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Applications of machine vision technology for conveyor belt deviation detection: A review and roadmap.

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Title: Applications of machine vision technology for conveyor belt deviation detection: A review and roadmap.
Authors: Han, Jiaming1,2,3 (AUTHOR), Fang, Ting1 (AUTHOR) FlyingFangT@163.com, Liu, Wensheng2 (AUTHOR), Zhang, Chenxiao1,4 (AUTHOR) chenxiaozhang1989@163.com, Zhu, Molin2 (AUTHOR), Xu, Jibin2 (AUTHOR), Ji, Jie2 (AUTHOR), He, Xianhua2 (AUTHOR), Wang, Zhang2 (AUTHOR), Tang, Min2 (AUTHOR), Dong, Chong1,3 (AUTHOR), Ma, Long1 (AUTHOR), Yang, Xinlong1 (AUTHOR)
Source: Engineering Applications of Artificial Intelligence. Dec2025:Part C, Vol. 161, pN.PAG-N.PAG. 1p.
Subjects: Conveyor belts, Computer vision, Artificial intelligence, Hazards, Freight & freightage
Abstract: Conveyor belt deviation is a frequent challenge in product transportation filed, and failure to promptly detect and rectify this anomaly not only significantly reduces transport efficiency but also poses a risk of serious safety accidents, leading to enormous economic losses. Traditional contact-based deviation detection technologies, with their inherent limitations of high costs and complicated maintenance, have struggled to meet the practical demands of long-distance conveyor belt inspection. In this context, non-contact machine vision technology has emerged as a prominent solution in the field of conveyor belt deviation detection, thanks to its notable advantages of a simple hardware structure and round-the-clock operational capability. Recently, with the rapid development of artificial intelligence theories, this research field has accumulated a series of effective solutions that have been proven through machine vision practical applications. This paper delves into the technical principles of the existing solutions, systematically summarizes them and objectively evaluates their strengths and weaknesses in practical applications. Based on this foundation, this paper also provides an insight on the future development trends of intelligent monitoring for conveyor belt deviation, aiming to offer valuable reference and guidance to technicians in related fields. [ABSTRACT FROM AUTHOR]
Copyright of Engineering Applications of Artificial Intelligence is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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PubType: Academic Journal
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  Data: Applications of machine vision technology for conveyor belt deviation detection: A review and roadmap.
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  Data: <searchLink fieldCode="JN" term="%22Engineering+Applications+of+Artificial+Intelligence%22">Engineering Applications of Artificial Intelligence</searchLink>. Dec2025:Part C, Vol. 161, pN.PAG-N.PAG. 1p.
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  Data: <searchLink fieldCode="DE" term="%22Conveyor+belts%22">Conveyor belts</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+vision%22">Computer vision</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Hazards%22">Hazards</searchLink><br /><searchLink fieldCode="DE" term="%22Freight+%26+freightage%22">Freight & freightage</searchLink>
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  Label: Abstract
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  Data: Conveyor belt deviation is a frequent challenge in product transportation filed, and failure to promptly detect and rectify this anomaly not only significantly reduces transport efficiency but also poses a risk of serious safety accidents, leading to enormous economic losses. Traditional contact-based deviation detection technologies, with their inherent limitations of high costs and complicated maintenance, have struggled to meet the practical demands of long-distance conveyor belt inspection. In this context, non-contact machine vision technology has emerged as a prominent solution in the field of conveyor belt deviation detection, thanks to its notable advantages of a simple hardware structure and round-the-clock operational capability. Recently, with the rapid development of artificial intelligence theories, this research field has accumulated a series of effective solutions that have been proven through machine vision practical applications. This paper delves into the technical principles of the existing solutions, systematically summarizes them and objectively evaluates their strengths and weaknesses in practical applications. Based on this foundation, this paper also provides an insight on the future development trends of intelligent monitoring for conveyor belt deviation, aiming to offer valuable reference and guidance to technicians in related fields. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Engineering Applications of Artificial Intelligence is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=188801786
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        Value: 10.1016/j.engappai.2025.112312
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      – SubjectFull: Artificial intelligence
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              Text: Dec2025:Part C
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