Citation

Chen S, Zhu L, Chen Y, Zheng X, Ji Q. China Saf. Sci. J. 2022; 32(8): 61-66.

Copyright

(Copyright © 2022, China Occupational Safety and Health Association, Publisher Gai Xue bao)

DOI

10.16265/j.cnki.issn1003-3033.2022.08.2315

PMID

unavailable

Abstract

In order to improve safety hazards management in hydropower project construction, nonlinear sequential characteristics of the hazards were analyzed, and a complex network model of the time series was built based on visual graph algorithm. Then, 3 160 hazard data of a hydropower station from 2016 to 2020 were mined, and parameters of the network ' s degree, degree distribution, power law index, clustering coefficient, diameter, average path length, etc. were calculated to reveal temporal characteristics of the hazards in the project construction. The results show that the discovery timing of the hazards in this project indicates obvious phased, scale-free and small-world evolutionary characteristics. As long intervals during the hazards will significantly undermine robustness performance of management in the whole project construction, controlling the few key time nodes can reduce risks in hydropower projects. It provides a theoretical method for further mining the prediction of sequential characteristics of safety hazards in hydropower project construction. © 2022 China Safety Science Journal. All rights reserved.

Language: zh