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Sensor-Based Precision Dimensional Measurement
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Sensor-Based Precision Dimensional Measurement

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 6608

Special Issue Editors

Prof. Dr. Liang-Chia Chen

E-Mail Website
Guest Editor
Department of Mechanical Engineering, National Taiwan University, 10617 Taipei, Taiwan
Interests: precision metrology; optical measurement; automated optical inspection (AOI); manufacturing; automation
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Chao-Ching Ho

E-Mail Website
Guest Editor
Graduate Institute of Manufacturing Technology, National Taipei University of Technology, Taipei 10617, Taiwan
Interests: industrial AI; in situ monitoring and inspection; laser drilling; electrical chemical discharge machining; machine vision

Special Issue Information

Dear Colleagues,

This Special Issue welcomes original articles that disclose novel sensing or measuring methodologies and instrumentations for precision dimensional measurements, including new measuring principles, novel optical or optomechatronic design and implementation, online measurements, online or in situ measurements, AI-based learning or strategies, micro/nano measurements, algorithms for uncertainty analysis and minimization, other advanced technologies for precision optical measurements, etc. Original optical measuring or sensing principles in science and technological applications for advanced technology development, as well as concern of the precision and uncertainty of the measuring methods reported, are essential in submitted manuscripts. Meanwhile, we expect authors to demonstrate in their papers: novelty, significance, the broader relevance of their work in relation to precision optical measurement.

Topics may cover but are not limited to the following areas:

  • Automated optical inspection (AOI).
  • Optical or optomechatronic design and implementation.
  • Sensor-based on-machine measurements, online or in situ measurements.
  • Novel optical measuring machines or platforms for nano-scale dimensional measurements.
  • Precision measurements from 2D to 3D, from analytical to free forms, from macro- to micro- to nanoscales, from static to dynamic, etc.
  • Novel sensors with AI-based learning or strategies for defect detection, defect classification or measuring uncertainty minimization.
  • Sensor-based optical measurements, such as triangulation principle, confocal microscopy, white light microscopy, interferometry or hybrid methods, etc.
  • Sensors with novel algorithms for uncertainty analysis and minimization.
  • Other advanced technologies for optical dimensional or morphological measurements.

Prof. Dr. Liang-Chia Chen
Prof. Dr. Chao-Ching Ho
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. Sensors is an international peer-reviewed open access semimonthly 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 2600 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.

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Published Papers (2 papers)

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Research

12 pages, 4318 KiB  
Communication
Innovative Image Processing Method to Improve Autofocusing Accuracy
by Chien-Sheng Liu and Ho-Da Tu
Sensors 2022, 22(13), 5058; https://doi.org/10.3390/s22135058 - 5 Jul 2022
Cited by 3 | Viewed by 2387
Abstract
For automated optical inspection, autofocusing microscopes play an important role in capturing clear images of the measured object. At present, the image processing part of optics-based autofocusing microscopes often has various factors, which makes it impossible to describe the image information of the [...] Read more.
For automated optical inspection, autofocusing microscopes play an important role in capturing clear images of the measured object. At present, the image processing part of optics-based autofocusing microscopes often has various factors, which makes it impossible to describe the image information of the semicircular (or elliptical) spot with a simple circle-finding method. Accordingly, this study has developed a novel algorithm that can quickly calculate the ideal center of the elliptical spot and effectively compensate the linearity of the focusing characteristic curve. A prototype model was used to characterize and verify the proposed algorithm. The experimental results show that by using the proposed algorithm, the autofocusing accuracy can be effectively improved to less than 1.5 μm. Full article
(This article belongs to the Special Issue Sensor-Based Precision Dimensional Measurement)
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18 pages, 6023 KiB  
Article
High Precision Visual Dimension Measurement Method with Large Range Based on Multi-Prism and M-Array Coding
by Xiao Zhou, Cong Zhou, Tingting Zhang, Xingang Mou, Jiaxin Xu and Yi He
Sensors 2022, 22(6), 2081; https://doi.org/10.3390/s22062081 - 8 Mar 2022
Cited by 1 | Viewed by 2952
Abstract
The visual dimension measurement method based on non-splicing single lens has the contradiction between accuracy and range of measurement, which cannot be considered simultaneously. In this paper, a multi-camera cooperative measurement method without mechanical motion is proposed for the dimension measurement of thin [...] Read more.
The visual dimension measurement method based on non-splicing single lens has the contradiction between accuracy and range of measurement, which cannot be considered simultaneously. In this paper, a multi-camera cooperative measurement method without mechanical motion is proposed for the dimension measurement of thin slice workpiece. After the calibration of the multi-camera imaging system is achieved through a simple and efficient scheme, the high-precision dimension measurement with a large field of view can be completed through a single exposure. First, the images of the edges of the workpiece are compressed and combined by splitting and merging light through the multi-prism system, and the results are distributed to multiple cameras by changing the light path. Then, the mapping relationship between the global measurement coordinates and the image coordinates of each camera is established based on the globally unique M-array coding, and the image distortion is corrected by the coding unit composed of black and white blocks. Finally, the edge is located accurately by edge point detection at the sub-pixel level and curve fitting. The results of measuring a test workpiece with the dimension of 24 mm × 12 mm × 2 mm through a single exposure show that the repeated measurement accuracy can reach 0.2 µm and the absolute accuracy can reach 0.5 µm. Compared with other methods, our method can achieve the large-field measurement through only one exposure and without the mechanical movement of cameras. The measurement precision is higher and the speed is faster. Full article
(This article belongs to the Special Issue Sensor-Based Precision Dimensional Measurement)
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