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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2020, Vol. 41 ›› Issue (9): 223806-223806.doi: 10.7527/S1000-6893.2020.23806

• Solid Mechanics and Vehicle Conceptual Design • Previous Articles     Next Articles

Dynamic load identification method for variable cross-section cantilever structure

WU Xiao1, ZENG Jie1, HU Zikang1, LI Ming2, HU Xitao1   

  1. 1. State Key Laboratory of Mechanical Structure Mechanics and Control, Nanjing University of Aeronautics and Astronautics, Nanjing 210016;
    2. Equipment Service Product Department, China Aviation Integrated Technology Research Institute, Beijing 100028
  • Received:2020-01-07 Revised:2020-02-06 Online:2020-09-15 Published:2020-04-10
  • Supported by:
    Aviation Science Foundation (20170252004, 20185644006); Shanghai Aerospace Science and Technology Innovation Fund (SAST2018-015); Jiangsu Provincial Key Research and Development Plan Industry Prospect and Common Key Technology Competition Project (BE2018047); Joint Innovation Fund of First Academy of Higher Learning; A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions

Abstract: In the field of aerospace, it is both necessary and important to determine the dynamic load on the structure for structural health monitoring. In this paper, a method of dynamic load identification based on FBG sensors and the Kalman filter is proposed. According to the element form of variable cross-section beams, the mass matrix and stiffness matrix of variable cross-section beams are firstly derived, and the dynamic equation of motion established. Then, taking the strain information measured by FBG sensors as the observation signal, the gain matrix, innovation sequence matrix and covariance matrix generated by the Kalman filter are used to obtain the sensitivity matrix and the gain matrix of estimation force. On this basis, the generalized regression model and its least square algorithm are adopted to estimate the dynamic load and determine the excitation position of the dynamic load. By means of numerical simulation and experiments, the dynamic load identification effect of this method under single point sine excitation, square wave excitation, saw tooth wave excitation and multi-point simultaneous excitation is verified. Results show that the algorithm proposed has good dynamic load identification effect and noise suppression ability. It can also provide technical support for future wind tunnel tests and real flight test environments such as real-time load identification and aerodynamic shape adaptive control, and structural health monitoring such as high aspect ratio wing surface aerodynamic pressure.

Key words: variable section cantilever structure, fiber Bragg grating (FBG) sensor, Kalman filter, dynamic load identification, recursive least square method

CLC Number: