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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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DTSTART:20191027T010000
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