PLC based laser scanning system for conveyor belt surface monitoring

This paper presents the design, implementation, and testing of an advanced conveyor belt surface monitoring system, specifically engineered for harsh and complex industrial environments. The system integrates multiple cutting-edge technologies, including programmable logic controllers (PLC), laser s...

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Bibliographic Details
Published in:Scientific reports 2024-11, Vol.14 (1), p.27914-26, Article 27914
Main Authors: Wang, Ranran, Li, Yingxiu, Yang, Fule, Wang, Zhuolin, Dong, Jianye, Yuan, Chunhong, Lu, Xin
Format: Article
Language:English
Subjects:
639/166/987
639/166/988
Adaptability
Automation
Cameras
Computer vision
Control systems
Conveyor belt monitoring
Data management
Data processing
Deep learning
Environmental monitoring
Humanities and Social Sciences
Laser scanning
Lasers
multidisciplinary
Programmable logic controller (PLC)
Science
Science (multidisciplinary)
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Summary:This paper presents the design, implementation, and testing of an advanced conveyor belt surface monitoring system, specifically engineered for harsh and complex industrial environments. The system integrates multiple cutting-edge technologies, including programmable logic controllers (PLC), laser scanning, industrial-grade cameras, and deep learning algorithms, particularly YOLOv7, to achieve real-time, high-precision monitoring of conveyor belt conditions. Key innovations include optimized detection location based on failure modes, advanced PLC integration for seamless automation, and intelligent dust-proof features to maintain accuracy in challenging conditions. Through strategic placement of detection devices and multi-mode control strategies (local, remote, and automatic), the system offers unparalleled adaptability and responsiveness. The system leverages robust data management for trend analysis and predictive maintenance, enhancing operational efficiency. The hardware architecture comprises PLC-based control systems, high-resolution industrial cameras, and laser emitters, while the software features a two-tier structure combining human-machine interaction (HMI) with real-time data processing capabilities. Experimental results show that the system is highly effective in detecting common belt defects such as foreign objects, tears, and shallow scratches, ensuring optimal operational efficiency and minimizing downtime. The system’s scalability, robust data management, and adaptability to low-light and dusty conditions make it ideal for deployment in large-scale industrial operations, where continuous monitoring and early fault detection are critical to maintaining productivity and safety.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-78985-0