基于经验小波变换及核概率密度的物体表面变形测量
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摘要
采用CCD相机采集物体变形前后的散斑图片,利用一维经验小波变换对散斑图片进行逐行分解,获得一系列的固有分量.根据分解后分量的核概率密度函数提出基于核概率密度的自适应降噪法,去除噪声干扰,提取跟变形信息相关的分量并重构,利用重构后的每一行获得变形前后重构散斑图.采用Hilbert法计算重构后散斑图的相位,对变形前后散斑图相位进行相减,根据相位差进行解包裹获得物体表面变形信息.实验结果表明该方法能够有效地对物体表面变形进行测量,且测量精度较经验模态分解提高4倍.
In order to accurately measure the surface deformation information,a surface deformation measurement method based on Empirical Wavelet Transform(EWT)and kernel probability density was proposed.Firstly,the CCD camera was used to collect the digital speckle pattern interferometry(DSPI)maps,the DSPI maps were decomposed to obtain a series of intrinsic components by EWT.According to the kernel probability density of the decomposed component,an adaptive de-noising method was proposed to extract the components with the deformation information,the components were reconstructed DSPI maps;Finally,using Hilbert method to calculate reconstructed DSPI phase,the DSPI phase before and after deformation was subtracted,and the surface deformation information was obtained by decoupling according to the phase difference.The experimental results showed that the method can effectively measure the object surface deformation,and the accuracy is improved by 4 times compared with the EMD method.
In order to accurately measure the surface deformation information,a surface deformation measurement method based on Empirical Wavelet Transform(EWT)and kernel probability density was proposed.Firstly,the CCD camera was used to collect the digital speckle pattern interferometry(DSPI)maps,the DSPI maps were decomposed to obtain a series of intrinsic components by EWT.According to the kernel probability density of the decomposed component,an adaptive de-noising method was proposed to extract the components with the deformation information,the components were reconstructed DSPI maps;Finally,using Hilbert method to calculate reconstructed DSPI phase,the DSPI phase before and after deformation was subtracted,and the surface deformation information was obtained by decoupling according to the phase difference.The experimental results showed that the method can effectively measure the object surface deformation,and the accuracy is improved by 4 times compared with the EMD method.
引文
[1]MA Bao-quan,ZHOU Zheng-gan.Progress and development trends of composite structure evaluation using noncontact nondestructive testing techniques in aviation and aerospace industries[J].Acta Aeronautica et Astronautica Sinica,2014,35(7):1787-1803.马保全,周正干.航空航天复合材料结构非接触无损检测技术的进展及发展趋势[J].航空学报,2014,35(7):1787-1803.
[2]BALASKO M,SVAB E,MOLNAR G,et al.Classification of defects in honeycomb composite structure of helicopter rotor blades[J].Nuclear Instruments and Methods in Physics Research Section A:Accelerators,Spectrometers,Detectors and Associated Equipment,2005,542(1):45-51.
[3]ZHU Xin-jun,DENG Yao-hui,TANG Chen,et al.Variational mode decomposition for phase retrieval in fringe projection 3Dshape measurement[J].Optics and Precision Engineering,2016,24(9):2318-2324.朱新军,邓耀辉,唐晨,等.条纹投影三维形貌测量的变分模态分解相位提取[J].光学精密工程,2016,24(9):2318-2324.
[4]XIONG Liu-dong,JIA Shu-hai,DU Yan-fen.Anovel algorithm for phase retrieval from a single carrier-frequency fringe pattern[J].Acta Optica Sinica,2010,30(1):123-126.熊六东,贾书海,杜艳芬.单幅载频条纹图的相位恢复新算法[J].光学学报,2010,30(1):123-126.
[5]GUO Yuan,MAO Qi,CHENG Xiao-tian,et al.Applied research of dual-wavelength shearography for flaw detection of composite material[J].Acta Photonica Sinica,2015,44(3):0312001.郭媛,毛琦,陈小天,等.双波长剪切散斑干涉法在复合材料缺陷检测中的应用[J].光子学报,2015,44(3):0312001.
