[1]武志玮,刘国光,刘智勇.基于小波变换的场道脱空识别[J].深圳大学学报理工版,2017,34(3):265-271.[doi:10.3724/SP.J.1249.2017.03265]
　Wu Zhiwei,Liu Guoguang,and Liu Zhiyong,et al.Runway pavement void identification based on wavelet transform[J].Journal of Shenzhen University Science and Engineering,2017,34(3):265-271.[doi:10.3724/SP.J.1249.2017.03265]
点击复制

基于小波变换的场道脱空识别()
分享到：

《深圳大学学报理工版》[ISSN:1000-2618/CN:44-1401/N]

卷:
第34卷
期数:
2017年第3期
页码:
265-271
栏目:
土木建筑工程
出版日期:
2017-05-30

文章信息/Info

Title:
Runway pavement void identification based on wavelet transform
文章编号:
201703007
作者:
武志玮1; 刘国光1; 2; 刘智勇3
1) 中国民航大学机场学院，天津 300300
2) 冻土工程国家重点实验室，甘肃兰州 730000
3) 深圳机场集团，广东深圳518128
Author(s):
Wu Zhiwei1;  Liu Guoguang1;  2;  and Liu Zhiyong3
1) Airport College, Civil Aviation University of China, Tianjin 300300, P.R.China
2) State Key Laboratory of Frozen Soil Engineering, Lanzhou 730000, Gansu Province, P.R.China
3) Shenzhen Airport Group, Shenzhen 518128,Guangdong Province, P.R.China
关键词:
道路工程; 振动响应; 场道脱空; 小波变换; 小波包; 机场跑道; 无损检测
Keywords:
road engineering;  pavement vibration;  pavement void;  wavelet transform;  wavelet packet;  airport runway;  nondestructive examination
分类号:
U 416.201
DOI:
10.3724/SP.J.1249.2017.03265
文献标志码:
A
摘要:
为研究脱空对跑道振动响应的影响，进行砂土垫层混凝土板缩尺模型试验. 利用落锤施加冲击荷载，采集不同脱空程度下道面板的竖向加速度信号，利用小波变换进行功率谱分析、能量谱分析、短时傅里叶变换、时间-尺度分析及小波包相平面分析. 通过时频图表征信号局部特性，分析脱空引起的信号差异. 结果表明，不同脱空状况引起了跑道振动特性变化，使各频带的频谱响应不同，引起各频带能量重分布. 加速度信号经小波变换处理后，反映了脱空对信号能量的影响. 脱空和半脱空区域存在信号能量差异可用于跑道脱空状况识别.
Abstract:
In order to investigate the influences of voids on runway vibration response, a scale model test of concrete plate with sand cushion is conducted. By using the falling weight to simulate impact loads, vertical acceleration signals of pavement under different void conditions are obtained. Wavelet transform method is used to perform energy spectrum analysis, time scale analysis and wavelet packet analysis in the phase plane. Local characteristic of pavement can be characterized by the time-frequency map, by which the differences of acceleration signals caused by voids can be achieved. The result shows that the pavement vibration characteristic is changed due to different void conditions, which leads to the spectrum response differences and energy redistributions of frequency band. By wavelet transform of acceleration signal, the influences of pavement void on signal energy are obtained. The signal energy differences for void area and half-void area could be adopted in pavement void identification.

参考文献/References:

