基于SG-SVD和波动抑制的沥青路面FBG感知信号降噪研究

doi:10.3969/j.issn.1674-0696.2026.07.08

重庆交通大学学报（自然科学版） ›› 2026, Vol. 45 ›› Issue (7): 67-75.DOI: 10.3969/j.issn.1674-0696.2026.07.08

• 智慧交通基础设施 • 上一篇

基于SG-SVD和波动抑制的沥青路面FBG感知信号降噪研究

黄婷婷1,2，刘宇佼3，沈典栋4，廖梦回1,2，陈彧1,2，余鑫4

(1. 武汉理工大学交通与物流工程学院，湖北武汉 430063； 2. 湖北省公路工程技术研究中心，湖北武汉 430063； 3. 武汉市工程咨询部有限公司，湖北武汉 430014； 4. 湖北交投京港澳高速公路改扩建项目管理有限公司，湖北武汉 430100)

收稿日期:2025-01-12 修回日期:2026-04-13 发布日期:2026-07-21
作者简介:黄婷婷（1992—），女，安徽六安人，讲师，博士,主要从事道路材料表面自由能理论方面的研究。E-mail:huangtingting@whut.edu.cn 通信作者：刘宇佼（2001—），女，湖南长沙人，硕士研究生，主要从事沥青路面智能监测方面的研究。E-mail:2359526609@qq.com
基金资助:
2022年湖北省交通运输厅科技项目（2022-11-2-5）

FBG sensing signal denoising of asphalt pavement based on SG-SVD and fluctuation suppression

Huang Tingting1,2,Liu Yujiao3, Shen Diandong4, Liao Menghui1,2, Chen Yu1,2, Yu Xin4

(1. School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan 430063, Hubei, China; 2. Hubei Provincial Highway Engineering Technology Research Center, Wuhan 430063, Hubei, China; 3. Wuhan Engineering Consulting Department Co., Ltd., Wuhan 430014, Hubei, China; 4. Hubei Communications Investment Group Beijing-Hong Kong-Macao Expressway Reconstruction and Extension Project Management Co., Ltd., Wuhan 430100, Hubei, China)

Received:2025-01-12 Revised:2026-04-13 Published:2026-07-21

摘要/Abstract

摘要： 为了提高光纤光栅传感器（fiber bragg grating, FBG）监测沥青路面结构内应变场和温度场的信号质量，提出一种联合卷积平滑（savitzky-golay, SG）、奇异值分解（singular value decomposition, SVD）以及波形抑制的光纤光栅感知信号降噪处理方法：首先进行信号的卷积平滑处理，减少信号不必要的波动；接着进行奇异值分解，结合奇异值大小筛选出主要的信号特征模式，实现数据的降维以及噪声过滤处理；最后强化数据特征并抑制信号非本质波动，增强数据稳定性。采用该方法进行路面结构响应仿真信号以及沥青路面实测结构响应信号的降噪处理，实测信号的峰值信噪比（peak signal to noise ratio, PSNR）由115.60 dB升高到121.48 dB，有效信号被增强，无效信号被削弱。该方法能够有效提高信号的可信度，更加真实监测行车荷载作用下沥青路面结构内部应变响应的变化信息。

关键词: 道路工程；沥青混合料；信号降噪；卷积平滑；奇异值分解；信噪比

Abstract: To improve the signal quality of fiber Bragg grating (FBG) sensors in monitoring the strain and temperature fields within asphalt pavement structures, an FBG sensing signal denoising processing method combining Savitzky-Golay (SG), singular value decomposition (SVD) and waveform suppression was proposed. First, convolution smoothing of the signal was carried out to reduce unnecessary fluctuations. Next, singular value decomposition was carried out, and the main signal feature patterns based on the size of singular values were selected out, achieving data dimensionality reduction and noise filtering processing. Finally, the data features were strengthened and non-essential signal fluctuations were suppressed to enhance data stability. The proposed method was applied for noise reduction processing of simulated signals of pavement structure response and measured structural response signals of asphalt pavement. The peak signal-to-noise ratio (PSNR) of the field-measured signal increased from 115.60 dB to 121.48 dB, with effective signals enhanced and ineffective signals weakened. The proposed method can effectively improve the credibility of signals and more accurately monitor the changes in internal strain response of asphalt pavement structures under driving loads.

Key words: highway engineering; asphalt mixture; signal noise reduction; Savitzky-Golay (SG); singular value decomposition; signal-to-noise ratio

中图分类号:

U416.217

黄婷婷1,2，刘宇佼3，沈典栋4，廖梦回1,2，陈彧1,2，余鑫4. 基于SG-SVD和波动抑制的沥青路面FBG感知信号降噪研究[J]. 重庆交通大学学报（自然科学版）, 2026, 45(7): 67-75.

