吉林大学学报(工学版) ›› 2017, Vol. 47 ›› Issue (4): 1301-1307.doi: 10.13229/j.cnki.jdxbgxb201704041

• 论文 • 上一篇    下一篇

基于自适应小波去噪法的精密超声波测距方法

诸葛晶昌1, 吴军2, 詹湘琳1, 于之靖1   

  1. 1.中国民航大学 电子信息与自动化学院,天津 300300;
    2.中国民航大学 航空工程学院,天津 300300
  • 收稿日期:2016-03-10 出版日期:2017-07-20 发布日期:2017-07-20
  • 通讯作者: 吴军(1986-),男,讲师,博士.研究方向:大尺寸光电检测技术,视觉测量和超声检测.E-mail:j_wu@cauc.edu.cn
  • 作者简介:诸葛晶昌(1981-),男,讲师,博士.研究方向:无损检测.E-mail:12315414@qq.com
  • 基金资助:
    国家自然科学基金项目(61405246,61102097); 国家自然科学基金委员会与中国民用航空局联合项目(U1333105); 中国民航大学科研启动基金项目(2010QD02S); 中央高校基本科研业务费专项资金项目(3122014D023,2014QD11X).

Precise ultrasonic ranging method based on self-adaptive wavelet de-noising

ZHUGE Jing-chang1, WU Jun2, ZHAN Xiang-lin1, YU Zhi-jing1   

  1. 1.College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China;
    2.School of Aeronautical Engineering, Civil Aviation University of China, Tianjin 300300, China
  • Received:2016-03-10 Online:2017-07-20 Published:2017-07-20

RICH HTML

1   

PDF (PC)

158

摘要： 超声脉冲飞行时间的精确提取决定了超声测距的精度,因此滤除接收信号中的噪声可有效提高其测距精度。针对传统的去噪方法无法随噪声的变化而自动调整去噪阀值和小波分层数的缺点,提出了一种自适应小波去噪法,通过实时提取接收信号中的噪声特征,自动选择最优的小波参数,有效地提高了接收信号信噪比,从而提高飞行时间提取精度。实验表明,在室内环境条件下测距误差小于0.28 mm,可满足大部分工业制造领域的距离测量应用。

关键词: 信息处理技术, 超声波测距, 自适应滤波, 阈值调节

Abstract: The ranging accuracy of an ultrasonic ranging system depends on how to extract the time of flight of ultrasonic pulse exactly. Therefore, the de-noising method for ultrasonic receiving signals plays an important role in high precise ultrasonic ranging system. Traditional de-noising methods can not automatically adjust their de-noising threshold and wavelet layers due to the fixed model, which limits their use in different environment. In order to improve the efficiency of the de-noising method for ultrasonic receiving signals, a self-adaptive wavelet de-noising method is proposed. This method can automatically choose the optimal wavelet parameters through real-timely extracting the characteristics of the noise in received signals. Then, the time of flight measurement accuracy can significantly increased by improving the signal-to-noise ratio of the ultrasonic received signals. Verification experiments show that the measurement error is less than 0.28 mm in indoor environment, which meets most of distance measurement requirement for industrial manufacturing.

Key words: information processing, ultrasonic ranging, self-adaptive filter, threshold adjustment

中图分类号: 

