Integrative binocular vision detection method based on infrared and visible light fusion for conveyor belts longitudinal tear

Tiezhu Qiao, Lulu Chen, Yusong Pang, Gaowei Yan, Changyun Miao

Research output: Contribution to journalArticleScientificpeer-review

25 Citations (Scopus)

Abstract

Real-time and reliable detection of conveyor belt longitudinal tear is an important task in mining operations. This paper presents a novel method of Integrative Binocular Vision Detection (IBVD) to detect the longitudinal tears of conveyor belts. Based on infrared and visible fusion, the IBVD sensor device collects the fusion images of the belt. After extracting the tear features by projection method, the progress of potential tears can be evaluated and the tears can be identified. The IBVD method is verified by an experiment platform fulfilling the acquisition, pro-processing and analysis of fusion images for tear detection. The fusion image processing time is less than 18 ms, which satisfies the requirement of real-time online monitoring. Compared to the individual measurement technique of either infrared detection or visible light detection, the average accuracy of the IBVD method reaches up to 96%, the IBVD method is more reliable in tear detection.

Original languageEnglish
Pages (from-to)192-201
JournalMeasurement
Volume110
DOIs
Publication statusPublished - 2017

Keywords

  • Infrared and visible light fusion
  • Integrative binocular vision detection (IBVD)
  • Longitudinal tear detection
  • Projection method

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