西华大学学报（自然科学版）2024，Vol.43Issue(1)：70-77,8.DOI:10.12198/j.issn.1673-159X.5253
基于SRCKF算法的多自由度非线性系统动载荷识别方法
Dynamic Load Identification Method for Multi-degree-of-freedom Nonlinear Systems Based on SRCKF Algorithm
摘要
Abstract
In order to identify the external dynamic load of a single dimensional,multi-degree-of-free-dom 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 identi-fied based on the square root cubature Kalman filtering algorithm with the vibration acceleration of each de-gree-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 iden-tification results for the stiffness nonlinear and the damping nonlinear system are 0.997 and 0.999,respect-ively.关键词
载荷识别/非线性系统/卡尔曼滤波/随机载荷/平方根容积卡尔曼滤波Key words
force measurement/nonlinear systems/Kalman filter/random load/square root cubature Kalman filte(SRCKF)分类
数理科学引用本文复制引用
龚璟淳,陈清华,厉砚磊,王开云..基于SRCKF算法的多自由度非线性系统动载荷识别方法[J].西华大学学报（自然科学版）,2024,43(1):70-77,8.基金项目
国家杰出青年科学基金(51825504) （51825504）
国家自然科学基金重点项目(U19A20110). （U19A20110）
