吉林大学学报(工学版) ›› 2023, Vol. 53 ›› Issue (6): 1566-1579.doi: 10.13229/j.cnki.jdxbgxb.20230037

• 综述 • 上一篇    

基于光纤传感技术的路面结冰智能监测研究进展

赵晓康(),胡哲,张久鹏(),裴建中,石宁   

  1. 长安大学 公路学院,西安 710064
  • 收稿日期:2023-01-12 出版日期:2023-06-01 发布日期:2023-07-23
  • 通讯作者: 张久鹏 E-mail:kronchd@126.com;zhjiupeng@chd.edu.cn
  • 作者简介:赵晓康(1987-),男,讲师,博士.研究方向:智慧道面与感知监测.E-mail:kronchd@126.com
  • 基金资助:
    中央高校基本科研业务费专项资金项目(300102213102);国家重点研发计划项目(2021YFB2600602)

Research progress in intelligent monitoring of pavement icing based on optical fiber sensing technology

Xiao-kang ZHAO(),Zhe HU,Jiu-peng ZHANG(),Jian-zhong PEI,Ning SHI   

  1. School of Highway,Chang'an University,Xi'an 710064,China
  • Received:2023-01-12 Online:2023-06-01 Published:2023-07-23
  • Contact: Jiu-peng ZHANG E-mail:kronchd@126.com;zhjiupeng@chd.edu.cn

摘要:

为了促进道路安全性智能感知技术应用,对国内外有关光纤传感路面结冰状态智能监测的研究进展进行了综述。首先,揭示了光纤式路面结冰检测原理;随后,经过分析不同光纤性能指标、常用探头分布模式以及多种弱信号检测方法,构建了光纤式路面结冰检测系统;然后,探讨了常见的结冰检测数据预处理及其厚度分析方法,并概括主要环境影响因素和提升检测效果的措施,分析了适用于光纤式路面结冰检测传感器的埋设工艺;最后,归纳并总结了当前结冰路面监测及预警研究现状,论述了现有研究存在的问题并尝试对路面结冰状态智能感知的发展方向进行展望。

关键词: 道路工程, 结冰路面, 结冰传感器, 光纤技术, 智能感知

Abstract:

In order to promote the application of road safety intelligent perception technology, the research progress about intelligent monitoring of pavement icing condition based on optical fiber sensing at home and abroad was overviewed. Firstly, the principle of fiber-optic pavement icing detection was revealed. Subsequently,based on the analysis of different optical fiber performance indexes, the distribution mode of common probes and various weak signal detection methods, the fiber-optic pavement icing detection system was constructed. Then, common icing detection data pre-processing and its thickness analysis methods were explored, the main environmental influencing factors and measures to enhance detection effectiveness were outlined, and burying technology of fiber-optic road icing detection sensor was analyzed. Finally, current research status of icing pavement monitoring and early warning were summarized, the existing problems were discussed, and the development direction of intelligent sensing of pavement icing condition was attempted to outlook.

Key words: road engineering, frozen pavement, ice sensor, optical fiber technology, intelligent perception

中图分类号: 

  • U416.214

图1

光纤式结冰传感器原理图[15]"

图2

光纤基本结构图"

图3

光纤全反射原理"

表1

聚合物光纤与石英光纤性能指标对比[19]"

指标聚合物光纤石英光纤
芯径/μm100~100062.5
数值孔径0.50.22
受光角/(°)6016
典型波长/nm650850/1300
典型损耗/(dB·km-11253.5/1
弹性模量/GPa3.272
拉伸长度/%5~101~2
光源成本/$3~56~25
连接器成本/$0.25~55~25
连接时间/min1~51~20

图4

同轴式光纤探头"

图5

楔形式光纤探头"

图6

复合端面式光纤探头"

表2

常见光纤探头分布模式"

探头分布模式应用情况优点缺点
同轴式检测薄冰冰厚灵敏度高,光纤信号响应较强检测范围小,不能识别冰型
楔形式检测厚冰冰厚检测范围大,识别不同冰型灵敏度较低,容易受光饱和现象影响
复合端面式区分明冰、霜冰和混合冰结合多种探头模式优势,扩大检测范围装配和端面集成校准复杂

表3

常见弱信号检测方法"