  • TH915.05
[1] Kim S Y, Yoon K S, Lee D H, et al. The localization of a mobile robot using a pseudolite ultrasonic system and a dead reckoning integrated system[J]. International Journal of Control, Automation and Systems,2011,9(2):339-347.
[2] Wibowo A, Sutikno S, Kushartantya K, et al. Parallel cascade fuzzy inference system at the environment changes, case study: automated guide vehicle robot using ultrasonic sensor[C]//International Conference on Advanced Computer Science and Information Systems (ICACSIS), Jakarta, Indonesia,2012:319-324.
[3] 张凯渊, 刘佩林, 钱久超, 等. 多传感器融合机器人室内定位系统设计与实现[J]. 信息技术, 2014(11):83-87.
Zhang Kai-yuan, Liu Pei-lin, Qian Jiu-chao, et al. Design and implementation of multi-sensor fused robot indoor localization system[J]. Information Technology, 2014(11):83-87.
[4] Wang X, Tang Z. A novel method for digital ultrasonic time-of-flight measurement[J]. Review of Scientific Instruments, 2010,81:105112.
[5] 蒋林, 闫继宏, 臧希喆, 等. 一种新的超声波绝对定位方法[J]. 吉林大学学报:工学版, 2009, 39(1):188-193.
Jiang Lin, Yan Ji-hong, Zang Xi-zhe, et al. New method for ultrasonic absolute localization[J]. Journal of Jilin University (Engineering and Technology Edition), 2009, 39(1): 188-193.
[6] Tsai W Y, Chen H C, Liao T L. An ultrasonic air temperature measurement system with self-correction function for humidity[J]. Measurement Science and Technology, 2005, 16(2): 548-555.
[7] 沈梦婷, 杨学友, 吴军. 基于相位叠加的 Cricket 系统信标节点识别方法[J]. 传感技术学报, 2013, 26(7): 981-985.
Shen Meng-ting,Yang Xue-you,Wu Jun.A method of identifying beacons of cricket system based on phase superposition[J]. Chinese Journal of Sensors and Actuators, 2013, 26(7): 981-985.
[8] 刘超, 田俊杰. 基于SOPC的高精度超声波雷达测距系统设计[J]. 电子产品世界, 2015, 22(11): 51-53.
Liu Chao, Tian Jun-jie. Design of high-precision ultrasonic radar ranging system based on SOPC[J]. Electronic Engineering & Product World, 2015, 22(11): 51-53.
[9] 刘丽艳, 杨洋, 刘芃宏, 等. 基于频谱分析方法的超声空化场三维重建及其分布[J].天津大学学报:自然科学与工程技术版,2014,47(11): 962-966.
Liu Li-yan, Yang Yang, Liu Peng-hong, et al. 3D reconstruction of ultrasonic cavitation field and its distribution based on spectral analysis[J]. Journal of Tianjin University(Science and Technology), 2014,47(11):962-966.
[10] Fu H, Du X K, Chen F. Application of ultrasonic ranging compensate in the pit robot based on Elman network[J]. Journal of China Coal Society,2005,30(6):783-787.
[11] San J L, Rodriguez-Hernandez Emeterio. Wavelet denoising of ultrasonic A-scans for detection of weak signals[C]//The 19th International Conference on Systems, Signals and Image Processing (IWSSIP), Vienna, Austria,2012:48-51.
[12] Om H, Biswas M. An improved image denoising method based on wavelet thresholding[J]. Journal of Signal & Information Processing, 2012,3(1):109-116.
