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UID:0-306@aerospace.technion.ac.il

DTSTART;TZID=Asia/Jerusalem:20200113T163000

DTEND;TZID=Asia/Jerusalem:20200113T173000

DTSTAMP:20230527T131534Z

URL:https://aerospace.technion.ac.il/events/aeroelastic-system-data-analys
 is-using-the-hilbert-huang-transform/

SUMMARY:Aeroelastic System Data Analysis Using the Hilbert-Huang Transform
DESCRIPTION:Lecturer:Ramya Raman\n Faculty:Department of Aerospace Engineer
 ing\n Institute:Technion – Israel Institute of Technology\n Location:Cla
 ssroom 165\, ground floor\, Library\, Aerospace Eng.\n Zoom: \n Abstract: 
 \n Details: \n Aeroelastic responses\, such as accelerations measured in f
 light\, are non-stationary signals in which the frequency content varies w
 ith flight speed and\, therefore\, in time. Aeroelastic responses might al
 so be nonlinear due to large structural deformations (in very flexible con
 figurations)\, structural free-play (e.g.\, in control surfaces)\, nonline
 ar aerodynamic forces (e.g.\, in transonic flight)\, or due to a very larg
 e excitation (e.g.\, in-store ejection). The objective of aeroelastic data
  analysis is to obtain an accurate representation of the dynamics of the n
 on-stationary nonlinear system. The current research study explores and co
 mpares several time-frequency methods for non-stationary nonlinear data an
 alysis\, including the Short-time Fourier transform (STFT)\, Wavelets\, an
 d the Hilbert-Huang Transform (HHT)\, with emphasis on the latter.\nIn the
  current research study\, the various time-frequency analysis methods were
  applied to aeroelastic response data of a wing obtained from computation 
 and a wind-tunnel test. The computational data included accelerations due 
 to gust excitation in multiple velocities. The wind tunnel data included a
 ccelerations measured at various speeds\, all the way to flutter. The data
  were analyzed using the above-mentioned signal processing techniques. Tim
 e-frequency responses are presented as Energy spectrum’s namely\, Spectr
 ogram\, Scalogram\, and HHT Spectrum (for the STFT\, Wavelets\, and HHT\, 
 respectively). These time-frequency graphs provide insight into system ide
 ntification and change in frequency content with time\, as the airspeed is
  increased. All three techniques yielded similar results when the data was
  analyzed for multiple velocities. However\, precise details were obtained
  with Scalogram and HHT spectrum when the data were analyzed for individua
 l speeds. Additionally\, damping ratios were calculated using HHT amplitud
 e energies and power spectral densities\, which provided the damping ratio
  of the stable and unstable modes for multiple velocities until flutter. T
 he advantages and shortcomings of different techniques are discussed in th
 e test cases.
CATEGORIES:Seminars
LOCATION:Classroom 165\, ground floor\, Library\, Aerospace Eng.

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TZID:Asia/Jerusalem

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DTSTART:20191027T010000

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