Laser ultrasonic signal processing by differential algorithm in special pipeline thickness measurement

Jian-shu CAO; Zhen-xing LUO; Bao-ping JI

doi:10.3788/OPE.20172505.1197

您当前的位置：

首页 >

文章列表页 >

Laser ultrasonic signal processing by differential algorithm in special pipeline thickness measurement

Modern Applied Optics | 更新时间：2020-07-07

- Laser ultrasonic signal processing by differential algorithm in special pipeline thickness measurement
- Optics and Precision Engineering Vol. 25, Issue 5, Pages: 1197-1205(2017)
- 作者机构：
  
  1.北京石油化工学院机械工程学院, 北京 102617
  2.北京化工大学机电工程学院, 北京 100029
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20172505.1197
  CLC： TE88
- Received：05 January 2017，
  
  Accepted：21 February 2017，
  
  Published：25 May 2017
- 稿件说明：
移动端阅览
Jian-shu CAO, Zhen-xing LUO, Bao-ping JI. Laser ultrasonic signal processing by differential algorithm in special pipeline thickness measurement[J]. Optics and precision engineering, 2017, 25(5): 1197-1205.
DOI：

Jian-shu CAO, Zhen-xing LUO, Bao-ping JI. Laser ultrasonic signal processing by differential algorithm in special pipeline thickness measurement[J]. Optics and precision engineering, 2017, 25(5): 1197-1205. DOI： 10.3788/OPE.20172505.1197.

摘要

为了实现特种管道在高温、高压、辐射等特殊环境下管壁厚度的非均匀性检测，提出一种基于微分算法的管道壁厚激光超声测量及特征信号处理方法。采用脉冲激光激励和激光干涉探测的激光超声方法，实验测得管道试件的宽频带激光超声信号。采用数字平均算法对宽带激光超声信号进行去噪处理，提高原始激光超声信号的信噪比。采用微分算法对激光超声信号进行特征提取处理，得到表征管壁厚度的激光超声特征信号。根据管道材料声速和激光超声传播时间反演计算得到管道试件的壁厚值，管壁厚度测量值与实际值的误差小于5%。研究表明，基于微分算法的管道壁厚激光超声测量及特征信号处理方法具有良好的信噪比、准确的信号特征量和较高的测量精度，可用于管道壁厚的在线实时检测以及因腐蚀、应力引起的管道壁厚不均匀性检测。

Abstract

In view of the nonuniformity of pipe wall thickness of the special pipe under special environments such as high temperature

high pressure

radiation

and others

a method for laser ultrasonic measurement and thickness feature signals processing based on the differential algorithm was proposed. The laser ultrasonic method was adopted with pulse laser excitation and laser interference detection for the experimental measurement of broad-band laser ultrasonic signals of the test piece of pipe. Then the broad-band laser ultrasonic signals were de-noised by average algorithm in order to increase the signal to noise ratio of the original laser ultrasonic signals. Furthermore

the feature of the de-noised ultrasonic signals was extracted by differential algorithm

outputting the laser ultrasonic feature signals of pipe wall thickness. According to the sound velocity of pipe material and the laser ultrasonic transit time

the thickness values for the test piece of pipe wall were deduced. The error between the measured and actual thicknesses was less than 5%. The result shows that the processing method for thickness feature signals based on differential algorithm can provide favorable signal to noise ratio

accurate signal feature quantity and higher measurement accuracy

thus can be used for online real-time measurement of wall thickness of pipe and the thickness nonuniformity leaded by erosion and stress.

关键词

Keywords

references

宋寿鹏, 李萍萍.基于卷积模型的超声回波分离技术及其应用[J].仪器仪表学报, 2009, 30(6):1175-1179.

SONG SH P, LI P P. Convolution-mode-based ultrasonic echo separation technology and its application[J]. Chinese Journal of Scientific Instrument , 2009, 30(6):1175-1179.(in Chinese)

吴德会, 游德海, 柳振凉, 等.交流漏磁检测法趋肤深度的机理与实验研究[J].仪器仪表学报, 2014, 35(2):327-336.

WU D H, YOU D H, LIU ZH L, et al ..Mechanism and experimental research on skin depth in AC magnetic flux leakage testing[J]. Chinese Journal of Scientific Instrument , 2014, 35(2):327-336.(in Chinese)

罗玉昆, 罗诗途, 罗飞路, 等.激光超声信号去噪的经验模态分解实现及改进[J].光学精密工程, 2013, 21(2):479-487.

LUO Y K, LUO SH T, LUO F L, et al .. Realization and improvement of laser ultrasonic signal denoising based on empirical mode decomposition[J]. Opt. Precision Eng ., 2013, 21(2):479-487.(in Chinese)

王洪水, 徐军, 孔令剑, 等.激光超声检测系统设计[J].红外与激光工程, 2007(z1):522-525.

WANG H SH, XU J, KONG L J, et al .. Design of the laser-ultrasonic detection system[J]. Infrared and Laser Engineering , 2007(z1):522-525.(in Chinese)

王洪超, 李亚安.局部投影降噪算法邻域半径参数的选择研究[J].系统仿真学报, 2007, 19(4):805-807.

WANG H CH, LI Y A. Determination of neighborhood size parameter of local projective algorithm for noise reduction[J]. Journal of System Simulation , 2007, 19(4):805-807.(in Chinese)

迟大钊, 刚铁, 孙昌立.基于自适应滤波的超声杂波抑制方法[J].焊接学报, 2015, 36(11):33-36.

CHI D ZH, GANG T, SUN CH L. Ultrasonic clutter suppression method using adaptive filter[J]. Transactions of the China Welding Institution , 2015, 36(11):33-36.(in Chinese)

童允, 黄松岭, 赵伟, 等.基于包络滤波的电磁超声检测数据降噪算法[J].高技术通讯, 2010(9):960-964.

