In this paper, a method for generating samples of a fully non-stationary zero-mean Gaussian process, having a target acceleration time-history as one of its own samples, is presented. The proposed method requires the following steps: i) divide the time axis of the target accelerogram in contiguous time intervals in which a uniformly modulated process is introduced as the product of a deterministic modulating function per a stationary zero-mean Gaussian sub-process, whose power spectral density (PSD) function is filtered by two Butterworth filters; ii) estimate, in the various time intervals, the parameters of modulating functions by least-square fitting the expected energy of the proposed model to the energy of the target accelerogram; iii) estimate the parameters of the PSD function of the stationary sub-process, once the occurrences of maxima and of zero-level up-crossings of the target accelerogram, in the various intervals, are counted; iv) obtain the evolutionary spectral representation of the fully non-stationary process by adding the various contribution evaluated in the various intervals.

在本文中，提出了一种生成具有目标加速时间历史作为其自身样本的完全非平稳零均值高斯过程样本的方法。所提出的方法需要以下步骤：i）将目标加速度图的时间轴划分为连续的时间间隔，在该时间间隔中，根据固定的零均值高斯子过程，引入统一调制过程作为确定性调制函数的乘积。功率谱密度（PSD）函数由两个Butterworth滤波器滤波；ii）在各个时间间隔内估算调制函数的参数通过最小二乘拟合将建议模型的预期能量与目标加速度图的能量进行拟合；iii）一旦在各个间隔内计算了目标加速度图的最大值和零水平向上交叉的次数，就估计固定子过程的PSD函数的参数；iv）通过添加在各个间隔中评估的各种贡献来获得完全非平稳过程的演化谱表示。