This paper proposes an approach to extract the mode shapes of beam-like structures from the dynamic response of a moving mass. When a mass passes through a beam containing several artificially installed humps, its ver...This paper proposes an approach to extract the mode shapes of beam-like structures from the dynamic response of a moving mass. When a mass passes through a beam containing several artificially installed humps, its vertical acceleration can be recorded. After applying fast Fourier transformation to the dynamic response, one can extract the mode shapes of the beam. The surface roughness was neglected compared to the humps and its adverse effect on the extraction was reduced. The passing mass performs as both “exciter” and “massage receiver”;therefore, this method requires only one single accelerometer, making it more convenient and time saving in practice. Moreover, to estimate the possible error in extracting mode shapes, a wavenumber domain filtering technique is used to reconstruct the general profiles of mode shapes. Experimental validation of this approach in laboratory scale was conducted. The experimental results show that the proposed method performs well in extracting lower order mode shapes. It should also be noted that the passing mass can not have a very high velocity (e.g. 80 mm/s), otherwise the mass may jump and separate from the beam, and the proposed method may fail to identify mode shapes.展开更多
Beam-like structures arde a class of common but important structures in engineering.Over the past few centuries,extensive research has been carried out to obtain the static and dynamic response of beam-like structures...Beam-like structures arde a class of common but important structures in engineering.Over the past few centuries,extensive research has been carried out to obtain the static and dynamic response of beam-like structures.Although build-ing the finite element model to predict the response of these structures has proven to be effective,it is not always suitable in all the application cases because of high computational time or lack of accuracy.This paper proposes a novel approach to predict the deflection response of beam-like structures based on a deep neural net-work and the governing differential equation of Euler-Bernoulli beam.The Prandtl-Ishlinskii model is introduced as an element of prediction model to simu-late the plasticity of this beam structure.Finally the application of the proposed approach is demonstrated through four numerical examples including linear elastic/ideal plastic beam under concentrated/sinusoidal load and elastic/plastic continues beam under seismic load to demonstrate a proof of concept for the effectiveness of this AI-based approach.展开更多
文摘This paper proposes an approach to extract the mode shapes of beam-like structures from the dynamic response of a moving mass. When a mass passes through a beam containing several artificially installed humps, its vertical acceleration can be recorded. After applying fast Fourier transformation to the dynamic response, one can extract the mode shapes of the beam. The surface roughness was neglected compared to the humps and its adverse effect on the extraction was reduced. The passing mass performs as both “exciter” and “massage receiver”;therefore, this method requires only one single accelerometer, making it more convenient and time saving in practice. Moreover, to estimate the possible error in extracting mode shapes, a wavenumber domain filtering technique is used to reconstruct the general profiles of mode shapes. Experimental validation of this approach in laboratory scale was conducted. The experimental results show that the proposed method performs well in extracting lower order mode shapes. It should also be noted that the passing mass can not have a very high velocity (e.g. 80 mm/s), otherwise the mass may jump and separate from the beam, and the proposed method may fail to identify mode shapes.
文摘Beam-like structures arde a class of common but important structures in engineering.Over the past few centuries,extensive research has been carried out to obtain the static and dynamic response of beam-like structures.Although build-ing the finite element model to predict the response of these structures has proven to be effective,it is not always suitable in all the application cases because of high computational time or lack of accuracy.This paper proposes a novel approach to predict the deflection response of beam-like structures based on a deep neural net-work and the governing differential equation of Euler-Bernoulli beam.The Prandtl-Ishlinskii model is introduced as an element of prediction model to simu-late the plasticity of this beam structure.Finally the application of the proposed approach is demonstrated through four numerical examples including linear elastic/ideal plastic beam under concentrated/sinusoidal load and elastic/plastic continues beam under seismic load to demonstrate a proof of concept for the effectiveness of this AI-based approach.
