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Non-destructive detection for mosaic ceramic surface defects based on convolutional neural networks

  • Dr. Guanping Dong received his Ph.D. degree in South China University of Technology, P. R. China. His research interests include machine vision, image recognition, defect detection, and visual image feature extraction.

     ORCID logo EMAIL logo     ,

    Shanwei Sun is a Master’s students at the Jingdezhen Ceramic University, Jingdezhen, P. R. China.

         ,

    Xiangyu Kong is a teacher of Guangdong Polytechnic of Science and Trade, Guangzhou, P. R. China. His research interests include smart manufacturing, defect detection technology.

         ,

    Nanshou Wu is a Ph.D. student at South China Normal University, Guangzhou, P. R. China, researching on biophotonic imaging technology.

         ,

    Hong Zhang is an undergraduate student at the Jingdezhen Ceramic University, Jingdezhen, P. R. China.

         ,

    Xiangyang Chen is a teacher of Guangdong University of Technology, Guangzhou, P. R. China. His research interests include robot trajectory optimization and visual detection.

         ,

    Dr. Hao Feng is a Professor of Jingdezhen Ceramic University, Jingdezhen, P. R. China. His research interests include intelligent manufacturing, ceramic defect detection, and energy saving technology.

         ,

    Pingnan Huang is a Ph.D. student at South China University of Technology, Guangzhou, P. R. China. His research interests focus on the design and optimization of micro-reaction systems.

         and

    Dr. Zixi Wang is a Professor in the Department of Mechanical Engineering, Tsinghua University, P. R. China. His research includes magnetic suspension bearing and magnetic drive technology, air floating bearing technology, and sealing technology.
Published/Copyright: August 11, 2023
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Materials Testing
From the journal Materials Testing Volume 65 Issue 9

Abstract

Mosaic ceramic art pattern with noble, elegant features, it is a unique form of art creation in ancient Greece and the ancient Rome period has been loved by artists and created a lot of classic large-scale exterior mosaic ceramic art works. Small size square mosaic ceramic as the basic raw material for the creation of large exterior mosaic art, it directly affects the quality of the work created by the artist, so these ceramic mosaic ceramic materials need to undergo rigorous inspection to meet the needs of the artist’s high-quality art creation. However, small size multi-color square mosaic ceramics are different from ordinary large target ceramics, they have the characteristics of small size and easy reflection, currently mainly using manual inspection, the existing automatic inspection methods have the problem of low efficiency and accuracy, cannot meet the needs of artists for the quantity and quality of mosaic ceramics. To solve these problems, this paper proposes a new convolutional network-based fast nondestructive testing method for detecting square mosaic tiles. The detection method is based on the convolutional neural network YOLOv5s model, and by introducing the AF-FPN module and the data enhancement module, the method further improves the recognition performance of the model relative to the original YOLOv5s model and achieves the fast detection of surface defects on square mosaic ceramics. The experimental results show that the detection method for small size multicolor square mosaic ceramic tile surface minor defects detection rate of up to 94 % or more, a single square mosaic ceramic detection time of 0.41 s. The method takes into account the detection accuracy and speed, can be fast and accurate screening of high-quality, defect-free small size multicolor square mosaic ceramic, to meet the artist’s requirements for high-quality mosaic ceramic raw materials Quality and quantity requirements, to ensure the quality of the creation of mosaic art patterns, to better show the charm of the mosaic art patterns role. At the same time, the method can not only be applied to the detection of mosaic ceramics, the method can also be applied to have a similar small volume, easy to reflect the characteristics of small target object defect detection.

Keywords: convolutional neural network; defect detection; nondestructive testing; square mosaic tiles; YOLOv5s model
Corresponding authors: Guanping Dong, Jingdezhen Ceramic University, Jingdezhen, China, E-mail: ; and Zixi Wang, State Key Laboratory of Tribology, Tsinghua University Department of Mechanical Engineering, Beijing, China, E-mail:

Funding source: The Fund of Science and Technology Program of Jingdezhen City

Award Identifier / Grant number: 20212GYZD009-19

Funding source: The Youth Fund of Jiangxi Provincial Department of Education

Award Identifier / Grant number: 72005256

Funding source: The PhD Research Start-up Fund of Jingdezhen Ceramic University

Award Identifier / Grant number: 20298002

Funding source: The Fund of Jiangxi Provincial Department of Education

Award Identifier / Grant number: GJJ2201020

Funding source: The National Key R&D Program of China

Award Identifier / Grant number: 2021YFB4001500

About the authors

Guanping Dong

Dr. Guanping Dong received his Ph.D. degree in South China University of Technology, P. R. China. His research interests include machine vision, image recognition, defect detection, and visual image feature extraction.

Shanwei Sun

Shanwei Sun is a Master’s students at the Jingdezhen Ceramic University, Jingdezhen, P. R. China.

