China Safety Science Journal ›› 2026, Vol. 36 ›› Issue (1): 35-41.doi: 10.16265/j.cnki.issn1003-3033.2026.01.0866

• Safety Science Theories and Methods • Previous Articles     Next Articles

Statistical analysis of knowledge graph of dust explosion accidents in China

ZHAO Kaigong()   

  1. Safety and Environmental Supervision Department, CHN Energy Investment Group Co., Ltd., Beijing 100011, China
  • Received:2025-08-16 Revised:2025-11-30 Online:2026-01-28 Published:2026-07-28

Abstract:

This study aims to systematically explore the temporal and spatial patterns, causal mechanisms, and prevention and control strategies of dust explosion accidents in China. Knowledge graph technology combined with statistical analysis was used to analyze the relevant literature and accident cases of dust explosion accidents in China from 1990 to 2024. A knowledge graph was constructed using CiteSpace visualization software to analyze the spatiotemporal distribution characteristics and the accident causality chain of dust explosion accidents. A four-layer prevention and control system framework of "hazard source-facility-management-emergency" was constructed, and its effectiveness was verified by typical cases. It is found that the risk of dust explosion shows the characteristics of "type differentiation" and "geographical migration", with frequent occurrence of dust, high fatality of coal dust and high secondary injury of grain dust explosions. The accident hotspots are showing a trend of shifting from the eastern to the central and western regions. Inadequate dust cleaning and defective dust removal systems are central causes, while operational violations and use of non-explosion-proof equipment are main triggering conditions, and the causal structure varies significantly with dust types. The implementation of differential and precise prevention and control strategies is the key means to improve the prevention and control efficiency of dust explosion accidents.

Key words: dust explosion accident, knowledge graph, CiteSpace, prevention and control system, statistical analysis

CLC Number: