Three-dimensional (3D) shape measurement methods based on fringe analysis could achieve high resolution and high accuracy. Fourier transform profilometry (FTP) uses a single fringe pattern is sufficient to recover the carrier phase for 3D shape measurement. Basically, FTP method applies Fourier transform to a fringe image and extracts the desired phase by applying a band-pass filter to obtain the desired carrier phase. Though successful, the single-pattern FTP method has the following major limitations: 1) it is sensitive to noise; 2) it is difficult to accurately measure an object surface with strong texture variations; and 3) it is difficult to measure detailed complex surface structures. To alleviate the influence of averaged background (i.e., DC) signal, the modified FTP method was proposed by taking another fringe pattern to remove DC from the fringe pattern. Even more robust, the modified FTP method still cannot achieve high accuracy for complex surface geometry or objects with strong texture. This is because to properly recover the carrier phase, FTP requires a properly designed filter to recover the carrier phase that might be polluted by surface texture or geometry. Hilbert transform, in contrast, is based on one inherent property of Hilbert transform: it shifts the phase of a sine function by $pi/2$. For a fringe pattern without DC component, the phase can be directly retrieved using Hilbert transform without filtering. This paper examines differences between these two methods and presents both simulation and experimental comparing results.
{"title":"Comparing Hilbert transform profilometry and Fourier transform profilometry (Conference Presentation)","authors":"Song Zhang","doi":"10.1117/12.2517870","DOIUrl":"https://doi.org/10.1117/12.2517870","url":null,"abstract":"Three-dimensional (3D) shape measurement methods based on fringe analysis could achieve high resolution and high accuracy. Fourier transform profilometry (FTP) uses a single fringe pattern is sufficient to recover the carrier phase for 3D shape measurement. Basically, FTP method applies Fourier transform to a fringe image and extracts the desired phase by applying a band-pass filter to obtain the desired carrier phase. Though successful, the single-pattern FTP method has the following major limitations: 1) it is sensitive to noise; 2) it is difficult to accurately measure an object surface with strong texture variations; and 3) it is difficult to measure detailed complex surface structures. To alleviate the influence of averaged background (i.e., DC) signal, the modified FTP method was proposed by taking another fringe pattern to remove DC from the fringe pattern. Even more robust, the modified FTP method still cannot achieve high accuracy for complex surface geometry or objects with strong texture. This is because to properly recover the carrier phase, FTP requires a properly designed filter to recover the carrier phase that might be polluted by surface texture or geometry. Hilbert transform, in contrast, is based on one inherent property of Hilbert transform: it shifts the phase of a sine function by $pi/2$. For a fringe pattern without DC component, the phase can be directly retrieved using Hilbert transform without filtering. This paper examines differences between these two methods and presents both simulation and experimental comparing results.","PeriodicalId":394633,"journal":{"name":"Dimensional Optical Metrology and Inspection for Practical Applications VIII","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129423456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiaobo Tian, A. Sohn, Yu Zhang, O. Spires, Rongguang Liang
We present a dual-mode snapshot interferometric system (DMSIS) for measuring both surface shape and surface roughness to meet the urgent need for on-machine metrology in optical fabrication. Two different modes, interferometer mode and microscopy mode, are achieved using Linnik configuration. To realize snapshot measurement, a pixelated polarization camera is used to capture four phase-shifted interferograms simultaneously. We have demonstrated its performance for off-line metrology and on-machine metrology by mounting it on a diamond turning machine.
{"title":"Dual-mode snapshot interferometric system for on-machine metrology (Conference Presentation)","authors":"Xiaobo Tian, A. Sohn, Yu Zhang, O. Spires, Rongguang Liang","doi":"10.1117/12.2518689","DOIUrl":"https://doi.org/10.1117/12.2518689","url":null,"abstract":"We present a dual-mode snapshot interferometric system (DMSIS) for measuring both surface shape and surface roughness to meet the urgent need for on-machine metrology in optical fabrication. Two different modes, interferometer mode and microscopy mode, are achieved using Linnik configuration. To realize snapshot measurement, a pixelated polarization camera is used to capture four phase-shifted interferograms simultaneously. We have demonstrated its performance for off-line metrology and on-machine metrology by mounting it on a diamond turning machine.","PeriodicalId":394633,"journal":{"name":"Dimensional Optical Metrology and Inspection for Practical Applications VIII","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122243350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Benchmark measurements for additive manufacturing of metals (Conference Presentation)","authors":"L. Levine, B. Lane","doi":"10.1117/12.2519509","DOIUrl":"https://doi.org/10.1117/12.2519509","url":null,"abstract":"","PeriodicalId":394633,"journal":{"name":"Dimensional Optical Metrology and Inspection for Practical Applications VIII","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128635925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This report evaluates some of the challenges faced with 2D camera based on-machine metrology and potential options with using 3D sensors for such Direct Write applications. Specifically, in order to fully exploit 3D direct write technology to surfaces in excess of 45 degree to the print direction, non-planar motion employing 4th and 5th rotary axes are often necessary. This report will outline a procedure for doing high accuracy rotary axis calibration. Furthermore, the use of online metrology solution to enable tuning of the rotary axis as well as for online print characterization will be detailed. These efforts will provide a fresh impetus to the use of 3D sensors for on-machine monitoring applications in additive manufacturing.
