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

为识别铁道车辆车钩等存在非线性刚度阻尼的单一维度、多自由度系统的外部动载荷,提出一种基于平方根容积卡尔曼滤波(SRCKF)算法的载荷识别方法。以一个二自由度的非线性弹簧阻尼系统为例,建立包含外部动载荷和系统部件状态变量的非线性过程函数,以各自由度振动加速度为观测量,基于平方根容积卡尔曼滤波算法识别外部动载荷。仿真结果表明,该方法可以较好地识别作用在多自由度非线性系统上的随机载荷,刚度非线性系统和阻尼非线性系统的识别结果相关系数分别为0.997和0.999。

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.