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Photonics
Special Issues
State-of-the-Art Optical Inspection Technology
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State-of-the-Art Optical Inspection Technology

A special issue of Photonics (ISSN 2304-6732). This special issue belongs to the section "Optical Interaction Science".

Deadline for manuscript submissions: closed (29 February 2024) | Viewed by 6662

Special Issue Editors

Dr. Xing Peng

E-Mail Website
Guest Editor
Laboratory of Science and Technology on Integrated Logistics Support, National University of Defense Technology, Changsha, China
Interests: additive manufacturing; defect detection; optical design; illuminance design; visible light communication; machine vision; multi-sensor inspection
Special Issues, Collections and Topics in MDPI journals
Dr. Xiang Sun

E-Mail Website
Guest Editor
School of Electrical and Automation Engineering, East China Jiao Tong University, Changbei Open and Developing District, Nanchang 330013, China
Interests: machine vision; polarization; visual measurement; wavelet algorithm; machine learning; non-imaging optical design; illumination design
Prof. Dr. Lingbao Kong

E-Mail Website
Guest Editor
Department of Optical Science and Engineering, Fudan University, Shanghai 200438, China
Interests: manufacturing process mechanics; 3D printing; ultra-precision manufacturing and metrology; freeform measurement and characterization; manufacturing process optimization; fring projection; 3D vision; VR/AR/MR; light field; machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the development process of modern industry and science, there are various requirements for industrial inspection technology. Industrial inspection technology is a complex interdisciplinary field that involves optical devices, optical processing, artificial intelligence, neurobiology, signal processing, computer science, image processing, machine learning and other fields. Especially in recent years, a series of important research achievements have been made in the field of industrial inspection technology. It is within this context that we announce the Special Issue of Photonics on “State-of-the-Art Optical Inspection Technology”.

This Special Issue intends to provide a timely opportunity for scientists and researchers, as well as engineers, to discuss and summarize the latest inspection methods in industrial applications. We invite papers that include, but are not exclusive to, the following topics: defect inspection; machine learning; hyperspectral imaging algorithms; image super-resolution; machine vision; image synthesis methods; illumination design; optical design; image fusion; non-destructive testing and evaluation; precision measurements and metrology; freeform design; manufacturing technology; precision machining; precision polishing; additive manufacturing. Both theoretical and experimental studies are welcome, as are comprehensive reviews and survey papers.

Dr. Xing Peng
Dr. Xiang Sun
Prof. Dr. Lingbao Kong
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Photonics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

defect inspection

machine learning

hyperspectral imaging algorithms

image super-resolution

machine vision

image synthesis methods

illumination design

optical design

image fusion

non-destructive testing and evaluation

precision measurements and metrology

freeform design

manufacturing technology

precision machining

precision polishing

additive manufacturing

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Published Papers (4 papers)

