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
李元梦 1李登华 2丁勇1
作者信息
- 1. 南京理工大学理学院,江苏 南京 210094
- 2. 南京水利科学研究院,江苏 南京 210029;水利部水库大坝安全重点实验室,江苏 南京 210029
- 折叠
摘要
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.
Abstract
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 fac-tors.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 opti-mal 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 pa-per can accurately and reliably reflect the changes and development trend of dam safety monitoring data,and has better a-daptability.
关键词
大坝监测/FFT/STL分解/时效分量Key words
dam monitoring/FFT/STL decomposition/aging component引用本文复制引用
基金项目
国家重点研发计划(2022YFC3005502)
国家自然科学基金项目(51979174)
国家自然科学基金联合基金项目(U2040221)
出版年
2024
NETL
NSTL
万方数据