摘要
高速铁路沉降监测数据采集过程中,通常因仪器、环境等因素导致其含有噪声。本文将极点对称模态分解(ESMD)方法引入到高速铁路沉降监测数据处理中,分析适用于ESMD算法的去噪方法,并结合传统去噪方法,采用数学模拟仿真实验和某高速铁路实测沉降监测数据,验证其可行性和有效性。分析结果表明,基于ES-MD的去噪算法处理后的沉降监测数据具有均方根误差最小、信噪比最大、与原始数据互相关系数最高的特点,该方法能够很好消除沉降监测数据中混杂的随机误差和异常波动,提高沉降监测数据的质量和可靠性。
In the process of high-speed railway settlement monitoring data acquisition,it usually contains noise due to instruments,environment and other factors.In this paper,the Extreme-point Symmetrical Mode Decomposition(ESMD)method is introduced into the settlement monitoring data processing of high-speed railway,and the denoising method suitable for ESMD algorithm is analyzed.Combined with the traditional denoising method,mathematical simulation experiments and measured settlement monitoring data of a high-speed railway are used to verify its feasibility and effectiveness.The analysis results show that the settlement monitoring data processed by the denoising algorithm based on ESMD have the characteristics of minimum root mean square error,maximum signal-tonoise ratio and the highest correlation with the original data.This method can eliminate the mixed random errors and abnormal fluctuations in the settlement monitoring data,and improve the quality and reliability of settlement monitoring data.
作者
何鹏
武思源
罗超
周诚勇
HE Peng;WU Siyuan;LUO Chao;ZHOU Chengyong(Faculty of Geoscience and Environmental Engineering,Southwest Jiaotong University,Chengdu 611756,China;China Construction Southwest Survey,Design and Research Institute Co.,Ltd.,Chengdu 610051,China)
出处
《测绘与空间地理信息》
2023年第5期162-166,共5页
Geomatics & Spatial Information Technology