检测方法检测原理特点
带通滤波法41利用功率谱密度在信号中较窄,而噪声相对较宽的特点滤掉大部分噪声滤波器带宽B越窄,信噪比提高越好
同步累积法42重复多次测量,使信号同相地累积起来,而噪声因其随机性相互抵消测量次数越多,信噪比改善越明显。
相关检测法43利用相关原理,输入信号与参考信号的互相关运算达到去除噪声目的抑制能力极强,基本滤去不同步噪声
锁定检测法44结合同步累积法和相关检测法,构成锁定放大器抗干扰能力强,把交流信号放大变成直流信号

图7

锁定检测法原理图[16]"

图8

弱信号检测电路结构设计图"

图9

冰厚与电压输出特性曲线[34, 50]"

图10

弯曲损耗与弯曲半径关系图"

图11

封装后传感器横断面[27,68]"

图12

道路结冰监测和预警系统结构[33,76]"

1 陈永恒, 刘鑫山, 熊帅, 等. 冰雪条件下快速路汇流区可变限速控制[J]. 吉林大学学报:工学版, 2018, 48(3): 677-687.
Chen Yong-heng, Liu Xin-shan, Xiong Shuai, et al. Variable speed limit control under snow and ice conditions for urban expressway in junction bottleneck area[J]. Journal of Jilin University (Engineering and Technology Edition), 2018, 48(3): 677-687.
2 谭忆秋, 李济鲈, 徐慧宁. 冰雪路面摩擦特性与运营风险管控研究综述[J]. 中国公路学报, 2022, 35(7): 1-17.
Tan Yi-qiu, Li Ji-lu, Xu Hui-ning. Review on friction characteristics and operation risk intelligent management of ice and snow pavement[J]. China Journal of Highway and Transport, 2022, 35(7): 1-17.
3 林赐云, 谢天承, 覃蔚, 等. 冰雪天气下交叉口信号配时优化方法[J]. 吉林大学学报:工学版, 2022, 52(10): 2316-2324.
Lin Ci-yun, Xie Tian-cheng, Qin Wei, et al. Optimization methods of intersection signal timing parameters under ice and snow condition[J]. Journal of Jilin University (Engineering and Technology Edition), 2022, 52(10): 2316-2324.
4 Ma Tao, Ding Xun-hao, Wang Hao, et al. Experimental study of high-performance deicing asphalt mixture for mechanical performance and anti-icing effectiveness[J]. Journal of Materials in Civil Engineering, 2018, 30(8): No.04018180.
5 梁曹佳, 叶林, 葛俊锋. 非接触式路面状态检测技术研究进展[J]. 传感器与微系统, 2019, 38(2): 1-4, 8.
Liang Cao-jia, Ye Lin, Ge Jun-feng. Research progress of non-contact road surface condition detection technology[J]. Transducer and Microsystem Technologies, 2019, 38(2): 1-4, 8.
6 孙有琴, 胡晓光, 王瑜. 高速公路路面结冰预警系统检测技术研究[J]. 智能城市, 2017, 3(12): 81-82.
Sun You-qin, Hu Xiao-guang, Wang Yu. Research on detection technology of highway pavement icing early warning system[J]. Intelligent City, 2017, 3(12): 81-82.
7 谭忆秋, 李济鲈, 徐慧宁. 寒区路面冰雪状态感知与预警[J]. 中国基础科学, 2020, 22(5): 9-15, 34.
Tan Yi-qiu, Li Ji-lu, Xu Hui-ning. Ice and snow state perception and warning of road in cold region[J]. China Basic Science, 2020, 22(5): 9-15, 34.
8 Zhang Jiu-peng, Wang Pei, Wang Hao, et al. Development and verification of integrated photoelectric system for noncontact detection of pavement ponding and freezing[J]. Structural Control & Health Monitoring, 2021, 28(6): No.e2719.
9 Wang Peng, Zhou Wen-song, Bao Yue-quan, et al. Ice monitoring of a full-scale wind turbine blade using ultrasonic guided waves under varying temperature conditions[J]. Structural Control & Health Monitoring, 2018, 25(4): No.e2138.
10 Zhao W, Xu L, Bai J, et al. Sensor-based risk perception ability network design for drivers in snow and ice environmental freeway: a deep learning and rough sets approach[J]. Soft Computing, 2018, 22(5): 1457-1466.
11 Gui K, Ge J F, Ye L, et al. The piezoelectric road status sensor using the frequency scanning method and machine-learning algorithms[J]. Sensors and Actuators A: Physical, 2019, 287: 8-20.
12 Roy S, Izad A, Deanna R G, et al. Smart ice detection systems based on resonant piezoelectric transducers[J]. Sensors & Actuators A Physical, 1998, 69(3): 243-250.
