IDEAS home Printed from https://ideas.repec.org/h/spr/prbchp/978-3-030-75166-1_19.html
   My bibliography  Save this book chapter

Research on the Cause of Personal Accidents in Electric Power Production Based on Capacity Load Model

In: AI and Analytics for Public Health

Author

Listed:
  • Penglei Li

    (Nanjing University of Aeronautics and Astronautics)

  • Chuanmin Mi

    (Nanjing University of Aeronautics and Astronautics)

  • Jie Xu

    (Wuxi Power Supply Branch of State Grid Jiangsu Electric Power Co. Ltd.)

Abstract

In order to explore the formation mechanism of personal accidents in electric power production, this paper constructs a directional weighted causative network model of personal accidents in electric power production based on the extraction of accident causative chains. Considering the uncertainty of the propagation path of causative factors in the network, this paper constructs the propagation evolution mechanism of node loads based on the capacity-load model of the successive failure theory, and then studies the process of the accident causative chains formed by the successive failures of the nodes in the network. Through the analysis, 39 accident causative chains with different lengths are obtained. The result shows that electric shock accidents are most likely to be triggered, and object strike accidents are more likely to cause serious casualties. It is necessary to focus on the prevention of sub causative chain with high frequency, so as to achieve the purpose of interrupting the chain and preventing accidents.

Suggested Citation

  • Penglei Li & Chuanmin Mi & Jie Xu, 2022. "Research on the Cause of Personal Accidents in Electric Power Production Based on Capacity Load Model," Springer Proceedings in Business and Economics, in: Hui Yang & Robin Qiu & Weiwei Chen (ed.), AI and Analytics for Public Health, pages 269-280, Springer.
    • Handle: RePEc:spr:prbchp:978-3-030-75166-1_19
    DOI: 10.1007/978-3-030-75166-1_19
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:prbchp:978-3-030-75166-1_19. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.