Fringe Texture Driven Droplet Measurement End-to-End Network Based on Physics Aberrations Restoration of Coherence Scanning Interferometry

Accurate and efficient measurement of deposited droplets’ volume is vital to achieve zero-defect manufacturing in inkjet printed organic light-emitting diode (OLED), but it remains a challenge due to droplets’ featurelessness. In our work, coherence scanning interferometry (CSI) is utilized to measu...

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Main Authors: Zhou Zhang, Jiankui Chen, Hua Yang, Zhouping Yin
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Micromachines
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Online Access:https://www.mdpi.com/2072-666X/16/1/42
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author Zhou Zhang
Jiankui Chen
Hua Yang
Zhouping Yin
author_facet Zhou Zhang
Jiankui Chen
Hua Yang
Zhouping Yin
author_sort Zhou Zhang
collection DOAJ
description Accurate and efficient measurement of deposited droplets’ volume is vital to achieve zero-defect manufacturing in inkjet printed organic light-emitting diode (OLED), but it remains a challenge due to droplets’ featurelessness. In our work, coherence scanning interferometry (CSI) is utilized to measure the volume. However, the CSI redundant sampling and image degradation led by the sample’s transparency decrease the efficiency and accuracy. Based on the prior degradation and strong representation for context, a novel method, volume measurement via fringe distribution module (VMFD), is proposed to directly measure the volume by single interferogram without redundant sampling. Firstly, the 3D point spread function (PSF) for CSI imaging is modeling to relate the degradation and image. Secondly, the Zernike to PSF (ZTP) module is proposed to efficiently compute the aberrations to PSF. Then, a physics aberration restoration network (PARN) is designed to remove the degradation via the channel Transformer and U-net architecture. The long term context is learned by PARN and beneficial to restoration. The restored fringes are used to measure the droplet’s volume by constrained regression network (CRN) module. Finally, the performances on public datasets and the volume measurement experiments show the promising deblurring, measurement precision and efficiency.
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institution Kabale University
issn 2072-666X
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series Micromachines
spelling doaj-art-ae5e4d96455241c9a44943e81ffb07862025-01-24T13:41:56ZengMDPI AGMicromachines2072-666X2024-12-011614210.3390/mi16010042Fringe Texture Driven Droplet Measurement End-to-End Network Based on Physics Aberrations Restoration of Coherence Scanning InterferometryZhou Zhang0Jiankui Chen1Hua Yang2Zhouping Yin3State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, ChinaState Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, ChinaState Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, ChinaState Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, ChinaAccurate and efficient measurement of deposited droplets’ volume is vital to achieve zero-defect manufacturing in inkjet printed organic light-emitting diode (OLED), but it remains a challenge due to droplets’ featurelessness. In our work, coherence scanning interferometry (CSI) is utilized to measure the volume. However, the CSI redundant sampling and image degradation led by the sample’s transparency decrease the efficiency and accuracy. Based on the prior degradation and strong representation for context, a novel method, volume measurement via fringe distribution module (VMFD), is proposed to directly measure the volume by single interferogram without redundant sampling. Firstly, the 3D point spread function (PSF) for CSI imaging is modeling to relate the degradation and image. Secondly, the Zernike to PSF (ZTP) module is proposed to efficiently compute the aberrations to PSF. Then, a physics aberration restoration network (PARN) is designed to remove the degradation via the channel Transformer and U-net architecture. The long term context is learned by PARN and beneficial to restoration. The restored fringes are used to measure the droplet’s volume by constrained regression network (CRN) module. Finally, the performances on public datasets and the volume measurement experiments show the promising deblurring, measurement precision and efficiency.https://www.mdpi.com/2072-666X/16/1/42droplet measurementcoherent scanning interferencephysics aberrationdeep learninginkjet printingimage restoration
spellingShingle Zhou Zhang
Jiankui Chen
Hua Yang
Zhouping Yin
Fringe Texture Driven Droplet Measurement End-to-End Network Based on Physics Aberrations Restoration of Coherence Scanning Interferometry
Micromachines
droplet measurement
coherent scanning interference
physics aberration
deep learning
inkjet printing
image restoration
title Fringe Texture Driven Droplet Measurement End-to-End Network Based on Physics Aberrations Restoration of Coherence Scanning Interferometry
title_full Fringe Texture Driven Droplet Measurement End-to-End Network Based on Physics Aberrations Restoration of Coherence Scanning Interferometry
title_fullStr Fringe Texture Driven Droplet Measurement End-to-End Network Based on Physics Aberrations Restoration of Coherence Scanning Interferometry
title_full_unstemmed Fringe Texture Driven Droplet Measurement End-to-End Network Based on Physics Aberrations Restoration of Coherence Scanning Interferometry
title_short Fringe Texture Driven Droplet Measurement End-to-End Network Based on Physics Aberrations Restoration of Coherence Scanning Interferometry
title_sort fringe texture driven droplet measurement end to end network based on physics aberrations restoration of coherence scanning interferometry
topic droplet measurement
coherent scanning interference
physics aberration
deep learning
inkjet printing
image restoration
url https://www.mdpi.com/2072-666X/16/1/42
work_keys_str_mv AT zhouzhang fringetexturedrivendropletmeasurementendtoendnetworkbasedonphysicsaberrationsrestorationofcoherencescanninginterferometry
AT jiankuichen fringetexturedrivendropletmeasurementendtoendnetworkbasedonphysicsaberrationsrestorationofcoherencescanninginterferometry
AT huayang fringetexturedrivendropletmeasurementendtoendnetworkbasedonphysicsaberrationsrestorationofcoherencescanninginterferometry
AT zhoupingyin fringetexturedrivendropletmeasurementendtoendnetworkbasedonphysicsaberrationsrestorationofcoherencescanninginterferometry