13 Troiano A, Pasero E, Mesin L. New system for detecting road ice formation[J]. IEEE Transactions on Instrumentation and Measurement, 2011, 60(3): 1091-1101.
14 Amoiropoulos K, Kioselaki G, Kourkoumelis N, et al. Shaping beam profiles using plastic optical fiber tapers with application to ice sensors[J]. Sensors, 2020, 20(9): No.2503.
15 Li W, Zhang J, Ye L, et al. A fiber-optic solution to aircraft icing detection and measurement problem[C]∥2009 IEEE International Conference on Information Technology and Computer Science, Kiev, Ukraine, 2009: 357-360.
16 熊平. 光纤式结冰传感器气象结冰探测应用研究[D]. 武汉: 华中科技大学人工智能与自动化学院, 2011.
Xiong Ping. Application of using fiber-optic ice sensor in meteorologic icing detection[D]. Wuhan: School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, 2011.
17 欧彦, 蒲翔, 周旭驰, 等. 路面结冰监测技术研究进展[J]. 公路, 2013, 58(4): 191-196.
Yan Ou, Pu Xiang, Zhou Xu-chi, et al. Review on icing detection techniques of pavement[J]. Highway,2013, 58(4): 191-196.
18 Gui K, Ye L, Ge J, et al. Road surface condition detection utilizing resonance frequency and optical technologies[J]. Sensors and Actuators A: Physical, 2019, 297: No.111540.
19 贾涛. 基于多模光纤的 ROF 技术研究[D]. 杭州: 浙江大学信息与电子工程学院, 2006.
Jia Tao. Study of the radio over fiber technology based on multimode fiber[D]. Hangzhou: School of Information and Electronic Engineering, Zhejiang University, 2006.
20 Ge J, Liu J, Gui K, et al. Atmospheric icing measurement and online ice type recognition for aircraft utilizing optical fiber sensor and machine learning algorithms[J]. Measurement, 2022, 205: No.112215.
21 Martinez J, Rodenas A, Stake A, et al. Harsh-environment-resistant OH-vibrations-sensitive mid-infrared water-ice photonic sensor[J]. Advanced Materials Technologies, 2017, 2(8): No.10700085.
22 Kadhim R A, Abdul A K K, Yuan L. Advances in surface plasmon resonance-based plastic optical fiber sensors[J]. IETE Technical Review, 2022, 39(2): 442-459.
23 He R J, Teng C X, Kumar S, et al. Polymer optical fiber liquid level sensor: a review[J]. IEEE Sensors Journal, 2022, 22(2): 1081-1091.
24 Antunes P F C, Varum H, Andre P S. Intensity-encoded polymer optical fiber accelerometer[J]. IEEE Sensors Journal, 2013, 13(5): 1716-1720.
25 陆侃. 道路结冰与积水智能传感器系统研究[D]. 合肥: 中国科学技术大学信息科学技术学院, 2016.
Lu Kan. Research on intelligent sensor system of road icing and road water logging[D]. Hefei: School of Information Science and Technology, University of Science and Technology of China, 2016.
26 石宁. 基于聚合物光纤传感器的道路结冰与积水检测研究[D]. 西安: 长安大学公路学院, 2018.
Shi Ning. Study on road ice and water monitoring based on polymer optical fiber sensing technology[D]. Xi'an: School of Highway, Chang'an University, 2018.
27 Bi Y Q, Pei J Z, Guo F C, et al. Implementation of polymer optical fibre sensor system for monitoring water membrane thickness on pavement surface[J]. International Journal of Pavement Engineering, 2021, 22(7): 872-881.
28 Li Guo-ping, Zhou Sheng-dang, Ma Ling, et al. Research on dual wavelength coaxial optical fiber sensor for detecting steel ball surface defects[J]. Measurement, 2019, 133: 310-319.
29 Mizushima Y, Saito T. Improving the accuracy of droplet measurement by optical fiber probe using 3D ray-tracing simulation[J]. Journal of Chemical Engineering of Japan, 2019, 52(2): 171-178.
30 Liu Zhi-hai, Wei Yong, Zhang Yu, et al. Reflective-distributed SPR sensor based on twin-core fiber[J]. Optics Communications, 2016, 366: 107-111.
