Adaptive multiswarm particle swarm optimization for tuning the parameter optimization of a three-element dynamic vibration absorber

Song, Qing Hui; Xiao, Lin; Song, Qing Jun; Jiang, HaiYan; Liu, Xiu Jie

doi:10.5194/ms-13-505-2022

Cited by 3 publications

(2 citation statements)

References 26 publications

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“…Nishihara et al [6] used the Newton-Raphson algorithm to optimize the parameters so that the maximum amplitude amplification coefficient of the linear primary system of the three-element-type DVA was the smallest under a given mass ratio. Song et al [7] discussed the parameter optimization methods of Voigt-type DVA and three-element-type DVA models based on the H ∞ optimization criterion and compared the performance of these different methods. Chen et al [8] applied a three-element-type DVA to suppress vibrations in vehicle bodies, and a formula for the design of the suspension parameters of the frame equipment was obtained.…”

Section: Introductionmentioning

confidence: 99%

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H∞ Optimization of Three-Element-Type Dynamic Vibration Absorber with Inerter and Negative Stiffness Based on the Particle Swarm Algorithm

Gao

Zhu

et al. 2023

Entropy

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Dynamic vibration absorbers (DVAs) are extensively used in the prevention of building and bridge vibrations, as well as in vehicle suspension and other fields, due to their excellent damping performance. The reliable optimization of DVA parameters is key to improve their performance. In this paper, an H∞ optimization problem of a novel three-element-type DVA model including an inerter device and a grounded negative stiffness spring is studied by combining a traditional theory and an intelligent algorithm. Firstly, to ensure the system’s stability, the specific analytical expressions of the optimal tuning frequency ratio, stiffness ratio, and approximate damping ratio with regard to the mass ratio and inerter–mass ratio are determined through fixed-point theory, which provides an iterative range for algorithm optimization. Secondly, the particle swarm optimization (PSO) algorithm is used to further optimize the four parameters of DVA simultaneously. The effects of the traditional fixed-point theory and the intelligent PSO algorithm are comprehensively compared and analyzed. The results verify that the effect of the coupling of the traditional theory and the intelligent algorithm is better than that of fixed-point theory alone and can make the two resonance peaks on the amplitude–frequency response curves almost equal, which is difficult to achieve using fixed-point theory alone. Finally, we compare the proposed model with other DVA models under harmonic and random excitation. By comparing the amplitude–frequency curves, stroke lengths, mean square responses, time history diagrams, variances and decrease ratios, it is clear that the established DVA has a good vibration absorption effect. The research results provide theoretical and algorithm support for designing more effective DVA models of the same type in engineering applications.

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Section: Introductionmentioning

confidence: 99%

“…The PSO algorithm can obtain more effective solutions when solving the problem of the multi-parameter optimization of vibration reduction structures. Some researchers [7,35] applied the PSO algorithm to study the parameter optimization of different types of DVAs to obtain an acceptable vibration performance.…”

Section: Introductionmentioning

confidence: 99%

H∞ Optimization of Three-Element-Type Dynamic Vibration Absorber with Inerter and Negative Stiffness Based on the Particle Swarm Algorithm

Gao

Zhu

et al. 2023

Entropy

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$${\mathrm{H}}_{\infty }$$ and $${\mathrm{H}}_{2}$$ Optimization of the Grounded-Type DVA Attached to Damped Primary System Based on Generalized Fixed-Point Theory Coupled Optimization Algorithm

Li,

Zhao,

Zhu

et al. 2023

J. Vib. Eng. Technol.

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AI-driven optimization of dynamic vibration absorbers with hydraulic amplifier and mechanical inerter integration

Shamseldin,

Abido,

Alofi

2024

Front. Mech. Eng.

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Dynamic vibration absorbers (DVAs) have been widely employed in vibration suppression applications for decades. While DVAs offer an effective solution, they are limited by the need for a high mass ratio between the DVA and the primary system to achieve significant vibration attenuation. To overcome this, researchers have introduced lever mechanisms, allowing for enhanced vibration suppression without increasing the mass ratio. However, levers, commonly used as amplification mechanisms, suffer from high inertia and limited amplification, particularly in larger applications. Another limitation is when DVAs are employed for energy harvesting as a secondary objective, they exhibit high sensitivity to system parameter variations, requiring extensive optimization. Various optimization techniques have been applied to DVAs for multi-objective optimization, including fixed-point theory, which is complex and requires intensive mathematical derivation, and simple metaheuristic techniques such as genetic algorithms (GA). This study proposes four novel DVAs using a hydraulic amplifier (HA) to address the limitations of traditional lever mechanisms and a mechanical inerter to improve the vibration damping. Also, multi-objective optimization was performed using particle swarm optimization (PSO) which is considered innovative in this application and compared with commonly used genetic algorithms (GA). The governing equations were derived using Newton’s second law and solved numerically with the Runge-Kutta method. An AI-based approach was utilized for HA design. The results show that integrating HA and mechanical inerters significantly enhances vibration attenuation and broadens the frequency response. Additionally, the location of the mechanical inerter is critical in reducing vibration amplitude. Also, the multi-objective PSO outperforms GA in solution diversity and quality. The proposed integration of HA in DVAs offers potential applications across various engineering fields.

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Adaptive multiswarm particle swarm optimization for tuning the parameter optimization of a three-element dynamic vibration absorber

Cited by 3 publications

References 26 publications

H∞ Optimization of Three-Element-Type Dynamic Vibration Absorber with Inerter and Negative Stiffness Based on the Particle Swarm Algorithm

H∞ Optimization of Three-Element-Type Dynamic Vibration Absorber with Inerter and Negative Stiffness Based on the Particle Swarm Algorithm

$${\mathrm{H}}_{\infty }$$ and $${\mathrm{H}}_{2}$$ Optimization of the Grounded-Type DVA Attached to Damped Primary System Based on Generalized Fixed-Point Theory Coupled Optimization Algorithm

AI-driven optimization of dynamic vibration absorbers with hydraulic amplifier and mechanical inerter integration

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