PREDICTION OF AIRCRAFT LOST OF CONTROL IN THE FLIGHT BY CONTINUATION, BIFURCATION, AND CATASTROPHE THEORY METHODS

K. Sibilski, M. Kowalski
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引用次数: 1

Abstract

Lost of Control in Flight (LOC-I) is ordinarily associated with flight outside of the normal flight envelope, with nonlinear behaviours, and with an inability of the pilot to control the aircraft. These results provide a means for analysing accident data to establish whether or not the accident should be classified as LOC-I. Moreover, they help identify when the initial upset occurred, and when control was lost. The analysis also suggests which variables were involved, thereby providing clues as to the underlying mechanism of upset. However, it does not provide direct links to the flight mechanics of the aircraft, so it cannot be used proactively to identify weaknesses or limitations in the aircraft or its control systems. Moreover, it does not explain how departures from controlled flight occur. The complexity of the disaster aetiology stems from both the scale and coupling of the systems (not only the physical aircraft systems but also the organizational systems that support the operation). This complexity creates a pattern of disaster that evolves or it is precipitated through a series of several small failures. The cusp catastrophe model facilitates the mapping of Reason’s latent failure model, providing a descriptive and predictive illustration of the emergence of latent conditions under the trigger of situational factors. The risk of an accident increases as the situational and systematic factors combine to create an inherent instability resulting in the catastrophic event
用延拓、分岔和突变理论方法预测飞机飞行失控
飞行中失去控制(LOC-I)通常与正常飞行包线之外的飞行、非线性行为以及飞行员无法控制飞机有关。这些结果为分析事故数据以确定该事故是否应归类为LOC-I提供了一种手段。此外,它们有助于确定最初的不安是何时发生的,以及何时失去控制。该分析还指出了涉及哪些变量,从而为沮丧的潜在机制提供线索。然而,它并不提供与飞机飞行力学的直接联系,因此它不能主动用于识别飞机或其控制系统的弱点或局限性。此外,它并没有解释如何偏离受控飞行。灾害病因学的复杂性源于系统的规模和耦合(不仅是物理飞机系统,还有支持操作的组织系统)。这种复杂性创造了一种灾难的模式,这种模式会通过一系列的小失败而演变或加速。尖点突变模型有助于映射Reason的潜在失效模型,为情境因素触发下潜在条件的出现提供描述性和预测性说明。当环境因素和系统因素结合在一起,造成固有的不稳定性,导致灾难性事件时,事故的风险就会增加
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