31 李薇, 叶林, 张杰, 等. 光纤式结冰传感器的试验研究[J]. 华中科技大学学报:自然科学版, 2009, 37(8): 16-18, 22.
Li Wei, Ye Lin, Zhang Jie, et al. Experimental study on the fiber-optic sensor for direct ice detection[J]. Journal of Huazhong University of Science&Technology(Natural Science Edition), 2009, 37(8):16-18, 22.
32 Lu K, Chen F. A fiber-optic icing sensor with multi-light paths[C]∥2016 International Conference on Electrical, Mechanical and Industrial Engineering, Phuket, Thailand, 2016: 63-66.
33 谭舒亚. 路面结冰检测技术的研究[D]. 武汉: 华中科技大学人工智能与自动化学院, 2015.
Tan Shu-ya. Research on road icing detection method[D]. Wuhan: School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, 2015.
34 李颀, 张尚玉. 基于ZigBee的高速公路结冰信息检测系统的设计[J]. 计算机测量与控制, 2015, 23(1): 22-24.
Li Qi, Zhang Shang-yu. Design of icy detection system for highway pavement based on ZigBee[J]. Computer Measurement & Control, 2015, 23(1): 22-24.
35 尹胜生, 叶林, 陈斌, 等. 可识别冰型的光纤结冰传感器[J]. 仪表技术与传感器, 2012(5): 9-11, 23.
Yin Sheng-sheng, Ye Lin, Chen Bin, et al. Fiber-optical icing sensor for detecting the icing type[J]. Instrument Technique and Sensor, 2012(5): 9-11, 23.
36 李薇, 侯睿, 程立. 基于忆阻桥效应的光纤式双光路结冰探测方法[J]. 传感技术学报, 2017, 30(2): 206-210.
Li Wei, Hou Rui, Cheng Li. An icing detection method using double optical paths based on memristor-bridge effect[J]. Chinese Journal of Sensors and Actuators, 2017, 30(2): 206-210.
37 Zou Jian-hong, Ye Lin, Ge Jun-feng. Ice type detection using an oblique end-face fibre-optic technique[J]. Measurement Science and Technology, 2013, 24(3): No.035201.
38 Mlyniec A, Ambrozinski L, Packo P, et al. Adaptive de-icing system-numerical simulations and laboratory experimental validation[J]. International Journal of Applied Electromagnetics and Mechanics, 2014, 46(4): 997-1008.
39 Gentry E S, Marshall H L, Hardcastle M J, et al. Optical detection of the pictor a jet and tidal tail: evidence against an IC/CMB jet[J]. Astrophysical Journal, 2015, 808(1): No.92.
40 Lu Si-liang, He Qing-bo, Wang Jun. A review of stochastic resonance in rotating machine fault detection[J]. Mechanical Systems and Signal Processing, 2019, 116: 230-260.
41 Varcheh H N, Rezaei P. Low-loss X-band waveguide bandpass filter based on rectangular resonators[J]. Microwave and Optical Technology Letters, 2022, 64(4): 701-706.
42 Lu Wei, Shi Xiao-jing, Sun Jian-feng, et al. Improving the signal-to-noise ratio of GM-APD coherent lidar system based on phase synchronization method[J]. Optics and Laser Technology, 2022, 150: No.107994.
43 Nie D H, Xie K, Zhou F, et al. A correlation detection method of low SNR based on multi-channelization[J]. IEEE Signal Processing Letters, 2020, 27: 1375-1379.
44 Kishore K, Akbar S A. Evolution of lock-in amplifier as portable sensor interface platform: a review[J]. IEEE Sensors Journal, 2020, 20(18): 10345-10354.
45 刘治军, 叶林, 陈斌, 等. 光纤式结冰传感器微弱信号检测电路的实现[J]. 仪表技术与传感器, 2012(3): 79-81.
Liu Zhi-jun, Ye Lin, Chen Bin, et al. Realization of lock-in detect circuit on weak signal detection of fibre-optical icing sensor[J]. Instrument Technique and Sensor, 2012(3): 79-81.
46 李飞. 基于数字相关的弱信号检测方法的研究[D]. 武汉: 华中科技大学计算机科学与技术学院, 2007.
Li Fei. Detection of weak signal based on digital correlation[D]. Wuhan: School of Computer Science and Technology, Huazhong University of Science and Technology, 2007.
