Cause analysis of multi-rotor UAV accidents based on FTA-BN model

Abstract

Abstract:

The analysis of the causes of multi-rotor unmanned aerial vehicle (UAV) accidents is helpful to realize the scientific prevention and control of multi-rotor UAV accidents. In this paper, 382 cases of multi-rotor UAV accidents

were investigated, and a fault tree analysis-Bayesian network (FTA-BN) model was established to analyze the

causes of multi-rotor UAV accidents. Firstly, a fault tree model was established with the multi-rotor UAV accident as the top event, the mid-air collision, crash and loss of contact of the multi-rotor UAV as the intermediate

events, and the accident causation events as the basic event. Then, according to the correspondence relationship

between the fault tree model and the Bayesian network, the fault tree model was transformed into a Bayesian network model. Finally, the posterior probability inference and sensitivity analysis of the Bayesian network model

were carried out by Netica software, and the main causative factors of accidents were obtained. The results

showed that the combined model can not only simplify the inference of the cause of UAV accidents, but also obtain more reliable inferences.

Key words:

multi-rotor UAV accidents, cause analysis, fault tree analysis (FTA), Bayesian network (BN)

CLC Number:

V279
X951

YUE Rentian, HAN Lei.

Cause analysis of multi-rotor UAV accidents based on FTA-BN model

[J]. Journal of Civil Aviation University of China, 2025, 43(4): 91-96.

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