航空学报 > 2022, Vol. 43 Issue (5): 125137-125137   doi: 10.7527/S1000-6893.2021.25137

基于吸引域与二元极值理论的结冰飞机飞行风险量化评估

伍强1, 徐浩军1, 裴彬彬1, 魏扬1, 张杨2   

  1. 1. 空军工程大学 航空工程学院, 西安 710038;
    2. 中国人民解放军 95633部队, 成都 611530
  • 收稿日期:2020-12-22 修回日期:2021-01-13 发布日期:2021-03-01
  • 通讯作者: 裴彬彬 E-mail:bin1940@163.com
  • 基金资助:
    国家自然科学基金(61873351)

Quantitative evaluation of flight risk of icing aircraft based on theory of region of attraction and binary extreme value

WU Qiang1, XU Haojun1, PEI Binbin1, WEI Yang1, ZHANG Yang2   

  1. 1. Aeronautics Engineering College, Air Force Engineering University, Xi'an 710038, China;
    2. 95633 Troops, Chinese People's Liberation Army, Chengdu 611530, China
  • Received:2020-12-22 Revised:2021-01-13 Published:2021-03-01
  • Supported by:
    National Natural Science Foundation of China (61873351)

摘要: 结冰会导致飞机飞行包线萎缩,在驾驶员没有正确处理的情况下极易发生飞行事故。为定量计算结冰条件下飞机飞行风险进而制定合理的结冰风险规避策略,以飞机纵向动力学系统为分析对象,基于吸引域方法计算得到飞机结冰后的二维吸引域及稳定边界,并以飞行状态超出稳定边界作为飞行事故判定条件。建立了典型的人-机-环系统模型,通过蒙特卡罗仿真提取了飞行安全关键参数极值样本;根据极值理论,建立二元极值Copula模型;通过遗传算法辨识模型参数,依据多种拟合优度检验方法确定最优分布模型,进而计算不同结冰影响程度下的飞行风险概率,并由此来指导驾驶员操纵,从而保证飞行安全。文中所述方法,为定量计算结冰条件下飞行风险概率提供了新的思路,具有较好的工程应用前景。

关键词: 飞行风险, 吸引域, 蒙特卡罗仿真, 极值理论, 二元极值Copula模型

Abstract: Icing will cause the flight envelope of the aircraft to shrink, and flight accidents are prone to occur if the pilot does not handle it properly. To quantitatively calculate the aircraft flight risk under icing conditions and formulate a reasonable icing risk avoidance strategy, the aircraft longitudinal dynamics system is analyzed. The two-dimensional region of attraction of the aircraft after icing is calculated based on the region of attraction method, and the flight state beyond the region of attraction is used as the judging criterion for flight accident. A typical man-machine-loop system model is established. The extreme value samples of key flight safety parameters are extracted through Monte Carlo simulation. According to the extreme value theory, a binary extreme value Copula model is established. The model parameters are identified by the genetic algorithm. A goodness-of-fit test method is used to determine the optimal distribution model, and then the flight risk probability under the conditions of different icing influence levels is calculated, which can provide guidance for the pilot to maneuver to ensure flight safety. The method proposed provides a new idea for quantitatively calculating the flight risk probability under icing conditions, and has good application prospects.

Key words: flight risk, region of attraction, Monte Carlo simulation, extreme value theory, binary extreme value Copula model

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