一种改进的ARMA模型参数估计方法

Improved Estimation Method for ARMA Model Parameters

针对自回归滑动平均(auto-regressive moving average,简称ARMA)模型参数谱估计容易出现谱峰漂移问题,提出一种基于组合目标函数和遗传算法的ARMA模型参数估计方法。通过最小均方误差准则获得ARMA模型参数初始估计,依据现代谱估计理论和连续函数极值存在的必要条件推导模型参数的频域约束方程,构造组合目标函数并采用遗传算法对模型参数初始估计值进行优化获得模型参数的最优解。将该方法用于车削状态下尾顶尖垂直方向振动加速度时间序列建模和谱估计,结果表明了方法的有效性。

To solve the problem of spectral peak deviation for auto-regressive moving average(ARMA) model parametric spectrum estimation,an ARMA parameter estimation method combined by objective function and gene algorithm(GA) is proposed.An initial estimate of the model parameters is acquired by minimizing Least Square Error.The constraint equation is derived according to modern spectrum theory and the necessary condition for the extreme value of continuous function.The combined objective function is constructed and the GA is used to optimize the initial parameter estimation.The method is used for modeling the vertical vibration acceleration data of back centre under turning condition and its spectrum estimation.Results demonstrate its efficiency.