TONG Y, HUANG S L, ZHAO W, et al .. An EMAT denoising algorithm based on envelope filtering[J]. Chinese High Technology Letters , 2010(9):960-964.(in Chinese)

龚志强, 邹明玮, 高新全, 等.基于非线性时间序列分析经验模态分解和小波分解异同性的研究[J].物理学报, 2005, 54(8):3947-3957.

GONG ZH Q, ZHOU M W, GAO X Q, et al .. On the difference between empirical mode decomposition and wavelet decomposition in the nonlinear time series[J]. Acta Physica Sinica , 2005, 54(8):3947-3957.(in Chinese)

马伦, 康建设, 孟妍, 等.基于Morlet小波变换的滚动轴承早期故障特征提取研究[J].仪器仪表学报, 2013, 34(4):920-926.

MA L, KANG J SH, MENG Y. et al .. Research on feature extraction of rolling bearing incipient fault based on Morlet wavelet transform[J]. Chinese Journal of Scientific Instrument , 2013, 34(4):920-926.(in Chinese)

朱浩瀚, 秦海琨, 张敏, 等.光纤布拉格光栅传感解调中的寻峰算法[J].中国激光, 2008, 35(6):893-897.

ZHU H H, QIN H K, ZHANG M, et al .. Peak detection algorithm in the demodulation for the fiber Bragg grating sensor system[J]. Chinese Journal of Lasers , 2008, 35(6):893-897.(in Chinese)

陶珂, 朱建军.多指标融合的小波去噪最佳分解尺度选择方法[J].测绘学报, 2012, 41(5):749-755.

TAO K, ZHU J J. A hybrid indicator for determining the best decomposition scale of wavelet denoising[J]. Acta Geodaetica et Cartographica Sinica , 2012, 41(5):749-755.(in Chinese)

吴光文, 王昌明, 包建东, 等.基于自适应阈值函数的小波阈值去噪方法[J].电子与信息学报, 2014, 36(6):1340-1347.

WU G W, WANG CH M, BAO J D, et al .. A wavelet threshold de-noising algorithm based on adaptive threshold function[J]. Journal of Electronics & Information Technology , 2014, 36(6):1340-1347.(in Chinese)

王发牛, 粱栋, 唐俊, 等.小波变换模极大值多尺度边缘检测[J].仪器仪表学报, 2006 (z3):2147-2149.

WANG F N, LIANG D, TANG J, et al .. Multiscale edge detection based on wavelet modulus maxima[J]. Chinese Journal of Scientific Instrument , 2006 (z3):2147-2149.(in Chinese)

秦旭达, 王太勇, 刘兴荣, 等.微分处理方法在漏磁检测信号分析中的应用研究[J].钢铁, 2004, 39(2):67-70.

QIN X D, WANG T Y, LIU X R, et al .. Research on differential algorithm and its application in magnetic flux leakage signal processing[J]. Iron and Steel , 2004, 39(2):67-70.(in Chinese)

杨柱中, 周激流, 晏祥玉, 等.基于分数阶微分的图像增强[J].计算机辅助设计与图形学学报, 2008, 20(3):343-348.

YANG ZH ZH, ZHOU J L, YAN X Y, et al .. Image enhancement based on fractional differentials[J]. Journal of Computer-aided Design & Computer Graphics , 2008, 20(3):343-348.(in Chinese)

张东, 塔西甫拉提·特依拜, 张飞, 等.分数阶微分在盐渍土高光谱数据预处理中的应用[J].农业工程学报, 2014, 30(24):151-160.

ZHANG D, TASHPOLAT·T, ZHANG F, et al .. Application of fractional differential in preprocessing hyperspectral data of saline soil[J]. Transactions of the Chinese Society of Agricultural Engineering , 2014, 30(24):151-160.(in Chinese)

靳世久, 王立宁, 李健, 等.原油管道漏点定位技术[J].石油学报, 1998, 19(3):105-109

JIN SH J, WANG L N, LI J, et al .. Study on leak point locating of crude oil pipelines[J]. Acta Petrolei Sinica , 1998, 19(3):105-109.(in Chinese)

曹建树, 姬保平, 罗振兴, 等.激光超声信号去噪方法的研究[J].激光与红外, 2016, 46(2):171-176.

CAO J SH, JI B P, LUO ZH X, et al .. Research on de-noising method for laser ultrasonic signal[J]. Laser & Infrared , 2016, 46(2):171-176.(in Chinese)

Views

1002

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Hyperspectral images feature extraction and classification based on fractional differentiation

Lightweight deep global-local knowledge distillation network for hyperspectral image scene classification

Dense pedestrian detection algorithm in multi-branch non-anchor frame network

Application of SENet generative adversarial network in image semantics description

Semi-supervised dual path network for hyperspectral image classification

Related Author

LIU Jing

LI Yang

LIU Yi

LIU Yingxu

PU Chunyu

XU Diankun

YANG Yichuan

HUANG Hong

Related Institution

School of Electronic Engineering， Xidian University

School of Electronic Engineering， Xi’an University of Posts and Telecommunications

Key Laboratory of Optoelectronic Technology and Systems of the Education Ministry of China， Chongqing University

Measurement and Control Technology and Instrument major， College of Optoelectronic Engineering， Chongqing University

School of Electrical Engineering， XinJiang University

AI问答

Address：No.3888 Dong Nanhu Road, Changchun, Jilin, China Postal code：130033
Tel：0431-86176855 Email：gxjmgc@ciomp.ac.cn
Technical support is provided by Beijing Founder electronics co., LTD 吉ICP备11002662号-17 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