Measurement and identification of the nonlinear dynamics of a jointed structure using full-field data; Part II - Nonlinear system identification - 2021
Amplitude-dependent characteristics; Digital Image Correlation (DIC); Energy-dependent characteristics; Jointed structures; Nonlinear system identification; Amplitude-dependent characteristic; Dependent characteristics; Digital image correlation; Digital image correlations; Energy dependent; Energy-dependent characteristic; Field data; Jointed structure; Non-linear system identification; Control and Systems Engineering; Signal Processing; Civil and Structural Engineering; Aerospace Engineering; Mechanical Engineering; Computer Science Applications
Résumé :
[en] The dynamic responses of assembled structures are greatly affected by the mechanical joints, which are often the cause of nonlinear behavior. To better understand and, in the future, tailor the nonlinearities, accurate methods are needed to characterize the dynamic properties of jointed structures. In this paper, the nonlinear characteristics of a jointed beam is studied with the help of multiple identification methods, including the Hilbert Transform method, Peak Finding and Fitting method, Dynamic Mode Decomposition method, State-Space Spectral Submanifold, and Wavelet-Bounded Empirical Mode Decomposition method. The nonlinearities are identified by the responses that are measured via accelerometers in a series of experiments that consist of hammer testing, shaker ringdown testing, and response/force-control stepped sine testing. In addition to accelerometers, two high-speed cameras are used to capture the motion of the whole structure during the shaker ringdown testing. Digital Image Correlation (DIC) is then adopted to obtain the displacement responses and used to determine the mode shapes of the jointed beam. The accuracy of the DIC data is validated by the comparison between the identification results of acceleration and displacement signals. As enabled by full-field data, the energy-dependent characteristics of the structure are also presented. The setup of the different experiments is described in detail in Part I (Chen et al., 2021) of this research. The focus of this paper is to compare nonlinear system identification methods applied to different measurement techniques and to exploit the use of high spatial resolution data.
Disciplines :
Ingénierie aérospatiale Ingénierie mécanique
Auteur, co-auteur :
Jin, Mengshi; AECC Shanghai Commercial Aircraft Engine Manufacturing Co. LTD., Shanghai, China ; School of Aerospace Engineering and Applied Mechanics, Tongji University, Shanghai, China
Kosova, Giancarlo ; Université de Liège - ULiège > Aérospatiale et Mécanique (A&M) ; Siemens Industry Software, Leuven, Belgium
Cenedese, Mattia ; Institute for Mechanical Systems, ETH Zürich, Zürich, Switzerland
Chen, Wei ; AECC Shanghai Commercial Aircraft Engine Manufacturing Co. LTD., Shanghai, China ; School of Aerospace Engineering and Applied Mechanics, Tongji University, Shanghai, China
Singh, Aryan; Department of Mechanical and Materials Engineering, University of Nebraska-Lincoln, Lincoln, United States
Jana, Debasish ; Department of Civil and Environmental Engineering, Rice University, Houston, United States
Brake, Matthew R.W. ; Department of Mechanical Engineering, Rice University, Houston, United States
Schwingshackl, Christoph W. ; Imperial College London, Mechanical Engineering, London, United Kingdom
Nagarajaiah, Satish ; Department of Civil and Environmental Engineering, Rice University, Houston, United States ; Department of Mechanical Engineering, Rice University, Houston, United States
Moore, Keegan J. ; Department of Mechanical and Materials Engineering, University of Nebraska-Lincoln, Lincoln, United States
Noël, Jean-Philippe ; Université de Liège - ULiège > Département d'aérospatiale et mécanique ; Control Systems Technology Group, Department of Mechanical Engineering, Eindhoven University of Technology, Netherlands
Langue du document :
Anglais
Titre :
Measurement and identification of the nonlinear dynamics of a jointed structure using full-field data; Part II - Nonlinear system identification
This work presents the results of the Tribomechadynamics Research Camp (2019) at Rice University, Houston, Texas, USA (http://tmd.rice.edu). The authors appreciate the chance to work together. The authors are also grateful to the SIEMENS and South Central Imaging for their sponsorship. Wei Chen and Mengshi Jin thank China Scholarship Council (CSC) for their financial support at Rice University. Giancarlo Kosova has been supported by the European Union's Horizon 2020 research and innovation program under the Marie Sk?odowska-Curie grant agreement No 764547. Debasish Jana and Satish Nagarajaiah acknowledge the grant from the Science and Engineering Research Board of India (SERB). The data used in the paper is available at https://github.com/mattiacenedese/BRBtesting.This work presents the results of the Tribomechadynamics Research Camp (2019) at Rice University, Houston, Texas, USA ( http://tmd.rice.edu ). The authors appreciate the chance to work together. The authors are also grateful to the SIEMENS and South Central Imaging for their sponsorship. Wei Chen and Mengshi Jin thank China Scholarship Council (CSC) for their financial support at Rice University. Giancarlo Kosova has been supported by the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 764547 . Debasish Jana and Satish Nagarajaiah acknowledge the grant from the Science and Engineering Research Board of India (SERB) .
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