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Generative adversarial nets in laser-induced fluorescence spectrum image recognition of mine water inrush

Author

Listed:
  • Jing Li
  • Yong Yang
  • Hongmei Ge
  • Yong Wang
  • Li Zhao

Abstract

Water inrush occurred in mines, threatens the safety of working miners which triggers severe accidents in China. To make full use of existing distinctive hydro chemical and physical characteristics of different aquifers and different water sources, this article proposes a new water source discrimination method using laser-induced fluorescence technology and generative adversarial nets. The fluorescence spectrum from the water sample is stimulated by 405-nm lasers and improved by recursive mean filtering method to alleviate interference and auto-correlation to enhance the feature difference. Based on generative adversarial nets framework and improved spectra features, the article proposes a novel water source discrimination-generative adversarial nets model in mines to solve the problem of data limitation and improve the discrimination ability. The results show that the proposed method is an effective method to distinguish water inrush types. It provides a new idea to discriminate the sources of water inrush in mines timely and accurately.

Suggested Citation

  • Jing Li & Yong Yang & Hongmei Ge & Yong Wang & Li Zhao, 2019. "Generative adversarial nets in laser-induced fluorescence spectrum image recognition of mine water inrush," International Journal of Distributed Sensor Networks, , vol. 15(10), pages 15501477198, October.
    • Handle: RePEc:sae:intdis:v:15:y:2019:i:10:p:1550147719884894
    DOI: 10.1177/1550147719884894
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    References listed on IDEAS

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    1. Wu Qiang & Li Bo & Chen Yulong, 2016. "Vulnerability Assessment of Groundwater Inrush from Underlying Aquifers Based on Variable Weight Model and its Application," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(10), pages 3331-3345, August.
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