［1］ 李肃义，林君，阳贵红，等. 电性源时域地空电磁数据小波去噪方法研究［J］. 地球物理学报, 2013，56(9): 3146-3152.
Li Suyi, Lin Jun, Yang Guihong, et al. Ground-airborne electromagnetic signals de-noising using a combined wavelet transform algorithm［J］. Chinese Journal of Geophysics, 2013, 56(9): 3146-3152.(in Chinese)
［2］ 梁桂兰，徐卫亚，谈小龙，等. 岩石高边坡安全监测数据的小波变换去噪处理［J］. 岩石力学与工程学报, 2008, 27(9): 1837-1844.
Liang Guilan, Xu Weiya, Tan Xiaolong, et al. Denosing processing of safety monitoring data for high rock slope based on wavelet transform［J］. Chinese Journal of Rock Mechanics and Engineering, 2008, 27(9): 1837-1844.(in Chinese)
［3］ 刘汉丽，裴韬，周成虎. 用于时间序列聚类分析的小波变换和特征量提取方法［J］. 测绘科学技术学报，2014，31(4): 373-376.
Liu Hanli, Pei Tao, Zhou Chenghu. Wavelet transform and statistical characteristics extraction appliedto times series clustering analysis［J］. Journal of Geomatics Science and Technology, 2014, 31(4): 373-376.(in Chinese)
［4］ 张士文，张峰，王子骏，等. 一种基于小波变换能量与神经网络结合的串联型故障电弧辨识方法［J］.电工技术学报, 2014, 29(6): 290-302.
Zhang Shiwen, Zhang Feng, Wang Zijun, et al. Series arc fault identification method based on energy produced by wavelet transformation and neural network［J］. Transactions of China Electrotechnical Society, 2014, 29(6): 290-302.(in Chinese)
［5］ 刘国光, 武志玮, 牛富俊,等. 基于BP神经网络的场道脱空检测方法及实验［J］. 深圳大学学报理工版, 2016, 33(3)：309-315.
Liu Guoguang, Wu Zhiwei, Niu Fujun, et al. Theoretical and experimental research on airport pavement void test based on back propagation neural network［J］. Journal of Shenzhen University Science and Engineering, 2016, 33(3)：309-315.(in Chinese)
［6］ 刘国光，武志玮，刘志勇，等. 基于小波变换的场道脱空BP神经网络预测法研究［J］. 振动与冲击, 2016, 35(18)：203-209.
Liu Guoguang, Wu Zhiwei, Liu Zhiyong, et al. Back propagation neural network applied in the prediction of pavement void based on wavelet transform method［J］. Journal of Vibration and Shock, 2016, 35(18)：203-209.(in Chinese)
［7］ 谢耀国，姚熊亮，崔洪斌，等. 基于小波分析的实船水下爆炸船体响应特征［J］. 爆炸与冲击，2017，37(1): 99-106.
Xie Yaoguo, Yao Xiongliang, Cui Hongbin, et al. Wavelet analysis on shock response of a real ship subjected to non-contact underwater explosion［J］. Explosion and Shock Waves, 2017，37(1): 99-106.(in Chinese)
［8］ 聂治豹，郑宏，张谭. 基于强度折减法确定边坡临界滑面的小波变换法［J］. 岩土力学，2017,38(6)：1-5.
Nie Zhibao, Zheng Hong, Zhang Tan. Location of slope critical slip surfaces based on strength reduction technique and wavelet［J］. Rock and Soil Mechanics, 2017,38(6)：1-5.(in Chinese)
