4.7 Article

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

Journal

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
Volume 61, Issue 5, Pages 1929-1952

Publisher

SPRINGER
DOI: 10.1007/s00158-019-02448-8

Keywords

Distributed dynamic load identification; Model equivalence; Sensor placement optimization; The rudder structure of hypersonic vehicles; Unknown-but-bounded uncertainties

Funding

  1. Pre-research Field Foundation of Equipment Development Department of China [61402100103]
  2. Aeronautical Science Foundation of China [2017ZA51012, 20182951014]
  3. Defense Industrial Technology Development Program [JCKY2016204B101, JCKY2017208B001]
  4. Science and Technology Foundation of China Aerospace Science and Industrial Corporation
  5. College Union Innovation Foundation of China Academy of Launch Vehicle Technology [CALT201704]

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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.

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