[6]LI Xiang-yu,HUANG Zhan-hua,ZHANG Hao,et al.Phase analysis method based on Hilbert transform in dynamic speckle pattern interferometry[J].Journal of Optoelectronics&Laser,2015(6):1111-1117.李翔宇,黄战华,张昊,等.动态散斑相位的希尔伯特变换分析方法[J].光电子激光,2015(6):1111-1117.
[7]SUN Hai-bin,SUN Ping.Out-of-planedisplacement measurement using optical vortex Phase Shifting[J].Acta Photonica Sinica,2016,45(11):1112001.孙海滨,孙平.基于光学涡旋相移技术的离面位移测量[J].光子学报,2016,45(11):1112001.
[8]ZHU Meng,LI Xiang-Yu,HUANAG Zhan-hua,et al.Dynamic deformation measurement using speckle shearography with carrier frequency generated by double-aperture[J].Optics and Precision Engineering,2013,21(7):1701-1706.朱猛,李翔宇,黄战华,等.双孔载频剪切散斑干涉法测量表面动态形变[J].光学精密工程,2013,21(7):1701-1706.
[9]ZUO C,CHEN Q,GU G,et al.High-speed three-dimensional profilometry for multiple objects with complex shapes[J].Optics Express,2012,20(17):19493-19510.
[10]ZUO C,SUN J,CHEN Q.Adaptive step-size strategy for noise-robust Fourier ptychographic microscopy[J].Optics Express,2016,24(18):20724-20744.
[11]ZHOU X,YANG T,ZOU H,et al.Multivariate empirical mode decomposition approach for adaptive denoising of fringe patterns[J].Optics Letters,2012,37(11):1904-1906.
[12]SUN J D,XIAO Q Y,WEN J T,et al.Natural gas pipeline leak aperture identification and location based on local mean decomposition analysis[J].Measurement,2016,79:147-157.
[13]BEGUM D,SARP E.Empirical mode decomposition of hyper spectral images for support vector machine classification[J].IEEE Transactions on Geoscience and Remote Sensing,2010,48(11):4071-4084
[14]XIAQ Q Y,LI J,BAI I L,et al.A small leak detection method based on VMD adaptive do-noising and ambiguity correlation classification intended for natural gas pipelines[J].Sensors,2016,16(12):1-16.
[15]GILLES J.Empirical wavelet transofmr[J].IEEE Transactions on Signal Processing,2013,61(16):3999-4010.
[16]KUMAR R,SAINI I.Empirical wavelet transforms based ECG signal compression[J].IETE Journal of Research,2014,60(6):423-431.
[17]LI Zhi-nong,ZHU Ming,CHU Fu-lei,et al.Mechanical fault diagnosis method based on empirical wavelet transform[J].Chinese Journal of Scientific Instrument,2014,35(11):2423-2432.李志农,朱明,褚福磊,等.基于经验小波变换的机械故障诊断方法研究[J].仪器仪表学报,2014,35(11):2423-2432.
[18]NGUYEN P,KANG M,KIM J M,et al.Robust condition monitoring of rolling element bearings using de-noising and envelope analysis with signal decomposition techniques[J].Expert Systems with Applications,2015,42(22):9024-9032.
[19]TRUSIAK M,PATORSKI K,WIELGUS M.Adaptive enhancement of optical fringe patterns by selective reconstruction using FABEMD algorithm and Hilbert spiral transform[J].Optics Express,2012,20(21):23463-23479.
[2]BALASKO M,SVAB E,MOLNAR G,et al.Classification of defects in honeycomb composite structure of helicopter rotor blades[J].Nuclear Instruments and Methods in Physics Research Section A:Accelerators,Spectrometers,Detectors and Associated Equipment,2005,542(1):45-51.
[3]ZHU Xin-jun,DENG Yao-hui,TANG Chen,et al.Variational mode decomposition for phase retrieval in fringe projection 3Dshape measurement[J].Optics and Precision Engineering,2016,24(9):2318-2324.朱新军,邓耀辉,唐晨,等.条纹投影三维形貌测量的变分模态分解相位提取[J].光学精密工程,2016,24(9):2318-2324.