47 张龙浩. 光纤阵列式结冰探测系统的研究[D]. 武汉: 华中科技大学人工智能与自动化学院, 2013.
Zhang Long-hao. The research of optical fiber array icing detection system[D]. Wuhan: School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, 2013.
48 Maya P, Calvo B, Sanz-Pascual M T, et al. Low cost autonomous lock-in amplifier for resistance/capacitance sensor measurements[J]. Electronics, 2019, 8(12): No.1413.
49 Chen X, Wei M, Chen K, et al. Research on weak signal detection of integral average digital lock-in amplifier[J]. Measurement Science and Technology, 2021, 32(10): No.105905.
50 但汉成, 刘扬, 凌桂香, 等. 光纤式结冰传感器探测沥青路面结冰过程[J]. 公路交通科技, 2014, 31(4): 7-15.
Dan Han-cheng, Liu Yang, Ling Gui-xiang, et al. Probing freezing process of ice on asphalt pavement with fiber-optic ice sensor[J]. Journal of Highway and Transportation Research and Development, 2014, 31(4): 7-15.
51 杨秋虎. 基于强度调制的光纤位移传感器信号处理技术研究及电路实现[D]. 武汉: 华中科技大学机械科学与工程学院, 2011.
Yang Qiu-hu. The research and design of signal processing technology of the optical fiber displacement sensor based on intensity modulation[D]. Wuhan: School of Mechanical Science and Engineering, Huazhong University of Science and Technology, 2011.
52 郑斌. 路面结冰影响因素研究及预测模型的构建[D]. 哈尔滨: 哈尔滨工业大学交通科学与工程学院, 2019.
Zheng Bin. Study on influencing factors of pavement icing and construction of prediction model[D]. Harbin: School of Traffic Science and Engineering, Harbin Institute of Technology, 2019.
53 Wen Zi-hao, Zhang Hui, Zhang Rong-hui. Safety-critical event identification on mountain roads for traffic safety and environmental protection using support vector machine with information entropy[J]. Sustainability, 2021, 13(8): No.4426.
54 Yang E, Yang Q, Li J, et al. Establishment of icing prediction model of asphalt pavement based on support vector regression algorithm and Bayesian optimization[J]. Construction and Building Materials, 2022, 351: No.128955.
55 谭舒亚, 葛俊锋, 叶林, 等. 基于多传感器的路面结冰检测系统[J]. 传感器与微系统, 2016, 35(1): 107-109.
Tan Shu-ya, Ge Jun-feng, Ye Lin, et al. Road surface icing detecting system based on multiple sensor[J]. Transducer and Microsystem Technologies, 2016, 35(1): 107-109.
56 Li W, Zhang J, Zheng Y, et al. Enlargement of measurement range in a fiber-optic ice sensor by artificial neural network[C]∥6th International Symposium on Neural Networks, Wuhan, China, 2009: 929-936.
57 陆凯旋. 基于智能道钉的路面冰雪及水体检测技术[D]. 哈尔滨: 哈尔滨工业大学交通科学与工程学院, 2020.
Lu Kai-xuan. Detection technology of ice, snow and water condition on road surface based on smart road studs[D]. Harbin: School of Traffic Science and Engineering, Harbin Institute of Technology, 2020.
58 Schermer R T, Cole J H. Improved bend loss formula verified for optical fiber by simulation and experiment[J]. IEEE Journal of Quantum Electronics, 2007, 43(10): 899-909.
59 Su Huai-zhi, Li Xing, Fang Bin, et al. Crack detection in hydraulic concrete structures using bending loss data of optical fiber[J]. Journal of Intelligent Material Systems and Structures, 2017, 28(13): 1719-1733.
60 Cheng Lin, Song Fu-bin, Zhang Kai, et al. A U-shaped-wound fiber macro-bending loss crack sensor improved by an optical splitter[J]. Optical Fiber Technology, 2020, 58: No.102259.
61 Wang H, Jiang L, Xiang P. Priority design parameters of industrialized optical fiber sensors in civil engineering[J]. Optics & Laser Technology, 2018, 100: 119-128.
