Bayesian-based aviation equipment residual life uncertainty prediction method and system

By dynamically updating uncertainty parameters using Bayesian methods and surrogate models, the problem of insufficient uncertainty quantification in digital twin technology is solved, enabling high-confidence prediction of the remaining life of aviation equipment and output of maintenance instructions, thereby improving the rationality and feasibility of decision-making.

CN121960125APending Publication Date: 2026-05-01CHINA AERO POLYTECH ESTAB
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Patent Information

Application Number
CN202511973254.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-25
Publication Date
2026-05-01

AI Technical Summary

Technical Problem

Existing digital twin technology cannot effectively quantify uncertainty in aviation equipment, resulting in unknown confidence levels in prediction results and making it difficult to support high-risk decision-making.

Method used

An observation function equation is constructed using a Bayesian approach. By combining a recursive Bayesian filtering algorithm and a surrogate model with a physical information neural network, the uncertainty parameters are dynamically updated to achieve probabilistic prediction of the remaining lifespan of aviation equipment.

Benefits of technology

It enables high-confidence prediction of the remaining lifespan of aviation equipment, outputs maintenance instructions, improves the rationality and feasibility of decision-making, and reduces the probability of decision-making errors due to insufficient information.

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Abstract

The invention provides a Bayesian-based aviation equipment residual life uncertainty prediction method and system. The method comprises the following steps: S1, constructing an observation function equation and a state parameter description equation of residual life of key or important systems, modules and parts of aviation equipment; s2, constructing an agent model; s3, solving joint posterior probability distribution and performing residual life prediction; and S4, according to the prediction probability distribution of the remaining life of the aviation equipment, generating an optimization control instruction or a maintenance instruction for the aviation equipment, and acting the optimization control instruction or the maintenance instruction on the aviation equipment. The method provided by the invention not only provides a theoretical basis for solving the problem of prediction, analysis and prediction of the service life of the aviation equipment, but also clearly defines how information and uncertainty thereof flow and convert between a physical world and a digital world, and provides a brand new thought for prediction of the uncertainty of the residual service life of the aviation equipment.
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