[4]XIONG Liu-dong,JIA Shu-hai,DU Yan-fen.Anovel algorithm for phase retrieval from a single carrier-frequency fringe pattern[J].Acta Optica Sinica,2010,30(1):123-126.熊六东,贾书海,杜艳芬.单幅载频条纹图的相位恢复新算法[J].光学学报,2010,30(1):123-126.
[5]GUO Yuan,MAO Qi,CHENG Xiao-tian,et al.Applied research of dual-wavelength shearography for flaw detection of composite material[J].Acta Photonica Sinica,2015,44(3):0312001.郭媛,毛琦,陈小天,等.双波长剪切散斑干涉法在复合材料缺陷检测中的应用[J].光子学报,2015,44(3):0312001.
[6]LI Xiang-yu,HUANG Zhan-hua,ZHANG Hao,et al.Phase analysis method based on Hilbert transform in dynamic speckle pattern interferometry[J].Journal of Optoelectronics&Laser,2015(6):1111-1117.李翔宇,黄战华,张昊,等.动态散斑相位的希尔伯特变换分析方法[J].光电子激光,2015(6):1111-1117.
[7]SUN Hai-bin,SUN Ping.Out-of-planedisplacement measurement using optical vortex Phase Shifting[J].Acta Photonica Sinica,2016,45(11):1112001.孙海滨,孙平.基于光学涡旋相移技术的离面位移测量[J].光子学报,2016,45(11):1112001.
[8]ZHU Meng,LI Xiang-Yu,HUANAG Zhan-hua,et al.Dynamic deformation measurement using speckle shearography with carrier frequency generated by double-aperture[J].Optics and Precision Engineering,2013,21(7):1701-1706.朱猛,李翔宇,黄战华,等.双孔载频剪切散斑干涉法测量表面动态形变[J].光学精密工程,2013,21(7):1701-1706.
[9]ZUO C,CHEN Q,GU G,et al.High-speed three-dimensional profilometry for multiple objects with complex shapes[J].Optics Express,2012,20(17):19493-19510.
[10]ZUO C,SUN J,CHEN Q.Adaptive step-size strategy for noise-robust Fourier ptychographic microscopy[J].Optics Express,2016,24(18):20724-20744.
[11]ZHOU X,YANG T,ZOU H,et al.Multivariate empirical mode decomposition approach for adaptive denoising of fringe patterns[J].Optics Letters,2012,37(11):1904-1906.
[12]SUN J D,XIAO Q Y,WEN J T,et al.Natural gas pipeline leak aperture identification and location based on local mean decomposition analysis[J].Measurement,2016,79:147-157.
[13]BEGUM D,SARP E.Empirical mode decomposition of hyper spectral images for support vector machine classification[J].IEEE Transactions on Geoscience and Remote Sensing,2010,48(11):4071-4084
[14]XIAQ Q Y,LI J,BAI I L,et al.A small leak detection method based on VMD adaptive do-noising and ambiguity correlation classification intended for natural gas pipelines[J].Sensors,2016,16(12):1-16.
[15]GILLES J.Empirical wavelet transofmr[J].IEEE Transactions on Signal Processing,2013,61(16):3999-4010.
[16]KUMAR R,SAINI I.Empirical wavelet transforms based ECG signal compression[J].IETE Journal of Research,2014,60(6):423-431.
[17]LI Zhi-nong,ZHU Ming,CHU Fu-lei,et al.Mechanical fault diagnosis method based on empirical wavelet transform[J].Chinese Journal of Scientific Instrument,2014,35(11):2423-2432.李志农,朱明,褚福磊,等.基于经验小波变换的机械故障诊断方法研究[J].仪器仪表学报,2014,35(11):2423-2432.
[18]NGUYEN P,KANG M,KIM J M,et al.Robust condition monitoring of rolling element bearings using de-noising and envelope analysis with signal decomposition techniques[J].Expert Systems with Applications,2015,42(22):9024-9032.
[19]TRUSIAK M,PATORSKI K,WIELGUS M.Adaptive enhancement of optical fringe patterns by selective reconstruction using FABEMD algorithm and Hilbert spiral transform[J].Optics Express,2012,20(21):23463-23479.