Research on Audio-Visual Detection Method for Conveyor Belt Longitudinal Tear

Chengcheng Hou; Tiezhu Qiao; Meiying Qiao; Xiaoyan Xiong; Yi Yang; Haitao Zhang

doi:10.1109/ACCESS.2019.2937660

IEEE Access (Jan 2019)

Research on Audio-Visual Detection Method for Conveyor Belt Longitudinal Tear

Chengcheng Hou,
Tiezhu Qiao,
Meiying Qiao,
Xiaoyan Xiong,
Yi Yang,
Haitao Zhang

Affiliations

Chengcheng Hou: ORCiD; Key Laboratory of Advanced Transducers and Intelligent Control System, Ministry of Education, Taiyuan University of Technology, Taiyuan, China
Tiezhu Qiao: Key Laboratory of Advanced Transducers and Intelligent Control System, Ministry of Education, Taiyuan University of Technology, Taiyuan, China
Meiying Qiao: School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo, China
Xiaoyan Xiong: Key Laboratory of Advanced Transducers and Intelligent Control System, Ministry of Education, Taiyuan University of Technology, Taiyuan, China
Yi Yang: Key Laboratory of Advanced Transducers and Intelligent Control System, Ministry of Education, Taiyuan University of Technology, Taiyuan, China
Haitao Zhang: Key Laboratory of Advanced Transducers and Intelligent Control System, Ministry of Education, Taiyuan University of Technology, Taiyuan, China

DOI: https://doi.org/10.1109/ACCESS.2019.2937660
Journal volume & issue: Vol. 7
pp. 120202 – 120213

Abstract

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As a key equipment for production and transportation, conveyor belts are widely used in the coal mining industry. Once the conveyor belt longitudinal tear occurs, it will seriously affect the production and even cause personal injury. Therefore, the longitudinal tear detection of the conveyor belt is extremely important. In this paper, the sound detection is introduced into the longitudinal tear detection of the conveyor belt, and an audio-visual detection method for conveyor belt longitudinal tear is proposed. Camera and microphone array are used to collect the image and sound signals of conveyor belt, and the conveyor belt is detected from both image and sound, respectively. Then the image and sound analysis results are combined to comprehensively judge the status of the conveyor belt. The experimental results show that the audio-visual detection method can accurately identify the normal, abnormal, and longitudinal tear of the conveyor belt. The detection accuracy is over 86.72% and the sensitivity of longitudinal tear detection is greater than 92.59%. The proposed audio-visual detection method is verified to meet the requirements of longitudinal tear detection of coal mining industry conveyor belts.

Published in IEEE Access

ISSN: 2169-3536 (Online)
Publisher: IEEE
Country of publisher: United States
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering
Website: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639

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