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A novel method of distributed dynamic load identification for aircraft structure considering multi-source uncertainties

机译:考虑多源不确定性的飞机结构分布式动态载荷识别新方法

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摘要

A series of work for distributed dynamic load identification is investigated in this paper considering unknown-but-bounded uncertainties in the aircraft structure. To facilitate the analysis, the complicated rudder structure is simplified to a plate structure based on the robust equivalence principle of mechanical property under multi-cases of flight environments. Aiming at the plate structure, a time domain-based model for distributed dynamic load identification is established through the acceleration response measured by sensors. Among them, the spatial distributed load is approximated by Chebyshev orthogonal polynomials at each sampling time, and load boundaries can be calculated by the Taylor-expansion-based uncertain propagation analysis. As keys to improve the reliability of recognition results, the optimization process for sensor placement is constructed by the particle swarm optimization algorithm, taking the robustness evaluation index and sensor distribution index into consideration. The validity and the feasibility of the proposed methodology are demonstrated by several numerical examples, and the results reveal that designer can make a rational tradeoff choice among the cost of sensor placement and the performance of load identification in a systematic framework.
机译:本文研究了一系列用于分布式动态载荷识别的工作,考虑到飞机结构中未知但有界不确定性。为了便于分析,基于机械性质在多余的飞行环境下的机械性能原理简化了复杂的舵结构。针对板结构,通过传感器测量的加速度响应建立了一种用于分布式动态载荷识别的基于时间域的模型。其中,空间分布式负载由每个采样时间的Chebyshev正交多项式近似,并且可以通过基于泰勒 - 扩展的不确定传播分析来计算负载边界。作为提高识别结果可靠性的键,传感器放置的优化过程由粒子群优化算法构成,考虑到鲁棒性评估指标和传感器分配指数。若干数值示例证明了所提出的方法的有效性和可行性,结果表明,设计者可以在系统框架中的传感器放置成本和负载识别性能之间进行合理的权衡选择。

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