IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i17p3205-d907052.html
   My bibliography  Save this article

Pollutant Migration Pattern during Open-Pit Rock Blasting Based on Digital Image Analysis Technology

Author

Listed:
  • Jiangjiang Yin

    (School of Resources and Safety Engineering, Central South University, Changsha 410083, China)

  • Jianyou Lu

    (School of Resources and Safety Engineering, Central South University, Changsha 410083, China)

  • Fuchao Tian

    (State Key Laboratory of Coal Mine Safety Technology, China Coal Technology & Engineering Group Shenyang Research Institute, Shenfu Demonstration Zone, Shenyang 113122, China)

  • Shaofeng Wang

    (School of Resources and Safety Engineering, Central South University, Changsha 410083, China)

Abstract

Previous studies have revealed that toxic gases and dust (smoke dust) are the most common pollutants generated by the blasting operations in open-pit mines, which might lead to a threat to the environment’s condition, health and safety, and properties protection around the blasting site. In order to deal with the problems, a pollution evaluation system was established based on the fractal dimension theory ( D box (P) ) and grayscale average algorithm ( G a ) in digital image-processing technology to recognize and analyze the distributions of the smoke-dust cloud, and subsequently determine the pollution degrees. The computation processes of D box (P) and G a indicate three fitted correlations between the parameters and diffusion time of smoke dust. Then, a pollution index ( Pi ) is put forward to integrate the global and local features of D box (P) and G a , and develop a hazard classification mechanism for the blasting pollutants. Results obviously denote three diffusion stages of the pollutants, mainly including generation stage, cloud-formation stage, and diffusion stage. In addition, it has been validated that the proposed system can also be utilized in single-point areas within a whole digital image. Besides, there are variation trends of the thresholds T 1 and T 2 in binarization with the diffusion of pollutants. With this identification and evaluation system, the pollution condition of smoke dust can be obviously determined and analyzed.

Suggested Citation

  • Jiangjiang Yin & Jianyou Lu & Fuchao Tian & Shaofeng Wang, 2022. "Pollutant Migration Pattern during Open-Pit Rock Blasting Based on Digital Image Analysis Technology," Mathematics, MDPI, vol. 10(17), pages 1-18, September.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:17:p:3205-:d:907052
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/17/3205/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/17/3205/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Meng Yuan & Jingyi Ouyang & Shuanning Zheng & Ye Tian & Ran Sun & Rui Bao & Tao Li & Tianshu Yu & Shuang Li & Di Wu & Yongjie Liu & Changyou Xu & Yu Zhu, 2022. "Research on Ecological Effect Assessment Method of Ecological Restoration of Open-Pit Coal Mines in Alpine Regions," IJERPH, MDPI, vol. 19(13), pages 1-14, June.
    2. Zizi Pi & Zilong Zhou & Xibing Li & Shaofeng Wang, 2021. "Digital Image Processing Method for Characterization of Fractures, Fragments, and Particles of Soil/Rock-Like Materials," Mathematics, MDPI, vol. 9(8), pages 1-13, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xiang Jia & Zhengxu Jin & Xiaoli Mei & Dong Wang & Ruoning Zhu & Xiaoxia Zhang & Zherui Huang & Caixia Li & Xiaoli Zhang, 2023. "Monitoring and Effect Evaluation of an Ecological Restoration Project Using Multi-Source Remote Sensing: A Case Study of Wuliangsuhai Watershed in China," Land, MDPI, vol. 12(2), pages 1-17, January.
    2. Xiong, Yu & Kong, Dezhong & Song, Gaofeng, 2024. "Research hotspots and development trends of green coal mining: Exploring the path to sustainable development of coal mines," Resources Policy, Elsevier, vol. 92(C).
    3. Zilong Zhou & Hang Yuan & Xin Cai, 2023. "Rock Thin Section Image Identification Based on Convolutional Neural Networks of Adaptive and Second-Order Pooling Methods," Mathematics, MDPI, vol. 11(5), pages 1-27, March.
    4. Jiawei Qi & Yichen Zhang & Jiquan Zhang & Chenyang Wu & Yanan Chen & Zhongshuai Cheng, 2023. "Study on the Restoration of Ecological Environments in Mining Area Based on GIS Technology," Sustainability, MDPI, vol. 15(7), pages 1-17, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:10:y:2022:i:17:p:3205-:d:907052. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.