基于FFT-STL的大坝监测数据时效分量提取与分析算法

FFT-STL-based Algorithm for Extracting and Analyzing the Aging Component of Dam Monitoring Data

研判监测物理量的变化趋势是否向危险方向发展是大坝监测资料定量分析的主要目的,但传统方法易受人为因素的影响。为此,提出了一种基于FFT-STL的大坝监测数据时效分量提取与分析算法,该算法采用FFT算法计算监测数据的周期,并将其作为输入参数传递给STL分解算法,自动提取数据的时效分量,采用不同类型的时效分量模型分别回归拟合优选最佳模型,最后依据变化速率对时效分量的趋势进行研判。经实例分析证明,与传统算法相比,所提算法能准确可靠地反映大坝安全监测数据的变化和发展趋势,且具有更好的适应性。

The main purpose of quantitative analysis of dam monitoring data is to determine whether the change trend of the monitored physical quantities is in the direction of danger,but the traditional methods are vulnerable to human factors.Therefore,this paper proposes an FFT-STL-based algorithm for extracting and analyzing the aging component of dam monitoring data.The algorithm uses the FFT algorithm to calculate the period of monitoring data,and passes it to the STL decomposition algorithm as input parameters to automatically extract the aging component of the data.The optimal model was selected by regression fitting of different types of aging component models.Finally,the trend of the aging component is studied according to the rate of change.Compared with the traditional algorithm,the algorithm in this paper can accurately and reliably reflect the changes and development trend of dam safety monitoring data,and has better adaptability.