the objective function using the particle swarm optimization algorithm. The substructure-based identification strategy reduces the number of sensor requirements and also improves the identification performance than the global identification technique. The method was applied to experiments involving a steel beam assembly connected by a single bolted lap joint with various tightening torques. Furthermore, validation studies were also conducted to predict the effectiveness of the proposed method in nonlinear parameter identification. The experimental structure applications have shown that the proposed method is effective for the nonlinear parameter identification of joints.