4.7 Article

Multispectral visual detection method for conveyor belt longitudinal tear

Journal

MEASUREMENT
Volume 143, Issue -, Pages 246-257

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.measurement.2019.05.010

Keywords

Conveyor belt; Longitudinal tear; Multispectral visual detection; Image fusion

Funding

  1. National Natural Science Foundation of China-Shanxi coal-based low-carbon joint fund [U1810121]
  2. Natural Science Foundation of China-Shanxi [201801D121180]

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As an important part of modern coal mine production, conveyor belts are widely used in the coal collection and transportation. In order to ensure the safe operation of the coal mine conveyor belt and solve the drawbacks of the existing conveyor belt longitudinal tear detection technology, a multispectral visual detection method for conveyor belt longitudinal tear is proposed in this paper. The experimental results show that the multispectral visual detection method not only can identify the conveyor belt longitudinal tear, but also accurately classifies and identify other states of the conveyor belt. The accuracy of multispectral visual detection method is over 90.06%, and the precision of longitudinal tearing recognition is over 92.04%. The proposed method is verified to meet the requirements of reliability and real-time in the industrial field. (C) 2019 Elsevier Ltd. All rights reserved.

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