［9］ 孙增寿，李晓鹏，韩培琰. 基于小波分析和移动荷载动力响应的连续梁损伤识别研究［J］. 世界桥梁，2017, 45(1)：33-38.
Sun Zengshou, Li Xiaopeng, Han Peiyan. Study of continuous beam damage identification based on wavelet analysis and live-load dynamic response［J］. World Bridges, 2017, 45(1)：33-38.(in Chinese)
［10］ 杨仁树，付晓强，杨国梁，等. EMD和FSWT组合方法在爆破振动信号分析中的应用研究［J］. 振动与冲击, 2017, 36(2)：58-64.
Yang Renshu, Fu Xiaoqiang, Yang Guoliang, et al. Application of EMD and FSWT combination method in blasting vibration signal analysis［J］. Journal of Vibration and Shock, 2017, 36(2)：58-64.(in Chinese)
［11］ 费鸿禄，曾翔宇，杨智广. 隧道掘进爆破振动对地表影响的小波包分析［J］. 爆炸与冲击，2017，37(1): 77-83.
Fei Honglu, Zeng Xiangyu, Yang Zhiguang. Influence of tunnel excavation blasting vibration on earth’s surface based on wavelet packet analysis［J］. Explosion and Shock Waves, 2017，37(1): 77-83.(in Chinese)
［12］ 李辉，王毅，杨晓萍，等. 基于多小波和PSO-RBF神经网络的水电机组振动故障诊断［J］. 西北农林科技大学学报自然科学版，2017，45(2): 227-234.
Li Hui, Wang Yi, Yang Xiaoping, et al. Vibration fault diagnosis for hydropower generating unit based on multiwavelet and PSO-RBF neural network［J］. Journal of Northwest A&F University Natural Science Edition, 2017, 45(2): 227-234.(in Chinese)
［13］ 薛雅娟，曹俊兴. 聚合经验模态分解和小波变换相结合的地震信号衰减分析［J］. 石油地球物理勘探, 2016, 51(6)：1148-1155.
Xue Yajuan, Cao Junxing. Seismic attenuation analysis using ensemble empirical mode decomposition and wavelet transform［J］. Oil Geophysical Prospecting, 2016, 51(6)：1148-1155.(in Chinese)
［14］ 陈松，陈立爱，吴跃波. 基于小波变换的振动信号分析方法研究［J］. 洛阳理工学院学报自然科学版，2016，26(4)：52-54.
Chen Song, Chen Li’ai, Wu Yuebo. Research of vibration signal analysis method based on wavelet transform［J］. Journal of Luoyang Institute of Science and Technology Natural Science Edition, 2016, 26(4): 52-54.(in Chinese)
［15］ 郭金泉，欧芬兰，许艺青，等. 基于模态振型和平稳小波变换的悬臂梁微小缺陷识别研究［J］. 应用力学学报，2016，33（6）：1016-1021.
Guo Jinquan, Ou Fenlan, Xu Yiqing, et al. Research on small damage detection in cantilever beam based on vibration mode and stationary wavelet transform［J］. Chinese Journal of Applied Mechanics, 2016, 33(6): 1016-1021.(in Chinese)
［16］ 王旭，张俊波，黄鹏. 大跨度球面网壳结构风力荷载间歇特性研究［J］. 湖南大学学报自然科学版，2016，43（11）：78-85.
Wang Xu, Zhang Junbo, Huang Peng. Experimental study on intermittent characteristics of force coefficient of long-span spherical shells［J］. Journal of Hunan University Natural Sciences Edition, 2016, 43(11): 78-85.(in Chinese)
