Control of Sound Noise Radiated From a Plate Using Dynamic Absorbers Under the Optimization by Neural Network

Nagaya, Kosuke; Li, L.

doi:10.1006/jsvi.1997.1201

Cited by 30 publications

(35 citation statements)

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“…Researchers have used other types of optimisation methods to reduce noise levels from structures such as neural networks [37], gradient descent methods [38], mathematical programming techniques [39], and H 2 decentralised methods [40].…”

Section: Previous Workmentioning

confidence: 99%

Vibro-acoustic noise control treatments for payload bays of launch vehicles: Discrete to fuzzy solutions

2005

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Section: Previous Workmentioning

confidence: 99%

Vibro-acoustic noise control treatments for payload bays of launch vehicles: Discrete to fuzzy solutions

2005

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“…The vibrations of higher modes can be suppressed by small damping, because a damping force is in proportion to the vibrating speed. The present authors presented a method for suppressing higher modal vibrations by using the fewer number of vibration absorbers with consideration of the damping phenomena just mentioned [19]. In the method, the absorbers control higher modes whose number is greater than the number of vibration absorbers.…”

Section: Response Of a Structure With Vibration Absorbersmentioning

confidence: 99%

Vibration Control of a Structure by Using a Tunable Absorber and an Optimal Vibration Absorber Under Auto-Tuning Control

Nagaya

Kurusu

Ikai

et al. 1999

Journal of Sound and Vibration

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“…However, few applications of neural networks as approximation scheme are known for structural acoustics. Nagaya and Li [4] applied a three-layered neural network system for optimization of fifteen variables. Another example of neural networks utilized holographic neural network [5].…”

Section: Introductionmentioning

confidence: 99%

Fast Vibroacoustic Optimization of Mechanical Structures Using Artificial Neural Networks

Ranjbar¹,

Marburg²

2013

IJMEA

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An artificial neural network (ANN) is adjusted to make analytical approximation of objective function for a specific structural acoustic application. It is used as the replacement of the main real objective function during the optimization process. The goal of optimization is to find the best geometry modification of the considered model which is supposed to produce lower values of the radiated sound power levels. The result of this study shows that the function approximation by neural networks can reduce the duration of optimization procedure. Furthermore, the tuning of ANN internal parameter settings is a real challenge to be considered.

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Control of Sound Noise Radiated From a Plate Using Dynamic Absorbers Under the Optimization by Neural Network

Cited by 30 publications

References 0 publications

Vibro-acoustic noise control treatments for payload bays of launch vehicles: Discrete to fuzzy solutions

Vibro-acoustic noise control treatments for payload bays of launch vehicles: Discrete to fuzzy solutions

Vibration Control of a Structure by Using a Tunable Absorber and an Optimal Vibration Absorber Under Auto-Tuning Control

Fast Vibroacoustic Optimization of Mechanical Structures Using Artificial Neural Networks

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