Abstract
Cable overload is one of the most critical contributors to early cable fires. This study proposes a hybrid Bayesian network (BN)-based fire risk analysis model, to investigate the evolution of overload-induced early cable fire risks. In particular, the fire risk transmission paths caused by cable overload are reported, considering the critical factors that likely lead to fires. A BN with a specific structure was considered using the fire risk transmission paths. Later, given the risk index system, a hybrid fire risk assessment model caused by cable overload was developed based on the entropy weight method. Subsequently, the corresponding risk levels were evaluated based on the evolution of the fire risk, using numerical simulations. Finally, a case study was conducted to validate the proposed methods, and the results indicated that the proposed methods can effectively evaluate the state of the cable and explain the causes of fire risk, which can be used for early fire warnings.
Highlights
Electrical wires and cables are important power conduits, supporting the rapidly evolving energy needs of modern societies
Combined with multi-factor coupling experiments of cable overload fires, the theory of risk transformation, and the Bayesian network (BN)-based risk assessment, this study proposes a composite early cable fire risk analysis method for investigating the fire risk in energized cables before cable fires, and for inferring the critical factors leading to cable fires
To investigate the early fire risk caused by cable overloads, this study proposed a hybrid risk analysis model called BN-RA
Summary
Electrical wires and cables are important power conduits, supporting the rapidly evolving energy needs of modern societies. There are 587,000 electrical fire-related disasters that occurred in China from 2015 to 2020, accounting for a large proportion of all incidents In this sense, to prevent the serious consequences of cable fires, the mechanisms underlying cable fires should be explored, and fire risk analysis models should be developed for providing early fire warnings. To estimate the risk level of overload-induced early cable fires, this study proposes a novel BN-based hybrid fire risk assessment model. Given the risk index system and combined with the entropy weighting method, the risk assessment model of overload-induced early cable fires is established, and the risk level is estimated based on the numerical simulations of risk evolution. To address the aforementioned concerns and research gaps, this study focuses on the overload-induced early cable fire risk analysis, based on the proposed BN and considering the effects of mechanical damage, cable aging, and other factors.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
