基于运营期地铁轨行区监测数据的去噪小波基函数选取  

Selection of Denoising Wavelet Basis Function Based on Monitoring Data of Subway Line Area during Operation

作　　者：余腾[1] 胡伍生[2] 赵升峰[3] 孙小荣[1] 陈永祥 

机构地区：[1]宿迁学院建筑工程学院,江苏宿迁223800 [2]东南大学交通学院,南京210096 [3]南京市测绘勘察研究院有限公司,南京210019 [4]江苏省地质矿产局第一地质大队,南京210041

出　　处：《铁道标准设计》2017年第8期116-120,共5页Railway Standard Design

基　　金：国家自然科学基金项目(41574022);江苏省科技支撑(工业)项目(BE2014026);江苏省高校自然科学研究项目(13KJB420004)

摘　　要：基于在用小波方法去除监测数据噪声时对于小波基选取尚无理论依据的现状,以运营期南京地铁2号线某区间的轨行区连续监测数据为例,提出采用小波阈值去噪法对连续长期轨行区监测数据进行处理。结合小波基选取的一般原则,选取3种常用小波基系结合实例数据进行研究,分析小波基去噪后残差余量,并基于均方根误差和信噪比指标分析不同基函数的去噪效果。计算实例表明,选用sym4小波基函数进行去噪,可获得更小的均方根误差,从而提高监测数据的信噪比,值得在地铁及相关变形监测数据处理中推广。Concerning the situation that there is no theoretical basis for the selection of wavelet basis,the wavelet threshold denoising method is employed to deal with the data from continuous long track line with reference to a section of Nanjing No. 2 subway line. Combined with the general principles for the selection of wavelet basis,three kinds of common wavelet basis are selected and combined with case data to study the wavelet denoising residual error and analyze the denoising effect of different basis functions based on the root mean square error and signal-noise ratio. The calculation results show that,when the sym4 wavelet function is used to denoise,the smaller root mean square error can be obtained to improve the SNR of the monitoring data. This method sees wide application in processing subway deformation monitoring data.

关 键 词：地铁 小波基函数 去噪 信噪比 

分 类 号：U231[交通运输工程—道路与铁道工程]