Research and Application of Double Layer Bayesian Network Model in Human Error Prevention in Flight Test

The present study employs the Bayesian network method to conduct risk assessment for test flights. Specifically, a double-layer Bayesian network model is established for assessing risks originating from human factors [1], aircraft performance, and environmental conditions during test flights. The model comprises two net-works: the operating condition risk assessment network and the task risk assessment network. The former is constructed by the test flight risk assessment model and enables prediction of the probability of accident risk and human error risk associated with various operating conditions during test flights. Compared to conventional statistical forecasting methods that rely solely on objective data, this approach allows for a wider range of effective information inputs, resulting in more accurate risk assessment outcomes. Notably, the proposed double-layer Bayesian network model constitutes a quantitative framework that explicitly captures the posterior probability of human error in relation to various test flight scenarios, which can inform targeted interventions to mitigate risk.