Proceedings of the 2019 International Conference on Modeling, Analysis, Simulation Technologies and Applications (MASTA 2019)

Defect Detection and Full Surface Characterization of High Curvature Cathode Filaments

Authors
Ding-rong Yi, Cai-hong Huang, Jing-fang Xie, Yu-ming Cai, Yong Qian, Ling-hua Kong
Corresponding Author
Ling-hua Kong
Available Online July 2019.
DOI
https://doi.org/10.2991/masta-19.2019.48How to use a DOI?
Keywords
Cathode filament, Digital scan, Surface characterization, Defect detection, Online quality inspection, High-curvature surfaces, Optical occlusion, Line detector
Abstract

Surface defects of cathode filaments of microwave magnetron would cause magnetron failure and scrapped microwave systems. Therefore, surface defects on cathode filaments must be carefully inspected. Conventionally, filaments are manually and visually inspected using their amplified images under an optical microscope. This is because automatic defect detection of cathode filaments is a challenging problem. The difficulty comings from its complex surface shape with multiple turns of high curvature spiral circles, which occlude each other. Such complex shape prevents capturing of sharp focusing images, which are essential for a computerized automatic detection algorithm. Further, the variable nature of production defects complicated the process of automatic defect detection task. To solve these problems, this paper proposes an automatic defect detection method to deal with issues related to complex shapes containing occlusions as well as high curvatures, particularly for the quality inspection of spiral shaped cathode filaments. The method includes a novel digital scanner, which sequentially brings all sections of the filament sides into sharp focusing of the optical imaging system. The method also employs multiple optical systems to imaging multi-sides of the spiral filament. The computational algorithm primarily uses line-detectors. In an evaluation experiment, the proposed method was used to automatically inspect over 14 million cathode filaments. Experimental results indicate that its false negative rate was 0.0065%, and its false positive rate was 6.83%. This indicates that the proposed method could successfully detect all kinds of surface defects at over 99.99% accuracy. It reduces the workload for manual inspection from 100% down to 93.17%, over an order of magnitude reduction. Further, the efficiency of the proposed method is 70 spiral filaments per minute, satisfying the requirements of online quality detection of existing manufacturing lines of filament cathodes.

Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2019 International Conference on Modeling, Analysis, Simulation Technologies and Applications (MASTA 2019)
Series
Advances in Intelligent Systems Research
Publication Date
July 2019
ISBN
978-94-6252-761-4
ISSN
1951-6851
DOI
https://doi.org/10.2991/masta-19.2019.48How to use a DOI?
Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Ding-rong Yi
AU  - Cai-hong Huang
AU  - Jing-fang Xie
AU  - Yu-ming Cai
AU  - Yong Qian
AU  - Ling-hua Kong
PY  - 2019/07
DA  - 2019/07
TI  - Defect Detection and Full Surface Characterization of High Curvature Cathode Filaments
BT  - Proceedings of the 2019 International Conference on Modeling, Analysis, Simulation Technologies and Applications (MASTA 2019)
PB  - Atlantis Press
SP  - 286
EP  - 292
SN  - 1951-6851
UR  - https://doi.org/10.2991/masta-19.2019.48
DO  - https://doi.org/10.2991/masta-19.2019.48
ID  - Yi2019/07
ER  -