{"title":"3D sensing for direct write error characterization for aerosol jet printing","authors":"Rajesh Ramamurthy, H. Chiu, K. Harding, R. Tait","doi":"10.1117/12.2518629","DOIUrl":"https://doi.org/10.1117/12.2518629","url":null,"abstract":"This report evaluates some of the challenges faced with 2D camera based on-machine metrology and potential options with using 3D sensors for such Direct Write applications. Specifically, in order to fully exploit 3D direct write technology to surfaces in excess of 45 degree to the print direction, non-planar motion employing 4th and 5th rotary axes are often necessary. This report will outline a procedure for doing high accuracy rotary axis calibration. Furthermore, the use of online metrology solution to enable tuning of the rotary axis as well as for online print characterization will be detailed. These efforts will provide a fresh impetus to the use of 3D sensors for on-machine monitoring applications in additive manufacturing.","PeriodicalId":394633,"journal":{"name":"Dimensional Optical Metrology and Inspection for Practical Applications VIII","volume":"61 36","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120888858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Over the past few decades, tremendous efforts have been devoted to developing various techniques for fringe analysis, and they can be broadly classified into two categories: (1) phase-shifting (PS) methods which require multiple fringe patterns to extract phase information and (2) spatial phase demodulation methods which allow phase retrieval from a single fringe pattern, such as the Fourier transform (FT), windowed Fourier transform (WFT), and wavelet transform (WT) methods. Compared with spatial phase demodulation methods, the multiple-shot phase-shifting techniques are generally more robust and can achieve pixel-wise phase measurement with higher resolution and accuracy. Furthermore, the phase-shifting measurements are quite insensitive to non-uniform background intensity and fringe modulation. Nevertheless, due to their multi-shot nature, these methods are difficult to apply to dynamic measurements and are more susceptible to external disturbance and vibrations. Thus, for many applications, phase extraction from a single fringe pattern is desired, which falls under the purview of spatial fringe analysis. Here, we demonstrate experimentally for the first time, to our knowledge, that the use of convolutional neural networks can substantially enhance the accuracy of phase demodulation from a single fringe pattern. Deep learning is a powerful machine learning technique that employs artificial neural networks with multiple layers of increasingly richer functionality. The effectiveness of the proposed method is verified using carrier fringe patterns under the scenario of fringe projection profilometry. Experimental results demonstrate its superior performance in terms of high accuracy and edge-preserving over two representative single-frame techniques: Fourier transform profilometry and windowed Fourier profilometry.
{"title":"Fringe analysis based on convolutional neural networks (Conference Presentation)","authors":"Shijie Feng, C. Zuo, Qian Chen, G. Gu","doi":"10.1117/12.2520144","DOIUrl":"https://doi.org/10.1117/12.2520144","url":null,"abstract":"Over the past few decades, tremendous efforts have been devoted to developing various techniques for fringe analysis, and they can be broadly classified into two categories: (1) phase-shifting (PS) methods which require multiple fringe patterns to extract phase information and (2) spatial phase demodulation methods which allow phase retrieval from a single fringe pattern, such as the Fourier transform (FT), windowed Fourier transform (WFT), and wavelet transform (WT) methods. Compared with spatial phase demodulation methods, the multiple-shot phase-shifting techniques are generally more robust and can achieve pixel-wise phase measurement with higher resolution and accuracy. Furthermore, the phase-shifting measurements are quite insensitive to non-uniform background intensity and fringe modulation. Nevertheless, due to their multi-shot nature, these methods are difficult to apply to dynamic measurements and are more susceptible to external disturbance and vibrations. Thus, for many applications, phase extraction from a single fringe pattern is desired, which falls under the purview of spatial fringe analysis. \u0000\u0000Here, we demonstrate experimentally for the first time, to our knowledge, that the use of convolutional neural networks can substantially enhance the accuracy of phase demodulation from a single fringe pattern. Deep learning is a powerful machine learning technique that employs artificial neural networks with multiple layers of increasingly richer functionality. The effectiveness of the proposed method is verified using carrier fringe patterns under the scenario of fringe projection profilometry. Experimental results demonstrate its superior performance in terms of high accuracy and edge-preserving over two representative single-frame techniques: Fourier transform profilometry and windowed Fourier profilometry.","PeriodicalId":394633,"journal":{"name":"Dimensional Optical Metrology and Inspection for Practical Applications VIII","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128300769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiaobo Tian, Hee-June Choi, A. Sohn, Yu Zhang, O. Spires, Dae Wook Kim, Rongguang Liang
We present a snapshot, adaptive null interferometric system for measuring freeform surfaces using deformable mirror as the null corrector to increase the measurement range. To compensate the wavefront for different surfaces, a computer controlled deformable mirror is used as an adaptive wavefront corrector. A deformable mirror control algorithm based on stochastic parallel gradient descent algorithm has been developed to drive the deformable mirror to null the interference fringe. Snapshot phase measurement is proposed in the optimization progress to increase the iterative speed. The surface shape of the deformable mirror is measured by a deflectometry system to calculate the shape of the surface under test.