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Research

25 pages, 7134 KiB  
Article
Fast and Accurate Measurement of Hole Systems in Curved Surfaces
by Ping Wang, Lingbao Kong, Huijun An, Minge Gao and Hailong Cui
Photonics 2023, 10(12), 1337; https://doi.org/10.3390/photonics10121337 - 2 Dec 2023
Viewed by 1457
Abstract
Curved surface structural parts with hole systems are widely used, and accurate measurement of the hole systems is crucial for assembly and functionality. This study presents a novel approach using machine vision and structural science principles to accurately measure spherical hole systems. We [...] Read more.
Curved surface structural parts with hole systems are widely used, and accurate measurement of the hole systems is crucial for assembly and functionality. This study presents a novel approach using machine vision and structural science principles to accurately measure spherical hole systems. We introduce key technologies, including measurement parameter definition, system design, and error modeling, in the paper. Our approach overcomes the limitations of existing methods, offering flexibility, precision, and automation measurement of the hole system. Experimental results demonstrate an accuracy of 0.348′ (arcminutes). This research contributes to the optical measurement of curved surface hole systems and improves their alignment and functionality. Full article
(This article belongs to the Special Issue State-of-the-Art Optical Inspection Technology)
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13 pages, 6487 KiB  
Article
Suppression for Phase Error of Fringe Projection Profilometry Using Outlier-Detection Model: Development of an Easy and Accurate Method for Measurement
by Guangxi Dong, Xiang Sun, Lingbao Kong and Xing Peng
Photonics 2023, 10(11), 1252; https://doi.org/10.3390/photonics10111252 - 13 Nov 2023
Viewed by 1092
Abstract
Fringe projection is an important technology in three-dimensional measurement and target recognition. The measurement accuracy depends heavily on the calibration of the absolute phase and projector pixels. An easy-to-implement calibration method based on the Random Sample Consensus (RANSAC) algorithm is proposed to exterminate [...] Read more.
Fringe projection is an important technology in three-dimensional measurement and target recognition. The measurement accuracy depends heavily on the calibration of the absolute phase and projector pixels. An easy-to-implement calibration method based on the Random Sample Consensus (RANSAC) algorithm is proposed to exterminate the phase error data and elevate the measurement accuracy in a fringe projection system. The reconstruction experiments of a double-sphere standard demonstrate that the uncertainties in radius and sphere-distance measurement are reduced to one thousandth of the measured value or even less, and the standard deviation in multiple measurements is restricted to within 50 μm. The measurement accuracy provided by the proposed RANSAC method can be improved by up to 44% compared with that provided by traditional least squared method (LSM). The proposed calibration method is easy and simple to implement, and it does not need additional hardware, but rather a calibration board. Full article
(This article belongs to the Special Issue State-of-the-Art Optical Inspection Technology)
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13 pages, 5899 KiB  
Article
A Novel Method for Quadrature Signal Construction in a Semiconductor Self-Mixing Interferometry System Using a Liquid Crystal Phase Shifter
by Yancheng Li, Zenghui Peng, Xiao Shen and Junfeng Wu
Photonics 2023, 10(10), 1121; https://doi.org/10.3390/photonics10101121 - 6 Oct 2023
Cited by 2 | Viewed by 1125
Abstract
We have established a novel method for quadrature signal construction in a semiconductor laser diode self-mixing interferometry system using two photodiodes and a beam splitter with a liquid crystal phase shifter (LCPS). This method entails placing an LCPS between the photodiode and the [...] Read more.
We have established a novel method for quadrature signal construction in a semiconductor laser diode self-mixing interferometry system using two photodiodes and a beam splitter with a liquid crystal phase shifter (LCPS). This method entails placing an LCPS between the photodiode and the beam splitter so that another phase shift self-mixing signal can be obtained. Then, an arctangent phase algorithm can be used to demodulate the pair of quadrature signals to reconstruct the vibration information of the target object. This method simplifies the self-mixing signal demodulation process and the reconstruction of vibration information. Our experimental results demonstrate the feasibility of using self-mixing phase shifter detection for self-mixing optical measurements. The work illustrates a sort of efficient and referable novel design guidance model which supports the quadrature signals construction in a self-mixing interferometer based on a semiconductor laser diode. Full article
(This article belongs to the Special Issue State-of-the-Art Optical Inspection Technology)
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22 pages, 9369 KiB  
Article
Single-Shot Three-Dimensional Measurement by Fringe Analysis Network
by Mingzhu Wan, Lingbao Kong and Xing Peng
Photonics 2023, 10(4), 417; https://doi.org/10.3390/photonics10040417 - 7 Apr 2023
Cited by 7 | Viewed by 1926
Abstract
Fringe projection profilometry (FPP) has been broadly applied in three-dimensional (3D) measurements, but the existing multi-shot methods, which mostly utilize phase-shifting techniques, are heavily affected by the disturbance of vibration and cannot be used in dynamic scenes. In this work, a single-shot 3D [...] Read more.
Fringe projection profilometry (FPP) has been broadly applied in three-dimensional (3D) measurements, but the existing multi-shot methods, which mostly utilize phase-shifting techniques, are heavily affected by the disturbance of vibration and cannot be used in dynamic scenes. In this work, a single-shot 3D measurement method using a deep neural network named the Fringe Analysis Network (FrANet) is proposed. The FrANet is composed of a phase retrieval subnetwork, phase unwrapping subnetwork, and refinement subnetwork. The combination of multiple subnetworks can help to recover long-range information that is missing for a single U-Net. A two-stage training strategy in which the FrANet network is pre-trained using fringe pattern reprojection and fine-tuned using ground truth phase maps is designed. Such a training strategy lowers the number of ground truth phase maps in the data set, saves time during data collection, and maintains the accuracy of supervised methods in real-world setups. Experimental studies were carried out on a setup FPP system. In the test set, the mean absolute error (MAE) of the refined absolute phase maps was 0.0114 rad, and the root mean square error (RMSE) of the 3D reconstruction results was 0.67 mm. The accuracy of the proposed method in dynamic scenes was evaluated by measuring moving standard spheres. The measurement of the sphere diameter maintained a high accuracy of 84 μm at a speed of 0.759 m/s. Two-stage training only requires 8800 fringe images in data acquisition, while supervised methods require 96,000 fringe images for the same number of iterations. Ablation studies verified the effectiveness of two training stages and three subnetworks. The proposed method achieved accurate single-shot 3D measurements comparable to those obtained using supervised methods and has a high data efficiency. This enables the accurate 3D shape measurement of moving or vibrating objects in industrial manufacturing and allows for further exploration of network architecture and training strategy with few training samples for single-shot 3D measurement. Full article
(This article belongs to the Special Issue State-of-the-Art Optical Inspection Technology)
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