Dynamic Load Identification Method for Multi-degree-of-freedom Nonlinear Systems Based on SRCKF Algorithm

In order to identify the external dynamic load of a single dimensional, multi-degree-of-freedom system with nonlinear stiffness damping, such as a railway car coupler, a loads identification method based on the square root cubature Kalman filter（SRCKF） algorithm is proposed. Taking a two-degree-of-freedom nonlinear spring-damped system as an example, a nonlinear process function containing external dynamic load and state variables of system components is established. The external dynamic load is identified based on the square root cubature Kalman filtering algorithm with the vibration acceleration of each degree-of-freedom as the observed quantity. The simulation results indicate that the method can identify the random load on the multi-degree-of-freedom nonlinear system well. The correlation coefficients of the identification results for the stiffness nonlinear and the damping nonlinear system are 0.997 and 0.999, respectively.