Huang Tingting1,2,Liu Yujiao3, Shen Diandong4, Liao Menghui1,2, Chen Yu1,2, Yu Xin4. FBG sensing signal denoising of asphalt pavement based on SG-SVD and fluctuation suppression[J]. Journal of Chongqing Jiaotong University(Natural Science), 2026, 45(7): 67-75.

/ 推荐

参考文献

［1］ Liu Zhen, Gu Xingyu, Ren Hua, et al. Three-dimensional finite element analysis for structural parameters of asphalt pavement: a combined laboratory and field accelerated testing approach［J］. Case Studies in Construction Materials, 2022, 17: e01221.
［2］ Soman R, Balasubramaniam K, Golestani A, et al. Actuator placement optimization for guided waves based structural health monitoring using fiber bragg grating sensors［J］. Smart Materials and Structures, 2021, 30(12): 125011.
［3］ Kahandawa G C, Epaarachchi J, Wang Hao, et al. Use of FBG sensors for SHM in aerospace structures［J］. Photonic Sensors, 2012, 2(3): 203-214.
［4］ Maheshwari M, Tjin S C, Ching W W, et al. FBG and FOPS for local and global structural health monitoring on a single fiber［J］. Smart Materials and Structures, 2015, 24(4): 045033.
［5］ Liao Menghui, Liang Sheng, Luo Rong, et al. The cooperative deformation test of an embedded FBG sensor and strain correction curve verification［J］. Construction and Building Materials, 2022, 342: 128029.
［6］ Liao Menghui, Liang Sheng, Luo Rong, et al. The moving load identification method on asphalt roads based on the BP neural network and FBG sensor monitoring［J］. Construction and Building Materials, 2023, 378: 131216.
［7］ Yang Xinyi, Wang Xingyu, Podolsky J, et al. Assessing vehicle wandering effects on the accuracy of weigh-in-motion measurement based on in-pavement fiber bragg sensors through a hybrid sensor-camera system［J］. Sensors, 2023, 23(21): 8707.
［8］ Zhou Xiaobo. Research on noise removal in fiber grating sensing signal［J］. International Journal of Advanced Network, Monitoring and Controls, 2018, 3(4): 87-91.
［9］刘巧红, 李斌, 林敏. 结合复方向滤波器组高斯尺度混合模型及非局部均值滤波的图像去噪［J］. 光学精密工程, 2014, 22(10): 2806-2814.
Liu Qiaohong, Li Bin, Lin Min. Image denoising with dual-directional filter bank GSM model and non-local mean filter［J］. Optics and Precision Engineering, 2014, 22(10): 2806-2814.
［10］葛伟, 齐志, 温闻, 等. 多种中值滤波算法在可重构架构上的映射实现［J］. 东南大学学报(自然科学版), 2014, 44(4): 697-702.
Ge Wei, Qi Zhi, Wen Wen, et al. Mapping of multiple Median filtering algorithms on reconfigurable architecture［J］. Journal of Southeast University (Natural Science Edition), 2014, 44(4): 697-702.
［11］ Huan Shengsheng, Lu Linjiao, Shen Tao, et al. Low velocity impact monitoring of composite tubes based on FBG sensors［J］. Sensors, 2024, 24(4): 1279.
［12］鲁一冰, 刘文清, 张玉钧, 等. 一种自适应层进式Savitzky-Golay光谱滤波算法及其应用［J］. 光谱学与光谱分析, 2019, 39(9): 2657-2663.
Lu Yibing, Liu Wenqing, Zhang Yujun, et al. An adaptive hierarchical Savitzky-Golay spectral filtering algorithm and its application［J］. Spectroscopy and Spectral Analysis, 2019, 39(9): 2657-2663.
［13］孙传铭, 魏隆, 张梦楠, 等. 自适应奇异值分解局放信号降噪方法［J］. 电工电能新技术, 2021, 40(5): 34-41.
Sun Chuanming, Wei Long, Zhang Mengnan, et al. Partial discharge denoising method based on adaptive singular value decomposition［J］. Advanced Technology of Electrical Engineering and Energy, 2021, 40(5): 34-41.
［14］ Golafshan R, Yuce Sanliturk K. SVD and Hankel matrix based de-noising approach for ball bearing fault detection and its assessment using artificial faults［J］. Mechanical Systems and Signal Processing, 2016, 70-71: 36-50.
［15］姚西桐. 沥青路面结构信息监测数据分析系统开发及应用［D］. 哈尔滨: 哈尔滨工业大学, 2018.
Yao Xitong. Development and application of asphalt pavement structure information data analysis system［D］. Harbin: Harbin Institute of Technology, 2018.
［16］ Yang Honggang, Lin Huibin, Ding Kang. Sliding window denoising K-singular value decomposition and its application on rolling bearing impact fault diagnosis［J］. Journal of Sound and Vibration, 2018, 421: 205-219.
［17］ Mao Qianjun, Fang Xi, Hu Yunpeng, et al. Chiller sensor fault detection based on empirical mode decomposition threshold denoising and principal component analysis［J］. Applied Thermal Engineering, 2018, 144: 21-30.
［18］朱红运, 王长龙, 王建斌, 等. 基于奇异值分解和Savitzky-Golay滤波器的信号降噪方法［J］. 计算机应用, 2015, 35(10): 3004-3007.
Zhu Hongyun, Wang Changlong, Wang Jianbin, et al. Signal denoising method based on singular value decomposition and Savitzky-Golay filter［J］. Journal of Computer Applications, 2015, 35(10): 3004-3007.