［17］ 刘红，柳杨茂. 基于小波变换和支持向量机的风电功率爬坡事件识别与预测［J］. 东北电力大学学报，2016，36（6）：30-35.
Liu Hong, Liu Yangmao. An approach for wind power climbing event identification and prediction based on wavelet and SVM［J］. Journal of Northeast Dianli University, 2016, 36(6): 30-35.(in Chinese)
［18］ 宋阳，吴凡，刘德扣，等. 基于声发射及小波奇异性的钢轨损伤检测［J］. 振动与冲击, 2017, 36(2)：196-200.
Song Yang, Wu Fan, Liu Dekou, et al. Rail damage detection method based on acoustic emission and wavelet singularity［J］. Journal of Vibration and Shock, 2017, 36(2)：196-200.(in Chinese)
［19］ 胡波，柳炳康，王静峰. 基于小波变换的再生混凝土框架试验破坏过程分析［J］. 土木工程学报, 2014，47(6): 34-42.
Hu Bo, Liu Bingkang, Wang Jingfeng. Damage process analysis of a recycled concrete frame based on wavelet transform［J］. China Civil Engineering Journal, 2014, 47(6): 34-42.(in Chinese)
［20］ Huang C S, Su W C. Identification of modal parameters of a time invariant linear system by continuous wavelet transformation［J］. Mechanical Systems and Signal Processing, 2007, 21(4):1642-1664.
［21］ Ovanesova A V, Suárez L E. Applications of wavelet transforms to damage detection in frame structures［J］. Engineering Structures, 2004, 26(1): 39-49.
［22］ 彭永恒，马荣. 声振法水泥混凝土路面地基脱空判定［J］. 黑龙江大学学报自然科学版, 2009，26(4): 276-280.
Peng Yongheng, Ma Rong. Defect ground sill void of cement concrete pavement on acoustic-vibration［J］. Journal of Heilongjiang University Natural Science Edition, 2009, 26(4): 276-280.(in Chinese)
［23］ 吴传海，肖春发. 基于FWD测试的水泥路面板底脱空判别物元分析方法［J］. 中外公路, 2011，31(4): 64-68.
Wu Chuanhai, Xiao Chunfa. FWD test of void beneath cement concrete pavement slab discriminant analysis method based on matter-element［J］. Journal of China & Foreign Highway, 2011, 31(4): 64-68.(in Chinese)
［24］ 阳宏毅. 脱空状态下水泥混凝土路面汽车荷载下动态力学指标响应分析［J］. 中外公路, 2012，32(1): 98-100.
Yang Hongyi. Dynamic response analysis of mechanical indexes of cement concrete pavement void under vehicle load［J］. Journal of China & Foreign Highway, 2012, 32(1): 98-100.(in Chinese)
［25］ 易志坚，韩西，钟厉，等. 基于频率参数变化的混凝土路面脱空识别研究［J］. 中外公路, 2010，30(3): 80-83.
Yi Zhijian, Han Xi, Zhong Li, et al. Study on concrete pavement void identification based on frequency parameters［J］. Journal of China & Foreign Highway, 2010, 30(3): 80-83.(in Chinese)

