State estimation and system model correction of aero-engines under multi-source uncertainty: A hierarchical variational inference approach

Key Points

• State estimation improves under multi-source uncertainty with variational inference methods, enhancing performance.
• The metric of accuracy in system model correction shows a significant uptick, with notable reductions in error rates.
• Analysis applied a hierarchical variational inference approach to assess model corrections and state estimations across various conditions.
• The findings highlight the need for advanced methodologies in aerospace engineering to manage uncertainties effectively.