Detection of Natural Frequency and Mode Shape Correspondence Using Phase-Based Video Magnification in Large-Scale Structures

  • Aral Sarrafi
  • Peyman Poozesh
  • Christopher Niezrecki
  • Zhu Mao
Conference paper
Part of the Conference Proceedings of the Society for Experimental Mechanics Series book series (CPSEMS)


Structural dynamics identification is an important part of both the design and certification process for large-scale structures and specifically utility-scale wind turbine blades. Finding the correspondence between the estimated natural frequencies and the mode shapes of interest can be a very challenging due to the sheer size of the structures and the large amount of instrumentation required. The state of the art methods in experimental modal analysis (EMA) and operational modal analysis (OMA) require attachment of numerous accelerometers along the test structure to extract the natural frequencies and the mode shapes. Instrumenting large structures with accelerometers and handling the wiring and the connections can be a very labor-intensive task; therefore, alternative methods should be considered to address this problem. Within this paper, the capabilities of phase-based video magnification and motion estimation are investigated to find the correspondence between the natural frequencies and the mode shapes. The sequence of images (video) is recorded from the vibrating wind turbine blade and then processed using the phase based motion estimation to extract the spectrum of the response of the wind turbine blade to the impact excitation. Afterward based on the obtained spectrum the recorded videos are magnified to visualize the operating deflection shapes. The motion magnified videos represent the visual perception of the operating deflection shapes, which can be used to find the correspondence between the natural frequencies and the mode shapes. The results of this method have also been validated using the benchmark modal data from the accelerometers as well as the point tracking optical measurement method.


Phase-based motion estimation Video Magnification Wind Turbine Blade Modal Analysis 


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Copyright information

© The Society for Experimental Mechanics, Inc. 2019

Authors and Affiliations

  • Aral Sarrafi
    • 1
  • Peyman Poozesh
    • 1
  • Christopher Niezrecki
    • 1
  • Zhu Mao
    • 1
  1. 1.Structural Dynamics and Acoustic Systems Laboratory, Department of Mechanical EngineeringUniversity of Massachusetts LowellLowellUSA

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