A Simplified Fifth Order Shear Deformation Theory Applied to Study the Dynamic Behavior of Moderately Thick Composite Plate

Parida, Sarada Prasad; Jena, Pankaj Charan

doi:10.1007/978-981-19-0296-3_8

Cited by 5 publications

(1 citation statement)

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“…By calculating the relative natural frequency and other data, the effect of crack depth and location on the dynamic characteristics of the beam was studied. Parida and Jena [7] studied the stress component, static deflection and natural frequency of materials, and compared the hypothesized theoretical results with the results of first-order shear deformation theory and finite element analysis, respectively, to compare and optimize the effects of different filling materials.…”

Section: Related Workmentioning

confidence: 99%

DIC measurement method based on binocular stereo vision for image 3D displacement detection

Dong

2023

J. meas. eng.

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The deformation detection of large machinery is usually achieved using three-dimensional displacement measurement. Binocular stereo vision measurement technology, as a commonly used digital image correlation method, has received widespread attention in the academic community. Binocular stereo vision achieves the goal of three-dimensional displacement measurement by simulating the working mode of the human eyes, but the measurement is easily affected by light refraction. Based on this, the study introduces particle swarm optimization algorithm for target displacement measurement on Canon imaging dataset, and introduces backpropagation neural network for mutation processing of particles in particle swarm algorithm to generate fusion algorithm. It combines the four coordinate systems of world, pixel, physics, and camera to establish connections. Taking into account environmental factors and lens errors, the camera parameters and deformation coefficients were revised by shooting a black and white checkerboard. Finally, the study first conducted error analysis on binocular stereo vision technology in three dimensions, and the relative error remained stable at 1 % within about 60 seconds. At the same time, three algorithms, including the spotted hyena algorithm, were introduced to conduct performance comparison experiments using particle swarm optimization and backpropagation network algorithms. The experiment shows that the three-dimensional error of the fusion algorithm gradually stabilizes within the range of [–0.5 %, 0.5 %] over time, while the two-dimensional error generally hovers around 0 value. Its performance is significantly superior to other algorithms, so the binocular stereo vision of this fusion algorithm can achieve good measurement results.

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Section: Related Workmentioning

confidence: 99%