{"title":"Compact snapshot freefrom null testing with adaptive optics (Conference Presentation)","authors":"Xiaobo Tian, Hee-June Choi, A. Sohn, Yu Zhang, O. Spires, Dae Wook Kim, Rongguang Liang","doi":"10.1117/12.2518789","DOIUrl":"https://doi.org/10.1117/12.2518789","url":null,"abstract":"We present a snapshot, adaptive null interferometric system for measuring freeform surfaces using deformable mirror as the null corrector to increase the measurement range. To compensate the wavefront for different surfaces, a computer controlled deformable mirror is used as an adaptive wavefront corrector. A deformable mirror control algorithm based on stochastic parallel gradient descent algorithm has been developed to drive the deformable mirror to null the interference fringe. Snapshot phase measurement is proposed in the optimization progress to increase the iterative speed. The surface shape of the deformable mirror is measured by a deflectometry system to calculate the shape of the surface under test.","PeriodicalId":394633,"journal":{"name":"Dimensional Optical Metrology and Inspection for Practical Applications VIII","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129229289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tristan G. Fleming, Troy R. Allen, Stephen G. L. Nestor, F. Altal, J. Fraser
Directly measuring morphology and temperature changes during laser processing (such as in keyhole welding and selective laser melting) can help us to understand, optimize, and control on-the-fly the manufacturing process. Even with such great potential, the technical requirements for such an in situ metrology are high due to the fast nature of the highly localized dynamics, all the while in the presence of bright backscatter and blackbody radiation, and possible obstructions such as molten ejecta and plumes. We have demonstrated that by exploiting coherent imaging through a single-mode fiber inline with the processing lens, we can image morphology at line rates up to 312 kHz, with sufficient robustness to achieve closed loop control of the manufacturing process. Applied to metal additive manufacturing, inline coherent imaging can directly measure powder layer thickness and uniformity, and formed track roughness including the onset of balling. Inline coherent imaging measures morphology dynamics but that is only part of the story. Temperature is also key to final part quality. Standard thermal imaging exploits blackbody radiation but are plagued by the highly variable emissivity of the region of interest, making quantitative measurement challenging. We were able to exploit the same apparatus used for coherent imaging to collect surface temperature profiles. Since we spectrally resolve a wide signature, we have overcome the emissivity problem to measure absolute temperature on the micron scale during laser processing.
{"title":"In-process imaging of morphology and temperature for laser welding and selective laser melting (Conference Presentation)","authors":"Tristan G. Fleming, Troy R. Allen, Stephen G. L. Nestor, F. Altal, J. Fraser","doi":"10.1117/12.2520188","DOIUrl":"https://doi.org/10.1117/12.2520188","url":null,"abstract":"Directly measuring morphology and temperature changes during laser processing (such as in keyhole welding and selective laser melting) can help us to understand, optimize, and control on-the-fly the manufacturing process. Even with such great potential, the technical requirements for such an in situ metrology are high due to the fast nature of the highly localized dynamics, all the while in the presence of bright backscatter and blackbody radiation, and possible obstructions such as molten ejecta and plumes. We have demonstrated that by exploiting coherent imaging through a single-mode fiber inline with the processing lens, we can image morphology at line rates up to 312 kHz, with sufficient robustness to achieve closed loop control of the manufacturing process. Applied to metal additive manufacturing, inline coherent imaging can directly measure powder layer thickness and uniformity, and formed track roughness including the onset of balling. Inline coherent imaging measures morphology dynamics but that is only part of the story. Temperature is also key to final part quality. Standard thermal imaging exploits blackbody radiation but are plagued by the highly variable emissivity of the region of interest, making quantitative measurement challenging. We were able to exploit the same apparatus used for coherent imaging to collect surface temperature profiles. Since we spectrally resolve a wide signature, we have overcome the emissivity problem to measure absolute temperature on the micron scale during laser processing.","PeriodicalId":394633,"journal":{"name":"Dimensional Optical Metrology and Inspection for Practical Applications VIII","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130143002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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