高速公路路基路面健康监测数据处理方法及其效果评估  

Data Processing Methods and Effectiveness Evaluation for Health Monitoring of Highway Subgrade and Pavement

作　　者：王书娟[1] 陈志国[1] 王亚博 易军艳[2] Wang Shujuan;Chen Zhiguo;Wang Yabo;Yi Junyan(Key Laboratory of Highway Construction and Maintenance Technology in Seasonally Frozen Regions,Traffic Industry,Jilin Institute of Transportation Science,Changchun 130012,China;School of Trafic Science and Engineering,Harbin Instituteof Technology,Harbin 150090,China)

机构地区：[1]吉林省交通科学研究所季节性冻土区公路建设与养护技术交通行业重点实验室,吉林长春130012 [2]哈尔滨工业大学交通科学与工程学院,黑龙江哈尔滨150090

出　　处：《市政技术》2025年第2期175-181,共7页Journal of Municipal Technology

基　　金：吉林省交通运输创新发展支撑(科技)项目(2022-1-4)。

摘　　要：随着交通运输行业的快速发展,高速公路作为重要的基础设施,面临着日益增长的交通量及其带来的重载压力与气候变化等外部因素的挑战,对路基和路面结构的安全性与使用寿命产生了深远影响。为保障高速公路的安全性与耐久性,实施路基路面的健康监测尤为重要。基于吉林某高速公路长寿命沥青路面试验段,构建了一个综合性的健康监测系统,布设了横向和纵向应变传感器、温度和湿度传感器、土压力计和渗压计等多种设备,实时采集路基和路面的动态响应特征和环境数据。然而,在监测过程中,存在数据冗余与存储、数据噪声、基线漂移和数据缺失或不完整等问题,严重影响了数据的质量及后续分析的可靠性。为此,提出了一系列数据处理方法,包括使用阈值法和斜率阈值法进行有效数据筛选,采用基线归零方法消除基线漂移,利用Savitzky-Golay滤波进行信号降噪,以及使用卡尔曼滤波处理数据缺失或不完整问题。研究结果表明,这些方法显著提高了数据质量和信噪比,其中Savitzky-Golay滤波有效保留了信号的关键特征。该研究为高速公路路基路面健康监测提供了高效且可靠的数据处理方案,显著提升了监测系统的整体性能,为路面养护和管理提供了科学依据。With the rapid development of the transportation industry,highways as critical infrastructure,are facing increasing traffic volumes,the external challenges of resulting heavy load pressures and climate change,which have profound impacts on the safety and service life of subgrade and pavement structures.In order to ensure the safety and durability of highways,health monitoring of subgrade and pavements is essential.Based on a long-life asphalt pave-ment test section of a highway in Jilin Province,a comprehensive health monitoring system was constructed,which was equipped with various devices,including transverse and longitudinal strain sensors,temperature and humidity sensors,soil manometer and Posmometer to collect real-time dynamic response characteristics and environmental data.However,during the monitoring process,issues such as data redundancy and storage,data noise,baseline drift,and data loss or incompleteness severely affected data quality and the reliability of subsequent analysis.Ther-fore,a series of data processing methods were proposed,including effective data filtering by threshold methods and slope threshold methods,eliminating baseline drift by baseline zeroing,signal noise reduction by Savitzky-Golay filtering,and handling data loss or incompleteness by Kalman filtering.The study results indicate that data quality and signal-to-noise ratio were significantly improved by these methods,key signal features was effectively pre-served by Savitzky-Golay filtering.This research provides an efficient and reliable data processing solution for the health monitoring of highway subgrade and pavements,significantly enhances the overall performance of the moni-toring system and offers a scientific basis for pavement maintenance and management.

关 键 词：路基路面 健康监测 噪声过滤 基线漂移 数据缺失 数据筛选 

分 类 号：U416[交通运输工程—道路与铁道工程]