62 闫光, 庄炜, 刘锋, 等. 具有增敏效果的光纤光栅应变传感器的预紧封装及传感特性[J]. 吉林大学学报:工学版, 2016, 46(5): 1739-1745.
Yan Guang, Zhuang Wei, Liu Feng, et al. Preload package and characteristics of a sensitizing effect sensor based Fiber Bragg Grating[J]. Journal of Jilin University (Engineering and Technology Edition), 2016, 46(5): 1739-1745.
63 Liu Y, Xie J, Liu S, et al. Research on the methodology of development and calibration of flexible encapsulated fiber Bragg grating sensors[J]. Measurement, 2022, 201: No.111730.
64 Ren P, Zhou Z. Low modulus polymer packaged optical fiber sensor for macrocrack monitoring in ice structures of cold regions[J]. Optical Engineering, 2014, 53(9): No.097102.
65 Liao Meng-hui, 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(B): No.128029.
66 Xia Xiao-peng, Zhang Yu-min, Lou Xiao-ping, et al. Half-size metal-packaged fiber Bragg grating for simultaneous measurement of strain and temperature[J]. Optical Engineering, 2019, 58(11): No.116104.
67 Wang H, Liu W, He J, et al. Functionality enhancement of industrialized optical fiber sensors and system developed for full-scale pavement monitoring[J]. Sensors, 2014, 14(5): 8829-8850.
68 Wang B J, Li K, Shi B, et al. Test on application of distributed fiber optic sensing technique into soil slope monitoring[J]. Landslides, 2009, 6: 61-68.
69 张权, 张庆宇, 王志斌, 等. 基于光纤布拉格光栅传感器的永久路面结构响应监测研究[J]. 传感器与微系统, 2021, 40(11): 76-79, 90.
Zhang Quan, Zhang Qing-yu, Wang Zhi-bin, et al. Research on permanent pavement structure response monitoring based on Fiber Bragg Grating sensor[J]. Transducer and Microsystem Technologies, 2021, 40(11): 76-79, 90.
70 王海朋, 谭忆秋, 董泽蛟, 等. 基于光纤光栅的沥青路面状态的实时监测[J]. 光电子激光, 2013, 24(11): 2186-2191.
Wang Hai-peng, Tan Yi-qiu, Dong Ze-jiao, et al. Real-time monitoring for asphalt pavement using fiber Bragg grating sensor[J]. Journal of Optoelectronics·Laser, 2013, 24(11): 2186-2191.
71 Weng X, Zhu H H, Chen J, et al. Experimental investigation of pavement behavior after embankment widening using a fiber optic sensor network[J]. Structural Health Monitoring, 2015, 14(1): 46-56.
72 谭舒亚, 葛俊锋, 叶林, 等. 非接触式路面结冰探测技术研究进展[J]. 公路, 2015, 60(6): 244-249.
Tan Shu-ya, Ge Jun-feng, Ye Lin, et al. Research progress of non-contact road icing detection technology[J]. Highway, 2015, 60(6): 244-249.
73 尹麒焕. 基于多参数的道路结冰安全预警系统研究[D]. 武汉: 武汉工程大学资源与土木工程学院, 2016.
Yin Qi-huan. Research on safety warning system of icy road base on multi-parameters[D]. Wuhan: School of Resources and Civil Engineering, Wuhan Institute of Technology, 2016.
74 冯金龙. 高速公路路面结冰检测系统的研究[D]. 南京: 南京信息工程大学信息与控制学院, 2011.
Feng Jin-long. Research of icy detection system for expressway pavement[D]. Nanjing: School of Information and Control, Nanjing University of Information Science and Technology, 2011.
75 郭慕瑶. 基于多传感信息的路面水冰雪识别研究[D]. 哈尔滨: 哈尔滨工业大学交通科学与工程学院, 2021.
Guo Mu-yao. Research on pavement water, ice and snow recognition based on multi-sensor information[D]. Harbin: School of Transportation Science and Engineering, Harbin Institute of Technology, 2021.
76 Chen Z, Xiong G, Sun Y, et al. An internet-of-things-enabled system for road icing detection and prediction[J]. IEEE Internet of Things Journal, 2022, 9(20): 20257-20269.
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