Identification for Critical Speeds of an Orthotropic Rectangular Plate in a Supersonic Flow using Neural Networks

2009 ◽  
Author(s):  
I. Takahashi
Keyword(s):  
Neural Networks ◽  
Supersonic Flow ◽  
Rectangular Plate ◽  
Critical Speeds ◽  
Orthotropic Rectangular Plate

Experimental force reconstruction on plates of arbitrary shape using neural networks

2021 ◽  
Vol 263 (3) ◽  
pp. 3407-3416
Author(s):  
Tyler Dare
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Inverse Problem ◽  
Artificial Neural Network ◽  
Rectangular Plate ◽  
Arbitrary Shape ◽  
Impulsive Force ◽  
Force Reconstruction ◽  
Output Space ◽  
Arbitrary Shapes

Measuring the forces that excite a structure into vibration is an important tool in modeling the system and investigating ways to reduce the vibration. However, determining the forces that have been applied to a vibrating structure can be a challenging inverse problem, even when the structure is instrumented with a large number of sensors. Previously, an artificial neural network was developed to identify the location of an impulsive force on a rectangular plate. In this research, the techniques were extended to plates of arbitrary shape. The principal challenge of arbitrary shapes is that some combinations of network outputs (x- and y-coordinates) are invalid. For example, for a plate with a hole in the middle, the network should not output that the force was applied in the center of the hole. Different methods of accommodating arbitrary shapes were investigated, including output space quantization and selecting the closest valid region.

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