Xiangyu Kong

Xiangyu Kong is a teacher of Guangdong Polytechnic of Science and Trade, Guangzhou, P. R. China. His research interests include smart manufacturing, defect detection technology.

Nanshou Wu

Nanshou Wu is a Ph.D. student at South China Normal University, Guangzhou, P. R. China, researching on biophotonic imaging technology.

Hong Zhang

Hong Zhang is an undergraduate student at the Jingdezhen Ceramic University, Jingdezhen, P. R. China.

Xiangyang Chen

Xiangyang Chen is a teacher of Guangdong University of Technology, Guangzhou, P. R. China. His research interests include robot trajectory optimization and visual detection.

Hao Feng

Dr. Hao Feng is a Professor of Jingdezhen Ceramic University, Jingdezhen, P. R. China. His research interests include intelligent manufacturing, ceramic defect detection, and energy saving technology.

Pingnan Huang

Pingnan Huang is a Ph.D. student at South China University of Technology, Guangzhou, P. R. China. His research interests focus on the design and optimization of micro-reaction systems.

Zixi Wang

Dr. Zixi Wang is a Professor in the Department of Mechanical Engineering, Tsinghua University, P. R. China. His research includes magnetic suspension bearing and magnetic drive technology, air floating bearing technology, and sealing technology.

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: This research was supported by the National Key R&D Program of China, Project No. 2021YFB4001500, and the PhD Research Start-up Fund of Jingdezhen Ceramic University, Project No. 20298002, and the Youth Fund of Jiangxi Provincial Department of Education, Project No. 72005256, and the Fund of Jiangxi Provincial Department of Education, Project No. GJJ2201020, and the Fund of Science and Technology Program of Jingdezhen City, Project No. 20212GYZD009-19.

  3. Conflict of interest statement: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Published Online: 2023-08-11
Published in Print: 2023-09-26

© 2023 Walter de Gruyter GmbH, Berlin/Boston

Articles in the same Issue

  1. Frontmatter
  2. Experimental evidence of hydrogen evolution from local anodic corrosion sites and its consequences for corrosion cracking mechanisms
  3. Weldability and mechanical behavior of CMT welded AISI 430 and HARDOX 500 steels
  4. Mechanical properties and microstructural features of rotary friction welded UNS S42000 martensitic stainless-steel joints
  5. Decarburization effects on high-cycle fatigue of uncoated press hardened steels
  6. Non-destructive detection for mosaic ceramic surface defects based on convolutional neural networks
  7. Low-velocity impact behaviours of sandwiches manufactured from fully carbon fiber composite for different cell types and compression behaviours for different core types
  8. Microstructural and numerical variation of friction spot welded AA7075 couples
  9. Crushing performance and optimization of bio-inspired multi-cell columns
  10. Collapse of a honeycomb sandwich composite in an aircraft radome
  11. A multi-strategy boosted prairie dog optimization algorithm for global optimization of heat exchangers
  12. Indentation creep behavior of Fe–8Ni–xZr oxide dispersion strengthened alloys
  13. Mechanical and tribological behavior of a hybrid WC and Al2O3 reinforced Al–4Gr composite
  14. Effect of vibration and cutting zone temperature on surface topography during hybrid cooling/lubrication assisted machining of Vanadis 10
  15. Thermal and mechanical properties of a new insulation composite material
https://doi.org/10.1515/mt-2023-0051
Keywords for this article
convolutional neural network; defect detection; nondestructive testing; square mosaic tiles; YOLOv5s model

Articles in the same Issue

  1. Frontmatter
  2. Experimental evidence of hydrogen evolution from local anodic corrosion sites and its consequences for corrosion cracking mechanisms
  3. Weldability and mechanical behavior of CMT welded AISI 430 and HARDOX 500 steels
  4. Mechanical properties and microstructural features of rotary friction welded UNS S42000 martensitic stainless-steel joints
  5. Decarburization effects on high-cycle fatigue of uncoated press hardened steels
  6. Non-destructive detection for mosaic ceramic surface defects based on convolutional neural networks
  7. Low-velocity impact behaviours of sandwiches manufactured from fully carbon fiber composite for different cell types and compression behaviours for different core types
  8. Microstructural and numerical variation of friction spot welded AA7075 couples
  9. Crushing performance and optimization of bio-inspired multi-cell columns
  10. Collapse of a honeycomb sandwich composite in an aircraft radome
  11. A multi-strategy boosted prairie dog optimization algorithm for global optimization of heat exchangers
  12. Indentation creep behavior of Fe–8Ni–xZr oxide dispersion strengthened alloys
  13. Mechanical and tribological behavior of a hybrid WC and Al2O3 reinforced Al–4Gr composite
  14. Effect of vibration and cutting zone temperature on surface topography during hybrid cooling/lubrication assisted machining of Vanadis 10
  15. Thermal and mechanical properties of a new insulation composite material
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