基于数字飞行员模型的航空器风险量化评估方法及系统

CN121435381BActive Publication Date: 2026-07-17NANJING UNIV OF AERONAUTICS & ASTRONAUTICS

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
Filing Date
2025-10-29
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Traditional aircraft assessment methods are costly, have insufficient scenario coverage, rely heavily on manual labor, and are difficult to achieve batch and automatic generation. In particular, in quantitative comparative studies of single-person and two-person crews, the sample size is insufficient, the statistical significance is not up to standard, and there is a lack of unified staged threshold standards and traceable over-limit intensity measurement methods.

Method used

An aircraft risk quantification assessment method based on a digital pilot model is adopted. By constructing a discrete practice/finite state machine driven digital pilot model and combining it with a multimodal coupled flight simulation system, Monte Carlo sampling is performed to conduct parallel batch execution simulations, forming a complete chain of evidence. Over-limit detection and hierarchical weighted calculation are then performed to achieve the quantification and traceability of risk scores.

Benefits of technology

It achieves low-cost, high-coverage risk assessment across all stages, supports comparative verification between single-person and two-person crews, improves the statistical significance and reproducibility of assessment data, and possesses risk attribution capabilities with sensitivity analysis and evidence chain support.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN121435381B_ABST
    Figure CN121435381B_ABST
Patent Text Reader

Abstract

本发明公开了基于数字飞行员模型的航空器风险量化评估方法及系统,属于飞行仿真与航空安全评估技术领域,包括S1、数字飞行员模型构建;S2、闭环集成代理模型与飞行仿真模型;S3、建立风险场景库与触发机制;S4、执行蒙特卡罗批量仿真与智能调度;S5、采集仿真数据并进行同步标注;S6、执行阶段化超限检测;S7、计算分层加权与综合评分;S8、将试验分级同时对批量结果进行置信区间与显著性检验;S9、模拟SPO与DPO进行对比;S10、多模态融合;S11、灵敏度分析与归因;S12、生成可追溯的证据链与报告。本发明采用上述方法及系统,能够在覆盖低概率高风险场景的同时输出可量化、可比较、可审计的运行风险结论。
Need to check novelty before this filing date? Find Prior Art