research-article

Application of Neural Network Technology in Defect Image Recognition

Authors:

Zhengpei Jiang,

Jie GengAuthors Info & Claims

ICMVA '21: Proceedings of the 2021 International Conference on Machine Vision and Applications

Pages 28 - 33

https://doi.org/10.1145/3459066.3459071

Published: 26 July 2021 Publication History

Abstract

Pressure vessels need non-destructive testing regularly, which requires more accurate and faster detection methods. The wall-climbing robot with visual sensor can carry out magnetic particle testing at the same time, and take real-time magnetic particle testing results. It has broad application prospective and application values. This paper presents a study on the crack defects of weld seams in pressure vessels. A neural network algorithm is introduced to recognize and classify a large number of pictures taken by a wall-climbing robot. An experiment was conducted. The results showed that the CNN method is efficient and economic way to complete the detection tasks. It is feasible to be integrated to the wall-climbing robot for the further automatic detection of defect images.

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Cited By

Tao HWu ZLing ZGeng J(2023)Predictive computing of human errors while training machine learning models2023 International Conference on Intelligent Computing and Next Generation Networks（ICNGN)10.1109/ICNGN59831.2023.10396775(1-6)Online publication date: 17-Nov-2023
https://doi.org/10.1109/ICNGN59831.2023.10396775
Andon ACovatariu G(2022)A Study on Image Processing Using Artificial Neural Networks in Civil EngineeringBulletin of the Polytechnic Institute of Iași. Construction. Architecture Section10.2478/bipca-2021-002767:3(85-94)Online publication date: 18-Jul-2022
https://doi.org/10.2478/bipca-2021-0027

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Application of Neural Network Technology in Defect Image Recognition

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cover image ACM Other conferences

ICMVA '21: Proceedings of the 2021 International Conference on Machine Vision and Applications

February 2021

75 pages

ISBN:9781450389556

DOI:10.1145/3459066

Copyright © 2021 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 July 2021

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the science and technology project of Zhejiang Provincial Administration for Market Regulation
the Opening Project of Key Laboratory of Special Equipment Safety Testing Technology of Zhejiang Province

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ICMVA 2021

ICMVA 2021: 2021 International Conference on Machine Vision and Applications

February 20 - 22, 2021

Singapore, Singapore

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Cited By

Tao HWu ZLing ZGeng J(2023)Predictive computing of human errors while training machine learning models2023 International Conference on Intelligent Computing and Next Generation Networks（ICNGN)10.1109/ICNGN59831.2023.10396775(1-6)Online publication date: 17-Nov-2023
https://doi.org/10.1109/ICNGN59831.2023.10396775
Andon ACovatariu G(2022)A Study on Image Processing Using Artificial Neural Networks in Civil EngineeringBulletin of the Polytechnic Institute of Iași. Construction. Architecture Section10.2478/bipca-2021-002767:3(85-94)Online publication date: 18-Jul-2022
https://doi.org/10.2478/bipca-2021-0027

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