<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In recent years, the optimization of eight-link pressure mechanism using ant colony algorithm is a research hotspot, but given the limitations of traditional ant colony algorithm, this paper improves the ant colony algorithm based on the SSA-IACO algorithm and develops the application and analysis of eight-link pressure mechanism and its dynamic simulation. Through the study of parameter settings before and after optimization, simulation analysis and other aspects, it is concluded that: the efficiency of the new scheme optimized by the improved ant colony algorithm is 88.86% higher than the original scheme. The stator power is reduced by 4.10% and the power factor is increased by 14.67% on average over the original scheme. The maximum magnitude of the free end torsion angle of the crankshaft system is 0.16 degrees, and the increased resonance speed is about 1800 rpm. The maximum torsion angle of the main harmonic (6th harmonic) is reduced from 0.54 to 0.16, and the damping effect is noticeable. When 0.7 ≤ <italic>ρ</italic> 0.8, and ρ is close to 0.7, the algorithm performs better. When 0.15 ≤ <italic>θ</italic> 0.2, and the value of θ is more comparable to 0.15, the algorithm obtains the optimal solution and the execution time is shorter than the [0.7,0.2] combination.</p>
</abstract>

In recent years, the optimization of eight-link pressure mechanism using ant colony algorithm is a research hotspot, but given the limitations of traditional ant colony algorithm, this paper improves the ant colony algorithm based on the SSA-IACO algorithm and develops the application and analysis of eight-link pressure mechanism and its dynamic simulation. Through the study of parameter settings before and after optimization, simulation analysis and other aspects, it is concluded that: the efficiency of the new scheme optimized by the improved ant colony algorithm is 88.86% higher than the original scheme. The stator power is reduced by 4.10% and the power factor is increased by 14.67% on average over the original scheme. The maximum magnitude of the free end torsion angle of the crankshaft system is 0.16 degrees, and the increased resonance speed is about 1800 rpm. The maximum torsion angle of the main harmonic (6th harmonic) is reduced from 0.54 to 0.16, and the damping effect is noticeable. When 0.7 ≤ ρ 0.8, and ρ is close to 0.7, the algorithm performs better. When 0.15 ≤ θ 0.2, and the value of θ is more comparable to 0.15, the algorithm obtains the optimal solution and the execution time is shorter than the [0.7,0.2] combination.

Eight-link pressure mechanism and its dynamic simulation based on improved ant colony algorithm optimization

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In recent years, the optimization of eight-link pressure mechanism using ant colony algorithm is a research hotspot, but given the limitations of traditional...

Eight-link pressure mechanism and its dynamic simulation based on improved ant colony algorithm optimization

Publié en ligne: 26 févr. 2024

Pages: -

Reçu: 10 janv. 2024

Accepté: 20 janv. 2024

DOI: https://doi.org/10.2478/amns-2024-0458

Mots clés
Ant colony algorithm, SSA-IACO algorithm, Improvement, Eight-link pressure structure, Dynamic simulation

© 2024 Song Liu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Eight-link pressure mechanism and its dynamic simulation based on improved ant colony algorithm optimization

Publié en ligne: 26 févr. 2024

Pages: -

Reçu: 10 janv. 2024

Accepté: 20 janv. 2024

DOI: https://doi.org/10.2478/amns-2024-0458

Mots clésAnt colony algorithm, SSA-IACO algorithm, Improvement, Eight-link pressure structure, Dynamic simulation

© 2024 Song Liu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Ant colony algorithm, SSA-IACO algorithm, Improvement, Eight-link pressure structure, Dynamic simulation