车轮转速信号混合噪声的非线性Volterra滤波方法

Removing mixed noise in locomotive wheel speed signal with a nonlinear Volterra filter

为保证机车黏着控制品质,提出车轮转速信号所含混合噪声(高斯噪声和冲击噪声)的非线性Volterra滤波方法,并结合混沌优化策略及动态随机局部搜索算子,提出动态随机局部搜索生物地理优化算法对Volterra滤波器模型参数进行优化求解.利用Volterra滤波器的结构优势(具有预测性能、兼具线性和非线性项),既能滤除混合噪声又可满足黏着控制的实时性要求.仿真实验结果表明,经优化求解的非线性Volterra滤波器实现了对车轮转速信号所含混合噪声的有效滤除.

In order to improve the design accuracy of the adhesion controller to ensure the quality of loco- motive optimization control, a nonlinear Volterra filtering method was proposed for the removal of mixed noise （Gaussian noise and spike noise） contained in the wheel speed signal. The nonlinear Volterra filter model for wheel speed signal was established on the Volterra series, and combined with the chaos optimi- zation strategy and dynamic random local search operator, a dynamic random local search biogeography- based optimization algorithm was proposed and applied to solve the parameters of the nonlinear Volterra filter model. Simulation results showed that, by utilizing the dual characteristics （linear and nonlinear characteristics） of the Volterra filter and the good searching ability of the dynamic random local search biogeography-based optimization algorithm, the optimized nonlinear Volterra filter could effectively re- move the mixed noise contained in the wheel speed signal.