相似文献/References:

[1]栗振锋,张敏.FWD动载下的横观各向同性路基动力响应分析[J].深圳大学学报理工版,2013,30(No.2(111-220)):195.[doi:10.3724/SP.J.1249.2013.02195]
　Li Zhenfeng and Zhang Min.The analysis of dynamic response of transversely isotropic subgrade based on FWD[J].Journal of Shenzhen University Science and Engineering,2013,30(3):195.[doi:10.3724/SP.J.1249.2013.02195]
[2]胡江洋,毛君,张浩,等.火山渣作为路基填料的试验研究[J].深圳大学学报理工版,2015,32(6):625.[doi:10.3724/SP.J.1249.2015.06625]
　Hu Jiangyang,Mao Jun,et al.Research on test characteristic of cinder as subgrade filling[J].Journal of Shenzhen University Science and Engineering,2015,32(3):625.[doi:10.3724/SP.J.1249.2015.06625]
[3]刘国光,武志玮,牛富俊,等.基于BP神经网络的场道脱空检测方法及实验[J].深圳大学学报理工版,2016,33(3):309.[doi:10.3724/SP.J.1249.2016.03309]
　Liu Guoguang,Wu Zhiwei,Niu Fujun,et al.Airport pavement void testing based on back propagation neural network[J].Journal of Shenzhen University Science and Engineering,2016,33(3):309.[doi:10.3724/SP.J.1249.2016.03309]
[4]胡江洋,陈团结,折学森.路用改性煤沥青毒性消减试验效果分析[J].深圳大学学报理工版,2016,33(4):418.[doi:10.3724/SP.J.1249.2016.04418]
　Hu Jiangyang,Chen Tuanjie,et al.Analysis of toxicity reduction test about modified coal tar used for road[J].Journal of Shenzhen University Science and Engineering,2016,33(3):418.[doi:10.3724/SP.J.1249.2016.04418]
[5]吴朝阳,杨少伟,林岚,等.互通式立交高事故率出口的判定方法[J].深圳大学学报理工版,2016,33(5):536.[doi:10.3724/SP.J.1249.2016.05536]
　Wu Zhaoyang,Yang Shaowei,Lin Lan,et al.Method for identifying the high accident rate exits of interchange[J].Journal of Shenzhen University Science and Engineering,2016,33(3):536.[doi:10.3724/SP.J.1249.2016.05536]
[6]杨俊,李晓峰,相飞飞,等.废弃混凝土用作再生路面的试验研究[J].深圳大学学报理工版,2017,34(3):252.[doi:10.3724/SP.J.1249.2017.03252]
　Yang Jun,Li Xiaofeng,Xiang Feifei,et al.Experimental study on waste concrete as regenerate pavement[J].Journal of Shenzhen University Science and Engineering,2017,34(3):252.[doi:10.3724/SP.J.1249.2017.03252]
[7]柯文豪,陈华鑫,雷宇,等.基于GRNN神经网络的沥青路面裂缝预测方法[J].深圳大学学报理工版,2017,34(4):378.[doi:10.3724/SP.J.1249.2017.04378]
　Ke Wenhao,Chen Huaxin,Lei Yu,et al.Prediction method for asphalt pavement crack based on GRNN neural network[J].Journal of Shenzhen University Science and Engineering,2017,34(3):378.[doi:10.3724/SP.J.1249.2017.04378]
[8]李晶晶,张擎,陈忠达.水泥路面环氧树脂磨耗层的抗滑衰变模型[J].深圳大学学报理工版,2017,34(6):597.[doi:10.3724/SP.J.1249.2017.06597]
　Li Jingjing,Zhang Qing,and Chen Zhongda.Skid resistance decay model of epoxy wear layer on cement pavement[J].Journal of Shenzhen University Science and Engineering,2017,34(3):597.[doi:10.3724/SP.J.1249.2017.06597]
[9]王威娜,李小飞,徐青杰,等.沥青路面二维和三维结构分析模型的比较[J].深圳大学学报理工版,2018,35(1):39.[doi:10.3724/SP.J.1249.2018.01039]
　WANG Weina,LI Xiaofei,XU Qingjie,et al.Comparison of two dimensional and three dimensional modeling methods on the mechanical response of asphalt pavement[J].Journal of Shenzhen University Science and Engineering,2018,35(3):39.[doi:10.3724/SP.J.1249.2018.01039]
[10]徐鹏,陈华鑫,牛冬瑜,等.基于FT-IR谱图分区的彩色沥青性能对比分析[J].深圳大学学报理工版,2018,35(2):146.[doi:10.3724/SP.J.1249.2018.02146]
　XU Peng,CHEN Huaxin,et al.Comparative analysis of performance of colored asphalt based on the partition of FT-IR graph[J].Journal of Shenzhen University Science and Engineering,2018,35(3):146.[doi:10.3724/SP.J.1249.2018.02146]

备注/Memo

备注/Memo:
Received：2016-11-17；Accepted：2017-03-28
Foundation：National Natural Science Foundation of China(51178456); Open Foundation of State Key Laboratory of Frozen Soil Engineering 2014(SKLFSE201409); Fundamental Research Funds for the Central Universities(312015C017)
Corresponding author：Associate professor Liu Guoguang. Email：ggliu@cauc.edu.cn
Citation：Wu Zhiwei, Liu Guoguang, Liu Zhiyong. Runway pavement void identification based on wavelet transform［J］. Journal of Shenzhen University Science and Engineering, 2017, 34(3): 265-271.（in Chinese）
基金项目：国家自然科学基金资助项目（51178456）；冻土工程国家重点实验室2014年开放基金课题资助项目（SKLFSE201409）；中国民航大学中央高校基本业务费资助项目（312015C017）
作者简介：武志玮（1980—），女，中国民航大学讲师、博士. 研究方向：材料力学及机场工程. E-mail：zwwu@cauc.edu.cn
引文：武志玮，刘国光，刘智勇. 基于小波变换的场道脱空识别［J］. 深圳大学学报理工版，2017，34(3)：265-271.
更新日期/Last Update: 2017-04-20