1673-159X

CN 51-1686/N

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: 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。

     

    Abstract: 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.

     

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