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BMC Public Health
Published in: BMC Public Health 1/2024

Open Access 01-12-2024 | Research

A chemical accident cause text mining method based on improved accident triangle

Authors: Zheng Li, Min Yao, Zhenmin Luo, Xinping Wang, Tongshuang Liu, Qianrui Huang, Chang Su

Published in: BMC Public Health | Issue 1/2024

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Abstract

Background

With the rapid development of China’s chemical industry, although researchers have developed many methods in the field of chemical safety, the situation of chemical safety in China is still not optimistic. How to prevent accidents has always been the focus of scholars’ attention.

Methods

Based on the characteristics of chemical enterprises and the Heinrich accident triangle, this paper developed the organizational-level accident triangle, which divides accidents into group-level, unit-level, and workshop-level accidents. Based on 484 accident records of a large chemical enterprise in China, the Spearman correlation coefficient was used to analyze the rationality of accident classification and the occurrence rules of accidents at different levels. In addition, this paper used TF-IDF and K-means algorithms to extract keywords and perform text clustering analysis for accidents at different levels based on accident classification. The risk factors of each accident cluster were further analyzed, and improvement measures were proposed for the sample enterprises.

Results

The results show that reducing unit-level accidents can prevent group-level accidents. The accidents of the sample enterprises are mainly personal injury accidents, production accidents, environmental pollution accidents, and quality accidents. The leading causes of personal injury accidents are employees’ unsafe behaviors, such as poor safety awareness, non-standard operation, illegal operation, untimely communication, etc. The leading causes of production accidents, environmental pollution accidents, and quality accidents include the unsafe state of materials, such as equipment damage, pipeline leakage, short-circuiting, excessive fluctuation of process parameters, etc.

Conclusion

Compared with the traditional accident classification method, the accident triangle proposed in this paper based on the organizational level dramatically reduces the differences between accidents, helps enterprises quickly identify risk factors, and prevents accidents. This method can effectively prevent accidents and provide helpful guidance for the safety management of chemical enterprises.
Appendix
Available only for authorised users
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Metadata
Title
A chemical accident cause text mining method based on improved accident triangle
Authors
Zheng Li
Min Yao
Zhenmin Luo
Xinping Wang
Tongshuang Liu
Qianrui Huang
Chang Su
Publication date
01-12-2024
Publisher
BioMed Central
Published in
BMC Public Health / Issue 1/2024
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-023-17510-w

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