[13] Zhou R, Bao W, Li N, et al. Mechanical equipment fault diagnosis based on redundant second generation wavelet packet transform[J]. Digital Signal Processing,2010,20:276-288.
[14] Shao L, Yan R, Li X, et al. From heuristic optimization to dictionary learning: a review and comprehensive comparison of image denoising algorithms[J]. IEEE Transactions on Cybernetics,2014,44:1001-1013.
[15] Zeng T, Ma J L, Fu B B, et al. An exploration of dynamic threshold wavelet shrinkage method for heart sound denoising[J]. International Journal of Information and Electronics Engineering,2015,5(2):93-97.
[16] 姚成, 司玉娟, 郎六琪, 等. 基于提升小波的心电信号P, T波检测快速算法[J]. 吉林大学学报:工学版,2013,43(增刊1): 177-182.
Yao Cheng,Si Yu-juan,Lang Liu-qi,et al.ECG P, T wave complex detection algorithm based on lifting wavelet[J].Journal of Jilin University(Engineering and Technology Edition),2013,43(Sup.1):177-182.
[17] 费业泰. 误差理论与数据处理[M]. 北京:机械工业出版社, 2010:20-23.
[18] 陈建, 孙晓颖, 林琳, 等. 一种高精度超声波到达时刻的检测方法[J].仪器仪表学报, 2012(11):2422-2428.
Chen Jian, Sun Xiao-ying, Lin Lin, et al. Method to precisely measure arrival time of ultrasonic[J].Chinese Journal of Scientific Instrument,2012(11): 2422-2428.
[1] 苏寒松,代志涛,刘高华,张倩芳. 结合吸收Markov链和流行排序的显著性区域检测[J]. 吉林大学学报(工学版), 2018, 48(6): 1887-1894.
[2] 徐岩,孙美双. 基于卷积神经网络的水下图像增强方法[J]. 吉林大学学报(工学版), 2018, 48(6): 1895-1903.
[3] 黄勇,杨德运,乔赛,慕振国. 高分辨合成孔径雷达图像的耦合传统恒虚警目标检测[J]. 吉林大学学报(工学版), 2018, 48(6): 1904-1909.
[4] 李居朋,张祖成,李墨羽,缪德芳. 基于Kalman滤波的电容屏触控轨迹平滑算法[J]. 吉林大学学报(工学版), 2018, 48(6): 1910-1916.
[5] 应欢,刘松华,唐博文,韩丽芳,周亮. 基于自适应释放策略的低开销确定性重放方法[J]. 吉林大学学报(工学版), 2018, 48(6): 1917-1924.
[6] 陆智俊,钟超,吴敬玉. 星载合成孔径雷达图像小特征的准确分割方法[J]. 吉林大学学报(工学版), 2018, 48(6): 1925-1930.
[7] 刘仲民,王阳,李战明,胡文瑾. 基于简单线性迭代聚类和快速最近邻区域合并的图像分割算法[J]. 吉林大学学报(工学版), 2018, 48(6): 1931-1937.
[8] 单泽彪,刘小松,史红伟,王春阳,石要武. 动态压缩感知波达方向跟踪算法[J]. 吉林大学学报(工学版), 2018, 48(6): 1938-1944.
[9] 姚海洋, 王海燕, 张之琛, 申晓红. 双Duffing振子逆向联合信号检测模型[J]. 吉林大学学报(工学版), 2018, 48(4): 1282-1290.
[10] 全薇, 郝晓明, 孙雅东, 柏葆华, 王禹亭. 基于实际眼结构的个性化投影式头盔物镜研制[J]. 吉林大学学报(工学版), 2018, 48(4): 1291-1297.
[11] 陈绵书, 苏越, 桑爱军, 李培鹏. 基于空间矢量模型的图像分类方法[J]. 吉林大学学报(工学版), 2018, 48(3): 943-951.
[12] 陈涛, 崔岳寒, 郭立民. 适用于单快拍的多重信号分类改进算法[J]. 吉林大学学报(工学版), 2018, 48(3): 952-956.
[13] 孟广伟, 李荣佳, 王欣, 周立明, 顾帅. 压电双材料界面裂纹的强度因子分析[J]. 吉林大学学报(工学版), 2018, 48(2): 500-506.
[14] 林金花, 王延杰, 孙宏海. 改进的自适应特征细分方法及其对Catmull-Clark曲面的实时绘制[J]. 吉林大学学报(工学版), 2018, 48(2): 625-632.
[15] 王柯, 刘富, 康冰, 霍彤彤, 周求湛. 基于沙蝎定位猎物的仿生震源定位方法[J]. 吉林大学学报(工学版), 2018, 48(2): 633-639.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
版权所有 © 《吉林大学学报(工学版)》编辑部
地址：长春市人民大街5988号　电话：+86-431-85095297　传真：+86-431-85094074　E-mail: xbgxb@jlu.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发