[1]	李耘宇1, 徐帆2, 王永生3, 刘浩3, 彭龙帆3. 基于频率谱和温度谱的纤维沥青混合料动态回弹模量研究[J]. 重庆交通大学学报（自然科学版）, 2025, 44(10): 1-9.
[2]	王元元1,2，李必杨1，周哲1，杨建华2，刘燕燕3. 路用双目融合结构光视觉算法与复杂环境影响分析[J]. 重庆交通大学学报（自然科学版）, 2025, 44(7): 67-74.
[3]	李骏1，何超1，刘震2，3，顾兴宇2，3. 基于多尺度加载试验的沥青路面结构参数设计方法[J]. 重庆交通大学学报（自然科学版）, 2024, 43(1): 31-38.
[4]	李志勇, 朱尚书. 明色化铺装材料的路用性能研究[J]. 重庆交通大学学报（自然科学版）, 2023, 42(2): 37-43.
[5]	熊锐1,2，冯宝珠1，乔宁1，纪括1，王昊宇1. 硫酸盐冻融循环条件下沥青性能评价[J]. 重庆交通大学学报（自然科学版）, 2022, 41(04): 70-75.
[6]	王民1,2，尚飞1，肖丽1，包广志3. 钢桥面浇注式沥青铺装复合梁疲劳损伤规律分析[J]. 重庆交通大学学报（自然科学版）, 2021, 40(03): 84-88.
[7]	李升连1,梁乃兴2,曾晟2. 采集方法对数字图像沥青混合料离析评价影响研究[J]. 重庆交通大学学报（自然科学版）, 2021, 40(03): 103-107.
[8]	周建昆1，曹源文2，温永杰2，赵江1，白丽萍3. 不同高度下摊铺路面的数字图像差异性研究[J]. 重庆交通大学学报（自然科学版）, 2021, 40(02): 89-94.
[9]	刘洪辉，李晓娟. 水性环氧乳化沥青高温流变性能研究[J]. 重庆交通大学学报（自然科学版）, 2020, 39(10): 67-73.
[10]	李海莲1，2，林梦凯1，2，王起才1，2. 高速公路沥青路面使用性能模糊区间评价方法研究[J]. 重庆交通大学学报（自然科学版）, 2020, 39(09): 80-87.
[11]	马丽英，李茂其，曹源文,董琴琴. 沥青桥面压实均匀性实时检测方法研究[J]. 重庆交通大学学报（自然科学版）, 2020, 39(02): 69-74.
[12]	吴国雄1,2，叶新雨1，余苗1，杨丹彤3. 基于黏弹性的橡胶改性沥青路面抗滑性能研究[J]. 重庆交通大学学报（自然科学版）, 2020, 39(02): 81-86.
[13]	付军1,3，刘智鸿1,2，左雪娜3，赖泽涵1，王学智1，丁庆军4. 区域气候变化对沥青路面夏季温度效应的影响分析[J]. 重庆交通大学学报（自然科学版）, 2020, 39(02): 87-94.
[14]	高建红，许有俊，杨圣春. 粒料类基层沥青路面动力响应研究[J]. 重庆交通大学学报（自然科学版）, 2019, 38(12): 57-62.
[15]	张东长1，宁斌权2，伍杰1，陈飞1. 渗透式薄层抗滑材料性能研究[J]. 重庆交通大学学报（自然科学版）, 2019, 38(10): 61-67.

基于SG-SVD和波动抑制的沥青路面FBG感知信号降噪研究

FBG sensing signal denoising of asphalt pavement based on SG-SVD and fluctuation suppression

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics